Citation
Regional and statewide trends in Florida's spring and well groundwater quality (1991-2003) ( FGS: Bulletin 69 )

Material Information

Title:
Regional and statewide trends in Florida's spring and well groundwater quality (1991-2003) ( FGS: Bulletin 69 )
Creator:
Copeland, Rick
Doran, Neal A.
White, Aaron J.
Upchurch, Sam B.
Place of Publication:
Tallahassee, FL
Publisher:
Florida Geological Survey
Language:
English

Subjects

Subjects / Keywords:
Wakulla Springs ( local )
Alexander Springs ( local )
Suwannee River, FL ( local )
Blue Spring, FL ( local )
City of Fanning Springs ( local )
Hornsby Spring ( local )
Groundwater ( jstor )
Nitrates ( jstor )
Natural springs ( jstor )

Record Information

Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
The author dedicated the work to the public domain by waiving all of his or her rights to the work worldwide under copyright law and all related or neighboring legal rights he or she had in the work, to the extent allowable by law.

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Binder1.pdf

Bulletin69-revised.pdf

Bulletin69revised2011Jan.pdf

GuideToAppendices.pdf

Bulletin69-revised_Page_413.txt

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Full Text





STATE OF FLORIDA
DEPARTMENT OF ENVIRONMENTAL PROTECTION
Herschel T. Vinyard Jr., Secretary


LAND AND RECREATION
Erma Slager, Acting Deputy Secretary

FLORIDA GEOLOGICAL SURVEY
Jonathan D. Arthur, State Geologist and Director


Bulletin No. 69 (Revised)




REGIONAL AND STATEWIDE TRENDS IN FLORIDA'S SPRING
AND WELL GROUNDWATER QUALITY (1991-2003)



By

Rick Copeland, Neal A. Doran, Aaron J. White, and Sam B. Upchurch


Published for the

FLORIDA GEOLOGICAL SURVEY
Tallahassee, Florida
2011







FLORIDA DEPARTMENT OF ENVIRONMENTAL PROTECTION
Herschel T. Vinyard Jr., Secretary


LAND AND RECREATION
Erma Slager, Acting Deputy Secretary


OFFICE OF THE FLORIDA GEOLOGICAL SURVEY
Jonathan D. Arthur, State Geologist and Director


ADMINISTRATIVE AND GEOLOGICAL DATA MANAGEMENT SECTION
Jacqueline M. Lloyd, Assistant State Geologist


Traci Billingsley, Business Manager
Doug Calman, Librarian Specialist
Brian Clark, Environmental Specialist
Jan DeLaney, Environmental Supervisor


Kerry Pond*, Archivist
Sara Sayers, Secretary Specialist
Carolyn Stringer, Operations Manager
Keith Wood*, Computer Programmer Analyst


GEOLOGICAL INVESTIGATIONS SECTION
Harley Means, Assistant State Geologist


Kevin Burdette*, Geologist
Seth Bassett*, Environmental Specialist
Ken Campbell, Professional Geologist
Bob Cleveland, Engineer Specialist
Adel Dabous*, Environmental Specialist
Andrew Flor*, Geologist
Rick Green, Professional Geologist
Eric Harrington, Engineering Technician
Ron Hoenstine, Professional Geologist
Jesse Hurd, Laboratory Technician
Clint Kromhout, Professional Geologist


Michelle Ladle*, Geologist
David Paul, Professional Geologist
Dan Phelps, Professional Geologist
Frank Rupert, Professional Geologist
Guy Richardson, Engineering Technician
Andy Smith, Professional Geologist
Wade Stringer, Engineering Specialist
Eric Thomas, Engineering Technician
Farman Ullah*, Geologist
Christopher Williams, Professional Geologist


HYDROGEOLOGY SECTION
Rodney DeHan, Environmental Administrator


Alan Baker*, Professional Geologist
Scott Barrett Dyer*, Environmental Specialist
Katy Etheridge*, Laboratory Technician
Cindy Fischler, Professional Geologist


Tom Greenhalgh, Professional Geologist
Paul Hansard, Environmental Consultant
Chantel lacoviello*, Environmental Specialist
Stewart Norton*, Environmental Specialist


* Temporary or student employee









STATE OF FLORIDA
DEPARTMENT OF ENVIRONMENTAL PROTECTION
Herschel T. Vinyard Jr., Secretary



LAND AND RECREATION
Erma Slager, Acting Deputy Secretary




FLORIDA GEOLOGICAL SURVEY
Jonathan D. Arthur, State Geologist and Director




Bulletin No. 69 (Revised)




REGIONAL AND STATEWIDE TRENDS IN FLORIDA'S SPRING
AND WELL GROUNDWATER QUALITY (1991-2003)




By

Rick Copeland, Neal A. Doran, Aaron J. White, and Sam B. Upchurch


Published for the

FLORIDA GEOLOGICAL SURVEY
Tallahassee, Florida
2011





















































Printed for the
Florida Geological Survey


Tallahassee
2011

ISSN 0271-7832


ii











TABLE OF CONTENTS

Executive sum m ary ........................................ xi
B ack g roun d ............................................................................................... x i
A approach ................................................................................................. xii
R esu lts an d C on clu sion s .................................................................................... ....................... ......... ...... x iii
S p rin g s ................................................................................................................................... ......... . . . x iii
W ells.............................................................................................................................. . .. . ......... xv
C concerns ............. . .......................... ......... . .................................................. xvi
Rock-matrix and saline indicators: Saltwater encroachment.................................. xvi
N u trien ts ....... ......................................................................................................................... ............... x v iii
M o n ito rin g ................................................................................................................................... .. ....... ...... x v iii
R ecom m en d action s ...................................................................................................................... ............... x ix
R ecom m en nation Syn op sis......................................................................................................... ............... xx i
Research ............................................. ............ ............... xxi
Monitoring ...... ........................... ................ ...... ................. xxi
Introduction ................................ ................. ....................... 1
A ckn ow ledg em en ts ........... .......................................................................................................................................... 2
Florida's springs .......................................................................................................................................................................... 2
Classification of springs .................................. ........................................3
O offshore Springs.................. .........................................................5
Spring recharge basins................... .....................................................................6
Overview of the hydrogeology of Florida's groundwater ......................................................... 7
Quality of groundwater and spring water ...................................................................... 9
Natural factors affecting groundwater and spring-water quality...................................................9
Differences in spring- and well-water quality ........................................ .......... 10
Indicators of groundwater and spring-water quality problems..................... ........... ..........10
Spring selection process .................. ...............................................................12
Well selection process ...... ......................... .................................13
M methods ........................................ 16
D definition of trends............................................. ................. 17
Problems with trends ...................... ............................... ........... .. .......18
"Remaining the same" Possibility of missed trends .................. ........................................................ 18
Outliers ............................................................................................................................................................................ 19
Detection levels ...... ......................... .................................19
Sparse data...................................................................................................................................................................... 21
Analytes and indicators .................................................................... ......... 22
Sam ple collection and laboratory analyses ..................................................................................................... 23
A nalytes used in this study ................ .................................................................25
G rouping of analytes ................ .................................................................25
Description of analyte groups ......................................................................................26
F field analytes........................................................................................................................... . .. ......... 26
Rock-matrix analytes ............................................................................................... ..........26
Saline or saltwater analytes....................................27
N u trient an alytes ............................................................................2 7
Other analytes .......................................27
D a ta ........................................................................................................................................................................... 2 7
D ata sources.. . . . ............................................................ .................................................. ............... 2 8
D ata v verification ............................. .................................................2 8
Data preparation .........................................28
T im e seq u en c es............................... ...................................................................2 9
D ata used for analyses and explanation of appendices ................................................................................... 29
Information goals and data analysis protocols.................................................30
Inform action introduction.................................................................... 30
O verview of statistical analyses procedures ................................................................................................... 30











D descriptive statistics ...................................................... .... ............ ............ 30
Kruskal-Wallis, Mann-Whitney, and Wilcoxon rank sum tests.......................................... ...............31
Deseasonalized data.................. ...................33
Mann-Kendall test .........................................34
Season al K en dall test.................. ..................................................................................... ................... 34
Sen slope...... ............................................................... 34
Sig n test...... . . ........... ........................................................................................................ ..........35
Caveats and assumptions............................................................. 35
R results ..................................................................................... . ........... 36
Springs...........................................................................................36
Northwest Florida Water Management District................................................36
Rock and saline analytes, nutrients, and flow............. .........................................................36
Suwannee River Water Management District .................................. ......................40
Rock-m atrix and saline analytes ............................................................. 41
Flow ................................................................ 46
N utrient analytes..................... ...... ......................... ............... ......... ..........51
St. Johns R iver W after M anagem ent D district ............................................................................................. 54
Rock-m atrix and saline analytes ............................................................. 55
N utrient an alytes................ .......................................................59
South est Florida W after M anagem ent ..................................................................................................... 59
R ock-m atrix and saline analytes ..............................................................59
Flow ................................................................ 66
N utrient analytes........................................................................................................................ .........66
Field analytes........................................................... ..................... 67
W ells...... ...................... .................................... ............... 67
Northwest Florida Water Management District..................................... ......... 71
W after lev els an d pH ...............................................................................7 1
Suw annee R iver W after M anagem ent D district ........................................................................................... 74
W after lev els an d p H ............................................................................................................ ........... 7 4
St. Johns River Water Management District ............... ......................................................76
Southwest Florida Water Management District......................................... 79
South Florida Water Management District..................................... ......... 81
D istrictw ide spring trends........................................................................................... 81
Districtwide spring trends in the Suwannee River Water Management District ................ .. ............86
Districtwide spring trends in the St. Johns River Water Management District ................... ............... 86
Districtwide spring trends in the Southwest Florida Water management District ................... ................86
Statewide spring trends............................................................... 100
Constrained version of statewide trends ......................................... ................. 101
Independence of springs and w ells .................................... ....................... 102
Districtwide well-water trends.............................................. 103
Evidence of districtwide well water-quality trends Northwest Florida Water Management District.......... 104
Evidence of districtwide well water-quality trends Suwannee River Water Management District............. 108
Evidence of districtwide well water-quality trends St. Johns River Water Management District ........ ... 110
Evidence of districtwide well water-quality trends Southwest Florida Water Management District......... 113
Evidence of districtwide well water-quality trends South Florida Water Management District............. 117
State ide w ell w ater-quality trends....................................................... ............................. ................. 120
Comparison of strong statewide trends for groundwater and spring water................................... 120
Constrained version of statewide trends .............................................................. 121
D discussion .................................... .................... .. ........................................................................... 122
Major cause of statewide trends: Drought and consequential saltwater encroachment ................................... 123
D rou g h t............................................................................................... ...... ....... ................. 12 6
Rock-matrix and saline indicator evidence in spring-water quality............................. ............ 128
Rock-matrix and saline indicator evidence in well-water quality ............................................................ 128
Regional to sub-regional evidence of saltwater encroachment ................................... 130
G roun dw after w ith draw als.................................................................................................... ....................... 133
G round after sum m ary ............ ..................................................................... 134



V










M miscellaneous and im portant issues ............................................. ......................................................... 134
Falling well-water levels a districtwide and statewide problem in wells......................... ..............1.34
Nitrogen and phosphorous nutrients Regional and local problem in springs................................137
Nitrogen in the Northwest Florida Water Management District.......................... ....... ............... 137
Nitrogen in the Suwannee River Water Management District................................... ................. 139
Nitrogen in the St. Johns River and Southwest Florida Water Management Districts ................................148
M arion C county ......... .............................................................. ................ 148
R rainbow Springs G group .............................................................. .................................. . ........... 148
C itrus C county ............. . ........ ......................................................................................... ............... 149
K ing's B ay Springs Group ...................................................................................... ....................... 149
H om osassa Spring s G group ..................................................................................... ........................ 149
C hassahow itzka Springs G roup .................................................................................. ....................149
H ernando C county ..........................................................................149
W eeki W achee Springs G group ................................................................................ .......................150
Boat Springs, Bobhill, and Magnolia Springs ........... .... ... ........ .. .... .............. 150
Hillsborough County... ... ... ... ...... ............. .. .................... ... ..........150
Lithia Spring and B uckhorn Spring................................................................................................ 150
Summ ary of the nitrate problem in spring water .................................................. .............................. 150
Phosphorus in spring water by water management district................................................. 150
Suwannee River W ater M anagem ent .............................................................. 151
St. Johns River and Southwest Florida Water Management Districts ....................................................161
Comparison of coastal to inland and tidal to non-tidal springs.......................... ...... ............... 162
Global factors influencing Florida's ground ater........................................................ ......................... 164
Global long-term cycles: Atlantic mutidecadal oscillation.....................................................................164
Global short-term cycles: El Nio and La Nifia ..................................... ..........................................166
A c id r a in ................................................................................ .................................................. . .................... 1 6 8
Implications of future low rainfall and increasing state water demands.................... .. ............... 168
Implications regarding long-term sustainability ................................................................... .................... 169
R e fe re n c e s ......................................................................................................................................1 7 1
Appendices (Note: Appendices B2,C,E,H,I,J,K,L,and M may also be found at:
http://publicfiles. dep. state, fl. us/FGS/FGS Publications/B/B69Appendices/ )
Appendix A Relationships among spring flows, rock, and salinity indicator concentration for
selected springs....................... ............. ................ ...... ................. 179
Appendix B Glossary of terms and possible causes of trends .................. .......... ...................... 183
A appendix B l G lossary .............................. ...................................... ............................. .......... . .......... 183
Appendix B2 Interpretations of the origins of temporal trends in Florida's groundwater.......................191
Appendix C Well construction and location data ................................................................................... 196
Appendix D Spring locations................................................. ......... 197
Appendix E Statistics............................... .................................. ..........1....... 99
Appendix El Statistical m ethodologies.............................................................................................. ...... 199
Appendix E2 Macro codes for the Mann-Kendall tests and Sen slope..............................................206
A p p en d ix F A n aly tes ............................................................................................ .....................................2 0 9
A appendix F A nalyte descriptions ....................................................... ................................................209
Appendix F2- Analyte list with STORET codes........................................................................216
Appendix G Data quality assurance (QA) officer contact information .................................. ...............219
A ppendix H D ata from springs and w ells.................................................... .............................................. 220
A appendix I D descriptive statistics .................................................................................. .............................22 1
Appendix J- Seasonality results .....................................................................................................................326
Appendix K M ann-Kendall and Sen slope results................................................. .............................. 346
A appendix L D istrictw ide m aps .................................................................................. ................................347
Appendix L1 Northwest Florida Water Management District springs................................................. 349
Appendix L2 Northwest Florida Water Management District wells ....................................... .......350
Appendix L3 Suwannee River Water Management District springs...................................... ......354
Appendix L4 Suwannee River Water Management District wells........................................................359
Appendix L5 St. Johns River Water Management District springs............................................................364
Appendix L6 St. Johns River Water Management District wells.......................................................368
Appendix L7 Southwest Florida Water Management District springs................................................. 372



vi










Appendix L8 Southwest Florida Water Management District wells ............................... ............... 377
Appendix L9 South Florida Water Management District Wells........................................................... 382
A appendix M R rainfall and tem perature data.............................................................. ............................... 386
Appendix N Atmospheric deposition station information ........................................ .......................... 393


Figures

Figure 1. Schematics of freshwater/saltwater transition zone and possible mechanism for saltwater
in tru sio n ................................................................................................................................... x v ii
Figure 2. Inverse relationship of flow to rock and saline indicator concentrations ............................. xx
Figure 3. Locations of Florida's springs ............................................................................................... 4
Figure 4. O offshore springs .................................................................................................................... 6
Figure 5. Median nitrate concentrations in 13 selected first-magnitude springs ......................................
Figure 6. Location of springs analyzed in this report........................................................................ 14
Figure 7. Location of Temporal Variability Network (TVN) wells.................................... .......... ... 15
Figure 8. Illustration of three options for water-quality trends........................................................... 18
Figure 9. Exam ple of a spurious trend ............................................................................................... 20
Figure 10. Example of sporadic, unsystematic, and incomplete sampling ............................................. 22
Figure 11. Monthly water temperatures plotted over the 1992 calendar year for an imaginary well ........31
Figure 12. Example illustration of seasonality with a six-year cycle................................... ........... .. 32
Figure 13. Location of Wakulla Spring within the NWFWMD ......................................... ........... ... 37
Figure 14. Increasing rock analytes at Wakulla Spring ......................................................................... 38
Figure 15. Decreasing nitrates and water levels at Wakulla Spring ................................... ............. 39
Figure 16. Location of springs within the SRWMD ......................................................................... 40
Figure 17. Increasing rock analytes at Fanning and Gilchrist Blue Springs........................................... 42
Figure 18. Increasing rock analytes at Suwannee Blue and Troy Springs............................................. 43
Figure 19. Increasing rock analytes at Manatee and Hart Springs...................................... ........... 44
Figure 20. Increasing rock analytes at Poe and Lafayette Blue Springs ............................................. 45
Figure 21. Decreasing flow at Fanning and Hart Springs............................................................... 47
Figure 22. Decreasing flow at Rock Bluff and Hornsby Springs ....................................................... 48
Figure 23. Decreasing flow at Poe and Ruth/Little Sulfur Springs..................................... .......... .... 49
Figure 24. Decreasing flow at Troy and Telford Springs ............................................................... 50
Figure 25. D decreasing nitrates at Poe Spring ...................................................................................... 52
Figure 26. Increasing nutrient analytes at Poe and Lafayette Blue Springs....................................... 53
Figure 27. Location of springs within the SJRWMD ............................................................................. 54
Figure 28. Increasing rock analytes at Palm Springs ........................................................................ 56
Figure 29. Increasing rock analytes at Sanlando Springs ............................................................... 57
Figure 30. Increasing rock analytes at Wekiwa Spring............................................. ........................ 58
Figure 31. Decreasing phosphate concentrations at Palm and Starbuck Springs.................................... 60
Figure 32. Location of springs within the SWFWMD............................................................................ 61
Figure 33. Increasing saline analytes at Rainbow and Bubbling Springs............................................. 63
Figure 34. Increasing saline analytes for Hunter and Trotter Main Springs.................................. 64
Figure 35. Increasing saline analytes for Weeki Wachee and Bobhill Springs .................................... 65
Figure 36. Decreasing flow at Homosassa No. 1 Spring ............................................................... 67
Figure 37. Long-term flow trends at two SWFWMD springs .............................................................. 68
Figure 38. Increasing nitrates at Hunter and Magnolia Springs........................................ ........... ..... 69
Figure 39. Increasing nutrient analytes at Weeki Wachee and Boyette Springs..................................... 70
Figure 40. Location of wells within the NWFWMD........................................................................ 71
Figure 41. Decreasing pH and water levels in NWFWMD wells (#91 and #129) .................................72
Figure 42. Decreasing pH and water levels in NWFWMD wells (#131 and #312)................................ 73










Figure 43. Location of wells within the SRWMD ............................................................................ 74
Figure 44. Decreasing pH and water levels in SRWMD wells (#1943 and #2465) ............................... 75
Figure 45. Decreasing pH and water levels in SRWMD wells (#2585 and #2675) ............................... 76
Figure 46. Location of wells within the SJRWMD................................................................................. 77
Figure 47. Temperature and specific conductance in SJRWMD wells (#1417 and #1763)................... 78
Figure 48. Temperature and specific conductance in SJRWMD well (#1762) ...................................... 79
Figure 49. Location of wells within the SWFWMD......................................................................... 80
Figure 50. Decreasing pH and water levels in SWFWMD wells (#996 and #1087) ............................ 82
Figure 51. Decreasing pH and water levels in SWFWMD well (#707) ................................................. 83
Figure 52. Location of wells within the SFWMD............................................................................. 84
Figure 53. Decreasing pH and water levels in SFWMD wells (#6490 and #3398).............................. 85
Figure 54. Weighted mean temperature and rainfall data in Florida (1991-2003)................................ 125
Figure 55. Relative position of rock-matrix and saline analytes in the Upper Floridan aquifer system. 126
Figure 56. Fresh groundwater wedge before and during a drought...................................................... 127
Figure 57. Water level and pH relationships for a well with a falling water table ............................... 129
Figure 58. Weighted mean annual rainfall during Sequence A ............................................................ 131
Figure 59. Exam ple of aliasing ......................................................................................................... 136
Figure 60. Nitrate concentrations in Wakulla Spring between 1972 and 2005..................................... 137
Figure 61. Flow adjustment for nitrate in Troy Spring ......................................................................... 140
Figure 62. Flow adjustment for TKN in Troy Spring ............................................................................. 141
Figure 63. Flow adjustment for nitrate in Hornsby Spring ................................................................... 142
Figure 64. TKN versus time and log of TKN versus log of flow in Hornsby Spring ........................... 143
Figure 65. Flow adjustment for nitrate in Fanning Spring.................................................................... 145
Figure 66. Flow adjustment for TKN in Fanning Spring ...................................................................... 146
Figure 67. Flow adjustment for phosphorus in Troy Spring................................................................. 152
Figure 68. Flow adjustment for phosphate in Troy Spring ................................................................... 153
Figure 69. Flow adjustment for phosphorus in Ruth/Little Sulfur Springs........................................... 154
Figure 70. Flow adjustment for phosphate in Ruth/Little Sulfur Springs............................................. 155
Figure 71. Flow adjustment for phosphorus in Fanning Spring.............................................................. 156
Figure 72. Flow adjustment for phosphate in Fanning Spring................................................................ 157
Figure 73. Flow adjustment for phosphorus in Little River Spring ...................................................... 158
Figure 74. Flow adjustment for phosphate in Little River Spring ........................................................ 159
Figure 75. Flow adjustment for a phosphate in Hornsby Spring .......................................................... 160
Figure 76. Atlantic Multidecadal Oscillation and Florida spring flow ................................................. 165
Figure 77. Sea surface temperature, La Nifia, and El Nifio..................................................................... 167
Figure 78. Average monthly pH from seven atmospheric rain stations (1991-2003)........................... 169
Figure Al. Juniper Springs alkalinity versus flow............................................................................... 179
Figure A2. Wakulla Spring sodium versus stage ................................................................................ 180
Figure A3. Alapaha River Rise Fanning sodium versus flow............................................................ 180
Figure A4. Fanning Spring sodium versus flow .................................................................................. 181
Figure A5. Poe Spring sodium versus flow .................................................................................. 181
Figure A6. Homosassa No. 3 Spring sodium versus flow ................................................................. 182
Figure A7. Chassahowitzka No. 1 Spring sodium versus flow.......................................................... 182


Tables
T able 1. Spring M magnitude .................................................................................................................. 3
Table 2. Florida's spring classification system .................................................................................... 5
Table 3. A nalyte and indicator list..................................................................................................... 23
Table 4. Analytes and indicators displaying trends ...................................... ................................... 24
Table 5. Analyte Groups........................................................................... ....... .. ........... 26










Table 6. Example of descriptive statistics table.................................................... ........................... 31
Table 7. Suwannee River Water Management District spring names and abbreviations .................... 41
Table 8. St. Johns River Water Management District spring names and abbreviations ...................... 55
Table 9. Southwest Florida Water Management District spring names and abbreviations ................. 62
Table 10. Spring trends in the SRWMD (plus Wakulla Spring), Sequence A (1991-2003)................. 87
Table 11. SRWMD (plus Wakulla Spring) districtwide trends based on sign tests, Sequence A ............ 87
Table 12. Spring trends in the SRWMD (plus Wakulla Spring), Sequence B (1991-1997)................... 88
Table 13. Spring trends in the SRWMD, (plus Wakulla Spring) Sequence C (1998-2003)................. 89
Table 14. SRWMD (plus Wakulla Spring) districtwide trends based on sign tests, Sequence C........... 89
Table 15. Spring trends in the SJRWMD, Sequence A (1991-2003)................................... ............ 90
Table 16. SJRWMD districtwide trends based on sign test, Sequence A........................................... 90
Table 17. Spring Trends in the SJRWMD, Sequence B (1991-1997)................................... ........... 91
Table 18. Spring Trends in the SJRWMD, Sequence C (1998-2003)................................... ........... 92
Table 19. SJRWMD districtwide trends based on sign tests, Sequence C............................................ 92
Table 20. Spring Trends in the SWFWMD, Sequence A (1991-2003) .................................................. 93
Table 20. Spring Trends in the SWFWMD, Sequence A (1991-2003) (continued)............................. 94
Table 21. SWFWMD districtwide trends based on sign tests, Sequence A............................................ 94
Table 22. Spring Trends in the SWFWMD, Sequence B (1991-1997).............................. ............... 95
Table 22. Spring Trends in the SWFWMD, Sequence B (1991-1997) (continued)............................... 96
Table 23. SWFWMD districtwide trends based on sign tests, Sequence B......................................... 96
Table 24. Spring Trends in the SWFWMD, Sequence C (1998-2003).............................. ............... 97
Table 24. Spring Trends in the SWFWMD, Sequence C (1998-2003) (continued)............................... 98
Table 25. SWFWMD districtwide trends based on sign tests, Sequence C............................................ 98
Table 26. Spring flow from three stations in the SWFWMD ............................................ ............... 99
Table 27. Statewide spring trend summary by WMD and time sequence............................................. 99
Table 28. Statewide trends based on sign tests for 57 springs, Sequence A (1991-2003).................... 100
Table 29. Statewide trends based on sign tests for 57 springs, Sequence B (1991-1997).................... 100
Table 30. Statewide trends based on sign tests for 57 springs, Sequence C (1998-2003).................... 101
Table 31. Statewide trends in at least two WMDs, Sequence A (1991-2003)...................................... 101
Table 32. Statewide trends in at least two WMDs, Sequence C (1998-2003)...................................... 102
Table 33. Selected statewide analyte results, Sequence A (1991-2003)................................................. 103
Table 34. Well trends in the NWFWMD, Sequence A (1991-2003).................................................... 105
Table 35. Potential NWFWMD districtwide trends, Sequence A ........................................................ 105
Table 36. Well trends in the NWFWMD, Sequence B (1991-1997).................................................... 106
Table 37. Potential NWFWMD districtwide trends, Sequence B......................................................... 106
Table 38. Well trends in the NWFWMD, Sequence C (1998-2003).................................................... 107
Table 39. Potential NWFWMD districtwide trends, Sequence C......................................................... 107
Table 40. Well trends in the SRWMD, Sequence A (1991-2003).......................................................... 108
Table 41. Potential SRWMD districtwide trends, Sequence A ............................................................ 108
Table 42. Well trends in the SRWMD, Sequence B (1991-1997)........................................................ 109
Table 43. Potential SRWMD districtwide trends, Sequence B............................................................. 109
Table 44. Well trends in the SRWMD, Sequence C (1998-2003)........................................................ 110
Table 45. Potential SRWMD districtwide trends, Sequence C............................................................. 110
Table 46. Well trends in the SJRWMD, Sequence A (1991-2003)......................................................111
Table 47. Potential SJRWMD districtwide trends, Sequence A..................................... ........... ..... 111
Table 48. Well trends in the SJRWMD, Sequence B (1991-1997) ...................................................... 112
Table 49. Potential SJRWMD districtwide trends, Sequence B ........................................................... 112
Table 50. Well trends in the SJRWMD, Sequence C (1998-2003) ...................................................... 113
Table 51. Potential SJRWMD districtwide trends, Sequence C........................................................... 113
Table 52. Well trends in the SWFWMD, Sequence A (1991-2003)...................................................... 114
Table 53. Potential SWFWMD districtwide trends, Sequence A......................................................... 114










Table 54. Well trends in the SWFWMD, Sequence B (1991-1997)....................................................... 115
Table 55. Potential SWFWMD districtwide trends, Sequence B ......................................................... 115
Table 56. Well trends in the SWFWMD, Sequence C (1998-2003)...................................................... 116
Table 57. Potential SWFWMD districtwide trends, Sequence C ......................................................... 116
Table 58. Well trends in the SFWMD, Sequence A (1991-2003) ........................................................ 117
Table 59. Well trends in the SFWMD, Sequence B (1991-1997) ........................................................ 118
Table 60. Well trends in the SFWMD, Sequence C (1998-2003)........................................................ 119
Table 61. Potential SFWMD districtwide trends, Sequence C............................................................. 119
Table 62. Statewide trends based on sign tests: Sequences A, B, and C .............................................. 120
Table 63. Statewide spring-water quality summary for rock and saline indicators .............................. 121
Table 64. Statewide trends for at least three WMDs: Sequences A, B, and C for combined
ground ater resources ............................................................................................................ 122
Table 65. Constrained statewide spring and groundwater-quality summary ........................................ 123
Table 66. Summarized annual weather data in Florida (1991-2003).................................................... 124
Table 67. Annual weather data, four WMDs compared to the SWFWD (1991-2003)......................... 131
Table 68. Summarized rainfall, Sequence C minus Sequence B .......................................................... 132
Table 69. Relationships among concentration and loading of nitrate and TKN versus
time and flow in selected springs in the SRWMD.................................................................. 147
Table 70. Inland and Coastal Springs within the SRWMD and the SWFWMD.................................. 162
Table 71. Comparison of coastal and inland springs for upward trends during Sequence C,
excluding springs within the SJRW M D .................................................................................. 163
Table 72. Comparison of tidal and non-tidal springs for upward trends during Sequence C
in the SW FW M D ............................................................................................................ 164






BULLETIN NO. 69


REGIONAL AND STATEWIDE TRENDS IN FLORIDA'S SPRING
AND WELL GROUNDWATER QUALITY (1991-2003)
by
Rick Copeland (PG #126), Neal A. Doran,
Aaron J. White, Sam B. Upchurch



INTRODUCTION

Florida is blessed with some of the most spectacular springs in the world. There are
estimated to be over 700 springs in the state. People have been attracted to our springs since
before Florida became a state. From a scientific perspective, some of Florida's springs have
been sampled for over a century. The FGS published its first Springs of Florida bulletin
(Ferguson et al., 1947), which documented the chemical and flow data of the major springs. The
bulletin was revised in 1977 (Rosenau et al., 1977) and a new bulletin was generated in 2004
(Scott et al., 2004). In each revision, additional chemical data were presented. Unfortunately, as
beautiful as the springs are, not all is well. As Florida's population continues to grow, water-use
and land-use changes are reflected in our spring water. The quantity and quality of spring water
are both changing, and at least some of the changes are directly related to human activities.

Since the 1940s Florida's population has grown from about two million to about 18
million in 2000. This means that Florida has increased its population by a rate of about 600
people per day for those 60 years. In fact, between the years 2000 and 2005, the net rate of
increase has been over 700 people per day (U.S. Census Bureau, 2006). In the year 2000,
Floridians withdrew 3.14 billion gallons of groundwater daily (Marella and Berndt, 2005).
Marella and Berndt (2005) indicated that agriculture and public supply accounted for over 82
percent oft he groundwater use. Based on these data, each person used over 150 gallons per day
of groundwater. It is not surprising that an extensive increase in water use has followed
Florida's population growth. Neither is it surprising that there has been a noticeable decline in
the discharge of many of Florida's springs and that the intensive land-use changes have been
followed by a noted deteriorations in spring-water quality. Scott et al. (2004) mentioned that one
of the most notable deteriorations has been the increase in nutrient concentrations in spring
water. While nutrients such as nitrogen and phosphorous are required by aquatic organisms for
growth and reproduction, when the concentrations are found to be higher than natural levels,
problems can arise. Since the 1970s, concentrations of nitrate, a soluble form of nitrogen, have
been found to be increasing in a number of Florida springs (Florida Springs Task Force, 2000).

Over the past several decades, flows in Florida's springs are declining and water quality
is degrading. The primary chemicals of concern are nutrients, including soluble forms of
nitrogen and phosphorus.

In order to improve and protect our springs, the Florida Springs Task Force (2000) made
a series of recommendations to the Governor of Florida. One was that Florida should implement
spring monitoring programs in order to detect and document long-term trends in water quality.
In addition, it was recommended that the state should conduct research in order to determine the









PREFACE


FLORIDA GEOLOGICAL SURVEY

Tallahassee, Florida
2011


The Florida Geological Survey (FGS), is publishing as its Bulletin No. 69 (Revised),
Regional and Statewide Trends in Florida's Spring and Well Groundwater Quality (1991-2003)
(Revised), authored by Rick Copeland, Neal A. Doran, Aaron J. White, and Sam B. Upchurch.

After the publication of the original publication, several minor errors were discovered.
Most errors were found in the statistical tables. This bulletin summarizes the results of a multi-
year cooperative investigation on spring and groundwater quality between the Florida
Department of Environmental Protection's FGS and the Bureau of Watershed Management,
Division of Environmental Assessment and Restoration. The data presented will be useful to
scientists, planners, and citizens in understanding the quality of Florida's groundwater resources.




Jonathan D. Arthur, Ph.D., P.G.
State Geologist and Director
Florida Geological Survey









EXECUTIVE SUMMARY


Background

Over the past several decades, it has been observed that the flows in Florida's springs are
declining and water quality is degrading. The primary chemical concern is considered to be
increased nutrients, including soluble forms of nitrogen and phosphorus. The sources are
predominantly from animal waste, human waste, and from the synthetic fertilizers used on lawns,
golf courses, or for agricultural activities.

In recognition of these issues, the Secretary of the Florida Department of Environmental
Protection (FDEP) directed the formation of the Florida Springs Task Force in 1999. The multi-
agency task force consisted of 16 scientists, planners, and citizens who were concerned about the
"environmental health" of Florida's springs. By 2000 the task force made a series of
recommendations to protect and restore Florida's springs. They are outlined in detail in Florida's
Springs: Strategies for Protection and Restoration (Florida Springs Task Force, 2000). Two of
the recommendations were to:

(1) Implement springs monitoring programs to detect and document long-term
trends in water quantity and quality

(2) Conduct research that will allow cause-and-effect relationships to be
established between land use and water management activities.

The purpose of monitoring is to both support research efforts and to confirm the effectiveness of
spring protection efforts. As a direct result of the first recommendation, the Florida Geological
Survey (FGS) took the lead in implementing a spring monitoring program. By 2004 it published
the latest Springs ofFlorida bulletin-a descriptive overview of Florida's springs.

The main purposes of this document are to: (1) determine trends in groundwater where
sufficient data are available; (2) establish prototype methods for evaluating and reporting trends
for future applications; and (3) enhance the efforts of determining cause-and-effect relationships
between anthropogenic activities and the resulting spring-water quality and quantity on regional
(water management district-wide) and statewide scales. The reason for the latter is that many
other publications have addressed the causes of trends on an individual spring basis. If we
attempted to develop an exhaustive list of possible causes of trends for each spring, it could take
many years to accomplish. We decided to emphasize regional and statewide scales. An endeavor
of this nature has never been attempted. If regional or statewide trends were found, the causes
and possible solutions to those causes may become the highest priority water management issues.

In order to fully comprehend the implications of trends in springs, a thorough
understanding of the behavior of groundwater in wells is also necessary. In 1983, the FDEP
began a statewide groundwater quality monitoring network (Florida Statutes 403.063). Scott et
al. (1991) stated that the purpose of the network was to detect or predict contamination of
Florida's groundwater resources. Currently, several thousand wells are included in the network.
However, a subset of the wells are conducive to trend analysis (the Temporal Variability









Network, or simply the TV Network). Since the FGS was asked to evaluate data for trends from
springs, it followed to simultaneously do the same for groundwater from TV Network wells.

Approach

The FGS spring monitoring program commenced operations in 2001. For many of the
springs, previous samples had never been collected, so long-term trend analyses were not
possible. However, the FGS contacted each of the four northern water management districts
(WMDs), the U.S. Geological Survey (USGS), and programs within the FDEP to request copies
of their historical spring-water quality and quantity data. The entities each graciously delivered
data to the FGS for analyses. It should be noted that the South Florida Water Management
District (SFWMD) had insufficient data for trend analyses.

The FGS obtained sufficient data, meeting preset criteria, from 58 springs and 46 wells
for the period January 1991 through December 2003. For reference, the study was divided into
three time sequences. Sequence A represents the entire length of the study (1991-2003).
Sequence B represents the January 1, 1991 December 31, 1997 time frame, while Sequence C
represents January 1, 1998 December 31, 2003. The two shorter sequences were used to assist
in identifying and evaluating shorter-term trends. As it turns out, Sequence B coincided with
relatively normal rainfall, whereas Sequence C covered a time that Florida experienced an
extended drought.

The analytes (constituents of interest) for this report can be broken down into five
groups: (1) nutrients, (2) saline (or salt-water), (3) rock-matrix (or rock), (4) field, and (5) other.
Of these, the three major groups are nutrients, saline, and rock-matrix. Nutrients are compounds
that are essential for the growth of living organisms. Unfortunately, high concentrations in
spring-water can adversely affect the biota in spring runs. Saline analytes are related to salts.
The most significant sources of salt are from the ocean or deep groundwater in Florida's
aquifers. High concentrations of saline compounds (e.g. sodium or chloride) can restrict the
usage of water. Rock-matrix analytes have their sources in the aquifer material (e.g. limestones
and dolostones). They occur naturally and, unless they occur in extremely high concentrations,
are generally not harmful to our environment. The field and other analyte groups consist of
miscellaneous constituents that are useful in explaining trends in other analytes.

Think of a trend as a direction of movement (Berube and Boyer, 1985). Although there
are many secondary questions that pertain to trends, trend analysis can be broken down to one
fundamental, primary question, "over time, are conditions changing (getting better or getting
worse), or are they remaining the same?" One can think in terms of concentrations of water
quality (measured by analytes) or water quantity (measured by flow or water levels). Subjective
descriptions-such as better, worse, and remaining the same-are based on objective changes
over time, or trends.

Throughout this report the term significant refers to statistical significance. Some of the
trends reflect very important changes in water quality, whereas some only represent relatively
minor changes in water quality that are not indicative of impending problems. If, during our
analyses, a trend was discovered, it was based on statistical significance. That is, within a









predefined probability, we do not expect the trend to occur randomly. Since not all of the
audience of this report is familiar with the statistical procedures employed, we decided to
simplify the procedures to the extent practical. For this reason, most analyses were restricted to
linear trends, using nonparametric techniques. Data were checked for seasonality, and if found,
were deseasonalized prior to trend analyses using a method recommended by the U.S
Environmental Protection Agency (EPA, 1989). Trend analyses were conducted using the
Mann-Kendall test, while the rates of change over time were determined using the Sen slope
(Gilbert, 1987).

Results and Conclusions

The most important conclusion to be derived from this report is that Florida springs truly
represent the "canary in the coal mine" with respect to assessing regional groundwater quality in
Florida. As will be summarized, springs are apparently much better at indicating over-all change
in a groundwater flow system than wells.

Monitoring wells only allow for the sampling of a discrete portion of the water in an
aquifer. They limit detection to a particular depth interval and a relatively limited spatial extent.
Karstic aquifers are especially limited in this respect as fractures and cavernous conduits may
direct water flow around or below the location of a monitoring well. On the other hand, the
quality of water discharging from a spring is an integral of the water quality of the total flow
system within a springshed. This water is derived from deep and shallow flow systems and
conduit and diffuse flow. Furthermore, the water quality, and flow, data are weighted according
to the relative importance of the flow systems and chemical sources within the springshed. As a
result, springs appear to be much better at detecting regional changes in a springshed water
quality than do wells. This conclusion is supported by the fact that water-quality trends were
much more obvious in spring data than in well data.

Springs

Of the analyte groups, rock-matrix and saline analytes had the greatest frequency of
trends. Both analyte groups showed strong negative correlations with spring flow. For example,
as spring flow decreased saline and rock-matrix analyte concentrations increased. The
relationship was observed throughout the state. The greatest increases in the concentrations of
rock-matrix and saline analytes occurred during a drought that occurred between late 1998 and
mid 2002.

There are several probable explanations and all can be a result of the drought. First,
during the drought there was less rainfall, and consequently there was less surface-water flow.
In karst terrains, much surface-water flows directly to groundwater through sinking streams
(swallets). Typically, this rapidly recharged groundwater is transmitted in well-developed
subsurface conduits. Thus, there is very little contact time with the aquifer matrix before it
discharges from springs, and it tends to have lower concentrations of rock-matrix analytes.
During a drought, there is a decrease in the proportion of freshly recharged "surface water." This,
at least partially explains the correlation between decreased spring discharge and increased
concentrations of rock analytes.










A second probable explanation is related to the removal of older, saline-rich and usually
more mineralized water from storage, often in the deeper portions of the Florida's aquifer
systems. Beneath the state of Florida lies a "lens" of fresh water, which is replenished by
rainfall. Freshly recharged water is flushed through Florida's karstic (sinkholes, caves, springs
etc.) aquifers relatively quickly to springs. In contrast, the deeper water is older (Upchurch,
1992; and Katz, 2004). Because it has been in contact with the aquifer matrix for a relatively
long period of time, the aquifer water has had a longer time to "pick up" dissolved matrix
material constituents such as calcium and magnesium, especially in the Floridan aquifer system.
With longer residence times, the older water tends to have higher concentrations of rock-matrix
material.

A third explanation is similar to the second. Older, mineralized residual saltwater, was
never fully flushed from the rock interstices in some portions of Florida (Johnson and Bush,
1986). With less rainfall during the drought, the water levels in the aquifers were lowered, and
the size of the freshwater "lens" decreased. With decreasing freshwater potentials (e.g., water
levels) the deeper and older connate water can find its way upward toward aquifer discharge
points, such as springs. Thus, during the drought, increased concentrations in rock-matrix and
saline analytes were observed, along with decreases in spring discharges. The trends were
statewide in scale. The magnitude of scale was the most surprising and most significant finding
of the study.

After the driest portion of the drought (2002), Florida's hydrologic conditions began to
recover and the concentrations of both types of analytes began to decrease, as rainfall, recharge,
and spring flow began to increase. The inverse relationship between spring-water discharge, and
both rock-matrix and saline analyte concentrations, was also observed in a study by Katz (2004).
In addition, Katz also found a positive correlation between concentrations of rock and saline
analytes and spring-water age.

Nutrients in groundwater discharging from springs were one of the most important
concerns of the Springs Task Force. Evaluation of trends in this report revealed that nutrient
trends in springs had an uneven, or patchwork, distribution across the state. That is, both
increasing and decreasing nutrient trends were common and were observed throughout Florida.
This suggests that the trends were often related to local land-use and water-use activities. As
such, most nutrient concentrations observed in springs are localized and should be analyzed in
relation to the corresponding springshed.

Nitrogen and phosphorus comprised the most frequent nutrient exhibiting trends.
Nitrogen in the form of nitrate (nitrate plus nitrite as N) had the greatest frequency of increasing
(degrading) trends. However, some springs actually had decreasing nitrate trends. Phosphorus,
as total phosphorus and orthophosphate, had both increasing and decreasing trends, depending on
the springshed.

Note that decreasing nutrient trends are not necessarily good news. During the drought,
an important observation was that some nitrate concentrations had positive correlations with
spring flow. One possible explanation is that nitrogen can be stored in the soils of Florida's
springsheds (Bruland et al., 2008). During the drought, soils may have stored the nitrogen









originating from fertilizer applications and the nitrogen did not find its way to the groundwater
regime. When rainfall conditions return to normal, the soils will release the nitrogen and
concentrations in spring water will eventually increase. On a similar note, decreases in
phosphorus in some areas may likewise not be a reflection of improved management. It is
possible that the upward migration of older water, with different chemistry, reduced the
phosphorus concentrations in many springs. If so, reduction of phosphorus could simply be a by-
product of mixing with deeper, higher pH water-not an improvement in water quality. This
mechanism is discussed by Hem (1985) and by Odum (1953). They indicated that the solubility
of phosphorous can be controlled by pH. Dissolved phosphorous is generally more abundant in
lower pH (more acidic) water. Conversely, higher pH (more basic) water contributes to the
precipitation of phosphate and lowers the concentration of dissolved phosphorous in
groundwater.

Wells

Within Florida's aquifers, the flow paths of spring-water can potentially be from both
deep and shallow sources. Conversely, wells typically are drilled to a specific depth in an
aquifer. Consequently, flow paths of well water are from a much narrower thickness of the
aquifer, relative to spring water flow paths. Although there are exceptions, most of the 46 wells
used in this study generally tap only the shallower portions of the aquifers. The wells tend to be
less than 30 m (100 feet) deep. Because of the shallower depth, the older, deeper, and more
mineralized deeper aquifer water had a lower probability of being observed in the shallow wells.
Thus, rock-matrix and saline trends were not seen as frequently in wells as in springs.
Nevertheless, decreasing trends in water levels within wells were common. In addition, pH-a
field analyte-had a positive correlation with water levels; as water levels in wells decreased, so
did pH.

A possible explanation for this positive correlation is as follows. Well intake zones for
most wells in Florida are generally set at specified depths below the lowest predicted aquifer
water levels. This is done in order to guarantee water to the well during drought conditions.
During dry times the upper surface of the saturated zone is lowered downward toward the
uppermost point of the intake zone. For the aquifers tapped by the 46 shallow wells used in this
study, most recharge is from water, typically rainfall, penetrating the land surface and moving
downward through the soil to the groundwater regime. Rainfall has a lower pH than most
aquifer water. The pH is lowered further as rainwater picks up carbonic acid as it moves
downward through Florida's soils (Freeze and Cherry, 1979; and Upchurch, 1992). Therefore,
as the water table (or the potentiometric surface in confined aquifers) drops, generally the
younger, freshly recharged water with lower pH has an increasing probability of entering well
intake zones. As such, the lowering of the water table is a potential cause for decreasing trends
in pH values across the state during the drought. A detailed description of this hypothesis, along
with other related hypotheses, is discussed in the body of this report.

Another field analyte that displayed a trend was well water temperature. Between 1991
and 2003, its temperature typically increased; the reason is believed to be an increase in air
temperature. Air temperature increased across Florida (Southeast Regional Climate Center,
2006). Since the wells used in this report tend to be shallow, it is believed that well water readily









responded to air temperature changes. On the other hand, the sources of spring water are from
shallow and deep portions of our aquifers. Deeper water tends not to respond to changes in air
temperature. Thus, spring water displayed fewer temperature trends than did well water.

Concerns

Rock-Matrix and Saline Indicators: Saltwater Encroachment

Saltwater encroachment is the displacement of fresh groundwater by the advance of
saltwater due to its greater density (Neuendorf et al., 2005). It can occur during a drought when
recharge declines and the freshwater "lens" shrinks in size. Over geologic time, it can occur with
sea-level rise. It can also occur when excessive groundwater pumping causes the advancement
of saltwater. Freeze and Cherry (1979) use the term saltwater intrusion as the migration of
saltwater into freshwater aquifers under the influence of groundwater development (pumping).
For this paper, we use the term intrusion to indicate a man-induced process and use the term
encroachment to make no distinction between natural and man-made causes.

Figure 1 (top) displays the unconfined, surficial aquifer system. The saltwater/freshwater
interface is represented by a transition zone. During a drought, the water table lowers, the
transition zone migrates inland and the thickness of the freshwater zone ("lens") decreases in
size.

In his work in northeastern Florida, Spechler (2001) mentioned several possible
mechanisms that can drive encroachment and intrusion. During the drought, they included: (1)
the movement of "un-flushed" pockets of relict seawater within the Floridan aquifer system, (2)
the landward movement of the freshwater/saltwater interface, (3) regional upcoming of saltwater
below pumped wells, and (4) the upward leakage of saltwater from deeper, saline water-bearing
zones through confining units. The latter can occur where the units are thin or are breached by
joints, fractures, collapse features, or other structural anomalies. Examples are displayed in
Figure 1 (bottom).

During the 1999-2002 drought, the flows in many springs decreased, and one spring
(Hornsby Spring) stopped flowing altogether for a period of time. In addition to the decreased
rainfall, there was an increased demand for groundwater (Verdi et al., 2006). The drought and
the subsequent lowering of aquifer water levels resulted in decreasing spring flows throughout
the state. The increased demand for groundwater during the drought exacerbated the problem in
some of the springs. The increasing trends in rock-matrix analytes during the drought is an
indication of a reduction in size of the fresh water "lens" underlying the state and an indication
of saltwater encroachment. Because the concentrations of saline analytes increased almost
everywhere in the state during the drought, it is an indication that encroachment occurred on a
statewide scale.






























i _,. ....... ;.i:. ._ ',T w %.-. .
----' -' %1y;*^ ^t ^ 0.1.%
.... -*,...--... ;.- ......' .
...*. 2 r,$ . .#Xt*',,.. ;**...*., ;,. :j ..i '.^
l..:....- ,. ... intermediate u. ,i n ..u.n. .. ..-. ..
,, ~. . ........,; . ..:.; ,....: : .. ..: .. '..
". : . :-. ,.-.- -, -. ; :.. ii`. ,


Modified from Cooper (1964)


UPPER pFLORO'NA





- --\ LOWE




UNDIFFERENTIATED CONFINING.UIIT


Modified from Spechler (2001)


Brackish water
- Saltwater
SI Freshwater


----- Direction of ground-water flow


Figure 1. Schematics of freshwater/saltwater transition zone and possible mechanisms
for saltwater/freshwater intrusion. Note Cooper (top) represents the saltwater/freshwater in-
terface in the surficial aquifer system as a transition zone, whereas Spechler (bottom) depicts it
as a sharp boundary.


xvii


Not to scale


Not to scale


EXPLANATION









The 1998-2002 drought was one of the worst historical droughts to affect Florida (Verdi
et al, 2006). Except for south Florida, during the drought the deficit rainfall ranged from about
10 inches in southwest Florida to almost 40 inches in northwest Florida. In order to make up for
the drought, groundwater pumping increased, largely for irrigation (Verdi et al., 2006). Because
an increase in groundwater pumping occurred during one of worst droughts, it is likely that
human-induced saline intrusion took place and contributed to the increase in saline and rock-
matrix analyte trends. On a statewide scale, the extent and severity of the intrusion is difficult to
quantify. However, within the northern portion of the SWFWMD, a water budget and a regional
groundwater flow model indicated that the increase [0.3 cm/yr (+0.1 in/yr)] in groundwater
withdrawals was less than 2.0% of the decline in recharge due to the decrease [18.3 cm/yr (7.2
in/yr)] in rainfall (Ron Basso, Southwest Florida Water Management District, personal
communications). Nevertheless, intrusion should be a concern. If another drought of this
magnitude occurs, depending on the amount of increased pumping, it could potentially have
adverse effects on the long-term sustainability of Florida's groundwater resources.

Nutrients

The Florida Springs Task Force (2000) indicated that Florida's springs face serious
threats due to rapid and continuing population growth. The state's increasing population has
resulted in extensive land-use changes, increased demand for freshwater, and an increased use of
fertilizers. As rainfall seeps through the soils, and moves the nutrients into Florida's underlying
aquifers, it creates localized degradation in Florida's groundwater resources. A report regarding
FDEP's Springs Initiative Program efforts (Florida Department of Environmental Protection, and
Florida Department of Community Affairs, 2002) noted that nitrates have increased since the
1970s. It also noted that over the past 30 years many of Florida's springs experienced an
increase in nuisance algae and invasive exotic aquatic plants. These plants tend to thrive on
excess nutrients and decrease dissolved oxygen levels in spring runs.

Analyses for the 1991-2003 time frame indicated that trends in nutrient concentrations in
Florida's spring-water increased in some springs, while they decreased in others. It is
encouraging to note that there are some decreasing trends. The fact that nutrients (especially
nitrate) tended to increase is an indication that some land-use management practices warrants
reevaluation. But as noted previously, the relationship of these apparent decreasing trends may
be related to diminishing spring flow.

Monitoring

The current study revealed an inverse relationship between rock and saline indicators and
spring flow. The relationship was observed across the state (Figure 2). Note that changes in
spring-water quality often lag behind changes in spring flow. For detail, the smaller charts
depicted in Figure 2 have been enlarged and can be found in Appendix A.

Historically, the WMDs and the USGS have monitored spring-water quality and
discharge. With the commencement of the Springs Initiative, FDEP joined in the monitoring
efforts. Considerable efforts were made to eliminate inconsistencies in monitoring activities.
Unfortunately, at the beginning of the study, the efforts were not always successful. Specifically,
the WMDs, USGS, and FDEP did not always monitor the same analytes, use the same laboratory


xviii









analytical methods, or collect flow data on the same date as chemical and biological data were
collected. In addition, they often sampled at different frequencies. All these inconsistencies
made statewide comparisons very difficult. The results of this investigation demonstrate that
statewide monitoring must continue. For this reason, it is hoped that, in the future, the state can
find ways to minimize monitoring inconsistencies.

Recommendations

One of the most surprising and most significant observations of this study was that rock-
matrix and saline analytes were increasing almost everywhere in Florida's springs, especially
during the drought of Sequence C (1998-2003). Saltwater encroachment is a hugely significant
issue. Saltwater can restrict water use and negatively affect freshwater ecology, and can
adversely affect the long-term term sustainability of Florida's water resources. The relationships
among rainfall, recharge, groundwater withdrawals, groundwater quality and levels, plus spring-
water flows warrant further research, as does the effects of global climate change.

The concentrations of at least one nutrient (nitrate) in numerous springs have been
excessively increasing since the 1970s (Florida Department of Environmental Protection and
Florida Department of Community Affairs, 2002). One of the most visible changes in spring-
water quality has been the increase in nuisance algae and invasive exotic aquatic plants. What is
the relationship between the increases in nutrients and the nuisance plants? Further research is
needed. In addition, land-use management practice modifications are needed in order to reverse
the increasing trends. It is beyond the scope of this study to elaborate on the management
strategies. For a detailed discussion of many of the available strategies, an excellent reference is:
Protecting Florida's Springs Land Use Planning Strategies and Best Management Practices
(Florida Department of Environmental Protection and Florida Department of Community
Affairs, 2002).

Spring-water quality is sensitive to changes in spring flow and to aquifer water levels.
Springs represent excellent natural sampling locations for monitoring saline encroachment. It is
recommended that, to the extent practical, springs should be incorporated into a statewide
saltwater encroachment monitoring network. The results of the spring monitoring could then
potentially be used to supplement well monitoring networks that are often used for saltwater
encroachment purposes.

Although the monitoring of springs and wells is critical for the sustainability of Florida's
water resources, not all analytes of concern are sampled. Synthetic organic, other supplementary
analytes supplementalss), as well as biological indicators, should be included on the monitoring
lists. It should be understood that supplementals are expensive to collect and analyze, and for
these reasons, they can only be sampled on a low frequency basis. It should also be noted that
supplemental monitoring is often determined by site-specific issues. For example, pesticides
may only be detected at certain times of the year or in certain locales, determined by land use
conditions. Supplementals such as pesticides, synthetic organic compounds, and trace metals
should occasionally be sampled.

























Poe Spring


L1 I1


A ^ 1


Homnassa No. 3 Chasmowitza No. 1
i-nuu~nr /
-I ?I J '* ..



SCALE
0 50 100 200 Miles
II I' I 'I Saine/Rock Indicator
0 75 150 300 km Flow/Stage




Figure 2. Inverse relationship of flow to rock and salinity indicator concentrations. Darker
lines represent water levels (whether by stage or spring flow); lighter lines represent saline or
rock-matrix indicators (sodium or alkalinity). Time axes vary. The graphs indicate reciprocity
between decreases in water levels and increases of salinity, regardless of location in the state.
Florida's spring-water chemistry shows a high sensitivity to changes in flow(See Appendix A
for enlarged versions of inset charts).









It is critical that evaluations of spring water and groundwater be clearly disseminated to
the public as efficiently as practical. One efficient method is the use of indices. Stock exchange
indices have been used in the financial community for many years. Groundwater quantity
indices are used by the Edwards Aquifer Authority in Texas. As an example, the authority use
real-time water levels in the Bexar County Index well as an index (indicator) for the entire
county. During dry times, as water levels fall, water restriction measures may be invoked by the
authority. When water levels rise, the restrictions are lifted (Edwards Aquifer Authority, 2006).
There are several potential indices that could be developed for use in Florida. If one or more
indices were developed, they have the potential to become very useful in informing the public
about the status of our springs. However, in order to be viable, buy-in by both the public and
scientific communities are essential. Hopefully, indices will be adopted in the future.

It is essential that technical reports regarding the results of analyses be generated
frequently and in a relatively short time frame. It is acknowledged that it takes a considerable
amount of time for an initial report to be generated. However, after the initial report, the lag time
between sample collection and report generation should reduce considerably. In addition,
subsequent reports using similar interpretative methods could employ computer programs to
create "boiler plate" reports as quickly as analytical data are received from a laboratory.

Standardized spring and well sampling throughout the state is a critical need. If
standardization is achieved, analyses of trends in the future will be much easier to conduct. This
in turn will make the resulting interpretations more comprehensive, and the dissemination of the
interpretive results will be more meaningful to the public. Specific aspects of the standardization
effort include: core and supplemental water-quality analytes and indicators, data reporting,
sampling and laboratory quality assurance, data management, data analysis, and assessment
reporting,

Recommendation Synopsis

Research

Determine the relationships between increases in nutrients and nuisance plants/algae

Determine the best land-use management practice needed in order to reverse increasing
nutrient trends

Improve our understanding of the relationships among: (1) rainfall, (2) recharge, (3)
groundwater withdrawals, (4) groundwater quality and levels, and (5) spring-water
quality and discharge

Develop a "spring environmental health" report card.


Monitoring

Recognize the importance of springs in saltwater encroachment monitoring and
incorporate spring monitoring into that effort










* Add supplemental analytes to spring monitoring lists on a periodic basis

* Develop spring water-quality and quantity interpretative reports on a regular basis

* Adopt area-wide randomized spring sampling on a periodic basis in order to produce a
synoptic report of all springs in Florida

* Continue to use the Florida Water Resource Monitoring Council to increase monitoring
efficiency. Topics for discussion should include:

core and supplemental water quality analytes and indicators
possible development of a "spring environmental health" index
possible implementation of the random sampling of springs
sampling and laboratory quality assurance
data management
data analysis
assessment reporting


xxii






FLORIDA GEOLOGICAL SURVEY


cause-and-effect relationship between land-use and water-management activities, and the
resulting changes in spring-water quality and quantity.

As a result of the Florida Spring Task Force's first recommendation, the FGS was asked
to evaluate historical spring data in order to detect and document trends in spring-water quality
and quantity. This document reports the findings of analyses for trends in springs, using data
from the Springs Initiative of FDEP, the WMDs, and the USGS spring sampling programs.


ACKNOWLEDGEMENT S

The authors wish to acknowledge a number of individuals and to thank them for their
assistance. From the Florida Department of Environmental Protection, Division of
Environmental Assessment and Restoration, Bureau of Watershed Management, we would like
to thank Gail Sloane and Jay Silvanima for supplying the authors with data from the TV Network
and their miscellaneous assistance on numerous occasions. Laura Morse assisted in supplying
quality assurance information. Debra Harrington, Rick Hicks, Gary Maddox, Jay Silvanima,
Chris Sedlacek and Paul Hansard (now with the Colorado School of Mines) supplied numerous
editorial comments during the course of the project. From the FGS, we would like to thank
Doug Calman, Rick Green, Tom Greenhalgh, Harley Means, Frank Rupert, Tom Scott, and
especially Ellen McCarron, for their many helpful editorial comments.

We would also like to acknowledge the efforts of numerous people from the water
management districts who supplied us with spring data and constructive comments regarding the
document. In particular the authors would like to thank Kris Barrios, Angela Chelette, Tony
Countryman, Kevin De Fosset, Tom Pratt, and Nick Wooten, from the Northwest Florida Water
Management District (NWFWMD); Ron Ceryak and David Hornsby of the Suwannee River
Water Management District (SRWMD); and Ron Basso, Eric DeHaven, David DeWitt, Joe
Haber, Robert Peterson, and Roberta Starks from the SWFWMD.

We would like to thank Brian Katz and Stuart Tomlinson of the USGS. Both individuals
supplied data and other information that was invaluable to the project. We would like to thank
Dr. Xu-Feng Niu of the Florida State University, Department of Statistics, for contributing to the
section regarding statistical methodologies and to Rich Smith, a graphic designer, who assisted
with making many of the figures.


FLORIDA'S SPRINGS

Scott et al. (2004) presented an excellent overview of Florida's springs. Although they
did not specifically evaluate trends, the authors described hundreds of Florida's springs,
including a description of their water quality. In doing so they described many aspects that
control the water quality and quantity of groundwater. With this in mind, their work can be
considered a precursor to the present trend analysis document. With the authors' permission,
much of the following introduction from the sections labeled "Florida's Springs" to "Differences
in Spring and Well Water Quality" are paraphrased from their work, "Springs of Florida."






BULLETIN NO. 69


Many terms relating to hydrogeology and springs may be unfamiliar to the reader. For this
reason a glossary of terms is found in Appendix Bi. In addition, Appendix B2 elaborates on the
sources of the analytes discussed in this report, along with the probable causes for the trends
observed.

Spring-water discharge comes primarily from the Floridan aquifer system, which is also
the state's principle source of groundwater. The springs provide a "window" into the aquifer,
allowing for a measure of the health of the aquifer. Chemical and biological constituents that
enter the aquifer through recharge processes may negatively affect the water quality in aquifers,
as well as the flora and fauna of springs and spring runs. The declines in water quality can be
directly attributed to Florida's increased population and changing land-use patterns (Florida
Springs Task Force, 2000).

Classification of Springs

Springs are most often classified on the amount of flow or discharge of water. The flow-
based classification listed in Table 1 is taken from Meinzer (1927) (Table 1). One discharge
measurement is all that is required to place a spring into one of eight magnitude categories.
However, it should be understood that each spring exhibits a variable discharge, depending upon
rainfall, recharge and groundwater withdrawals within their recharge areas. This can result in a
spring being classified as a first magnitude spring at one point in time and a second magnitude at
another. In the past, a spring assigned a magnitude when it was first described and continued
with that magnitude designation even though the discharge may have changed considerably over
time. To alleviate this confusion, the FGS (Copeland, 2003) adopted a system using the
historical median of the flow measurements to classify a spring's magnitude. Using the new
system along with the Meinzer system, a spring's magnitude is now based on the median value
of all annual median discharge measurements for the period of record. Of the over 700 springs
inventoried by the FGS, there are 33 first-magnitude springs, 191 second-magnitude, and 151
third-magnitude springs. Most are located in the northern portion of the state (Figure 3).

Table 1. Spring Magnitude.
Discharge
Magnitude Metric Units English Units
1 > 2.832 cms > 100 cfs (> 64.6 mgd)
2 > 0.283 to2.832cms > 10 to100 cfs (> 6.46 to 64.6 mgd)
3 > 0.028 to 0.283 cms > 1 to 10 cfs (> 0.646 to 6.46 mgd)
4 > 0.0063 to 0.028 cms > 100 gpm to 1 cfs (> 100 to 448gpm)
5 > 0.631 to6.308 1ps 10 to 100 gpm
6 > 0.063 to 0.631 lps > 1 to 10 gpm
7 > 0.473 to 3.785 1pm > 1 pint/minto 1 gpm
8 < 0.473 1pm < 1 pint/min
cms = cubic meters per second Ips = liters per second
cfs = cubic feet per second pint/min = pints per minute
mgd = million gallons per day 1pm = liters per minute
gpm = gallons per minute






FLORIDA GEOLOGICAL SURVEY


* 462 FGS Visited Springs
O Springs from all Databases
Water


0 25 50 Miles N

0 50 100 Kilometers
.7 .' "


Figure 3. Locations of Florida's springs (From Scott et al., 2004).


A second spring classification system is also in use. The Florida Spring Classification
System (Copeland, 2003) (Table 2) is based on an assumption that karst activities have
influenced almost all springs in Florida. Under this system, all springs in Florida can be
classified into one of four categories, based on the spring's point of discharge. Is the point of
discharge a vent or is it a seep and is the point of discharge located onshore or offshore? Since all
springs are either vents or seeps, the classification can be simplified into the following
categories.

A spring vent is defined as an opening that concentrates groundwater discharge to the
Earth's surface, including the bottom of the ocean. The opening is significantly larger than the
average pore space of the surrounding aquifer matrix. A vent is occasionally considered to be a
cave, and groundwater flow from this type of vent is typically turbulent. On the other hand, a
spring seep is composed of one or more small openings in which water discharges diffusely (or
"oozes") from the groundwater environment. The diffuse discharge originates from the
intergranular pore spaces in the aquifer matrix. Flow from seeps is typically laminar.






BULLETIN NO. 69


Offshore Springs

Springs occur both onshore and offshore in Florida. Currently, little is known about the
offshore, or submarine springs, with the exception of the Spring Creek Group-the largest spring
group in Florida, averaging more than one billion gallons of water discharged per day (maximum
flow estimated at more than two billion gallons of water per day [Rosenau et al., 1977; Lane,
2001]). Offshore or submarine springs (Figure 4) are known to exist off Florida's Atlantic and
Gulf of Mexico coastlines. These springs are most common in the offshore portion of Florida
from Crystal Beach Spring (Figure 4, Spring No. 7) to Bear Creek Spring (Figure 4, Spring No.
1). Offshore springs have also been identified off the northeastern and southwestern parts of the
Florida and the western panhandle (Rosenau et al., 1977) (Figure 4). Water-quality data from
some of these springs indicate that, at best, the water is brackish. There are anecdotal reports of
"fresh water" flowing from Florida's offshore springs.


Table 2. Florida's Spring Classification System. (From Copeland, 2003)
SPRINGS
Onshore Offshore
Vent Onshore Vent Offshore Vent
Examples Examples
Karst spring Offshore karst spring
Resurgence (River Rise) Unnamed offshore vent
Estavelle (intermittent resurgence or Offshore estavelle vent
exsurgence)
Subaqueous riverine vent
Subaqueous lacustrine vent
Sand boil
Seep Onshore Seep Offshore Seep
Examples Examples
Subareal riverine seep Unnamed offshore seep
Subaqueous lacustrine seep Offshore estavelle seep







FLORIDA GEOLOGICAL SURVEY


SUBMARINE SPRINGS 7
1. Bear Creek Spring
2. Cedar Island Spring
3. Cedar Island Springs
4. Choctawhatchee Springs
5. Crays Rise
6. Crescent Beach
7. Crystal Beach Spring
8. Freshwater Cave
9. Mud Hole
10. Ocean Hole Spring SCALE
11. Ray Hole Spring
12. Red Snapper Sink 0 80 kms
13. Spring Creek Springs Group
14. Tarpon Springs 0 50 Miles
15. Jewfish Hole
16. Unnamed Spring No. 4



Figure 4. Offshore Springs (From Rosenau et al., 1977).


Spring Recharge Basins


In addition to the awareness of increasing trends in contaminants such as nitrate over the
past several years (Figure 5), there has also been an increased awareness on the drainage basins
that supply water to Florida's groundwater and springs. The amount of water and the nature and
concentrations of chemical constituents that discharge from springs are functions of the geology,
hydrology, weather conditions and land uses within the spring recharge basin. This type of basin,
often referred to as a springshed, consists of those areas within groundwater and surfacewater
basins that contribute to the discharge of the spring (Dehan, 2002; Copeland, 2003). The
springshed consists of all areas where water can be shown to contribute to the groundwater flow
system that discharges from the spring of interest. Karst systems frequently include sinking
streams that transmit surface water directly to the aquifer; the recharge basin may include surface
water drainage basins that bring water into the spring drainage from outside of the groundwater
basin.






BULLETIN NO. 69


Median Nitrate Concentrations in 13
Selected Springs in Florida

1.0
9 0.9
S0.8
0.7 -
z 0.6
0.5
0 0.4-
0
z 0.3-
O 0.2 -
z 0.1 -
0.0 -
I I
1970 1980 1990 2000
Year

Figure 5. Median nitrate concentrations in 13 selected first-mag-
nitude springs. Springs are Alexander, Chassahowitzka Main,
Fanning, Ichetucknee, Jackson Blue, Madison Blue, Manatee,
Rainbow, Silver, Silver Glen, Volusia Blue, Wakulla, and Wacissa #2
(From Scott et al., 2004).


OVERVIEW OF THE HYDROGEOLOGY OF FLORIDA'S GROTUNDWNATER

Florida enjoys a humid, subtropical climate throughout much of the state (Henry, 1998).
Rainfall, in the region of the major springs (Figure 1), ranges from 127 cm (50 inches) to over
152 cm (60 inches) per year. As a result of the climate and the geologic framework of the state,
Florida has an abundant supply of fresh groundwater. Scott (2001) estimated that more than 8.3
billion cubic meters [2.2 quadrillion (2.2 x 1012) gallons] of freshwater are contained within
Florida's aquifers. However, only a very small percentage of freshwater is available as a
renewable resource for human consumption.

The Florida peninsula is the exposed portion of the broad Florida Platform. The Florida
Platform, as measured at the 200 meter (more than 600 ft) below sea level contour, is more than
483 km (300 miles) wide. It extends more than 240 km (150 miles) westward under the Gulf of
Mexico, and more than 113 km (70 miles) under the Atlantic Ocean. The present day Florida
peninsula is less than one half of the total platform.

The Florida Platform is composed of a thick sequence of variably permeable carbonate
sediments, limestone and dolostone, lying on older igneous, metamorphic and sedimentary rocks.
The Cenozoic carbonate sediments may exceed 1,220 m (4,000 ft) thick. A sequence of sand, silt
and clay with variable amounts of limestone and shell overlie the carbonate sequence (see Scott
et al, 1991 and Scott, 1992b for discussion of the Cenozoic sediment sequence and the geologic






FLORIDA GEOLOGICAL SURVEY


structure of the platform). In portions of the west-central and north-central peninsula and in the
central panhandle, the carbonate rocks, predominantly limestone, occur at or very near the
surface. Away from these areas, the overlying sand, silt and clay sequences become thicker. As
the rocks sediments compacted and were subjected to other geologic forces, fractures formed.
These fractures allowed water to move more freely through the sediments and provided the
template for the development of Florida's many cave systems.

There are three major aquifer systems in Florida, the Floridan, the intermediate and the
surficial aquifer systems (Southeastern Geological Society, 1986; Scott et al., 1991). The
Floridan aquifer system (FAS) occurs within a thick sequence of permeable carbonate sediments
(see Miller, 1986 and Berndt et al., 1998 for discussion of the FAS). In some areas, it is overlain
by the intermediate aquifer system (IAS) and the intermediate confining unit (ICU) which
consists of carbonates, sand, silt and clay. The surficial aquifer system (SAS) overlies the IAS
(or the FAS where the IAS is absent), and is composed of sand, shell and some carbonate. The
vast majority of Florida's springs result from discharge from the Upper Floridan aquifer system
(UFAS), a subdivision of the FAS as discussed by Miller (1986).

Typical natural recharge to the FAS originates as rainwater. As the acidic rainwater
percolates downward to the FAS, it is made slightly more acidic by carbon dioxide from the
atmosphere and organic acids in the soil. Once in the FAS, the groundwater dissolves portions
of the limestone and enlarges naturally occurring fractures. The dissolution enhances the
permeability of the sediments and forms cavities and caverns. Sinkholes are formed by the
collapse of overlying sediments into the cavities. Occasionally, the collapse of the roof of a cave
creates an opening to the land surface. See Lane (1986) for a description of sinkhole types
common in Florida.

Recharge to the FAS occurs over approximately 55 percent of the state (Bemdt et al.,
1998). Recharge rates vary from less than 2.54 cm (one inch) per year to more than 25.4 cm (10
inches) per year. Water entering the upper portion of the FAS eventually discharges from a
spring. The water has variable residence times. Katz et al. (2001) and Katz (2004) found that
water flowing from larger springs had a mean groundwater residence time of more than 20 years
and may reflect the mixing of older and younger waters.

Florida's springs occur primarily in the northern two-thirds of the peninsula and the
central panhandle where carbonate rocks are at or near the land surface. Most of these springs
produce water from the UFAS which consists of sediments that range in age from Late Eocene
(approximately 36 38 million years old [my]) to mid-Oligocene (approximately 33 my).
Miocene to Pleistocene sediments (24 my to 10,000 years) often are exposed in the springs.

The geomorphology of the state, coupled with the geologic framework, controls the
distribution of springs. The springs occur in areas where karst features (for example, sinkholes
and caves) are common, the potentiometric surface of the FAS is high enough and the surface
elevations are low enough to allow groundwater to flow at the surface. Springs generally occur
in lowlands near rivers and streams. There are a number of springs known to flow from vents
within river channels and many more are thought to exist. Homsby and Ceryak (1998) identified
many newly recognized springs in the channels of the Suwannee and Santa Fe Rivers. Springs






BULLETIN NO. 69


that have yet to be described have been found within the Apalachicola River between Gadsden
and Jackson Counties (H. Means, Florida Geological Survey, personal communication, 2004).

Weather and climatic events affect the appearance of spring water. For example, during
periods of higher than normal precipitation, such as hurricanes, some springs may reverse flow.
When this occurs, stream water flows into the aquifers. During these times, spring water often
has a dark appearance because of the presence of tannins from surfacewater sources. Once
stream levels drop enough, the dark waters again reverse flow. When this occurs, discharge
becomes much clearer. Dryer periods also affect the appearance of springs. For example, during
1998 2002, Florida experienced a major drought with a rainfall deficit in places totaling more
than 127 cm (50 in) (Verdi et al., 2006). The resulting reduction in recharge from the drought,
along with the normal withdrawals, caused a lowering of the potentiometric surface in the FAS.
Many first magnitude springs experienced a significant flow reduction. Some springs ceased
flowing completely. The appearance of the springs also changed as river and lake levels
declined reducing the size of the spring-water body and exposing sediments along the banks.


QUALITY OF GROUNDWATER AND SPRING WATER

Natural Factors Affecting Groundwater and Spring-Water Quality

Most of the Florida land mass is a peninsula that is surrounded by saltwater. Relict
saltwater also underlies the entire state. The reason for this is that the Florida Platform consists
of carbonate rocks that were deposited in a shallow ocean. At the time of deposition, saltwater
existed in their intergranular pore spaces. Gradually over geologic time, sea level was lowered
relative to its position when the carbonate sediments were deposited. Through compaction and
down warping of sediments on both sides of the Platform, a series of complex fracture patterns
developed. The patterns are often reflected at land surface and have actually influenced the
pathways of many of Florida's streams.

Over geologic time, as sea level lowered, the central portion of the Florida Platform was
exposed to the atmosphere. As rainfall percolated downward it eventually replaced the upper
portion of saltwater in the developing aquifers with a freshwater "lens." Today, the irregularly
shaped "lens" is generally thickest in the central portion of the state, where it is over 610 m
(2,000 ft) thick (Klein, 1975). It becomes narrow toward Florida's coastline. The base of the
"lens" is typically a transitional rather than a sharp boundary. Groundwater in the deeper portion
of the "lens", and along the coasts, is mixed with saltwater and has relatively high concentrations
of saline indicators such as sodium (Na), chloride (Cl), and sulfate (SO4).

Water discharging from Florida's aquifer systems and springs has its primary source from
rainfall. Much of the rainfall reaching land surface flows overland to surfacewater bodies,
evaporates, or is transpired by plants. However, a portion of the rainfall percolates downward
through the sediments, or enters sinkholes, where it recharges the aquifers. During its travel
downward from land surface to the water table, and during residence within Florida's aquifer
systems, many factors affect the water chemistry.






FLORIDA GEOLOGICAL SURVEY


A long residence time may allow sufficient time for chemical reactions between the water
and the aquifer rock. As such, water chemistry reflects the composition of the aquifer rock.
Typical residence times range from less than several days (in secondary produced caverns and
sinkholes) to centuries (Hanshaw et al., 1965).

A second factor affecting groundwater chemistry is flow path, which is the length and
depth of the path that the groundwater follows as it flows through an aquifer (Upchurch, 1992).
In general, shallow, short flow paths (which are characteristic of the SAS) result in shorter
residence times for chemical reactions to take place. Consequently, the total dissolved solid
(TDS) content is less than in longer flow-path systems. If the flow path is long (on the order of
tens of kilometers), such as commonly occurs in the FAS, reactions between rock and water
become more probable and the TDS content of the water would be greater as a result of
continued rock-water chemical reactions. Because of the residence time and the flow paths of the
groundwater within an aquifer, the quality of spring water is typically reflective of the
interactions of the major rock types in the aquifer and the groundwater itself.

A third factor which is of particular interest is intergranular porosity (pores through
which water passes between the individual rock matrix grains). Even though Florida's aquifers
have large, secondary cavernous pores spaces, most of the pores tend to be small (Upchurch,
1992). Fortunately, whenever the pores are very small, they act as filters for microbes, small
organic substances, and clay minerals. In general, this results in naturally filtered groundwater
that is very pure and desirable for both drinking water and recreation. Unfortunately, some
pollutants are not always removed and our aquifers can become contaminated.

Differences in Spring- and Well-Water Quality

The processes controlling the water quality in wells is very similar to those controlling
spring-water quality with at least one major difference. Wells are often drilled to production
zones as close to land surface as is economical. This is the situation for the wells used in this
study, which are for the most part monitoring wells. Monitoring wells tend be shallow (median
depth 80 feet (24 m) (Appendix C). Most water in these shallow wells represents young,
recently recharged water. On the other hand, because springs are major discharge points, spring-
water can be considered to be an integrator of water from the entire springshed. Spring water is
a mixture of young, shallow, freshly recharged water and older water from the deeper portions of
the aquifer. For this reason, spring water tends to be older than the relatively shallow water
found in the monitoring wells used in this study.

Indicators of Groundwater and Spring-Water Quality Problems

Spring water, while it resides in the aquifer, is considered to be groundwater. However,
once spring water exits from the spring onto the earth's surface, it is considered to be surface
water. Because of this change, the question arises whether regulators should apply groundwater
or surfacewater quality standards to the water. Primary and secondary standards with maximum
contaminant limits (MCLs) may exist for an analyte while the water is considered groundwater,
but differ for surface water; or vice versa. Drinking water standards are protective of human






BULLETIN NO. 69


health while surface water criteria are protective of aquatic biota. Although several analytes fall
into this category, Nitrate (NO3 + NO2 as N), and hereafter abbreviated NO3, is a good example.
Based on drinking water criteria, nitrate has a groundwater threshold value of 10 mg/L (Florida
Department of Environmental Protection, 1994). However, no numeric nitrate criteria exist for
surface water, other than Class I surface water which is used for drinking water. The FDEP is
currently developing criteria for spring water. Until legal numeric criteria are established for
nitrates, it should be understood that any reference to threshold values in the following text
simply infers potential water-quality problems.

One of the more disturbing aspects about Florida's groundwater quality has been the
documented steady increase of nitrate over the past several decades (Jones et al., 1996;
Champion and DeWitt, 2000; Means et al., 2003). An example is displayed in Figure 5 (From
Scott et al., 2004). It shows that nitrate concentrations have a greater than 19-fold increase in
nitrate concentrations in 13 selected first-magnitude springs (Alexander, Chassahowitzka Main,
Fanning, Ichetucknee Main, Jackson Blue, Madison Blue, Manatee, Rainbow Group composite,
Silver Main, Silver Glen, Volusia Blue, Wakulla, and Wacissa #2 Springs) between the 1970s
and 2000.

The natural background nitrate concentrations in Florida groundwater are less than 0.05
mg/L (Upchurch, 1992). During the 2001-2002 time frame, the FGS sampled 125 spring vents.
Of the 125 spring vents sampled, none had nitrate concentrations exceeding the 10 mg/L
threshold for Class I surface and drinking water. Fifty-two of the spring vents sampled had
nitrate concentrations exceeding 0.50 mg/L (42 percent) and 30 (24 percent) had concentrations
greater than 1.00 mg/L. Thus, over 40 percent of the sampled springs had at least a ten-fold
increase in nitrate concentrations above background and approximately one quarter of them had
at least a 20-fold increase. The elevated nitrate concentrations may adversely affect the aquatic
ecosystem in springs and spring runs. Further research is still needed and is currently being
sponsored by the Springs Initiative Program. The FDEP is aware of the nitrate issues and has
worked with other governmental agencies to develop a series of steps to reduce nitrate
concentrations in groundwater and springs in the middle Suwannee River Basin where many of
Florida's springs are located (Copeland et al., 2000). The FDEP Bureau of Watershed
Management and the Florida Department of Community Affairs are active in coordinating the
development of spring protection measures.

Another groundwater quality concern is the influence of saline water. Several springs
have concentrations of chloride (Cl; a saline indicator) exceeding the 250 mg/L threshold for
drinking water. Springs with this type of water tend to be located along Florida's coast and along
the St. Johns River. The ultimate source of the saline indicators is from naturally occurring saline
water within the FAS (Klein, 1975), or from sea water near Florida's coasts. When the
concentrations of saline indicators are increasing, it may be the result of: (1) natural
circumstances such as drought, (2) the consequent upcoming of groundwater within the FAS, or
(3) lateral intrusion of salt water due to increased groundwater pumping.

Enterococcus and total coliform bacteria represent a third concern. It is generally
believed that these bacteria originate in fecal matter from warm-blooded animals (Jelinkova
and Rotta, 1978). Total coliform concentrations in several springs has exceeded the






FLORIDA GEOLOGICAL SURVEY


drinking water standard of four colonies per 100 ml (Florida Department of Environmental
Protection, 1994). However, it has been determined that these bacteria can complete their normal
life-cycle outside of warm-blooded animals, especially in environments found in parts of Florida
(Fujioka and Byappanahalli, 2004), thus the concentrations of fecal coliform may not necessarily
represent a direct link to warm-blooded animal pathogens. Further research is needed before
definitive conclusions can be made regarding the source of fecal bacteria. Another concern is
concentrations of enterococcus and fecal coliform bacteria with regards to swimming. The
Florida Department of Health has set beach swimming standards and advisory thresholds for
both organisms. To date, exceedances of the standards and thresholds in springs have not been a
problem. Nevertheless, many residents swim in spring runs and these bacteria are a concern.


SPRING SELECTION PROCESS

Very little spring-water quality sampling, mostly by the USGS, occurred until the 1940s.
In 1947, the FGS published its first edition of "Springs of Florida" (Ferguson et al., 1947) which
documented the water quality in the major springs of Florida. The document was revised in 1977
and many previously undocumented springs were sampled (Rosenau et al., 1977). It should also
be noted that during the 1970s, the three northern water management districts were formed.
They were the NWFWMD, the SRWMD, and the (Saint Johns River Water Management District
(SJRWMD). Within a few years, these WMDs, along with the USGS and the already established
SWFWMD, occasionally collected spring-water quality samples. By the 1990s, the NWFWMD,
SRWMD, SJRWMD, and SWFWMD had established periodic to regular sampling, often with
the assistance of the USGS, of springs within their jurisdiction.

Partially due to the sampling efforts of the WMDs, in the 1990s it became apparent that
the water quality in some of Florida's springs was deteriorating. For this reason, in 1999 the
Secretary of the Florida Department of Environmental Protection directed the formation of a
multi-agency Florida Springs Task Force to provide recommendations for the protection and
restoration of Florida's springs. In late 2000 the Task Force made recommendations for the
preservation and restoration of Florida's springs to the Secretary, and in 2001 the Florida
Legislature passed the Florida Springs Initiative. The Initiative authorized funds for FDEP to
begin investigating the status of Florida springs and develop strategies for protecting them. As a
result of the Initiative, the four WMDs, FDEP, and the FGS have cooperated to monitor Florida's
springs.

The Springs Initiative has been responsible for the collection of spring-water quality
since 2001. Beginning with that year, much of the data used in this report were obtained from
Springs Initiative-sponsored samples. Methods of evaluating the data used in this report can be
used in the future to analyze the spring data currently being generated as a result of the Springs
Initiative. In the meantime, data of spring-water quality collected as part of WMD spring
sampling programs were used for this interpretative report.

The FGS requested spring data from each of the four northern WMDs in order to analyze
spring-water quality and quantity for trends. The districts delivered available data to the FGS in
2002 and 2003. It was soon discovered the WMDs had only sporadically sampled their springs






BULLETIN NO. 69


through the 1980s. However, beginning in the early 1990s each district had begun to sample
springs in a semi-consistent manner. Even though data do exist for many springs, only 58
springs (Figure 6) were ultimately included in the analysis; one from the NWFWMD, 14 from
the SRWMD, 15 from the SJRWMD, and 28 from the SWFWMD. Selection was determined
based on the consistency of the data. As a working definition, we considered consistency to be
the longest string of data in terms of time, along with the greatest number of analytes. We also
wanted the largest number of springs to be included that met our concept of consistency. With
these criteria in mind we determined that the time period from January 1991 through December
2003 represented the time in which the most consistent data existed for the greatest number of
springs. We realize that there are several springs that have decades of data. We also realize that
since commencement of the Springs Initiative, many springs now have data, but the time
sequences are short. As a result, our data interpretations are valid only for the 1991-2003 time
frame.

A discussion of analytes evaluated and frequencies of sampling will be discussed later.
Figure 6 displays the location of the included springs in the analyses. A list of the names of
springs, along with location information, can be found in Appendix D.


WELL SELECTION PROCESS

In 1983, the Florida Legislature passed the Water Quality Assurance Act (Florida
Statutes, 1983, Chapter 403.063). As a result, FDEP, with the assistance of the five water
management districts, plus several counties (Alachua, Broward, Collier, Lee, Miami-Dade, and
Palm Beach) established extensive groundwater monitoring networks. The purpose was to
document both ambient groundwater quality conditions (Background Network) and to detect
changes in Florida's groundwater quality resulting from the effects of various land uses and
potential sources of contamination (Very Intense Study Area Network [Scott et al., 1991]). Both
networks were in operation until 2000. A major subdivision of the Background Network was the
Temporal Variability (TV) Network. The TV Network consists of a series of strategically-
located Background Network wells scattered throughout the state. They are sampled on a
monthly to quarterly frequency.

Beginning in 1996, FDEP began a major redesign of its water resource monitoring
efforts. The purpose of the redesign was to characterize the environmental conditions of
Florida's water resources and to determine if those conditions are changing over time. The
revised network (The Status Network) became operational in early 2000. A detailed description
of the Status Network is presented by Copeland et al. (1999). Throughout the redesign process,
the TV Network only had minor modifications. The stated purpose of the redesigned network is
to evaluate temporal variability of Florida's groundwater quality and to determine whether
concentrations of the sampled analytes are increasing or decreasing over time. The TV Network
consists of 46 wells (Figure 7); 25 wells monitor confined groundwater and 21 wells monitor
unconfined groundwater. The wells tap each major aquifer system and are scattered throughout
each of Florida's five WMDs. As can be seen in Figure 7, some of the well locations represent







FLORIDA GEOLOGICAL SURVEY


N




S


Legend
Springs
SNWFWMD
S SFWMD
SSJRWMD
SRWMD
S SWFWMD









Miles
0 30 60 90

Kilometers
0 70 140 210


V


I

2LI


Figure 6. Location of springs analyzed in this report. (A list of the spring names can be found in
Appendix C.)






BULLETIN NO. 69


Legend
Wells
NWFWMD
SFWMD
M SJRWMD
- SRWMD
I SWFWMD


4 '

~i~I


Miles
0 50 100 150
Kilometers
0 75 150 225


Figure 7. Location of Temporal Variability Network (TVN) wells. (A list of well identifiers can
be found in Appendix D.)






FLORIDA GEOLOGICAL SURVEY


clusters of wells. Wells that monitor confined ground water are sampled quarterly (thought to
have less temporal variability), whereas wells that monitor unconfined groundwater are sampled
monthly.

With respect to the WMDs, the NWFWMD has eight wells, the SRWMD has 10 wells,
the SJRWMD has nine wells, the SWFWMD has 11 wells, and the SFWMD has eight wells in
the TV Network that had significant data for analyses. A list of well names can be found in
Appendix C, along with well construction data.


METHODS

This report uses a relatively simple methodology to determine the condition of spring and
groundwater quality. Most analyses boil down to the single straightforward question, "are
conditions getting better, getting worse, or remaining the same?" Though this report is based
upon several statistical procedures, all address this single question.

With this simple objective in mind, additional elaboration is required to expand upon the
connection with actual statistical tests and methods. First, since "better" and "worse" are
subjective and qualitative questions, an approach that will quantify them is needed. Thus, a
somewhat more objective and quantitative form of the above question becomes, "for the 1991-
2003 period of record, are the indicators decreasing, increasing, or remaining the same?" This
frames the question of quality in the terms of changing quantities between two end-points (i.e.,
the start and finish of a time period of interest); changes in quantities, such as flow and loading,
can be objectively tested in a variety of ways.

In order to test quantities, the last remaining questions are: (1) which quantities and, (2)
over what period of time? These further conditions must be defined. The first question is which
quantities? For this report, as many indicators as possible were tested. This allowed the authors
to ask questions of the largest possible scale; limiting the number of indicators only limits the
possible number of observations and maximizing the number of observations allows the most
comprehensive view of changes that might be of concern. Second, for the quantities examined an
increase or decrease in concentration must be addressed over a time frame. Therefore, in order to
maximize the effectiveness of the analysis, the longest possible time series was chosen for as
many springs as possible. In summary, the choice was for the longest possible time frame for
data with the highest quality, for as many indicators possible, and for as many springs as
possible. Laboratory and collection methodologies have varied over the last several decades in
the state of Florida. Variations include not only differences among WMDs, but even use of
different laboratories by the same district, changes within laboratories, incomplete sampling
intervals due to varying purposes and other reasons. Because of this, the earliest starting point for
which data quality could be uniformly assumed to be high (in this case 1991) was chosen; this
created the longest possible time series for analysis (1991-2003) for as many springs as possible.

Regarding the second question, for this report, we chose trend analysis to evaluate a
given time series (between 1991 and 2003) for linear trends. Note that Urquhart and Kincaid
(1999) mentioned that trends may deviate from strict linearity. Nevertheless, they mentioned






BULLETIN NO. 69


that if a trend is present, a linear trend will be present, regardless of the type of mathematical
structure of the trend, e.g. cyclic, episodic, or a stair-step look.

For this report, we were not only interested in detecting the presence of a trend we were
also interested in a statistical method that was relatively insensitive to missing sampling points
(e.g., gaps in data series), outliers, and, data that seldom had normal (Gaussian) distributions.
Based upon these reasons, our choice for analysis was the non-parametric, Mann-Kendall (MK)
test for trends. Discussions of the MK test and other statistical procedures used in the study,
including the corresponding assumptions, are found in Appendix E.

Our last clarification involves interpretation of trends; not all increases are bad nor are all
decreases good. For example, a decrease in nitrate is desirable and is considered to be good. On
the other hand, a long-term decrease in flow is not desirable, since it may indicate an overuse of
the resource. Thus, it can be considered to be bad. Another example, an increase or decrease in
pH may not be considered to be good (if it is extreme), since this analyte is best defined by an
optimal middle range; being far outside that range on either side is bad. The point is that change,
in one direction or another, can be tested and the result has implications regarding the
improvement or degradation of the system in question.

Definition of Trends

Natural systems in general undergo two main types of change: cyclic and linear (A and B,
top of Figure 8). Cyclic change is common in nature. Two common examples of cyclic changes
include diurnal and seasonal changes. Natural changes can also be linear, moving conditions
from one state to another without returning to the original state. The focus of this report is to
document linear trends in water quality and quantity. It is also assumed that trends in certain
analytes are most likely anthropogenic, rather than natural in origin. In this case, three possible
linear trend scenarios can be tested. In each case, a chemical component of a groundwater system
(whether spring or well) can be plotted as a concentration against time (Figure 8, bottom). The
first scenario (on the left) is that the system is increasing in concentration for a particular analyte
(for which the symbol, "+", will be used in this report). One case could be phosphorus. Over a
period of interest, change of concentration can be tested at a specific level of confidence (e.g., at
a 95 percent confidence level, or an a level of 0.05). This means that by the end of the time
period, the concentration was high enough to warrant the designation of being higher than
expected by chance fluctuation alone. Such values are marked as being highly unlikely to have
occurred unless notable changes to the system were introduced. In the opposite case (on the
right), the concentration could have decreased significantly (represented by "-"). Such a trend
suggests a substantial change to the physical environment and would therefore be recorded. The
third scenario (middle chart) is that neither case was observed. As will be detailed below, this is
not a positive statement affirming uniform conditions for the system in question; rather it is a
general category for all conditions not classified within the former two situations. This is a
default option and it is likely that a number of valid trends that could escape detection and be
included in this scenario.






FLORIDA GEOLOGICAL SURVEY


/


3 observations for trends:
Increasing Trend (+) Unable to confirm


Decreasing Trend (-)


Time


Figure 8. Illustration of three options for water-quality trends. Trends can either increase (+), decrease (-), or
otherwise cannot be confirmed. Depending on the analyte, the interpretation is that the system is getting better,
getting worse, or remaining the same. Taking the example of phosphorus, if the trend is increasing, the situation is
getting worse. If the trend is decreasing, it is getting better. Finally, if neither, nothing can be confirmed. All
analyses in this report are assigned to one of these three observations.

Problems with Trends

Trend analyses were largely straightforward and posed few problems. Visual analysis of
time series plots showed that the majority of significant trends were based on a large amount of
data that indeed demonstrated an obvious tendency. However, several exceptions arose and their
handling is addressed in the following sections.

"Remaining the Same" Possibility of Missed Trends

The last case scenario in the phrase "getting better, getting worse or remaining the same"
leaves a question as to the identity of the last category. Note that the last observation-
"...remaining the same"-cannot be addressed statistically. It is, therefore, considered the
alternative case to the situation of an increasing or decreasing trend. Because of this
"...remaining the same" amounts to a catch-all for all remaining observations (i.e., trends that
neither increased nor decreased). Though simple in principle, a clarification should be stated.
Within this last category remains interesting, important, and valuable information-cycles,
interesting structure, nonlinear trends, or other phenomena. More problematic, it is likely the
analyses conducted here "missed" a number of trends (due to the strict confidence limit).


A. Cycle
4-2
2

2 -4
-4 V
0 5 10 15 20 25
Time (years)


B. Trend
30
0 2 ..........-------- ............. ..

o10 -------......... .------- .......-----....---
0
0 5 10 15 20 25
Time (years)


Variable






BULLETIN NO. 69


However, it is important to state once again that the purpose for this study was neither to find all
the trends possible, nor to find the largest number of trends; rather, the purpose was to identify
all the trends that could be confidently, statistically labeled as such. Other studies employing
greater power (i.e., ability to detect more trends) could, and probably should, be conducted. But
since this is the first such statewide analysis of water-quality trends, the goal was to minimize the
number of false trends-while maximizing the number of true trends-in order to get the best
picture of where the clearest problems exist.

Outliers

Statisticians often encounter data that lies outside of an expected range of values. The
reasons for this may include data transmission errors, failed laboratory analyses, contaminated
samples, and sometimes accurate data recording unusual situations-causes are not always
visible to analysts. This report was no exception. Technically, there are really only two ways of
dealing with such data. One is to set arbitrary guidelines in advance and handle the data in
accordance. This may include removing outliers that occur above or below a certain accepted
range, e.g. adjust the data. The other approach is to include all outliers in the dataset and
analyze the data regardless. The rationale is that well-maintained data sometimes records outliers
but, with sufficient data, the effects will be minimal. This report chose the latter option and
included all data in all analyses-none were discarded. Their presence was accounted for and
accommodated in several ways. The first was simply by the choice of analysis. Nonparametric
statistics are relatively insensitive to the influence of extreme data points (outliers).

A large number of "bad" data points can still influence even a nonparametric analysis.
Cross-checking results and examining raw data can assist with this judgment. In order to
compare and check the influence of outlying data, every nonparametric statistical trend test [the
Mann-Kendall (MK) will be discussed later] result was checked against a linear regression
parametricc test) of the same data. Further, both analyses were conducted with different
statistical packages: Minitab (Minitab, 2003) for MK and S-PLUS (S-PLUS, 2003) for cross
checking regression analyses. Visual examination of each individual time series was conducted
to corroborate the results of the statistical tests; suspicious data sets were re-analyzed.
Inspections revealed that in the vast majority of cases, reported statistical trends were composed
of time series that showed clear visual trends. Comparison of MK results to linear regressions
(though parametric) showed surprising similarity. Not only did the non-parametric MK results
closely match the parametric analyses, but both were surprisingly unaffected by outliers; thus
providing strong confirmation that both the data was of high quality and that it gave robust
signals.

Detection Levels

Though the data used in these analyses were the best available in terms of quality
assurance, other factors had to be considered. The analysis of outliers demonstrated that
consistency of data handling, laboratory reporting, and subsequent quality assurance was good.
Yet an additional issue surfaced in the plotted time series: the effect of laboratory detection
limits. For statistical purposes, if a sample's concentration was below the laboratory's method
detection limit, it was considered to be the detection limit. For example, where improvements in







FLORIDA GEOLOGICAL SURVEY


laboratory methodologies over time lowered the minimum detection value for several analytes,
trend analyses detected significant downward trends where no such trend existed. Indeed, a
number of time series plots revealed that a number of trends-statistically significant by MK
tests-were actually the artifact of such "stair step" patterns trending down over time (Figure 9).

All data series, therefore, were checked visually for such spurious results. Those data
series found exhibiting such results were removed from consideration in the final analyses.
These were assigned the designation "DL" (detection level) in result tables (e.g., "plus-minus"
charts which will be discussed later); trends created by detection level artifacts were removed
from further analysis.





Well 1943: Example of Detection Limits


0.20-




0.15-


E
LI_


U.UU I I I I I I
2/12/1990 11/8/1992 8/5/1995 5/1/1998 1125/2001 10/22/2003
Date





Figure 9. Example of a spurious trend. Detection limit changes can
generate the appearance of false trends. All time series for all analytes
were visually checked for aberrant results since visual inspection was
was necessary to identify artifacts.


EnEEE EEEEEEn






BULLETIN NO. 69


Sparse Data

The quantity and consistency of existing data varied widely depending on sampling
agency, analyte, and location of springs or wells. Given the amount of data used for the time
series studied herein, a distinction should be made concerning how the quantity of data affected
its quality. First, all reported analyses had sufficient data for time series analysis. Sufficient data
constituted a minimum of 10 points for the entire series. Many software packages would not
generate statistical results without a minimum set of points-which was often 10 values. At the
same time, there is a difference between what constitutes a sufficient amount of data and how
that (sufficient) quantity is structured through time. The former issue concerns whether an
analysis could be conducted while the latter has implications for the reliability of the
interpretation. On one end of the spectrum, some locations only had 10 values, while at the other
some had in excess of 100 values. As it turns out, considering both springs and wells, the
median number of data for the 1991-2003, Sequence A, time frame was 38.

Long-term, consistent data collection is an ideal situation for analysis. However, most
data sets were between the extremes of a lot or too little. Much of the data used here can be
described by the term "sparse data" which we use to mean there are not very many data points in
the time sequence but there were a minimum of ten. Often the spring data were collected for
some other purpose than for time-series analysis having little structure at all. This results in
"messy data." Messy or disorderly data includes missing values, outliers, transcription errors, or
extreme and skewed results. Simply stated, a high proportion of time sequences have varying
amounts of missing data. The missing data hinders reliable data interpretation. One example of
"messy data" is nitrate concentrations at Wakulla Spring (Figure 10). An example is as follows.
Suppose a large number of data points exist at the beginning of the time series, nothing in the
middle, and one point at the opposite end of the series. Also, suppose a trend is detected. The
problem with such a trend is that although it is statistically valid, it may be entirely dependent
upon the single point at the one end of the series. If such a trend is labeled valid, then poor
judgment was used. The best interpretation for a trend exists when there is an abundance of
points sampled consistently for the longest period of time.

Time gaps in data series were the most common problem. In a number of cases data
collected early in the time series were followed by one or more data collection gaps of varying
temporal duration. Such trends are dependent upon the connection of two (occasionally more)
clusters of data. Though the trends may be valid, they are not ideal; this example underscores the
necessity for sampling agencies to implement consistent collection plans over the long term.
Though the data can often be used, its utility can be challenged, or considered suspect. The
reason is that the value of any individual data point is a function of the number and reliability of
nearby data points to which it can be compared over the long term. Data that are sparse,
inconsistently collected, or have large time gaps are substantially less valuable than a consistent,







FLORIDA GEOLOGICAL SURVEY


Wakulla Spring Time Sequence A (1991-2003)


1.1 *

1.0



0 0.8 -
0
Z
S0.7-

0.6

0.5-

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
Date
Figure 10. Example of sporadic, unsystematic, and incomplete sampling.
Only seven points were collected in the final eightyears of this Wakulla Spring
study. Sparse, inconsistent sampling after 1994 meant the trend seen here was
dependent on relatively few points collected in 2000. Though the trend is statis-
tically valid, this is an excellent illustration of the need for consistentlong-
term data collection. Ironically, though budget issues are often responsible for
gaps in sampling, note that missing data greatly reduces the value of points
remaining. Note no data were obtained after 2001 even though Sequence A
continued through 2003.

well-documented time series. Sparse data collection was a significant issue in several notable
springs. For example the trend for nitrate at Wakulla Spring for Sequence A included a six-year
"gap" (1994-2000) during which there was only one sample collected. Although the statistical
conclusion that nitrate concentrations at Wakulla were decreasing is valid (to be discussed later),
with the lack of data during the 1994-2000 time frame, some may doubt the interpretation of a
decreasing trend.

Incomplete data sets existed for many analytes and indicators. Time series for some
analytes (e.g., iron) only had a handful of points over the 13 years. For such very small sets,
trend analysis was meaningless and these were excluded from analysis.


ANALYTES AND INDICATORS

A total of 48 chemical constituents and indicators, with a period of record 1991-2003,
were analyzed for this study. A list of analytes and their corresponding STORET codes can be
found in Appendix F. Data were obtained from several different sources. The state water
management districts offered the most information, followed by FDEP and the USGS. Each
agency used their respective sampling and analysis procedures under whatever guidelines that
were being followed for that particular period of time. This complicated the statistical analyses.
However, identification of useful data led to a field of 48 different analytes of water quality with






BULLETIN NO. 69


a temporal span of 13 years. Table 3 lists, in alphabetical order by column, all of the analytes
examined in this study.


Table 3. Analyte and Indicator List.
Analyte/Indicator
Color Depth to Groundwater Total Chloride
Dissolved Alkalinity Dissolved Phosphorus Total Dissolved Solids
Dissolved Calcium Dissolved Phosphate Total Fluoride
Dissolved Chloride Dissolved Sulfate Total Kjeldahl Nitrogen
Dissolved Fluoride Dissolved Strontium Total Magnesium
Dissolved Iron Enterococci Bacteria Total Nitrate
Dissolved Potassium Fecal Coliform Total Nitrate Nitrite
Dissolved Magnesium Mean Daily Flow Total Organic Carbon
Dissolved Manganese pH Total Phosphorus
Dissolved Sodium Residuals Total Phosphate
Specific Conductance,
Dissolved Ammonia Field Total Potassium
Specific Conductivity,
Dissolved Nitrate Lab Total Strontium
Dissolved Nitrate,
Nitrogen Temperature Total Sulfate
Dissolved Nitrate Nitrite Total Alkalinity Turbidity (Hatch Meter)
Dissolved Organic Carbon Total Bicarbonate Turbidity, Field Sampling
Water Level (feet relative to mean sea
Dissolved Oxygen Total Calcium level)


Sample Collection and Laboratory Analyses

Because many different agencies and laboratories were used to collect and analyze
groundwater samples, unwanted variability was potentially introduced that affected the trend
analyses. At a minimum, potential variability was introduced by: (1) different sampling
personnel, techniques and equipment, (2) sample transport from the field to the laboratory, (3)
environmental and laboratory contamination, (4) concurrent use of several analytical
laboratories, and (5) varying methods of reporting results.

For additional information on the analytes, including abbreviations and units for those 27
analytes that had detectable trends, see Table 4. Spring and well water samples were collected






FLORIDA GEOLOGICAL SURVEY


Table 4. Analytes and Indicators Displaying Trends
Analyte Abbreviation Unit of Measure
Alkalinity Alk mg/L
Ammonia/Ammonium NH3 or NH4 mg/L
Calcium Ca mg/L
Chloride Cl mg/L
Discharge or flow cfs or cubic feet per second
(ft3/sec); one cfs = 0.028 cubic
meters per second
Dissolved Oxygen DO mg/L
Fluoride F mg/L
Iron Fe gg/L and mg/L
Magnesium Mg mg/L
Nitrate as N NO3 or NO3 + NO2 mg/L
Nitrogen (total) N mg/L
Orthophosphate as P PO4 mg/L
pH
Potassium K mg/L
Sodium Na mg/L
Specific Conductance SC gS/cm at 25 C
Stage feet above datum

Strontium Sr glg/L
Sulfate SO4 mg/L
Temperature (of water) Temp C
Total Dissolved Solids TDS mg/L
Total Kjeldahl Nitrogen TKN mg/L
Total Organic Carbon TOC mg/L
Total Phosphorus P mg/L
Total Suspended Solids TSS mg/L
Turbidity Turb NTU (Current)*
JTU (Historic)
Water Level/Stage WL(msl) feet above mean level (1988)
*JTU and NTU are approximately equivalent, though not identical
msl = mean sea level (National Geodetic Vertical Datum, 1988)


by several agencies and a private company for the SRWMD. Regarding springs, the agencies
include the SRWMD (plus its subcontractor), the SJRWMD, the SWFWMD, and the USGS. For
wells, samples were collected by the NWFWMD, the SRWMD and its subcontractor, the






BULLETIN NO. 69


SJRWMD, the SWFWMD, the SFWMD, and the FDEP. In addition, multiple analytical
laboratories were used to process the samples.

For the 1991-2003 time sequence, spring sampling and analyses faced all of the potential
aforementioned problems. During the same time period, especially during the early days of the
operation of the TV Network, well monitoring encountered many of the same problems that
spring monitoring encountered. The TV Network is operated by the FDEP and by the mid
1990s, the FDEP reduced a considerable portion of unwanted variability by adopting a policy of
using a standardized sampling protocol, a standardized method of sample transport, a single
analytical laboratory, and a standard set of analytical methods and reporting protocols. It is
hoped that one day, spring monitoring throughout Florida will also adopt similar protocols that
will reduce variability.

In spite of the potential variability, not all is negative. For all water samples and data used
in this report, each corresponding sampling agency and/or analytical laboratory has an
individually-approved quality assurance/quality control (QA/QC) plan on file with FDEP.
Regarding QA/QC, the contact for each WMD, FDEP, and the USGS are found in Appendix G.

It should be noted that by 2001, in an effort to achieve standardization, the FDEP adopted
a recommended method for spring-water quality sampling. An overview of the protocols is
found in Scott et al. (2004). The TV Network is managed by the Watershed Monitoring Section
(WMS) of the FDEP. It recently produced an overview of its well water sampling protocols
(Florida Department of Environmental Protection, 2003).


Analytes used in this study

Multiple agencies collected water-quality samples for this publication; however one
agency may have sampled one analyte, while another agency sampled a similar analyte that was
closely related to the first. This was quite common for the analytes nitrate, ammonia, phosphate,
phosphorus, magnesium, sodium, potassium and chloride. Most often, the difference was
between the collection of the dissolved (filtered sample) and total (unfiltered sample) form of the
analyte. It would be preferable if sufficient data in both the dissolved and total forms of these
analytes were available. Unfortunately, it was not always the case. It was decided to combine
the total and dissolved forms because of the importance placed on nutrients in order to obtain a
time series with a sufficient number of data values. We do not recommend this procedure in the
future because it would be better to use one or both of the forms in conducting statistical
analyses. In the recommendations section (discussed later) we recommend a more consistent set
of analytes be used in the future. Nevertheless, for this study, we occasionally used a combined
surrogate form of nitrate, ammonia, phosphate, phosphorus, magnesium, sodium, potassium and
chloride. We did this solely for the purpose of obtaining a sufficient amount of data necessary
for data analyses.

Grouping of Analytes

For convenience, and in an effort to better understand groundwater quality trends, the
analytes (or indicators) were divided into several groups. They are: (1) Field, (2) Rock-matrix






FLORIDA GEOLOGICAL SURVEY


or Rock, (3) Saline or Saltwater, (4) Nutrient, and (5) Other analytes. However, because of
occasional chemical complexities, many analytes are grouped into more than one category.
Table 5 lists them by group. Note that analytes in the table only refer to those that displayed
trends. A detailed description of each analyte is found in Appendix F.


Table 5. Analyte Groups
Rock-Matrix Saline or
Field (Rock)* saltwater Nutrient Other
Discharge Alk Ca Ca and Mg TSS


DO Ca Cl
pH F K
SC Fe Na
Temp
K SC
WL(msl) or Mg SO4
Stage
P04 and P TDS
SC WL(msl) or
Stage
SO4
Sr


Turb
TOC


I NI J


*Light gray indicates common rock and saline-related indicators while dark gray shows common nutrient analytes.


Descriptions of Analyte Groups

Each analyte represents a measure or variable that can be used to assist in judging the
overall health of Florida's groundwater. Field analytes such as discharge, water level, and flow
describe quantity, but they can also greatly affect quality. The rock analytes suggest upcoming of
water from deep within Florida's aquifers. The saline analytes suggest intrusion or upcoming of
water from the deep portions of our aquifers, and the nutrient analytes are those that stimulate
biological growth or are present as a direct result of biological activity.

Field Analytes

Field analytes represent a grouping for convenience. Measurements of field analytes
were conducted prior to collecting samples for laboratory analyses. The analytes in this group
that were used for trend analyses include: discharge (or flow), dissolved oxygen (DO), pH,
specific conductance (SC), water temperature (Temp), and water level [water level relative to
mean sea level (msl) based on the North American Vertical Datum (NGVD) of 1988)].

Rock-Matrix Analytes

Rock-matrix analytes are those indicative of the rocks making up an aquifer. Because of
natural rock weathering, water that has had a long residence time in an aquifer system has a






BULLETIN NO. 69


greater probability of having a high concentration of dissolved rock matrix material. Rock
indicators include: alkalinity (Alk), calcium (Ca), magnesium (Mg), plus to a lesser extent,
fluoride (F), iron (Fe), pH, potassium (K), strontium (Sr), sulfate (SO4), phosphorous (P),
orthophosphate (P04) and SC. Since phosphate and phosphorus are often found in the mineral
fluorapatite, these two analytes are also included in the rock-matrix group.

Saline or Saltwater Analytes

Saline analytes are those associated with salts within either connate water or seawater.
Connate waters are those waters trapped within the sediments at the time of their deposition.
Since the original sediments were deposited in a marine environment, the pore spaces contain
very old saltwater. Saline analytes are obviously also found in the seawater located along
Florida's coasts. The major difference is the age of water. High concentrations of saline
analytes are often an indication of horizontal saltwater encroachment. However, they can also be
an indication of encroachment of highly mineralized water from the deeper portion of Florida's
aquifers, below the fresh-water "lens". The encroachment can be caused by the depletion of the
less dense fresh-water "lens" during a very dry period (e.g. a drought), or by the upcoming of
connate water during periods of heavy groundwater withdrawals. Pumping of groundwater
increased during dry periods and this process exacerbated the apparent intrusion process. Saline
analytes include: calcium, chloride, potassium, sodium (Na), specific conductance, sulfate, total
dissolved solids (TDS), plus water level (MSL) and stage.

Nutrient Analytes

Nutrients represent naturally occurring compounds or elements that are essential for the
growth of living organisms. However, if found in high concentrations, over-enrichment of
nutrients eutrophicationn) in a body of surface water can lead to an overgrowth of plant life
(including algae) and possibly a loss of dissolved oxygen. For this report, nutrient analytes
include: organic carbon, phosphate, phosphorus, a series of nitrogen related species, and to a
lesser extent, Mg, Ca, K, and sulfur in the form of sulfate. The nitrogen related species include
nitrogen, ammonia, total kjeldahl nitrogen, nitrate, and nitrite.

Other Analytes

Analytes in the "other" category do not fit in any of the other four categories. They
represent a miscellaneous group. For trend analyses, the analytes included in this group are
suspended solids, and turbidity.


DATA

The original data were from several sources. The data used for the trends analyses
discussed in this document are in Appendix H.






FLORIDA GEOLOGICAL SURVEY


Data Sources

The majority of the water-quality data from the springs were collected and analyzed by
the water management districts. The data for wells were obtained from the FDEP Watershed
Monitoring Section.


Data Verification

The analysis of the data was verified several times with processes including internal and
external reviews in addition to repeat analyses by each author. The internal review consisted of
audits performed by two of the authors (N. Doran and A. White). These audits included hand-
eye verification of every analysis figure for accuracy. Repeat calculations were performed and
compared with the first value made using new values calculated from the original data. When
errors were found, the data were recalculated by at least two of the co-authors and then replaced.

The external verification was conducted through multiple meetings with WMD staff.
During these meetings many of the actual samplers and initial compilers of the data were present.
Two rounds of discussion took place; once before this document was compiled and again as it
neared completion. These meetings lasted for several hours and many comments were made on
procedures and verification policies. Each concern was subsequently addressed and is exhibited
in the subsequent sections of this document.

Data Preparation

Preparing the data for analysis included addressing the problems of seasonality, missing
values, duplicate data, censored data and detection limits. The data variation caused by seasonal
cycles increases the difficulty of detecting long-term trends. This problem can be alleviated by
removing the cycles before applying tests or by using tests unaffected by the cycles (Gilbert,
1987).

Missing values (i.e., samples that were never collected) cause their own special
difficulties for analysis. For example, suppose 12 monthly water samples were scheduled to be
collected from a selected well in a given year. Suppose that for a variety of reasons, only 10
were actually collected. Thus, the well had two missing values for each indicator sampled.
Unless otherwise stated for the statistical analyses, missing values were treated as if they were
never collected. For example, if only 10 samples were collected, then descriptive statistics were
based on 10, instead of 12 samples.

Duplicate data resulted from two samples collected from the same spring or well
consecutively. The two samples were then labeled as representing two different sampling
events and sent to a laboratory for analyses for the same set of analytes. The purpose of
duplicates is to evaluate the internal precision of a laboratory. For statistical analyses, it was
decided that the primary sample, collected first in the time sequence, would be used. The second
duplicate sample was only used for quality assurance evaluations.






BULLETIN NO. 69


The minimum detection level for analytes from analytical laboratories can cause
environmental data to be censored. That is, the distributions are truncated at their lower ends
near the laboratory detection level. As stated earlier, for statistical analyses, all data reported as
"Below Detection Level (BDL)" were arbitrarily set at the detection level. In addition, it should
be noted that for a given analyte, over the period of record, the laboratory detection levels
changed, giving multiple detection limits.


Time Sequences

Data for analyses were segmented into three time sequences: Sequence A (1991-2003),
Sequence B (1991-1997), and Sequence C (1998-2003). The first sequence spanned the entire
sampling period, January 1, 1991 to December 31, 2003. The two smaller time sequences were
used to assist in identifying and evaluating shorter-term trends (five to six years).

Within the time sequences, each analyte needed to have a minimum of 10 data points in
order for any statistics to be performed. In addition to the minimum number of 10 data points, it
was arbitrarily decided that for Sequence A at least three data points from Sequence B and at
least three data points from Sequence C needed to be present. If Sequence A lacked this
additional criterion, then no analyses were performed on the sequence. As an example, suppose
a spring had 15 data points, 12 in Sequence C and three in Sequence B. An analysis for trend
was conducted for Sequence A, and C, but not B. If a spring only has 14 data points, 12 in
Segment C and two in Segment B, then no analyses was performed for Sequence A nor
Sequence B. However, the statistical analysis was conducted for Sequence C. A question
arises, are only three data points sufficient to represent the time Sequence B or C within
Sequence A? It certainly is not desirable and is an example of "messy" data. This situation was
considered to be sufficient for trend analyses because this study represented the first statewide
analyses for trends. Fortunately, this was not a common situation and, hopefully in the future,
available data will be less "messy."

Data Used for Analyses and Explanation of Appendices

All data presented in this report represent a collaborative effort among the five water
management districts, the U.S. Geological Survey and the Florida Geological Survey for spring
data, plus Alachua, Palm Beach, Broward, Miami-Dade, Lee, and Collier Counties for well data.
This is significant since each sampling agency has its own agenda resulting in different reasons
for the collection of a particular analyte.

Resultant data for both springs and wells can be found in Appendix H. The appendix
contains the actual concentrations for the analytes measured. The state is broken down into three
regions, Northwest, Central, and South Florida. Within each regional folder, the data are placed
in their respective WMD. Missing data were noted with an asterisk. In the folder, the results of
the MK analyses along with the corresponding n (number of data points) and the Sen Slope (SS)
for each spring and well (to be discussed later) can also be found. The format is similar to that
within the data folder. Finally, plus/minus charts (to be discussed later) are also included.






FLORIDA GEOLOGICAL SURVEY


The data in the statistical analysis folder are temporal data. A numerical value of -9999
was included to maintain the order of the spread sheet. A value of -9999 can either mean that
data are missing or it can mean that there are an insufficient number of samples to perform the
statistical analyses (procedures to be discussed later).

The remaining data were placed in tables. The tables contain the following information:
(1) the identification (ID) that names the spring (or well), (2) its location in latitude and
longitude, (3) the time sequence, (4) the dates for which samples were obtained, (5) a p-value for
significant increase, (6) a p-value for significant decrease, (6) the total number of samples within
the sequence, (7) the calculated SSs, and (8) the trend results. With regards to the results, the
tables indicate whether there was a significant increase (UP), decrease (DOWN), or no evidence
of trend. Throughout this report an upward trend will be designated with either an up arrow (t)
or a plus sign (+). A downward trend will either be designated with a down arrow (1) or a
negative sign (-).


INFORMATION GOALS AND DATA ANALYSIS PROTOCOLS

Information Introduction

The purpose of data analyses was to document water-quality trends in Florida's springs
and wells for the period 1991 2003. Prior to evaluation, a list of information goals was
developed. The goals were then turned into specific questions for which statistical procedures
could be used in an attempt to answer them. The questions are listed below and are followed by a
discussion of the statistical procedures used in this report. A more detailed discussion of all
statistical procedures used in this report can be found in Appendix E. 1 and E2. Minitab Release
14 (Minitab, 2003) and S-PLUS 6.2 Professional Edition (S-PLUS, 2003) were used for all
analyses. The six questions were:

1. What were the statistical distributions for each of the sampled analytes?
2. For Sequence A (the longest time sequence), for each analyte, and for each
spring or well, was seasonality present?
3. For each sequence, for each analyte, and for each spring or well, were
linear time series trends present?
4. If trends were present, what were their slopes?
5. For springs or wells with detectable trends, were they spatially related?
6. If evidence was found to indicate that the degrading trends were man-induced,
what are plausible solutions and recommendations?


Overview of Statistical Analyses Procedures

Descriptive Statistics

Descriptive statistics were produced for each analyte at each spring and well (station) for
the longest time sequence. The descriptions can be found in Appendix I. For each sampled
station for Sequence A, the tables list the analyte (or indicator), the measurement unit, the







BULLETIN NO. 69


number of samples collected, the number of samples with concentrations below the laboratory
detection level (BDL), the minimum value, the first, second and third quartiles, and the
maximum value. The first, second and third quartiles (Ql, Q2, and Q3) correspond to the 25th,
50th (median), and 75th percentile respectively. An example of the descriptive statistics is
presented in Table 6. For a given analyte, the reported minimum concentration value in the table
often reflected the minimum detection level reported by the analytical laboratory.

Table 6. Example of Descriptive Statistics Table
(Sequence A; January, 1991 December, 2003)
Analyte Meas. Num. Num. Min Q1 Median Q3 Max.
Unit Samp. BDLs Value Value Value Value Value
NO3 mg/L 30 7 0.05 0.09 1.00 2.00 10.30
PO4 mg/L 29 4 0.05 0.10 0.10 0.15 1.30



Kruskal-Wallis, Mann-Whitney, and Wilcoxon Rank Sum Tests

Seasonality can be thought of as periodic fluctuations or cycles. As an example, Figure
11 displays monthly water temperatures for an imaginary well during the 1992 calendar year.
Not surprisingly the temperature is highest during the summer and lowest during the winter
months, indicating that for temperature there exists a one year cycle.


Figure 11. Monthly water temperatures plotted over the 1992 calendar
year for an imaginary well.

Cycles are not restricted to calendar years. They can occur over virtually any length of
time. Figure 12 displays an example of a cycle longer than one year. In the example, the
concentration of an imaginary analyte has a six year cycle or season. Depending on the variable
of interest, it may or may not have been influenced by cycles whose frequencies are longer than
13 years; Sequence A was 13 years in length (1991-2003). It is difficult to make that


Monthly Water Temperatures
(Calendar Year 1992)
22.6-

22.5-

22.4-

' 22.3-

S22.2-

22.1-

22.0-

21.9-
1/1/1992 3/1/1992 5/1/1992 7/1/1992 9/1/1992 11/1/1992 1/1/1993
Date






FLORIDA GEOLOGICAL SURVEY


determination of the cycle's influence on the analyte. With this in mind, the authors were
concerned with the influence of shorter term cycles on Sequence A. Since ground-water samples
were collected on a quarterly and monthly basis while springs were sampled either on a quarterly
or quasi-quarterly fashion, it was decided to determine if cycles in those frequencies were
present in the data.





6
4
2
0

S-2

o -4
-6 I I I I
0 5 10 15 20 25
T im e (years)


Figure 12. Example illustration of seasonality with a six-year cyde.


For each spring or well for Sequence A, the presence of seasonality for each sampled
analyte was determined using a Kruskal-Wallis (KW) test (Hollander and Wolfe, 1973; Gilbert,
1987). Quarterly and monthly seasonality tests were conducted because stations were generally
sampled quarterly and occasionally monthly. It should be noted that monthly seasonality tests
could only be conducted if samples were collected on a monthly or quasi-monthly basis. For the
most part, monthly samples were only collected for 24 of the 46 wells and only for field analytes.
On the other hand, quarterly samples were obtained on the remaining wells and quasi-quarterly
samples were collected on most of the springs. The quasi-quarterly sampling by the WMDs and
the arbitrary seasonal breakdown was as follows: (1) December February, (2) March May, (3)
June August, and (4) September November. It should be noted that as we conducted the
analyses for trends, we found that, based on the four arbitrary seasons, most analytes did not
display significant seasonality. We recognize that in the future, with the acquisition of additional
data and with additional trend analyses, a better breakdown may be discovered. Nevertheless,
for this analysis exercise, the KW test was used to compare the distribution of two or more
populations (seasons) by indirectly comparing their median values during each season as defined
by this study. If we had defined only two seasons, the KW test is equivalent to a Mann-Whitney
(MW) test (Conover, 1999). Both tests are discussed in greater detail in Appendix E. It should
also be noted that the results of the MW test are identical to another very similar test; the
Wilcoxon rank sum test (WT) (Conover, 1999). The WT test was occasionally used during this






BULLETIN NO. 69


study because some of the statistical software used included the WT test rather than the MW test.
Conover (1999) discusses the WT test in detail. Results of the WT test are identical with those of
the MW test.

Consider a situation in which one wants to determine if two populations have the same
statistical distributions for a given season and samples are therefore obtained for each season.
For the MW test, the null hypothesis is that the median of the two populations are the same while
the alternate hypothesis is that they are not. The two samples are combined into a single ordered
sample from smallest to highest. Each observation is then assigned a rank without regard to
which sample it originally came from. The sum of the ranks assigned to those values from one
of the populations is then generated. If the rank sum of the corresponding population is very
small (or very large), there is an indication that the values from one population tends to be
smaller (or larger) than the values from the other. If so, the distributions of the two populations
are not equal. If the rank sums of the two populations are not equal, neither are their medians.

Returning to the KW test, it compares the distribution of more than two populations (e.g.,
seasons). For this report, each test was two-sided. The null hypothesis is that the median
concentration of an analyte sampled in any season is equal to the median of the remaining
seasons. The alternate hypothesis is that the median concentration for at least one season is not
equal to the others. Under the latter scenario, it is assumed that seasonality does exist. For
quarterly data, tests were conducted assuming that each quarter was a season. For monthly data
sets, tests were conducted assuming that each month was a season. The level of significance was
preset to a = 0.05.

For example, 38 temperature samples were collected at Weeki Wachee Main Spring for
time Sequence A. However, data were not available for the period 1991 through most of 1993.
Data were available for the 1993-2001 time frame. All samples were sampled on a quarterly
basis; nine in each of seasons (1), (2), and (4), plus ten in season (3). The KW test compared the
median values for each of the four seasons and, based on the test, it was concluded that the
median of at least one season did not equal the other medians. Thus, it was concluded that
quarterly seasonality does exist for the spring with respect to temperature. Since monthly data
were not available, no conclusion could be made regarding monthly seasonality. Results for
these analyses are found in Appendix J.

Deseasonalized Data

If seasonal cycles were present in the data, the data were deseasonalized using a method
presented by Intelligent Decision Technologies (1998). Although most measurements of central
tendency used in this report pertain to the medians, means were used (Sen, 1968) in the
deseasonalization transformation equation (Intelligent Decisions Technologies, 1998). The Sen
method subtracts the mean of the corresponding season from each datum and then adds the
overall average (mean) of the sequence back to the original datum. For example, suppose 10
years of quarterly data were collected at a site for chloride. Suppose the overall mean of the data
for the 10 year period was 1.0 unit while the mean of the winter quarter was 0.2 mg/L. Now
suppose a concentration for a particular winter quarter sample was 1.2 mg/L. In mg/L, the
corresponding transformed, deseasonalized datum becomes:






FLORIDA GEOLOGICAL SURVEY


x = (original) [seasonal (winter) mean] + (overall mean) = (transformed x)
x = 1.2 mg/L 0.2 mg/L + 1.0 mg/L = 2.0 mg/L.

Mann-Kendall Test

Gilbert (1987) stated that the Mann-Kendall (MK) test can be viewed as a nonparametric
test for zero slope of the linear regression of time-ordered data versus time. Given that it is a
nonparametric technique, it does not depend on an assumption of a particular underlying
distribution. The test identifies correlations in data through temporally ranking the data and then
determining the number of times the concentration goes up or down relative to the previous time
step. It only uses the relative magnitudes of the data rather than their measured values.

Data reported as trace or below the minimum detection level (MDL) were used by
assigning a common value that was smaller than, or equal to, the smallest measured value in the
data set. For this report, below detection level (BDL), was assigned an arbitrary value equal to
the detection level (DL).

Once the seasonality tests were completed (results found in Appendix J), each analyte
was tested for a linear trend using the MK test (a = 0.05) for each time sequence. A macro
program was used for the analysis while working within Minitab [Appendix E. 1)]. However, if
data were insufficient (n < 10), the MK test was not conducted. For this exercise, we always
used a one-sided test. The reason was that we had a preconceived idea as to whether or not a
downward (or upward) trend was an indication that conditions were getting worse (or better).
The results of the MK tests are found in Appendix K.

Seasonal Kendall Test

A common test used in the analyses of time series is the Seasonal Kendall (SK) test
(Gilbert, 1987). It is an adoption of the MK test, and can be used if there is seasonality in the
data. The SK test is the technique of choice. Unfortunately, it has a set of requirements that
were not obtainable. Miller et al. (2004) mentioned that the test requires that the percentage of
censored data (e.g. data reported as BDL) be no more than about five percent. In addition,
Miller stated that there should only be one censoring level. This latter requirement was not
obtainable because our data were obtained from agencies operating independently of each other.
The agencies used multiple laboratories with multiple detection levels, which amounted to
multiple censoring levels. Thus, the SK test was not used in this investigation. In the future, as
better and more consistent data are obtained, the SK test is the recommended test.

Sen Slope

If a trend was found to exist for either non-seasonal or seasonal data, its corresponding
slope was determined using a Sen Slope (SS) estimator (Sen, 1968; and Gilbert, 1987). The
estimator measured the median difference between successive concentration observations over
the time series. The SS was used only to measure the magnitude of the slope. It was not used as
a hypothesis test. Results are found in Appendix K.






BULLETIN NO. 69


Sign Test

For each analyte exhibiting a trend, a map showing the location of the corresponding
station was created. In addition to statistical evaluations, visual estimates were made as to
whether clusters of corresponding upward or downward trends existed. Associations with depth,
land use, and other relationships were evaluated. The last statistical procedure used was the sign
test (Sullivan, 2004). The sign test is a relatively simple procedure to conduct. It was used to
determine if a significant number of stations demonstrated upward or downward trends over a
geographical region. Note that one spring in the SWFWMD was not used in the analyses. The
reason will be discussed later.

As an example, suppose during Sequence A, 29 of the 57 springs displayed an upward
trend for nitrate. Can it be concluded that there exists an upward statewide trend? What if 40 (or
45) of the springs demonstrated upward trends? If one thinks of the causes of trends in
individual stations as being random processes, we could expect about half of the springs to have
upward trends, while about half should have downward trends. On the other hand, if a large
proportion of the springs had upward trends, we might be suspicious that one or more
phenomena were affecting springs and causing the upward trends over a region. Finally, if an
extremely large proportion of the springs demonstrated upward trends, we would become even
more confident that the phenomena were affecting the upward concentrations over a region.

For the sign test, one assigns a (+) value if there is an upward trend and a (-) value if
there is a downward trend. Sullivan (2004) stated that zeros add nothing to the test and therefore
should be eliminated from further analysis. Thus, all springs demonstrating no trend were
assigned a value of zero (0) and were eliminated from further analyses. The test simply
compares the proportion of + values to the values. For this exercise, a was preset to 0.05 for
the level of significance for these evaluations.

Caveats and Assumptions

It should be noted that this study was not set up as a designed experiment. We took
existing data and attempted to evaluate them. As a consequence, there were many less-than-
perfect situations that we needed to address in order to conduct the statistical analyses related to
this project. Whenever one takes existing data which were originally collected with a variety of
goals in mind and attempts to evaluate them with a new set of objectives, problems should be
expected. For example, R.A Fisher, a statistician sometimes referred to as the "Father of
Modern Statistics" (Sullivan, 2004), once stated, "To call in the statistician after the experiment
is done may be no more than asking him to perform a postmortem examination: he may be able
to say what the experiment died of" This quote is appropriate for our study. We faced many
unpleasant situations with regard to the data analyses.

One of the major sources of problems pertained to the assumptions of the statistical
procedures (see Appendix E). Generally these tests assumptions are: (1) the measurements are
mutually independent, (2) the observations are random, (3) the populations are continuous, and
(4) the scales or measurements are at least ordinal. For the sign test, the assumptions are slightly






FLORIDA GEOLOGICAL SURVEY


different: (1) the stations are mutually independent, (2) the measurement scale is at least ordinal,
and (3) if the probable outcome of a sign is (+) or (-), for one station, the same is true for all
other stations. With the exception of the independence issue, the assumptions were valid. The
issue of dependency will be addressed during the discussion of the results of the study.

RESULTS

The trend results of every spring and well for each analyte can be found in Appendix K.
What follows is a set of examples from selected springs and wells. Our purpose is to give the
reader a generalized idea about the behavior of analytes during the study period. Although some
discussion regarding the causes of trends at an individual spring will be discussed, the emphasis
of this report is on regional and statewide trends. A discussion regarding the possible sources of
the analytes and the most probably causes of trends can be found in Upchurch (1992) and
Appendix B2. The trend results are divided into both springs and wells by water management
district. There were no springs analyzed in the SFWMD. Thus springs were geographically
divided into the NWFWMD, SRWMD, SJRWMD, and SWFWMD. A note is needed regarding
the relationship between time-series figures and Sequences. If sufficient data were available,
time series analyses were generated for each Sequences A, B, and C. However, if data were
missing for the front or back end of the Sequence, the corresponding figures still cover the entire
sequence. As an example, the first series discussed is for magnesium in Wakulla Spring during
Sequence A (1991-2003). Unfortunately, no data exists for the last two years of the sequence.
Nevertheless, the figure displays the entire sequence. This is true for all time series discussed.

Springs

Northwest Florida Water Management District

In the NWFWMD, only Wakulla Spring (Figure 13) had sufficient data for analyses for
this study. Wakulla was sampled through a piece of tubing placed into a major conduit of the
spring. Thus, the samples are considered spring-water samples. However, for years, the FDEP
has, for administrative purposes, considered the tubing to be a well (Well 67 in the Temporal
Variability Network). Since FDEP considers the station to be a well and the fact that the tubing
taps a spring vent, the station for this report was analyzed both as a spring and a well. Stage data
were collected at the spring vent, and stage was used in lieu of water levels.

Rock and Saline Analytes, Nutrients, and Flow

Rock-matrix analytes included cations such as calcium and magnesium. Wakulla Spring
shows an increase in dissolved magnesium over time Sequence A (1991-2003). Increases in
magnesium and specific conductance (SC) are illustrated in Figure 14. The time series for
magnesium at Wakulla, like many analytes, showed inconsistent sampling over the period of
record. In this case the time period from 1994 to 2000 contained only one point. For the
given data, the MK






BULLETIN NO. 69


Wakulla




Legend t ;
Springs
NWFWMD
SRWMD



Miles N
10 20 40 60
Kilometers W E
15 30 60 90 S

Figure 13. Location of Wakulla Spring within the NWFWMD.

test confirmed an increasing trend (p < 0.05). For almost every time-series figure, the median
value of the second half of the sequence was compared to median of the first half, using the
Wilcoxon rank sum test (WT). This enabled us to not only determine the slope of the trend, but
to also better evaluate magnitude of change during the time series. There was a significant
change over the period of record (p < 0.05). Whether by analysis of trends, or comparison of two
halves of the time sequence, the latter half of the study revealed elevated values of dissolved
magnesium. The missing data from the intervening years in the magnesium time series (Figure
14, top) appear to be accounted for in the time series for SC (Figure 14, bottom). Wakulla Spring
showed a clear increase in SC over time. The probable causes for the increases in magnesium
and SC, will be discussed later on a districtwide and statewide perspective.

Figure 15 (top) displays a trend for nitrate-nitrite concentrations in Wakulla Spring for
the 1991-2003 time frame. The time series shows noticeable data gaps from 1995 to 2000 and
again during 2001-2003. In the Wakulla Basin, Chelette et al. (2002) indicated that there are
several significant sources of nutrients. These include effluent from a large spray field, fertilizer
application, and numerous onsite waste disposal treatment sites (OSTDS) within the basin, and
up-gradient of the spring. Fortunately, it appears, since 1991, the concentration of nitrate has
significantly decreased. Nitrate in the form of dissolved nitrate-nitrite declined (Figure 15, top).








FLORIDA GEOLOGICAL SURVEY







Wakulla Spring Time Sequence A (1991-2003)


105


10.0


S9.5-


i 9.0


85


8.0


7.5


1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003


MK p-value = 0.0002 nB=15 nc=6
WT p-value = 0.0112 SS= 0.0750


300 -






0
250


;"

200
200 -


Wakulla Spring Time Sequence A (1991-2003)





* U.
*
*~ ~ a a'- ^ y
fa WL^ ^ a ar.

*a *
ME^


1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
Date
MK p-value <0.0001 ns = 52 nc=53
WT p-value <0.0001 SS =0.52587


Figure 14. Increasing rock analytes at Wakulla Spring. Magnesium
(top) and specific conductance (SC) (bottom) have upward trends
(p < 0.05). Tests include MK for time series trends, (WT) on sequences
B and C (first and second half of study), plus SS calculations on the
rates of changes.


j jr( Tlljl I I /rtl I~ Il/llj I rl /








BULLETIN NO. 69




Wakulla Spring Time Sequence A (1991-2003)


1.1 -


1.0


Sa-
3 0.9

Co
o 0.8
0
z
5 0.7-


0.6-


0.5


1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
Date
MK p-value = 0.024 ne = 15 nc = 6
WT p-value= 0.035 SS= -0.01


Wakulla Spring Time Sequence A (1991-2003)


U M
199* .



1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003


MK p-value =0.0005 nE= 52 nc=53
WT p-value =0.0412 SS -0.0063


Figure 15. Decreasing nitrates and water levels at Wakulla Spring.
Dissolved nitrate (top) and water levels (bottom) had significant trends.
Tests (p = 0.05) included MK and WT. WT compare medians of the
first and second halves of the study. (1.0 m = 3.3 ft)


U U




U

U'


U


a






FLORIDA GEOLOGICAL SURVEY


MK and WT tests indicate that whether by trend analysis or comparison of the first and second
half of the time sequences, concentrations of nitrogen decreased. Loper et al. (2005) suggested
that the decreasing nitrate concentrations were due to lowered concentrations of effluent from a
large spray field located within 16 km (10 mi) of the spring. Figure 15 (bottom) illustrates a
significant drop in stage level.

Suwannee River Water Management District

Figure 16 displays the locations of the 15 springs located in the Suwannee River Water
Management District (SRWMD) used in this report. The spring names and the abbreviations are
found in Table 7.


Figure 16. Location of springs within the SR\MID.






BULLETIN NO. 69


Table 7. Suwannee River Water Mana ement District Spring Names and Abbreviations.
Spring Abbreviation Spring Abbreviation
Alapaha Rise ALR Poe Spring POE
Gilchrist Blue Spring GIL Blue Ruth/Little Sulfur Springs RLS
Fanning Spring FAN Rock Bluff Spring RKB
Hart Spring HAR Royal Spring ROY
Hornsby Spring HOR Suwannee Blue Spring SBL
Lafayette Blue Spring LBS Telford Spring TEL
Little River Spring LRS Troy Spring TRY
Manatee Spring MAN

Many of the springs are located along the Suwannee River, along a section of the river
which is roughly perpendicular to the coast, at least in its lower stretch. Numerous trends were
noted along an approximate south to north, or lower to upper, river direction. (Specific results are
found in Appendix K).

Rock-Matrix and Saline Analytes

Calcium, magnesium, and sodium increased strongly in the SRWMD over Sequence A.
Increases were particularly strong in the latter half of the study (Sequence C). Increasing trends
were dominant for several analytes. Magnesium and sodium had significant increases in eight of
14 springs with no decreases. Calcium increased in nine springs. Examples of increases in the
rock indicators are shown in Figures 17-20. Figures 17 and 18 illustrate trends in calcium for
four springs over Sequence A while Figures 19 and 20 demonstrate patterns for magnesium for
four springs over Sequence A or C, depending on the spring.

Note that for many of the time-series figures that compared two stations, the vertical
scales do not coincide. By keeping the vertical scales constant, occasionally the variability of
one graph became so small that you could not see it. In the end, we decided it was better to use
inconsistent vertical and to emphasize variability over time.

Changes in calcium in springs for the lower Suwannee River are similar to changes in
springs farther north. Fanning Spring (FAN) and Gilchrist Blue Spring (GIL Blue) illustrate two
of the nine springs that exhibited an increase in calcium (Figure 17). In addition to calcium,
FAN showed significant increases in other rock-matrix and saline indicators including alkalinity,
chloride, potassium, magnesium, sodium, and specific conductance. The time series plot in
Figure 17 shows a gradual increase in calcium from 60 mg/L in 1995 to approximately 80 mg/L
in 2003; the gradual increase had a low variance around the best fit line. When data for
sequences B and C were compared, Sequence C data had clearly higher medians (WT test p-
value, <0.0001, illustrated by box plots in inset figure in bottom corer). Like FAN, for
Sequence A, calcium concentrations in GIL Blue increased. The initial concentration was about
50 mg/L and ended with 65 mg/L; both springs increased in concentration by approximately 20
mg/L. GIL Blue also had many other analytes with upward trends that mirrored FAN: alkalinity,
chloride, magnesium, sodium, and specific conductance. Springs farther north (Figure 18) had
similar looking trends to those springs located farther south (Figure 17), although the overall
trends in other analytes were different. Suwannee Blue Spring (SBL) and Troy Spring (TRY)
together had increases in only







FLORIDA GEOLOGICAL SURVEY



Fanning Springs Time Sequence A (1991-2003)


5/22/1997


10/11/1999
Date


3/1/2002


MKp-value =0.0005 nA= 10 n = 40
WTp-value<0.0001 SS =0.2694


Gilchrist Blue Spring Time Sequence A (1991-2003)










* -^. *
*
U mmmm




U




mm U


1993 1994 1995
MK p-value =0.0005
WT p-value =0.0563


1996 1997 1998 1999 2000 2001 2002
SS= 0.2694 Date
nA =8 nB =33


Figure 17. Increasing rock analytes at Fanning and Gilchrist Blue
Springs. Fanning (top) and Gilchrist Blue Springs (bottom) had
significant increases in calcium. Tests (p < 0.05) included MK for
for trend, WT on Sequences B and C, plus SS calculations on the rate
of change. Beginning and ending sampling dates for the two springs
are not the same.


a


S40-



20-


01--
1/1/1995


7/21/2004


65-


60-


-55-


50-


45-


40-








BULLETIN NO. 69




Suwannee Blue Spring Time Sequence A (1991-2003)


401
4/1/1997

MK p-value
WT p-value


s


50



40


12/4/1998 8/8/2000 4/12/2002
:0.0001 SS= 0.2565 Date
:0.0001 nA = 23 nB= 24


Troy Spring Time Sequence A (1991-2003)


U




P U


EUr ^ *- SE

m*

*

*
t


8/5/1995 5/1/1998
:0.0001 SS= 0.1782 Date
0.0006 nA= 18n =42


1/25/2001 10/22/2003


Figure 18. Increasing rock analytes at Suwannee Blue and Troy Springs.
Suwannee Blue (top) and Troy Spring (bottom) had significant increases in
calcium. Tests (p < 0.05) included MK for trend, WT on Sequences B and C,
plus SS calculations on the rate of change. Beginning and ending sampling
dates for the two springs are not the same.


12/16/2003


11/8/1992
MK p-value
WT p-value









FLORIDA GEOLOGICAL SURVEY




Manatee Spring Time Sequence A (1991-2003)


10/1/1997


2/2/2000


6/5/2002


MKp-value<0.0001 SS= 0.0351 Date
WTp-value<0.0001 n =22 n2=22






Hart Springs Time Sequence C (1998-2003)


0.3
5/1/1996
MK p-value
WT p-value:


4/12/1998 3/24/2000
=0.0017 SS= 0.066667 Date
=0.006 n1=9 n2=9


3/5/2002


2/15/2004


Figure 19. Increasing rock analytes at Manatee and Hart Springs.
Manatee (top) and Hart Springs (bottom) had significant increases in
magnesium. Tests (p < 0.05) included MK for trend, WT on the first (1)
half and the second (2) half of both time series. Beginning and ending
sampling date for springs are not the same.


*
* ^

.^ ^ m
.^-'" *
^ **
-^-"'"'
^^^ ^' *
m^-^^


6/1/1995


10/6/2004


E 5.0

51-
I

4.5-




4.0-


N.


U U


I I I I I I








BULLETIN NO. 69




Poe Spring Time Sequence C (1998-2003)


2
6/26/1997

MK p-value
WT p-value


4/2/1999 1/7/2001 10/15/2002 7/22/2004
Date
:0.0001 SS= 0.0830
:0.0001 nt=22 n2=22


Lafayette Blue Spring Time Sequence A (1991-2003)


9/11/1997


MK p-value <0.0001 SS = 0.0745
WT p-value =0.0082 nt=22 n2=22


10/13/1999
Date


11/13/2001


12/16/2003


Figure 20. Increasing rock analytes at Poe and Lafayette Blue Springs.
Poe (top) and Lafayette Blue Spring (bottom) had significant increases in
magnesium. Tests (p < 0.05) included MK for trend, WT on the first and
second half of both series, and SS calculation on rate of change. Beginning
and ending sampling dates for the springs are not the same.


I-
16



14 -




1-



10-



8-


U U

U .
U~


8/11/1995






FLORIDA GEOLOGICAL SURVEY


calcium, magnesium and sodium. Unlike FAN and GIL Blue, SBL and TRY exhibited no linked
trends in alkalinity, chloride, potassium, or specific conductance.

Toward the south, Manatee (MAN) and Hart (HAR) (Figure 19) began the time series
with approximately four mg/L of magnesium; by the conclusion of the series, they were at six to
seven mg/L. Further north, Poe Spring (Poe) (Figure 20) began at about four mg/L in 1998 and
rose to about 10 mg/L in late 2002. Lafayette Blue Springs (LBS) (Figure 20)( began at about
eight mg/L in 1998 and rose to about 14 mg/L in 2001.

Flow

The SRWMD consistently collected flow or discharge data at specific spring vents during
the same day that they collected water samples from their springs. However, the SRWMD did
not begin collecting discharge data until the 1997-1998 time frame.

During Sequence C, for the SRWMD, flow rates decreased significantly in 12 of 16
springs. There was not an increase in flow rate in any of the springs during the same time
sequence. In addition, the degree of decrease in flow was sometimes severe. Figures 21-24
illustrate the trends for eight springs starting at the lower end of the Suwannee River and moving
inland and northward.

Springs at the lowest end of the Suwannee River included Fanning (FAN) and Hart
(HAR) Springs (Figure 21). Both springs show substantial drops in flow levels. By the end of the
period of record, flow was reduced to approximately half the levels seen at the beginning of the
time series. FAN's highest recorded flows were near 120 cubic feet per second (cfs), but ended
near 50 cfs. HAR's highest recorded flow was approximately 90 cfs and fell to near 40 cfs at the
end fo the time series.

Upstream from these springs are Rock Bluff (RKB) on the Suwannee and Hornsby
(HOR) Springs on the Santa Fe River (Figure 22). Both displayed even sharper declines in flow.
Rock Bluff went from a high of 50 cfs to under 20; flow was reduced to zero cfs briefly in 2001.
Hornsby showed an even stronger decline: over 200 cfs was measured in 1998 and the flow
reduced to zero cfs during a period starting in early 2000. This was followed by a small recovery
of flow rate in 2003.

Poe Spring, on the Santa Fe River, and Little River Sulfur Spring (LRS) on the middle
Suwannee region had strong declines in flow rate (Figure 23 (Sequence A; but mostly C)). Poe
Spring recorded discharges of 60 to 80 cfs near the beginning of the time series but declined to
near 20 cfs by the end. LRS began the time series with a flow rate near 90 cfs and ended near
20. Decline in flow at LRS closely followed a regression line fit to the date (Figure 23, bottom).

Troy (TRY) and Telford (TEL) Springs both had downward trends in flow. Though flow
at Troy was approximately three times higher than Telford (Figure 24; Sequence A, but mostly
C)), there was a slight increase in flow in mid-1998 followed by a decrease for both springs in
early 2000, and then another slight increase in flow occurred in late 2001. Overall, both springs
seem to show that flow was reduced by at least half, with LRS indicating a reduction in flow by a
third at the end of the time series.







BULLETIN NO. 69


Fanning Springs Time Sequence C (1998-2003)


1/1/1997 5/10/1998 9/16/1999 1/22/2001
MK p-value <0.0001 SS =0.2773 Date
WTp-value=0.0002 n=11 n2= 11

Hart Springs Time Sequence C (1998-2003)


06//1
6/12/1996


5/13/1998 4/12/2000 3/13/2002


6/1/2002


2/11/2004


MKp-value <0.0001 SS =-3.2411
WTp-value =0.0012 n1=9 n2=9




Figure 21. Decreasing flow at Fanning and Hart Springs. Between 1998
and 2001 Fanning (top) and Hart Springs (bottom) had significant de-
creases in flow. Tests (p <0.05) included MK for trend, WT, plus an
SS calculation on rate of change. Over the period of record, flow at both
springs was reduced significantly. Beginning and ending sampling dates are
not the same. [One cfs equals 0.028 cubic meters per second (cms).]








FLORIDA GEOLOGICAL SURVEY



Rock Bluff Springs Time Sequence C (1998-2003)


1/1/1997 10/2/1998
MKp-value <0.0001 SS =1.0039
WT p-value =0.0001 nl=14 n2=14


7/2/2000 4/2/2002
Date


Hornsby Spring Time Sequence C (1998-2003)











*+


11/5/1998


9/8/2000


7/13/2002


MKp-value =0.0003 SS=-3.4692 Date
WTp-value=0.0006 n= 17 n= 17


Figure 22. Decreasing flow at Rock Bluff and Hornsby Springs. Rock
Bluff (top) and Homsby Springs (bottom) had significant decreases in flow.
Tests (p < 0.05) included MK for trend, WT, plus an SS calculation. For both
Rock Bluff and Homsby, flow reduced dramatically. Homsby Springs flow
stopped for a period after late 2000. Beginning and ending sampling dates are
not the same. (One cfs = 0.028 cms)


1/1/2004


300




200

if


100




0-


1/1/1997


5/16/2004








BULLETIN NO. 69



Poe Spring Sequence A (1991- 2003)


11/26/1998


MK p-value <0.0009 SS =-0.925
WTp-value=0.0065 n =22n2=22


10/20/2000
nr'o


Little River Spring Sequence A (1991- 2003)


1/1/1997 8/9/1998 3/17/2000 10123/2001
MK p-value <0.0001 SS -2.1420 Date
WTp-value=0.0039 n1=15 n2= 16


6/112003


Figure 23. Decreasing flow at Poe and Little River Springs. Poe (top)
and Little River Springs (bottom) had significant decreases in flow. Tests
(p < 0.05) included MK for trend, WT, plus an SS calculation on rate of
change. For both Poe and Little River flow reduced to about one third by
the end of the series. Beginning and ending sampling dates are not the same.
(One cfs = 0.028 cms)


80-





so-





40


U U
U


111/11997


9/14/2002


8/9/2004


Date








FLORIDA GEOLOGICAL SURVEY



Troy Spring Time Sequence A (1991-2003)


1/1/1997

MK p-value
WT p-value


8/9/1998 3/17/2000 10/23/2001

<0.0001 SS=0.1782 Date
=0.0221 n= 13 n2=13


Telford Spring Time Sequence A (1991-2003)


8/1/1998


MK p-value <0.0001
WT p-value =0.1547 SS =-0.6674
nt=15 n2=15


3/1/2000
Date


9/30/2001


Figure 24. Decreasing flow at Troy and Telford Springs. Troy (top) and
Telford Springs (bottom) had significant decreases in flow. Tests (p < 0.05)
included MK for trend, WT, plus an SS calculation on rate of change. Over
the period of record, flow at both Troy and Telford was reduced by half. Be-
ginning and ending sampling dates are not the same. (One cfs = 0.028 cms)


6/1/2003


U
UI

U

S a
U U .
U U U


10 -
1/1/1997


5/1/2003






BULLETIN NO. 69


Nutrient Analytes

For the study period, nutrients in the SRWMD had more complex patterns than the
patterns of either the salinity indicators or flow. While some nutrient trends were very strong,
others were not as clear. During Sequence A, o fthe 15 springs in the SRWMD, TKN increased
significantly in nine springs (with no decreasing trends). Nitrate appeared to decrease (downward
trend in six springs, while it increased in three springs). At the same time, other nutrients-
phosphorus and phosphate specifically-appeared to increase. For phosphorus, there were five
springs with increasing trends and only one spring indicating a decrease; for phosphate there
were four springs with increasing trends and only one spring with a decreasing trend.

The FDEP has a maximum nitrate standard of 10 mg/L for groundwater and Class I
surface water before considering the water impaired. Both water standards are directed toward
maintaining drinking water quality (Florida Department of Environmental Protection, 1994).
Currently, there is not a numeric standard that is directed toward changes and concentrations of
biota in surface water. However, FDEP has established a non-legal threshold for nitrate and
phosphorus for surface water (Florida Department of Environmental Protection, 2004). The
thresholds were based on a statewide evaluation of chlorophyll concentrations in lakes. The
groundwater-surface water relational assessment (SRA) limit is 0.45 mg/L for nitrate.
Groundwater nitrate concentrations exceeding the 0.45 mg/L limit suggest that there is a
potential for adverse affects on aquatic organisms in the spring runs. Technically, the threshold
level applies only to surface water and there is a need to establish a groundwater to surface water
interaction for the threshold to be relevant. Since springs represent an interaction between
groundwater and surface water, we used the threshold level for comparative purposes. Figures
25 and 26 represent examples of changes in nutrients in springs of the SRWMD. Figure 25 is
an example of a decreasing nitrate trend. Nitrate significantly decreased from 1998-2003 for Poe
Spring. For comparative purposes the SRA was chosen as a fixed reference and is the gray line in
Figure 25. Poe Spring exceeded the SRA recommendations prior to 1999, but then declined to
levels below the SRA. Possible reasons for the decline in nitrate in the Suwannee Basin will be
discussed later.

While nitrate often decreased in the SRWMD, TKN rose significantly. Phosphorus also
exhibited some increasing concentrations. Total phosphorus at Poe Spring (Figure 26) almost
doubled from 1999 to 2003. Phosphorus and phosphate both increased at several springs. An
even greater number of upward trends, however, were seen for TKN. Figure 26 (bottom) shows
an increase in TKN at Lafayette Blue Spring over the study period. The plot also illustrates
some of the differences between nutrient and saline trends. While saline and rock-matrix analyte
plots give evidence of clear increases, trend lines for nutrient plots were sometimes less well
defined and potentially not as strong. Figure 26 shows a significant upward trend for total
phosphorus (MK test, p < 0.05) though the p-value of 0.0443 does not indicate such a strong
increasing trend; data for the first and second half of the time sequence were not significantly
different (WT p-value = 0.3633). The potential causes of nutrient and other trends will be
discussed later.








FLORIDA GEOLOGICAL SURVEY











Poe Spring Time Sequence C (1998-2003)


7/1/1997 4/1/1998 1//1199910/1/19997/1/2000 411/2001 111/200210/1/20027/1/2003
Date
MKp-value <0.0001 SS =-0.0090
WTp-value <0.0001 ni= 22 n2= 23

Figure 25. Decreasing nitrates at Poe Spring. The horizontal line represents
The FDEP's SRA limit for total nitrate (0.45 mg/L). Levels exceeded recommended
SRA limit prior to late 1999 but since then were significantly lower.


1.2





S0.8


o
z
i1--
0.4





0.0








BULLETIN NO. 69






Poe Spring Time Sequence C (1998-2003)


5/1/1997


1/30/1999


10/30/2000


7/31/2002


5/1/2004


MKp-value <0.0001 SS = 0.0007
WTp-value= 0.0001 n= 22 n2 = 23


Lafayette Blue Spring Time Sequence A (1991-2003)

















M 0.
M




^^^^==
m^ -'"'


111/1995


6/18/1997


12/5/1999


5/22/2002


11/7/2004


MK p-value = 0.0443 SS= 0.0012
WTp-value= 0.3633 nB= 6 nc= 41

Figure 26. Increasing nutrient analytes at Poe and Lafayette Blue Springs.
Poe (top) and Lafayette Blue (bottom) illustrate two increasing nutrients in
the SRWMD: one for phosphorus and the other for TKN. Poe shows a clear
increase in phosphorus while TKN at Lafayette Blue illustrates one of the many
increasing TKN trends in SRWMD springs. Beginning and ending sampling
dates for these springs are not the same.


0.14



0.12-



0 0.10-


I-
0.08



0.06



0.04-


mmm
U




U
*U
U<^'
U U


*U


r m
**
m m -$


0.4-




0.3-




E 0.2-
z
I-



0.1-




0.0-






FLORIDA GEOLOGICAL SURVEY


St. Johns River Water Management District

The springs located in the St. Johns River Water Management District (SJRWMD) and
used in this report are found in Figure 27. Spring names and abbreviations are found in Table 8.


Figure 27. Location of Springs within the SJRWMD.






BULLETIN NO. 69


Table 8. St. Johns River Water Management District Spring Names and Abbreviations
Spring Abbreviation Spring Abbreviation
Alexander Spring Alexander Salt Springs Salt
Apopka Spring Apopka Sanlando Springs Sanlando
Fern Hammock Springs Fern Silver Glen Springs Silver G
Juniper Springs Juniper Starbuck Spring Starbuck
Miami Spring Miami Sweetwater Spring Sweetwater
Palm Spring Palm Volusia Blue Spring Vol Blue
Ponce De Leon Spring PDL Wekiwa Spring Wekiwa
Rock Spring Rock

Calcium, strontium, fluoride, and pH increased in a significant number of springs over
time Sequence A, while phosphate levels decreased. With respect to individual springs, Miami,
Palm, Sanlando, and Wekiwa Springs had at least eight analytes with increasing trends over
Sequence A, while Volusia Blue Spring (Vol Blue) and Sweetwater Spring decreased in at least
eight analytes over the same time sequence. Alexander, Salt, and Silver Glen (Silver G) Springs
each had six or fewer analytes showing any trend (positive or negative). Sequence B had no
districtwide trends. During Sequence C fluoride and pH increased in a large number of springs
while flow decreased at many locations.


Rock-Matrix and Saline Analytes

Increasing trends were associated with the following rock-matrix analytes: strontium,
calcium, pH and fluoride increased over Sequence A. Nine springs had significant increases in
calcium and pH while one spring had a decreasing trend for theses analytes. Both fluoride and
strontium increased in 10 springs. Strontium decreased in one, whereas fluoride decreased in
none. No trends were observed in Sequence B. Within Sequence C, upward trends were
observed for fluoride and pH, while flow decreased. Thus, major changes for the SJRWMD, like
other districts, occurred during 1998 to 2003 (Sequence C).

Figures 28-30 depict increases in two rock-matrix analytes for three springs in Seminole
and Orange Counties. Not depicted are Starbuck, Rock, and Apopka, which showed the same
pattern. Alkalinity and strontium suggest changing chemistries. Both analytes increased in
Palm, Sanlando, and Wekiwa Springs. All plots show trends closely fitting an increasing best-fit
line. Starting at about 116 mg/L for alkalinity, Palm Springs increases to about 126 mg/L.
Sanlando Springs begins at about 130 mg/L and increases to approximately 150 mg/L.
Strontium at Sanlando Springs began around 60 tg/L and ended over 90 with little variation in
the upward trend. Wekiwa Spring started at a higher level (near 100 gg/L) and ended the time
series at about 140 jtg/L. Wekiwa Spring is also unique in showing an apparently quick increase
in concentration between 1993 and 1995. Palm Springs differed from the other two springs in
having strontium concentrations at the start of the study three to four times higher than the other
two springs.








FLORIDA GEOLOGICAL SURVEY




Palm Springs Time Sequence A (1991-2003)






U











U


1118/1992 8/5/1995 5/1/1998
MK p-value = 0.0141 SS= 0.1291 Date
WTp-value= 0.0209 inb=7 n =21


1/25/2001 10/22/2003


Palm Springs Time Sequence A (1991-2003)




*
*


11/8/1992 8/5/1995 511/1998
MK p-value= 0.0029 SS= 1.2289 Date
WTp-value=0.0081 nb=6 n,=20


1/25/2001 10/22/2003


Figure 28. Increasing rock analytes at Palm Springs. Alkalinity (top)
and strontium (bottom) increased significantly over Sequence A. Tests
(p < 0.05) included MK for trend, WT on sequences B and C, plus an SS
calculation. Beginning and ending dates for the springs were not the same.


1241


I
S120
I-
118-


116-


114-


-



290




250-


I))) I








BULLETIN NO. 69




Sanlando Springs Time Sequence A (1991-2003)


146



141



A 136


I-
131



126



121


11/8/1992 8/5/1995

MK p-value= 0.0010 SS= 0.417
WTp-value=0.0032 nb=6 ni =21


5/1/1998 1/25/2001 10/22/2003
Date


Sanlando Springs Time Sequence A (1991-2003)


90 -





3 80


t-


70-





60-


1118/1992 8/5/1995 5/1/1998 1/25/2001 10/22/2003
Date
MK p-value < 0.0001 SS = 0.625
WT p-value = 0.0009 nb = 6 n, = 20


Figure 29. Increasing rock analytes at Sanlando Springs. Alkalinity (top)
and strontium (bottom) increased significantly over Sequence A. Tests
(p < 0.05) included MK for trend, WT on sequences B and C, plus an SS
calculation on rate ofchange. Beginning and ending sampling dates for these
springs were not the same.


*"
==
ge


- 5


I


*H


* *







FLORIDA GEOLOGICAL SURVEY




Wekiwa Spring Sequence A (1991-2003)





120-

















1 212/1990 11/8/1992 8/5/1995 5/1/1998 1/25/2001 10122/2003

MK p-value <0.0001 SS 0.3568 Date
WT p-value<0.0001 nb=21 n,=21

Wekiwa Spring Time Sequence A (1991-2003)




180-


160 -


140 *


120


100


80
2/12/1990 11/8/1992 8/5/1995 5/1/1998 1/25/2001 10/22/2003
MK p-value< 0.0001 SS= 0.368 Date
WTp-value<0.0001 nb=17 n,=21


Figure30. Increasing rock analytes at Wekiwa Spring. Alkalinity (top)
and strontium (bottom) increased significantly over SequenceA. Tests
(p < 0.05) included MK for trend, WT on sequences B and C, plus an SS
calculation. Beginning dates for these springs were not the same.
80 ------- l --------------------i --









calculation. Beginning dates for these springs were not the same.






BULLETIN NO. 69


Nutrient Analytes

For the study period, there were fewer nutrients trends in the SJRWMD than in other
WMDs. For example, both phosphorus and TKN demonstrated few to no changes (no increases
or decreases for phosphorus, no increases and two decreases for TKN). Nitrate showed no clear
trend direction. For example, in the seven springs showing trends for nitrate, three increased and
four decreased. With respect to nutrients, only phosphate showed consistent trends across the
district. Eleven springs decreased in phosphate while no springs increased.

Figure 31 shows two phosphate trends, which also are considered to be Rock-matrix
analytes. Phosphate levels for both Palm and Starbuck Springs fell by nearly half of the initial
concentrations. Phosphate at Palm Springs (top figure) began the time series at approximately
0.15 mg/L and dropped to about 0.09 in 2002. Values from the end of the time series, 2002 to
2003, suggest a rise in concentrations. Starbuck levels began near 0.17 mg/L and fell to about
0.12 mg/L. Similar to Palm Springs, Starbuck appears to record a rise in concentrations near the
end of the time series in 2003.


Southwest Florida Water Management District

Figure 32 shows the locations of the springs in the SWFWMD. Table 9 displays the
corresponding spring abbreviations.

Note that after our analyses, the SWFWMD notified the authors and told us that they now
question the validity of using Boyette Spring data. They now believe it receives a significant
portion of its water from a nearby sinkhole (< 1 kilometer away) and much of the receiving water
is dairy waste (Morrison, 2000). Since the individual spring analyses were already completed,
we decided to keep the spring in the analyses. However, because of the point-source dairy
contamination, Boyette Spring data were removed from districtwide and statewide analyses.
Also, the SWFWMD was the only WMD to analyze for bicarbonate, rather than alkalinity.

The SWFWMD springs had strong trends in rock-matrix, saline and nutrient indicators.
Similar to the SRWMD, rock-matrix and saline indicators rose significantly. Unlike the
SRWMD, nutrient indicators showed different types of trends. Differences in behavior of
nutrients between the SRWMD and SWFWMD suggest regional differences exist between these
two areas. Similarities in rock-matrix and saline trends between the SRWMD and SWFWMD
suggest these trends extend beyond district boundaries. Some springs showed more changing
chemistries than others. Betty Jay, Boyette, and Tarpon Hole Springs had many analytes with
increasing trends. Buckhorn Main and Hidden River No. 2 Spring had a number of decreasing
trends. Those showing no trends among the analytes studied during time Sequence B included
Boat, Bobhill, Rainbow Swamp No. 3, and Wilson Head Springs.

Rock-Matrix and Saline Analytes

Strong increases in both rock-matrix and saline analytes were evident in springs in the
SWFWMD during time Sequence A. Analytes with increasing trends include bicarbonate,








FLORIDA GEOLOGICAL SURVEY





Palm Springs Time Sequence A (1995-2003)


1995 1996 1997 1998 1999 2000 2001 2002 2003
Date
MK p-value < 0.0220 SS = -0.0013
WTp-value< 0.0081 nb = 6 nc =19


Starbuck Spring Time Sequence A (1991-2003)


0.19




0.17


0.15
2" 0.15 -




0.13




0.11
11/8/1992
MK p-value
WT p-value


8/5/1995 5/1/1998 1/25/2001 10/22/2003
0.0096 SS =-0.0013 Date
0.0218 nb 6 n =20


Figure 31. Decreasing phosphate concentrations at Palm and Starbuck
Springs. Palm (top) and Starbuck Springs (bottom) illustrate the most
sharply decreasing nutrient (phosphate) in the district. Both springs show
substantial reductions since the beginning of the time series, with a potential
increase at the end of the series. Note samples were not collected until 1995.


0.18


0.16


> 0.14


" 0.12


0.10


0.08


U I


% "E







BULLETIN NO. 69


Figure 32. Location of springs within the SWFWMD.






FLORIDA GEOLOGICAL SURVEY


Table 9. Southwest Florida Water Management District Spring Names and Abbreviations
Spring Abbreviation Spring Abbreviation
Betty Jay Spring Betty Jay Hunters Spring Hunters
Boat Spring Boat Lithia Main Spring Lithia Main
Bobhill Spring Bobhill Magnolia Spring Magnolia
Boyette Spring Boyette Pump House Spring Pump House
Bubbling Spring Bubbling Rainbow No. 1 Spring Rainbow No. 1
Buckhor Main Spring Buckhorn Main Rainbow No. 4 Spring Rainbow No. 4
Catfish Spring Catfish Rainbow No. 6 Spring Rainbow No. 6
Chassahowitzka Chassahowitzka Rainbow Bridge Seep Rainbow Bridge
No. 1 Spring No. 1 Seep
Chassahowitzka Chassahowitzka Rainbow Swamp Rainbow
Main Spring Main Spring No. 3 Swamp No. 3
Hidden River Hidden River Salt Spring Salt
Head Spring Head
Hidden River Hidden River Tarpon Hole Spring Tarpon Hole
No. 2 Spring No. 2
Homosassa Homosassa Trotter Main Spring Trotter Main
No. 1 Spring No. 1
Homosassa Homosassa Weeki Wachee Main Weeki Wachee
No. 2 Spring No. 2 Spring Main
Homosassa Homosassa Wilson Head Spring Wilson Head
No. 3 Spring No. 3

calcium, chloride, potassium, magnesium, sodium, conductivity, sulfate, strontium, and total
dissolved solids. Of these, increases strongly attributable to rock chemistries were bicarbonate
and strontium. Regarding salinity, rises in sodium, chloride, and total dissolved solids were
observed. Analytes in common to both groups included calcium, potassium, magnesium, specific
conductance, and sulfate (which showed strong increases). Similar to other districts, Sequence B
had very few trends. The majority of the influence for these increases occurred during time
Sequence C.

Chloride increased in 18 springs. Figures 33-35 depict the chloride trends from several
springs in the northern SWFWMD along the Gulf Coast.

Springs occur from north to south along the Gulf Coast. Figure 33 includes two springs
from southern Marion County, one of the northernmost counties in SWFWMD. These springs,
Rainbow No. 6 and Bubbling Springs, increased in chloride concentrations, both springs show a
steady increase during the years of Sequence A. Both springs began with 3.0-4.0 mg/L of
chloride and ended the time series with approximately 5.0-6.0 mg/L.

For a couple of springs just to the south in Citrus County, the increase in chloride was
more dramatic (Figure 34). Hunters Spring (top) began the time series with approximately 50
mg/L of chloride. Values rose quickly at one point, more than doubling, and then declined.
Trotter Main (bottom) showed a similar pattern, though with sharper changes. Trotter Main had
values of approximately 50 mg/L near the start, as did Hunters, but then increased to nearly 250









BULLETIN NO. 69






Rainbow No. 6 Spring Time Sequence A (1991-2003)


3.0 1


1995 1996 1997 1998 1999 2000 2001 2002 2003
MK p-value = 0.0002 SS = 0.0321 Date
WTp-value< 0.0001 b = 16 n= 23



Bubbling Spring Time Sequence A (1991-2003)


6.5 -



6.0 -



0)5.5 -



5.0


1994 1995 1996 1997 1998

MKp-value= 0.0002 SS = 0.0417
WTp-value= 0.0014 nb 13 nc=23


1999 2000 2001 2002 2003
Date


Figure 33. Increasing saline analytes at Rainbow and Bubbling Springs.
Rainbow No. 6 (top) and Bubbling Springs (bottom) had significant increases
in chloride. Tests (p < 0.05) included MK for trend, WT on sequences B and
C, plus an SS calculation on rate of change. Beginning and ending dates for
these springs are not the same.


*






* ^- m " a .^
U





*
5U





U
U

U


.. *.


*


'' '' '' '' '' '' '' '' '' '''


4.0 1


*








FLORIDA GEOLOGICAL SURVEY





Hunter Spring Time Sequence A (1991-2003)


110-



90-


C)
E
S70



50-



30-



10


MK p-value = 0.0005 SS= 1.5802
WT p-value = 0.0033 nb = 12 nc= 20


Trotter Main Spring Time Sequence A (1991-2003)




U

U


U



U*
*

*
"/
^^^-"*'"'

*m 5 My^'
*m. a" ^
^^ ^ "


1995 1996 1997
MK p-value< 0.0001 SS
WT p-value = 0.0009 nb
23


1998 1999 2000 2001
0.1133 Date
15 n,=


Figure 34. Increasing saline analytes for Hunters and Trotter Main
Springs. Hunter (top) and Trotter Main Springs (bottom) had significant
increases in chloride. Tests (p < 0.05) included MK for trend, WT on
sequences B and C, plus an SS calculation on rate of change. Beginning
and ending dates for these springs are not the same.


1995 1996 1997 1998 1999 2000 2001
Date


U






S.*





*


2002 2003


250-



200-



IO-
150


6
100-



50-


2002 2003








BULLETIN NO. 69







Weeki Wachee Sequence A (1991-2003)


7





6
*








5 -


1995 1996 1997 1998 1999 2000 2001 2002 2003
Date

MK p-value< 0.0001 SS = 0.0457
WT p-value <0.0032 nb 15 n-= 23


Bobhill Spring Time Sequence A (1991-2003)


17


15 -


13

011



9


7


5


1995 1996 1997 1998 1999 2000 2001 2002 2003


MKp-value< 0.0001 SS 0.1133
WTp-value<0.0009 nb=14 n,=19


Date


Figure 35. Increasing saline analytes for Weeki Wachee and Bobhill Springs.
Weeki Wachee (top) and Bobhill Springs (bottom) had significant increases in
chloride. Tests (p <0.05) included MK for trend, WT on sequences B and C,
plus an SS calculation on rate of change.






FLORIDA GEOLOGICAL SURVEY


mg/L at one point-a five-fold increase. Figure 35 depicts chloride concentrations at Weeki
Wachee and Bobhill Springs. Weeki Wachee began the time series with only about 6.0 mg/L of
chloride and ended with a concentration of about 8.0 mg/L. Bobhill Spring began about 5.0 mg/L
and ended with about a 9.0 mg/L chloride concentration.

Flow

Flow data were available for only three gaging stations within the SWFWMD. While
there were inadequate data to make statistical conclusions for the SWFWMD, data from the
three' stations suggested possible declines similar to the SRWMD. Homosassa No. 1 flow levels
declined for the years 1996-2003 (Figure 36). Longer-term trends are depicted in Figure 37,
which further illustrates declines in flow. Since the 1960s, average yearly flow for Rainbow
Springs has declined (dark gray line indicates a timeline for Sequence A). WT tests between the
first and second half of the data series show a difference between the two data series. However,
for data representing time Sequence A, results do not indicate a significant difference. This
suggests that trends on the scale of this study (i.e., 13 years) may sometimes be missed in spite of
being part of a larger change (e.g. 40 years of data).

Long-term flow in Weeki Wachee Springs flow data (Figure 37, bottom) has an equally
interesting pattern. Although no regression is displayed, flow data going back to 1904 displays a
rise until the 1960s, followed by a decline until the present. Gray lines illustrate the time line for
Sequence A and that for post-1960. The range in flow during this time appears to be two-fold
(100 to 250 cfs). Such a pattern may reveal that short-period trends may be part of longer-term
cycles for groundwater; implications of this will be addressed later.

Nutrient Analytes

For Sequence A, nitrate increased strongly (19 springs with upward trends, only one
down), while ammonia, phosphate, phosphorus, TKN, and total organic carbon showed little
indication of trends. Since TKN, phosphorus, and total organic carbon decreased somewhat
(though not significantly) it seems to indicate that nitrate-nitrogen alone showed the strongest
increase for SWFWMD. All other analytes showed little change or even evidence of a slight
decline. Also unlike patterns seen in the rock and saline indicators, nitrate increased during both
sequences B and C. This is in contrast with the rock analytes which showed strongest activity
during Sequence C.

Figure 38 and 39 illustrate nutrient trends and their variability for SWFWMD. Hunter and
Magnolia Springs (Figure 38), illustrate clear increases in nitrate over Sequence A. Nitrate
increases occurred regardless of initial concentrations at the beginning of the time series. For
example, Hunter Spring (top) had a consistent increase from a low initial value (about 0.25
mg/L) to just under the SRA threshold of 0.45 mg/L. Hunter remained under the SRA value for
the time period. Magnolia Spring showed a rate of increase similar to Hunter (SS = 0.0046 and
0.0042, respectively). However, Magnolia began the time series with a higher starting value
(about 0.35 mg/L). The trend for Magnolia crossed over the SRA threshold (Figure 38, bottom,
gray line marks SRA value). Similarly Weeki Wachee (Figure 39, top), began the time series







BULLETIN NO. 69


with a value near 0.45 mg/L and increased to 0.8 mg/L by the end of the time sequence. All three
springs had similar rates of change yet differed in their initial concentrations of nitrate.
Homosassa No. 1 Spring Flow


0
80-


60-



40-


1/21996 1/2/1998 12/2000
Date
LRp-value < 0.0001
n =2879 WTp-value < 0.0001


1/2/2002 12/2004


Figure 36. Decreasing flow at Homosassa No. 1 Spring. Flow rates
declined significantly from 1996 to 2003. (One cfs = 0.028 cms)

Overall, TKN showed little activity (one trend up, four down for Sequence A). Figure 39
(bottom) shows a trend in TKN for Boyette Spring. It started with relatively low initial values
and was followed with a rapid increase in 1998. Values went from near 0.5 mg/L to over 3.0
mg/L in short period of time.

Field Analytes


Only two Field analytes demonstrated decreasing trends over Sequence A, pH and
temperature. The analyte pH decreased in 10 springs, while temperature decreased in eight. The
trends for pH largely occurred in Sequence C.

Wells

The wells used for this study are a subdivision of FDEP's Background Network. The
subdivision is referred to as the Temporal Variability (TV) Network. Although independent of
springs, it was believed that evaluating trends in wells would shed insight as to the chemical
behavior of Florida's groundwater. The TV Network subdivides wells into whether they are
confined or unconfined. Because of the small number of confined and unconfined wells per
WMD, for districtwide and statewide analyses, the wells were also combined into one pool (All).


I


I I I 1 I I I I I I








FLORIDA GEOLOGICAL SURVEY



Decreasing trends in water levels and pH were often observed. Because of the drought, the
lowering of water levels was predictable. However, the decrease in pH was unexpected.
Plausible reasons for the declines will be discussed later.

Rainbow Springs Average Flow (1965-2003)


900-



800



S700



600
600-


500


1970


Um


1990 2000
Year


Weeki Wachee Flow (1904-2003)



Eu


: 0
I. .mm 1


I n m0
m.. f .

* .,* .- n .



S ... I_"' .



r U

.U,
1


1960s to Present



1991-2003
Present study
time line


3/30/1905


8/15/1932


1/1/1960


5/19/1987


Date


Figure 37. Long-term flow trends at two SWFWMD springs. Rainbow (top) and Weeki
Wachee Springs (bottom) show historic changes. For Rainbow, points represent average
flow per year. Although no regression line on the graph, Weeki Wachee data since 1904
(bottom) showed a rise until about 1960 followed by a subsequent fall. Dark gray lines repre-
sent time line for Sequence A. (One cfs = 0.028 cms)


1980


1991-2003
Present
study time
line


250




S200
[T


150 -


I I I I I I I I


~

~
a
a a







BULLETIN NO. 69





Hunter Spring Time Sequence A (1991-2003)


O 0.30
z



0.25



0.20


2/12/1990
MK p-value
WT p-value =


11/8/1992 8/5/1995 5/1/1998 1/25/2001 10/22/2003
0.0001 SS = 0.0046 Date
0.0001 nb =12 n,= 20


Magnolia Spring Time Sequence A (1991-2003)


1995 1996 1997 1998 1999 2000 2001 2002 2003
MK p-value < 0.0001 SS = 0.0042 Date
WT p-value = 0.0001 nb= 13 n = 23


Figure 38. Increasing nitrates at Hunters and Magnolia Springs. Hunters
(top) and Magnolia Springs (bottom) illustrate the most actively increasing
nutrient trend in the district (nitrate). Hunters' increase remained below the
the SRA (0.45 mg/L). Magnolia Spring's increase in nitrate began below
the SRA and ends above it; thus it crosses a recommended limit. Beginning
and ending dates for these springs were not the same.


U U








FLORIDA GEOLOGICAL SURVEY




Weeki Wachee Time Sequence A (1991-2003)








*










.

SRAValue =0 45mg/L
*


8/5/1995
MK p-value < 0.0001 SS= 0.0055
WTp-value =0.0111 n = 15 n1=


5/1/1998
Date
23


Boyette Spring Time Sequence A (1991-2003)


2/12/1990


11/8/1992


8/5/1995
Date


MK p-value= 0.0005 SS= 0.0100
WT p-value= 0.0002 nb= 27 n= 22


Figure 39. Increasing nutrient analytes at Weeki Wachee and Boyette
Springs. Weeki Wachee (top) shows a clear increase in nitrate in Sequence
A. Most of the time series for Sequence A included values above 0.45 mg/L.
Boyette (bottom) illustrates an unusual trend in TKN. TKN values sometimes
rose suddenly over a very short period of time in 1998. SWFWMD staff indicat-
ed the source of the TKN was probably from a nearby dairy waste lagoon.
Beginning and ending dates for these springs were not the same.


0.5-
z


0.5-



0.4


1/25/2001


10/22/2003


S m m m mm
-~ ~ **


5/1/1998






BULLETIN NO. 69


Northwest Florida Water Management District

Northwest Florida wells (Figure 40) showed a lowering of water levels for Sequence A
(six of eight wells were down, with no increasing trends). Temperature increased in five wells,
while the analyte sodium and sulfate increased in four wells. No wells demonstrated downward
trends for temperature, sodium, and sulfate. The analyte pH decreased in four wells.






131 312 f






Legend
N Wells
NWFWMD
SRWMD



Miles N
0 20 40 60
Kilometers
0 30 60 90 s

Figure 40. Location of wells within the N\\ F\\ NID.


Changes in sequences B and C reflected those in Sequence A. For Sequence B water
level fell (six of eight wells had decreasing levels, while none increased). Several wells also
showed increases in sodium (increased in four wells, decreased in none) and conductivity
(increased in five wells, decreased in none).

Unlike springs, where the main influences on the chemistries occurred during Sequence
C, the only notable analyte in well data demonstrating a change was pH. The analyte decreased
in six of eight wells studied (and increased in none).

Water Levels and pH

Figures 4 land 42 illustrate several of these trends. The association of water level and pH
suggest a relationship between the two analytes and will be discussed later. A drop in water
levels occurred in both unconfined and confined wells. Confined aquifer Well 312 (Figure 42)
showed a 5 m (15 ft) decline over the period of record.









FLORIDA GEOLOGICAL SURVEY





Well 91 Time Sequence A: pH and WL


-- WL 16


4 ..911


'" ''-* i
.j& ,rJ


6-
6 A a

- a A AA







3-



2
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003


Date

MKp-value= 0.0010 nb =80 n,= 66
WT p-value = 0.0028 SS =-0.0016


U *' *
Eu. U


-11
uW
E,


Water Level
MK p-value < 0.0001 nb =81 n= 54
WT p-value < 0.0001 SS = -0.0161


Well 129 Time Sequence A: pH and WL
-- PH
pH
a u WL



A r. A A





S. *. .

i I I I I I I
**








1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
Date


PH
MK p-value =0.0158 nb= 53 n,= 36
WTp-value =0.0001 SS= -0.0012


12



10



- 8



6



-4


Water Level
MKp-value<0.0001 nb = 53 n= 24
WT p-value < 0.0001 SS = -0.0466


Figure 41. Decreasing pH and water levels in NWFWMD wells (#91 and
#129). Tests (p < 0.05) included MK for trend, WT on sequences B and
C, plus an SS calculation on rate of change.


6.2-











5.4





5.0


-- --


~EII ~L I


16































4.5-


BULLETIN NO. 69





Well 131 Time Sequence A: pH and WL


S. --- WL 20


aa 19






SE15
SA 17










-14


1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003


PH
MK p-value
WT p-value


Date
Date Water Level
0.0001 nb =53 n= 66 MKp-value < 0.0001 nb = 52 n = 55
=0.0004 SS = -0.0030 WTp-value< 0.0001 SS = -0.0187


Well 312 Time Sequence A: WL


70-



65-



" 60-



55-



50-


1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
Date Water Level
MK p-value < 0.0001 nb =81 n= 35
WT p-value < 0.0001 SS = -0.0893




Figure 42. Decreasing pH and water levels in NWFWMD wells (#131
and #312). Tests (p < 0.05) included MK for trend, WT on sequences B
and C, plus an SS calculation on rate of change. Water level is in feet
above mean seal level. (One m = 0.3048 ft)


| WL















^a
A
a

A
&- w







P
6


-' 7'^
^ "

'h^


~


P






FLORIDA GEOLOGICAL SURVEY


Suwannee River Water Management District

The locations of the SRWMD TV wells are displayed in Figure 43. Decreasing water
level trends were observed in the SRWMD. Temperature rose in Sequence C (seven increased
and none decreased). Trends in Sequence A suggested the same pattern as in northwest Florida:
declines in water level and pH.


Figure 43. Location of wells within the SRWMD.

Water Levels and pH


Over the period of record, water level and pH trends looked similar to other districts. As
two examples (Figure 44) of unconfined wells (Wells 1943 and 2465), a drop in water level
appeared to be accompanied by a decrease in pH. Note that Well 2465 had rapidly declining
water levels but a relatively slower change in pH. The water level decreased approximately 5 m
(15 feet) by the end of the study. Confined groundwater showed similar patterns. Figure 45
shows water level and pH falling simultaneously for wells 2585 and 2675. In Well 2585, the
water level drop is a minimum of 3 m (15 ft); some points in the early time series have
substantially higher water level values [18 m (60 ft)] and suggest the difference was even greater.
By far the most extreme water level difference was recorded was Well 2675. From a high point
of 27 m (90 ft) msl in 1994, water levels fell to approximately 9 m (30 ft) by 2003. This is
nearly 18 m (60 ft) difference is due to its location near the Alapaha River. Local karst features
create differences in water levels in response to rainfall. Like other wells in the district, Well
2675 experienced a decline in pH.









BULLETIN NO. 69


Well 1943: pH and WL


- --- pH
WL

20


-U .


U



.-' A
MI

4 AA.I .


12/31/1993


4/1/1997
Date


7/1/2000


10/1


12


10


/2003


pH Water Level
MK p-value = 0.0405 n= 44 n = 45 MK p-value = 0.0499 n = 43 n = 39
WT p-value = 0.3388 SS = -0.0011 WT p-value = 0.0051 SS=-0.0114


Well 2465 Time Sequence A: pH and WL

pH
S- WL


1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
fpH Date Water Level
MK p-value = 0.0013 nb = 68 n,= 64 MK p-value <0.0001 n = 56 n= 59
WT p-value = 0.0001 SS = -0.0009 WT p-value < 0.0001 SS = -0.0944





Figure 44. Decreasing pH and water levels in SR\\ MD wells (#1943
and #2465). Both wells are unconfined. Tests (p < 0.05) included MK for
trend, WT on sequences B and C, plus an SS calculation on rate of change.
The beginning sampling dates for wells are not the same. (One m = 0.3048 ft.)


10/1/1990


A








FLORIDA GEOLOGICAL SURVEY







Well 2585 Time Sequence A: pH and WL


6.6


6.1
2/12/1990 6/27/1991 11/8/1992 3/23/

lH nb = 72 nc= 35
MK p-value = 0. 0491
WT D-value = 0.0011 SS= -0.0009


1994 8/5/1995 12/17/1996 5/1/1998
Date
Water Level n = 64 n, = 34
MK p-value < 0.0001
WT D-value = 0.0142 SS = -0.1066


Well 2675 Time Sequence A: pH and WL


1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
eIl Date Water Level
MK p-value <0.0001 nb = 73 n= 63 MK p-value = 0.0043 nr 39 n. =31
WTlp-value=0.0002 SS=-0.0016 WT p-valu <0.0001 SS -0.0656



Figure 45. Decreasing pH and water levels in SRWMID wells (#2585
and #2675). Both wells are confined. Tests (p <0.05) included NlK for
trend, WT on Sequences B and C, plus SS calculations. Note beginning
sampling dates for wells are not the same. (One m = 0.3048 ft.)


St. Johns River Water Management District


Figure 46 displays the location of TV Network wells in the SJRWMD. The trends for the
wells shown in Figure 46 in the SJRWMD were slightly different from both the NWF\\F W ID and


pH





*. -
S .... .


pH





; '
WL





, mm




Full Text

PAGE 1

STATE OF FLORIDA DEPARTMENT OF ENVIRONMENTAL PROTECTION Michael W. Sole, Secretary LAND AND RECREATION Robert G. Ballard, Deputy Secretary FLORIDA GEOLOGICAL SURVEY Jonathan D. Arthur, State Geologist and Director Bulletin No. 69 REGIONAL AND STATEWIDE TRE NDS IN FLORIDAÂ’S SPRING AND WELL GROUNDWATER QUALITY (1991-2003) By Rick Copeland, Neal A. Doran, Aar on J. White, and Sam B. Upchurch Published for the FLORIDA GEOLOGICAL SURVEY Tallahassee, Florida 2009

PAGE 2

FLORIDA DEPARTMENT OF ENVIRONMENTAL PROTECTION Michael W. Sole, Secretary LAND AND RECREATION Robert G. Ballard, Deputy Secretary OFFICE OF THE FLORIDA GEOLOGICAL SURVEY Jonathan D. Arthur, State Geologist and Director ADMINISTRATIVE AND GEOLOGICAL DATA MANAGEMENT SECTION Jacqueline M. Lloyd, Assistant State Geologist Traci Billingsley, Business Manager Leslie Knight, Administrative Assistant Paulette Bond, Professional Geologist Frank Rupert, Professional Geologist Doug Calman, Librarian Specialist Ginger Shirah, S ecretary Specialist Brian Clark, Environmental Specialist Carolyn Stringer, Management Analyst Jan DeLaney, Environmental Supervisor Keith Wood, Computer Programmer Jeff Erb, Systems Programmer Analyst GEOLOGICAL INVESTIGATIONS SECTION Rick Copeland, Assistant State Geologist Drew Butler, Laboratory Technician Jesse Hurd, Laboratory Technician Ken Campbell, Professional Geologist Michelle Ladle, Laboratory Technician Bob Cleveland, Engineer Specialist Mike Nash, Laboratory Technician Adel Dabous, Environmental Specialist Stuart Norton, Environmental Specialist Cindy Fischler, Professional Geologist David Paul, Professional Geologist Rick Green, Professional Geologist Dan Phelps, Professional Geologist Paul Hansard, Environmental Consultant Guy Richardson, Engineering Technician Eric Harrington, Engineering Technician Wade Stringer, Engineering Specialist Laura Hester, Laboratory Technician Christopher Williams, Geologist Ron Hoenstine, Professional Geologist Supervisor HYDROGEOLOGY SECTION Harley Means, Professional Geologist James Bobrycki, Environmental Specialist Patrick Madden, Laboratory Technician John Carroll, Environmental Specialist James McClean, Government Analyst Caitlin Cerame, Environmental Specialist Kunle Olumide, Environmental Consultant Richard Deadman, Environmental Specialist Amber Raynsford, Environmental Specialist Lisa Fulton, Environmental Specialist Melinda Spall, Environmental Specialist Josue Gallegos, Geologist Eric Thomas, Environmental Specialist Tom Greenhalgh, Professional Geologist Alex andra Walrath, Geographical InformaClint Kromhout, Professional Geologist tion System Technician STRATEGIC PROJECTS Rodney DeHan, Environmental Manager Scott Barrett Dyer, Environmental Specialist

PAGE 3

STATE OF FLORIDA DEPARTMENT OF ENVIRONMENTAL PROTECTION Michael W. Sole, Secretary LAND AND RECREATION Robert G. Ballard, Deputy Secretary FLORIDA GEOLOGICAL SURVEY Jonathan D. Arthur, State Geologist and Director Bulletin No. 69 REGIONAL AND STATEWIDE TRE NDS IN FLORIDAÂ’S SPRING AND WELL GROUNDWATER QUALITY (1991-2003) By Rick Copeland, Neal A. Doran, Aar on J. White, and Sam B. Upchurch Published for the FLORIDA GEOLOGICAL SURVEY Tallahassee, Florida 2009

PAGE 4

ii Printed for the Florida Geological Survey Tallahassee 2009 ISSN 0271-7832

PAGE 5

iii PREFACE FLORIDA GEOLOGICAL SURVEY Tallahassee, Florida 2009 The Florida Geological Survey (FGS), is publishing as its Bulletin No. 69, Regional and Statewide Trends in FloridaÂ’s Spring and Well Groundwater Quality (1991-2003), authored by Rick Copeland, Neal A. Doran, Aar on J. White, and Sam B. Upchurch. This publication summarizes the results of a multi-year cooperative investigation on spring and groundwater quality between the Florid a Department of Envi ronmental ProtectionÂ’s FGS and the Bureau of Watershed Management , Division of Environmental Assessment and Restoration. The data presented will be useful to scientists, planners, and citizens in understanding the quality of FloridaÂ’s groundwater resources. Jonathan D. Arthur, Ph.D., P.G. State Geologist and Director Florida Geological Survey

PAGE 6

iv TABLE OF CONTENTS Executive summary.............................................................................................................. .....................................xi B ackground................................................................................................................ ...........................................xi Approach.................................................................................................................. ...........................................xii Results and Conclusions................................................................................................... ..................................xiii Springs.............................................................................................................. .............................................xiii Wells....................................................................................................................... .........................................xv Concerns.................................................................................................................. ...........................................xvi Rock-matrix and salin e indicators: Saltwat er encroachment............................................................ .............xvi Nutrients................................................................................................................... ...................................xviii Monitoring................................................................................................................ ........................................xviii Reco mmendations........................................................................................................... ...................................xix Recomme ndation S ynopsis................................................................................................... ..............................xxi Research............................................................................................................. ...........................................xxi Monitoring........................................................................................................... ..........................................xxi Introduc tion................................................................................................................... ..............................................1 Acknowledgements............................................................................................................... ......................................2 Florida’s springs.............................................................................................................. ............................................2 Classifica tion of springs................................................................................................. ........................................3 Offshore Springs.......................................................................................................... ...........................................5 Spring recharge basins.................................................................................................... ........................................6 Overview of the hydrogeology of Florida’s groundwa ter.......................................................................... .................7 Quality of groundwater and spring water........................................................................................ ............................9 Natural factors affecting groundw ater and spring -water quality................................................................ .............9 Differences in spring and well-wa ter qu ality................................................................................. ......................10 Indicators of groundwater and spring-water qua lity prob lems................................................................... ...........10 Spring selec tion process....................................................................................................... .....................................12 Well selecti on process......................................................................................................... ......................................13 Methods........................................................................................................................ .............................................16 Defin ition of trends...................................................................................................... .........................................17 Problems with trends...................................................................................................... ......................................18 “Remaining the sa me” Possibility of missed trends.................................................................. ....................18 Ou tliers............................................................................................................. ...............................................19 Detec tion le vels............................................................................................................ ...................................19 Sparse data................................................................................................................. ......................................21 Analytes and indicators.............................................................................................................................................22 Sample collecti on and laborator y anal yses................................................................................. ..........................23 Analytes used in this study............................................................................................... ....................................25 Groupin g of an alyt es...................................................................................................... ......................................25 Description of analyte groups............................................................................................. ..................................26 Field an alyt es....................................................................................................... ............................................26 Rock-matrix analytes................................................................................................. ......................................26 Saline or saltwater analytes......................................................................................... .....................................27 Nutrient analytes.................................................................................................... ..........................................27 Other analytes....................................................................................................... ...........................................27 Data........................................................................................................................... ................................................27 Data sources.............................................................................................................. ............................................28 Data verification......................................................................................................... ..........................................28 Data preparation.......................................................................................................... .........................................28 Time sequences....................................................................................................... .........................................29 Data used for analyses and explanation of appendices...................................................................... ...................29 Information goals and data analysis protocols.................................................................................. .........................30 Informat ion introd uction.................................................................................................. .....................................30 Overview of statis tical analyses procedures............................................................................... ..........................30

PAGE 7

v Descrip tive sta tistic s..................................................................................................... ..................................30 Kruskal-Wallis, Mann-Whitney , and Wilcoxon ra nk sum tests.................................................................. ...31 Deseason alized data........................................................................................................ ................................33 Mann-K endall test.......................................................................................................... ................................34 Seasona l Kendall test...................................................................................................... ................................34 Sen slope........................................................................................................... ..............................................34 Sign test.................................................................................................................. ........................................35 Caveats and assumptions.................................................................................................... ............................35 Results........................................................................................................................ ...............................................36 Springs................................................................................................................... ...............................................36 Northwest Flor ida Water Manage ment District.......................................................................... .....................36 Rock and saline analytes, nutrie nts, and flow.......................................................................... ...................36 Suwannee River Water Management District.................................................................................... ............40 Rock-mat rix and salin e analytes....................................................................................... .........................41 Flow.................................................................................................................. .........................................46 Nu trient an alyt es..................................................................................................... ...................................51 St. Johns River Wate r Management District................................................................................... ................54 Rock-mat rix and salin e analytes....................................................................................... .........................55 Nu trient an alyt es..................................................................................................... ...................................59 Southwest Florida Water Management.......................................................................................... .................59 Rock-mat rix and salin e analytes....................................................................................... .........................59 Flow.................................................................................................................. .........................................66 Nu trient an alyt es..................................................................................................... ...................................66 Field an alytes........................................................................................................ .....................................67 Wells..................................................................................................................... ................................................67 Northwest Flor ida Water Manage ment District.......................................................................... .....................71 Wa ter levels and pH................................................................................................... ...............................71 Suwannee River Wate r Management District.................................................................................... .............74 Wa ter levels and pH................................................................................................................................ 74 St. Johns River Wate r Management District................................................................................... ................76 Southwest Florida Wa ter Management District................................................................................. ..............79 South Florida Wate r Management District..................................................................................... .................81 Districtwi de spring trends................................................................................................ .....................................81 Districtwide spring tr ends in the Suwannee River Water Management District.............................................86 Districtwide spring tr ends in the St. Johns River Water Management District...............................................86 Districtwide spring tre nds in the Southwest Florida Wa ter management District ..........................................86 Statewide spri ng trends........................................................................................................ .............................100 Constrained version of statewide trends........................................................................................ ...................101 Independence of sp rings and wells.............................................................................................. .....................102 Districtwide we ll-water trends................................................................................................. .........................103 Evidence of districtwide well water-quality trends Northwest Flor ida Water Management District..........104 Evidence of districtwide well water-quality trends Suwannee River Water Management District.............108 Evidence of districtwide well water-qua lity trends St. Johns River Wa ter Management DistrictÂ…Â…Â…Â…110 Evidence of districtwide well water-quality trends Southwest Florida Wa ter Management DistrictÂ…Â…...113 Evidence of districtwide well water-quality trends South Florid a Water Management District.................117 Statewide well water-quality trends....................................................................................... .............................120 Comparison of strong statewide tr ends for groundwater and spring water.................................................... .....120 Constrained version of statewide trends....................................................................................... ......................121 Discussion..................................................................................................................... ...........................................122 Major cause of statewide trends: Drough t and consequential saltw ater encroachment......................................123 Drought................................................................................................................... ............................................126 Rock-matrix and saline indicator evidence in spring-wate r quality.................................................... ...........128 Rock-matrix and saline indicator evidence in well-wate r quality...................................................... ............128 Regional to sub-regional evidence of saltwater encroachment.......................................................... ............130 Groun dwater withdrawals.............................................................................................. ................................133 Groundwater summary.................................................................................................. ................................134

PAGE 8

vi Miscellaneous and important issues........................................................................................ ...........................134 Falling well-water levels – a districtwide and statew ide problem in wells............................................ ........134 Nitrogen and phosphorous nutr ients – Regional and lo cal problem in springs........................................... ...137 Nitrogen in the Northw est Florida Water Ma nagement District.......................................................... ..........137 Nitrogen in the Suwa nnee River Water Mana gement District............................................................. ..........139 Nitrogen in the St. Johns River an d Southwest Florida Water Ma nagement Dist ricts..................................148 Mari on County.................................................................................................. .......................................148 Rainbow Springs Group....................................................................................... .................................148 Citrus Coun ty.................................................................................................................. ..........................149 King’s Bay Springs Group.................................................................................................. .................149 Homosassa Springs Group................................................................................................... ................149 Chassahowitz ka Springs Group.............................................................................................. ..............149 Hernando County................................................................................................................ ......................149 Weeki Wachee Springs Group................................................................................................ .............150 Boat Springs, Bobhill, and Magnolia Springs…… …………………………………… ………………150 Hillsborough County……………………… ……………………………… ……………………………..150 Lithia Spring and Buckhorn Spring......................................................................................... .............150 Summary of the n itrate problem in spring water........................................................................ ....................150 Phosphorus in spring water by water mana gement district............................................................... ..............150 Suwannee River Water Management........................................................................................ ................151 St. Johns River and Southwest Florida Water Management Districts................................................. ......161 Comparison of coasta l to inland and tidal to non-tidal springs................................................... ...............162 Global factors infl uencing Florida’ s groundwater......................................................................... ....................164 Global long-term cycles : Atlantic mutidecad al osc illation................................................................ ..............164 Global short-term cycles: El Niño and La Niña......................................................................... .....................166 Acid rain................................................................................................................... .......................................168 Implications of future low rainfall and increasing state water demands................................................... .........168 Implications rega rding long-term sustaina bility.......................................................................... ......................169 References..................................................................................................................... ..........................................171 (Appendix Online references can be found at http://www.uflib.ufl.edu/ufdc/?b=UF00095137 ) Appendix A – Relationships among spring flows, rock, and salinity indicator concentration for selected springs................................................................................................... .........................................179 Appendix B – Glossary of terms and possible causes of trends.............................................................. ...........183 Appendix B1 – Glossary.............................................................................................. .................................183 Appendix B2 – Interpretations of the or igins of temporal trends in Florida’s groundwater....................Online Appendix C – Well co nstruction and location data.......................................................................... .............Online Appendix D – Spring locations............................................................................................. ..............................191 Appendix E – Statistics................................................................................................... ...............................Online Appendix E1 – Statistical methodologies.............................................................................. ...................Online Appendix E2 – Macro code s for the Mann-Kendall tests and Sen slope..................................................O nline Appendix F – Analytes..................................................................................................... ..................................193 Appendix F1 – Analyte descriptions................................................................................... ..........................193 Appendix F2 – Analyte list with STORET codes.......................................................................... .................200 Appendix G – Data quality assu rance (QA) officer co ntact information...................................................... .....203 Appendix H – Data from springs and wells.................................................................................. .................Online Appendix I – Descriptive statistics....................................................................................... .........................Online Appendix J – Seasonality results.......................................................................................... .........................Online Appendix K – Mann-Ke ndall and Sen slope results........................................................................... ...........Online Appendix L – Districtwide maps............................................................................................ .......................Online Appendix L1 – Northwest Florida Water Management District springs..................................................On line Appendix L2 – Northwest Florida Water Manageme nt District wells.....................................................O nline Appendix L3 – Suwannee Ri ver Water Management District sp rings.....................................................On line Appendix L4 – Suwannee River Water Management District wells........................................................O nline Appendix L5 – St. Johns River Water Management District springs...................................................... .Online Appendix L6 – St. Johns River Water Manageme nt Distri ct wells........................................................ ..Online Appendix L7 – Southwest Florida Water Management District springs..................................................On line

PAGE 9

vii Appendix L8 – Southwest Florida Water Manageme nt District wells.....................................................O nline Appendix L9 – South Florida Water Manageme nt Distri ct Wells.......................................................... ..Online Appendix M – Rain fall and temper ature data................................................................................. ................Online Appendix N – Atmospheric deposition stati on information.................................................................... ............203 Figures Figure 1. Schematics of freshwater/saltwater transition zone and possible mechanism for saltwater intrusion....................................................................................................... ............................xvii Figure 2. Inverse relationship of flow to rock and saline indicator concentrations..................................xx Figure 3. Locations of Florida’s springs....................................................................................... ..............4 Figure 4. Offshore springs..................................................................................................... .....................6 Figure 5. Median nitrate concentrations in 13 selected first-magnitude springs........................................7 Figure 6. Location of springs analyzed in this report.......................................................................... ......14 Figure 7. Location of Temporal Variability Network (TVN) wells.........................................................15 Figure 8. Illustration of three options for water-quality trends.............................................................. ..18 Figure 9. Example of a spurious trend......................................................................................... ............20 Figure 10. Example of sporadic, unsys tematic, and incomplete sampling...............................................22 Figure 11. Monthly water temperatures plotted ov er the 1992 calendar year for an imaginary well........31 Figure 12. Example illustration of seaso nality with a sixyear cycle........................................................32 Figure 13. Location of Wakulla Spring within the NWFWMD...............................................................37 Figure 14. Increasing rock an alytes at Waku lla Spring.......................................................................... ..38 Figure 15. Decreasing nitrates and wate r levels at Wakulla Spring.........................................................39 Figure 16. Location of springs within the SRWMD................................................................................ .40 Figure 17. Increasing rock analytes at Fanning and Gilchrist Blue Springs.............................................42 Figure 18. Increasing rock analytes at Suwannee Blue and Troy Springs................................................43 Figure 19. Increasing rock analytes at Manatee and Hart Springs............................................................44 Figure 20. Increasing rock analytes at Poe and Lafayette Blue Springs...................................................45 Figure 21. Decreasing flow at Fanning and Hart Springs......................................................................... 47 Figure 22. Decreasing flow at Rock Bluff and Hornsby Springs.............................................................48 Figure 23. Decreasing flow at Poe and Ruth/Little Sulfur Springs...........................................................49 Figure 24. Decreasing flow at Troy and Telford Springs......................................................................... 50 Figure 25. Decreasing nitrates at Poe Spring................................................................................... .........52 Figure 26. Increasing nutrient analytes at Poe and Lafayette Blue Springs..............................................53 Figure 27. Location of springs within the SJRWMD............................................................................... 54 Figure 28. Increasing rock an alytes at Palm Springs............................................................................ ....56 Figure 29. Increasing rock anal ytes at Sanlando Springs........................................................................ .57 Figure 30. Increasing rock an alytes at Wekiwa Spring........................................................................... ..58 Figure 31. Decreasing phosphate concentrati ons at Palm and Starbuck Springs......................................60 Figure 32. Location of springs within the SWFWMD..............................................................................6 1 Figure 33. Increasing saline analytes at Rainbow and Bubbling Springs.................................................63 Figure 34 Increasing saline analytes for Hunter and Trotter Main Springs.............................................64 Figure 35. Increasing saline analytes for Weeki Wachee and Bobhill Springs........................................65 Figure 36. Decreasing flow at Homosassa No. 1 Spring..........................................................................6 7 Figure 37. Long-term flow tre nds at two SWFWMD springs..................................................................68 Figure 38. Increasing nitrates at Hunter and Magnolia Springs................................................................69 Figure 39. Increasing nutrient analytes at Weeki Wachee and Boyette Springs.......................................70 Figure 40. Location of wells within the NWFWMD................................................................................7 1 Figure 41. Decreasing pH and water levels in NWFWMD wells (#91 and #129)...................................72 Figure 42. Decreasing pH and water levels in NWFWMD wells (#131 and #312)..................................73

PAGE 10

viiiFigure 43. Location of wells within the SRWMD.................................................................................. ..74 Figure 44. Decreasing pH and water levels in SRWMD wells (#1943 and #2465).................................75 Figure 45. Decreasing pH and water levels in SRWMD wells (#2585 and #2675).................................76 Figure 46. Location of wells within the SJRWMD................................................................................. ..77 Figure 47. Temperature and specific conducta nce in SJRWMD wells (#1417 and #1763).....................78 Figure 48. Temperature and specific c onductance in SJRWMD well (#1762)........................................79 Figure 49. Location of wells within the SWFWMD................................................................................. 80 Figure 50. Decreasing pH and water levels in SWFWMD wells (#996 and #1087)................................82 Figure 51. Decreasing pH and water levels in SWFWMD well (#707)...................................................83 Figure 52. Location of wells within the SFWMD.................................................................................. ...84 Figure 53. Decreasing pH and water levels in SFWMD wells (#6490 and #3398)..................................85 Figure 54. Weighted mean temperature a nd rainfall data in Florida (1991-2003)..................................125 Figure 55. Relative position of rock-matrix and saline analytes in the Upper Floridan aquifer system.126 Figure 56. Fresh groundwater wedge before and during a drought........................................................127 Figure 57. Water level and pH relationships for a well with a falling water table.................................129 Figure 58. Weighted mean annual rainfall during Sequence A..............................................................131 Figure 59. Example of aliasing................................................................................................. ..............136 Figure 60. Nitrate concentrations in Wakulla Spring between 1972 and 2005.......................................137 Figure 61. Flow adjustment fo r nitrate in Troy Spring.......................................................................... .140 Figure 62. Flow adjustment for TKN in Troy Spring.............................................................................1 41 Figure 63. Flow adjustment for nitrate in Hornsby Spring.....................................................................14 2 Figure 64. TKN versus time and log of TKN versus log of flow in Hornsby Spring.............................143 Figure 65. Flow adjustment for nitrate in Fanning Spring......................................................................1 45 Figure 66. Flow adjustment for TKN in Fanning Spring........................................................................146 Figure 67. Flow adjustment for phosphorus in Troy Spring...................................................................152 Figure 68. Flow adjustment for phosphate in Troy Spring.....................................................................153 Figure 69. Flow adjustment for phospho rus in Ruth/Little Sulfur Springs.............................................154 Figure 70. Flow adjustment for phospha te in Ruth/Little Sulfur Springs...............................................155 Figure 71. Flow adjustment for phosphorus in Fanning Spring..............................................................156 Figure 72. Flow adjustment for phosphate in Fanning Spring................................................................157 Figure 73. Flow adjustment for ph osphorus in Little River Spring........................................................158 Figure 74. Flow adjustment for ph osphate in Little River Spring..........................................................159 Figure 75. Flow adjustment for a phosphate in Hornsby Spring............................................................160 Figure 76. Atlantic Multidecadal Osc illation and Florida spring flow...................................................165 Figure 77. Sea surface temperatur e, La Niña, and El Niño.....................................................................16 7 Figure 78. Average monthly pH from seven atmospheric rain stations (1991-2003).............................169 Figure A1. Juniper Springs – alkalinity versus flow............................................................................ ...179 Figure A2. Wakulla Spring – sodium versus stage................................................................................ .180 Figure A3. Alapaha River Rise Fanning – sodium versus flow..............................................................180 Figure A4. Fanning Spring – sodium versus flow................................................................................. .181 Figure A5. Poe Spring – sodium versus flow..................................................................................... ....181 Figure A6. Homosassa No. 3 Spring – sodium versus flow...................................................................182 Figure A7. Chassahowitzka No. 1 Spring – sodium versus flow............................................................182 Tables Table 1. Spring Magnitude..................................................................................................... ...................3 Table 2. Florida’s spri ng classifica tion system............................................................................... ...........5 Table 3. Analyte and indicator list........................................................................................... ................23 Table 4. Analytes and indicators displaying trends............................................................................ .....24 Table 5. Analyte Groups……………………………………………………………………..................26

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ixTable 6. Example of d escriptive statis tics table.............................................................................. .........31 Table 7. Suwannee River Water Management District spring names and abbreviations........................41 Table 8. St. Johns River Water Management District spring names and abbreviations..........................55 Table 9. Southwest Florida Water Management District spring names and abbreviations.....................62 Table 10. Spring trends in the SRWMD (p lus Wakulla Spring), Sequence A (1991-2003).....................87 Table 11. SRWMD (plus Wakulla Spring) districtwi de trends based on sign tests, Sequence A............87 Table 12. Spring trends in the SRWMD (plu s Wakulla Spring), Sequence B (1991-1997).....................88 Table 13. Spring trends in the SRWMD, (plu s Wakulla Spring) Sequence C (1998-2003).....................89 Table 14. SRWMD (plus Wakulla Spring) districtwi de trends based on sign tests, Sequence C.............89 Table 15. Spring trends in the SJRWMD, Sequence A (1991-2003).......................................................90 Table 16. SJRWMD districtwide trends based on sign test, Sequence A.................................................90 Table 17. Spring Trends in the SJRWMD, Sequence B (1991-1997)......................................................91 Table 18. Spring Trends in the SJRWMD, Sequence C (1998-2003)......................................................92 Table 19. SJRWMD districtwide trends based on sign tests, Sequence C................................................92 Table 20. Spring Trends in the SWFWMD, Sequence A (1991-2003)....................................................93 Table 20. Spring Trends in the SWFWMD , Sequence A (1991-2003) (continued).................................94 Table 21. SWFWMD districtwide trends based on sign tests, Sequence A..............................................94 Table 22. Spring Trends in the SWFWMD, Sequence B (1991-1997).....................................................95 Table 22. Spring Trends in the SWFWMD , Sequence B (1991-1997) (continued).................................96 Table 23. SWFWMD districtwide trends based on sign tests, Sequence B..............................................96 Table 24. Spring Trends in the SWFWMD, Sequence C (1998-2003).....................................................97 Table 24. Spring Trends in the SWFWMD , Sequence C (1998-2003) (continued).................................98 Table 25. SWFWMD districtwide trends based on sign tests, Sequence C..............................................98 Table 26. Spring flow from three stations in the SWFWMD...................................................................99 Table 27. Statewide spring trend summary by WMD and time sequence................................................99 Table 28. Statewide trends based on sign tests for 57 springs, Sequence A (1991-2003)......................100 Table 29. Statewide trends based on sign tests for 57 springs, Sequence B (1991-1997)......................100 Table 30. Statewide trends based on sign tests for 57 springs, Sequence C (1998-2003)......................101 Table 31. Statewide trends in at l east two WMDs, Sequence A (1991-2003)........................................101 Table 32. Statewide trends in at l east two WMDs, Sequence C (1998-2003)........................................102 Table 33. Selected statewide analyte results, Sequence A (1991-2003).................................................103 Table 34. Well trends in the NWFWMD, Sequence A (1991-2003)......................................................105 Table 35. Potential NWFWMD dist rictwide trends, Sequence A..........................................................105 Table 36. Well trends in the NWFWMD, Sequence B (1991-1997)......................................................106 Table 37. Potential NWFWMD dist rictwide trends, Sequence B...........................................................106 Table 38. Well trends in the NWFWMD, Sequence C (1998-2003)......................................................107 Table 39. Potential NWFWMD dist rictwide trends, Sequence C...........................................................107 Table 40. Well trends in the SRWMD, Sequence A (1991-2003)..........................................................108 Table 41. Potential SRWMD districtwide trends, Sequence A..............................................................108 Table 42. Well trends in the SRWMD, Sequence B (1991-1997)..........................................................109 Table 43. Potential SRWMD districtwide trends, Sequence B...............................................................109 Table 44. Well trends in the SRWMD, Sequence C (1998-2003)..........................................................110 Table 45. Potential SRWMD districtwide trends, Sequence C...............................................................110 Table 46. Well trends in the SJRWMD, Sequence A (1991-2003)........................................................111 Table 47. Potential SJRWMD dist rictwide trends, Sequence A.............................................................111 Table 48. Well trends in the SJRWMD, Sequence B (1991-1997)........................................................112 Table 49. Potential SJRWMD dist rictwide trends, Sequence B.............................................................112 Table 50. Well trends in the SJRWMD, Sequence C (1998-2003)........................................................113 Table 51. Potential SJRWMD dist rictwide trends, Sequence C.............................................................113 Table 52. Well trends in the SWFWMD, Sequence A (1991-2003).......................................................114 Table 53. Potential SWFWMD dist rictwide trends, Sequence A...........................................................114

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xTable 54. Well trends in the SWFWMD, Sequence B (1991-1997).......................................................115 Table 55. Potential SWFWMD dist rictwide trends, Sequence B...........................................................115 Table 56. Well trends in the SWFWMD, Sequence C (1998-2003).......................................................116 Table 57. Potential SWFWMD dist rictwide trends, Sequence C...........................................................116 Table 58. Well trends in the SFWMD, Sequence A (1991-2003)..........................................................117 Table 59. Well trends in the SFWMD, Sequence B (1991-1997)..........................................................118 Table 60. Well trends in the SFWMD, Sequence C (1998-2003)..........................................................119 Table 61. Potential SFWMD distri ctwide trends, Sequence C...............................................................119 Table 62. Statewide trends based on sign tests: Sequences A, B, and C................................................120 Table 63. Statewide spring-water quality summary for rock and saline indicators................................121 Table 64. Statewide trends for at least thr ee WMDs: Sequences A, B, and C for combined groundwater resources.......................................................................................... ..................122 Table 65. Constrained statewide spri ng and groundwater-quality summary..........................................123 Table 66. Summarized annual weather data in Florid a (1991-2003)......................................................124 Table 67. Annual weather data, four WM Ds compared to the SWFWD (1991-2003)...........................131 Table 68. Summarized rainfall, Sequence C minus Sequence B............................................................132 Table 69. Relationships among concentration and loading of nitrate and TKN versus time and flow in selected springs in the SRWMD..................................................................147 Table 70. Inland and Coastal Springs within the SRWMD and the SWFWMD....................................162 Table 71. Comparison of coastal and inland sp rings for upward trends during Sequence C, excluding the SJRWMD........................................................................................... ..............163 Table 72. Comparison of tidal and non-tidal springs for upward trends during Sequence C in the SWFWMD ................................................................................................ ..................164

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xi EXECUTIVE SUMMARY Background Over the past several decades, it has been obs erved that the flows in Florida’s springs are declining and water quality is degrading. The pr imary chemical concern is considered to be increased nutrients, including soluble forms of nitrogen and phosphorus. The sources are predominantly from animal waste, human waste, and from the synthetic fertilizers used on lawns, golf courses, or for agricultural activities. In recognition of these issues, the Secretary of the Florida Department of Environmental Protection (FDEP) directed the formation of th e Florida Springs Task Force in 1999. The multiagency task force consisted of 16 scientists, planners, and citizen s who were concerned about the “environmental health” of Florida’s springs. By 2000 the task force made a series of recommendations to protect and restore Florid a’s springs. They are outlined in detail in Florida’s Springs: Strategies for Pr otection and Restoration (Florida Springs Task Force, 2000). Two of the recommendations were to: (1) Implement springs monitoring programs to detect and document long-term trends in water quantity and quality (2) Conduct research that will allow ca use-and-effect relationships to be established between land use and water management activities. The purpose of monitoring is to both support research efforts and to confirm the effectiveness of spring protection efforts. As a direct result of the first recommendation, the Florida Geological Survey (FGS) took the lead in implementing a spring monitoring program. By 2004 it published the latest Springs of Florida bulletin—a descriptive overv iew of Florida’s springs. The main purposes of this document are to: (1 ) determine trends where sufficient data are available; (2) establish prot otype methods for evaluating a nd reporting trends for future applications; and (3) enhance the efforts of de termining cause-and-effect relationships between anthropogenic activities and the resulting spring-wa ter quality and quantity on regional (water management district-wide) and statewide scales. The reason for the latter is that many other publications have addressed the ca uses of trends on an individual spring basis. If we attempted to develop an exhaustive list of possible causes of trends for each spring, it c ould take many years to accomplish. We decided to emphasize re gional and statewide scal es. An endeavor of this nature has never been attempted. If region al or statewide trends were found, the causes and possible solutions to those causes may become th e highest priority water management issues. In order to fully comprehend the implica tions of trends in springs, a thorough understanding of the behavior of groundwater in wells is also necessary. In 1983, the FDEP began a statewide groundwater qua lity monitoring network (Florida Statutes 403.063). Scott et al. (1991) stated that the purpose of the networ k was to detect or predict contamination of Florida’s groundwater resources. Currently, severa l thousand wells are incl uded in the network. However, a subset of the well s are conducive to trend analysis (the Temporal Variability

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xii Network, or simply the TV Network). Since the FG S was asked to evaluate data for trends from springs, it followed to simultaneously do the same for groundwater from TV Network wells. Approach The FGS spring monitoring program commen ced operations in 2001. For many of the springs, previous samples had never been coll ected, so long-term trend analyses were not possible. However, the FGS contacted each of the four northern water management districts (WMDs), the U.S. Geological Survey (USGS), and programs within the FDEP to request copies of their historical spring-water quality and quantity data. The entities each graciously delivered data to the FGS for analyses. It should be noted that the South Florida Water Management District (SFWMD) had insufficient data for trend analyses. The FGS obtained sufficient data, meeting pr eset criteria, from 58 springs and 46 wells for the period January 1991 through December 2003. For reference, the study was divided into three time sequences. Sequence A represents the entire length of the study (1991-2003). Sequence B represents the January 1, 1991 – December 31, 1997 time frame, while Sequence C represents January 1, 1998 – December 31, 2003. Th e two shorter sequences were used to assist in identifying and evaluating s horter-term trends. As it turn s out, Sequence B coincided with relatively normal rainfall, whereas Sequence C covered a time that Florida experienced an extended drought. The analytes (constituents of interest) for this report can be broken down into five groups: (1) nutrients, (2) sa line (or salt-water), (3) rock-matrix (or ro ck), (4) field, and (5) other. Of these, the three major groups are nutrients, saline, and rock -matrix. Nutrients are compounds that are essential for the growth of living orga nisms. Unfortunately, high concentrations in spring-water can adversely affect th e biota in spring runs. Saline an alytes are related to salts. The most significant sources of salt are from the ocean or deep gr oundwater in Florida’s aquifers. High concentrations of saline compounds (e.g. sodium or chloride) can restrict the usage of water. Rock-matrix analytes have thei r sources in the aquifer material (e.g. limestones and dolostones). They occur na turally and, unless they occur in extremely high concentrations, are generally not harmful to our environment. The field and other analyte groups consist of miscellaneous constituents that are useful in explaining trends in other analytes. Think of a trend as a direction of moveme nt (Berube and Boyer, 1985). Although there are many secondary questions that pertain to trends, trend analys is can be broken down to one fundamental, primary question, “over time, are conditions changing (get ting better or getting worse), or are they remaining the same?” One can think in terms of concentrations of water quality (measured by analytes) or water quantity (measured by flow or water levels). Subjective descriptions—such as better, worse, and rema ining the same—are based on objective changes over time, or trends. Throughout this report the term significant refers to statistical significance. Some of the trends reflect very important ch anges in water quality, whereas some only represent relatively minor changes in water quality that are not i ndicative of impending problems. If, during our analyses, a trend was di scovered, it was based on statistical significance. That is, within a

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xiii predefined probability, we do not expect the tr end to occur randomly. Since not all of the audience of this report is familiar with the statistical procedures employed, we decided to simplify the procedures to the extent practical. Fo r this reason, most analys es were restricted to linear trends, using nonparametric techniques. Data were checked for seasonalit y, and if found, were deseasonalized prior to trend analys es using a method recommended by the U.S Environmental Protection Agency (EPA, 1989). Trend analyses were conducted using the Mann-Kendall test, while the rates of change over time were determined using the Sen slope (Gilbert, 1987). Results and Conclusions The most important conclusion to be derived from this report is that Florida springs truly represent the “canary in the coal mine” with re spect to assessing regional groundwater quality in Florida. As will be summarized, springs are appa rently much better at indicating over-all change in a groundwater flow system than wells. Monitoring wells only allow for the sampling of a discrete portion of the water in an aquifer. They limit detection to a particular depth interval and a relatively limited spatial extent. Karstic aquifers are especially limited in this respect as frac tures and cavernous conduits may direct water flow around or below the location of a monitoring well. On the other hand, the quality of water discharging from a spring is an integral of the water quality of the total flow system within a springshed. This water is de rived from deep and shallow flow systems and conduit and diffuse flow. Furthe rmore, the water quality, and fl ow, data are weighted according to the relative importance of the flow systems and chemical sources within the springshed. As a result, springs appear to be much better at de tecting regional changes in a springshed water quality than do wells. This conc lusion is supported by the fact th at water-quality trends were much more obvious in spring data than in well data. Springs Of the analyte groups, rock-matrix and salin e analytes had the greatest frequency of trends. Both analyte groups showed strong negativ e correlations with sp ring flow. For example, as spring flow decreased saline and rock-mat rix analyte concentrations increased. The relationship was observed throughout the state. The greatest increa ses in the concentrations of rock-matrix and saline analytes occurred duri ng a drought that occurre d between late 1998 and mid 2002. There are several probable expl anations and all ca n be a result of the drought. First, during the drought there was less rainfall, and c onsequently there was less surface-water flow. In karst terrains, much surface-water flows di rectly to groundwater through sinking streams (swallets). Typically, this rapidly recharge d groundwater is transmitted in well-developed subsurface conduits. Thus, there is very little contact time with the aquifer matrix before it discharges from springs, and it te nds to have lower concentrati ons of rock-matrix analytes. During a drought, there is a decrease in the propor tion of freshly recharged “surface water.” This, at least partially explains the correlation be tween decreased spring discharge and increased concentrations of rock analytes.

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xiv A second probable explanation is related to th e removal of older, sa line-rich and usually more mineralized water from storage, often in the deeper portions of the Florida’s aquifer systems. Beneath the state of Florida lies a “l ens” of fresh water, which is replenished by rainfall. Freshly recharged water is flushed th rough Florida’s karstic (sinkholes, caves, springs etc.) aquifers relatively quickly to springs. In contrast, the deeper water is older (Upchurch, 1992; and Katz, 2004). Because it has been in c ontact with the aquifer matrix for a relatively long period of time, the aquifer water has ha d a longer time to “pick up” dissolved matrix material constituents such as calcium and magnesium , especially in the Floridan aquifer system. With longer residence times, the older water tend s to have higher concentrations of rock-matrix material. A third explanation is similar to the second. Older, mineralized residual saltwater, was never fully flushed from the rock interstices in some portions of Florida (Johnson and Bush, 1986). With less rainfall during the drought, the wate r levels in the aquifers were lowered, and the size of the freshwater “len s” decreased. With decreasing freshwater potentials (e.g., water levels) the deeper and older connate water ca n find its way upward toward aquifer discharge points, such as springs. Thus, during the drought , increased concentrations in rock-matrix and saline analytes were observed, along with decreases in spring discharges. The trends were statewide in scale. The magnitude of scale wa s the most surprising and most significant finding of the study. After the driest portion of the drought (2002) , Florida’s hydrologic conditions began to recover and the concentrations of both types of an alytes began to decrease, as rainfall, recharge, and spring flow began to increase. The inverse relationship between spri ng-water discharge, and both rock-matrix and saline analyte concentrations , was also observed in a study by Katz (2004). In addition, Katz also found a pos itive correlation betw een concentrations of rock and saline analytes and spring-water age. Nutrients in groundwater discharging from springs were one of the most important concerns of the Springs Task Force. Evaluation of trends in this report revealed that nutrient trends in springs had an uneven, or patchwork, distribution acro ss the state. That is, both increasing and decreasing nutrient trends were common and were observed throughout Florida. This suggests that the trends were often related to local land-use and water-use activities. As such, most nutrient concentrations observed in springs are locali zed and should be analyzed in relation to the corres ponding springshed. Nitrogen and phosphorus comprised the most frequent nutrient exhibiting trends. Nitrogen in the form of nitrate (nit rate plus nitrite as N) had the greatest frequency of increasing (degrading) trends. However, some springs actu ally had decreasing nitrate trends. Phosphorus, as total phosphorus and orthophosph ate, had both increasing and decreasing trends, depending on the springshed. Note that decreasing nutrient tre nds are not necessa rily good news. During the drought, an important observation was that some nitrate concentrations had positive correlations with spring flow. One possible explanation is that nitr ogen can be stored in the soils of Florida’s springsheds (Bruland et al., 2008). During the drought, soils ma y have stored the nitrogen

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xv originating from fertilizer appl ications and the nitrogen did not find its way to the groundwater regime. When rainfall conditi ons return to normal, the soil s will release th e nitrogen and concentrations in spring water will eventually increase. On a similar note, decreases in phosphorus in some areas may likewise not be a reflection of improved management. It is possible that the upward migration of older wa ter, with different chemistry, reduced the phosphorus concentrations in many springs. If s o, reduction of phosphorus could simply be a byproduct of mixing with deeper, higher pH water —not an improvement in water quality. This mechanism is discussed by Hem (1985) and by Odum (1953). They indicated that the solubility of phosphorous can be controlled by pH. Disso lved phosphorous is generally more abundant in lower pH (more acidic) water. Conversely, highe r pH (more basic) water contributes to the precipitation of phosphate and lowers the c oncentration of diss olved phosphorous in groundwater. Wells Within Florida’s aquifers, the flow paths of spring-water can potentially be from both deep and shallow sources. Conversely, wells t ypically are drilled to a specific depth in an aquifer. Consequently, flow paths of well wa ter are from a much narrower thickness of the aquifer, relative to spring water flow paths. Although there are exceptions, most of the 46 wells used in this study generally tap only the shallower portions of the aquifers. The wells tend to be less than 30 m (100 feet) deep. Because of the shallower dept h, the older, deeper, and more mineralized deeper aquifer water had a lower proba bility of being observed in the shallow wells. Thus, rock-matrix and saline trends were not seen as frequently in wells as in springs. Nevertheless, decreasing trends in water levels within wells were common. In addition, pH—a field analyte—had a positive correla tion with water levels; as water levels in wells decreased, so did pH. A possible explanation for this positive correl ation is as follows. Well intake zones for most wells in Florida are generally set at spec ified depths below the lo west predicted aquifer water levels. This is done in order to guarant ee water to the well during drought conditions. During dry times the upper surface of the satu rated zone is lowered downward toward the uppermost point of the intake zone . For the aquifers tapped by the 46 shallow wells used in this study, most recharge takes place fr om water, typically rainfall, penetrating the land surface and moving downward through the soil to the groundwat er regime. Rainfall has a lower pH than most aquifer water. The pH is lowered furt her as rainwater picks up carbonic acid as it moves downward through Florida’s soils (Freeze and Ch erry, 1979; and Upchurch, 1992). Therefore, as the water table (or the potentiometric surf ace in confined aquifers) drops, generally the younger, freshly recharged water with lower pH ha s an increasing probabil ity of entering well intake zones. As such, the lowering of the water table is a potential cause for decreasing trends in pH values across the state during the drought. A detailed description of this hypothesis, along with other related hypotheses, is di scussed in the body of this report. Another field analyte that displayed a trend was well water temperature. Between 1991 and 2003, its temperature typically increased; the reason is believed to be an increase in air temperature. Air temperature increased acro ss Florida (Southeast Re gional Climate Center, 2006). Since the wells used in this report tend to be shallow, it is believed that well water readily

PAGE 18

xvi responded to air temperature chan ges. On the other hand, the s ources of spring water are from shallow and deep portions of our aquifers. Deep er water tends not to respond to changes in air temperature. Thus, spring water displayed fewe r temperature trends th an did well water. Concerns Rock-Matrix and Saline Indicators: Saltwater Encroachment Saltwater encroachment is the displacement of fresh groundwater by the advance of saltwater due to its greater density (Neuendorf et al., 2005). It can o ccur during a drought when recharge declines and the freshwat er “lens” shrinks in size. Over geologic time, it can occur with sea-level rise. It can also occur when ex cessive groundwater pumping causes the advancement of saltwater. Freeze and Cherry (1979) use the term saltwater intrusion as the migration of saltwater into freshwater aquifers under the influence of groundwater development (pumping). For this paper, we use the term intrusion to indicate a man-induced process and use the term encroachment to make no distinction between natural and man-made causes. Figure 1 (top) displays the unc onfined, surficial aquifer syst em. The saltwater/freshwater interface is repres ented by a transition zone. During a drought, the water table lowers, the transition zone migrates inland a nd the thickness of the freshwater zone (“lens”) decreases in size. In his work in northeastern Florida, Sp echler (2001) menti oned several possible mechanisms that can drive encroachment and in trusion. During the dro ught, they included: (1) the movement of “un-flushed” pockets of relict s eawater within the Floridan aquifer system, (2) the landward movement of the fr eshwater/saltwater interface, (3 ) regional upconing of saltwater below pumped wells, and (4) the upward leakage of saltwater from deeper, saline water–bearing zones through confining units. Th e latter can occur where the units are thin or are breached by joints, fractures, collapse features, or other structural anomalies. Examples are displayed in Figure 1 (bottom). During the 1999-2002 drought, the flows in ma ny springs decreased, and one spring (Hornsby Spring) stopped flowing altogether for a period of time. In addition to the decreased rainfall, there was an increased demand for gr oundwater (Verdi et al., 2006). The drought and the subsequent lowering of a quifer water levels resulted in decreasing spring flows throughout the state. The increased demand for groundwater during the drought exacerbated the problem in some of the springs. The increasing trends in rock-matrix analytes during the drought is an indication of a reduction in size of the fresh water “lens” underlying the state and an indication of saltwater encroachment. Because the concen trations of saline analytes increased almost everywhere in the state during th e drought, it is an indication that encroachment occurred on a statewide scale.

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xvii Figure 1. Schematics of freshwater/saltwa ter transition zone and possible mechanisms for saltwater/freshwater intrusion. Note Cooper (top) represents the saltwater/freshwater interface in the surficial aquifer system as a tr ansition zone, whereas Spechler (bottom) depicts it as a sharp boundary. Modified from Spechler (2001) Modified from Cooper (1964) surficial aquifer system intermediate confining unit Not to scale Not to scale

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xviii The 1998-2002 drought was one of the worst histor ical droughts to aff ect Florida (Verdi et al, 2006). Except for south Florida, during th e drought the deficit rainfall ranged from about 10 inches in southwest Florida to almost 40 inches in northwest Florida. In order to make up for the drought, groundwater pumping increased, largely fo r irrigation (Verdi et al., 2006). Because an increase in groundwater pumping occurred dur ing one of worst droughts, it is likely that human-induced saline intrusion took place and c ontributed to the increase in saline and rockmatrix analyte trends. On a statewide scale, the ex tent and severity of the intrusion is difficult to quantify. However, within the northern portion of the SWFWMD, a wa ter budget and a regional groundwater flow model indicated that the increase [0.3 cm/y r (+0.1 in/yr)] in groundwater withdrawals was less than 2.0% of the decline in recharge due to the decrease [18.3 cm/yr (7.2 in/yr)] in rainfall (Ron Basso, Southwest Fl orida Water Management District, personal communications). Nevertheless, intrusion should be a concern. If another drought of this magnitude occurs, depending on the amount of increased pumping, it could potentially have adverse affects on the long-te rm sustainability of FloridaÂ’s groundwater resources. Nutrients The Florida Springs Task Force (2000) indi cated that FloridaÂ’s springs face serious threats due to rapid and con tinuing population growth. The st ateÂ’s increasing population has resulted in extensive land-use changes, increased demand for freshwater, and an increased use of fertilizers. As rainfall seeps through the soils, and moves the nutrients into FloridaÂ’s underlying aquifers, it creates localized degradation in FloridaÂ’s groundwater resources. A report regarding FDEPÂ’s Springs Initiative Program efforts (Florida Department of Environmental Protection, and Florida Department of Community Affairs, 2002) noted that nitr ates have increased since the 1970s. It also noted that over the past 30 years many of Fl oridaÂ’s springs experienced an increase in nuisance algae and in vasive exotic aquatic plants. These plants tend to thrive on excess nutrients and decrease dissolved oxygen levels in spring runs. Analyses for the 1991-2003 time frame indicated th at trends in nutrient concentrations in FloridaÂ’s spring-water increased in some spri ngs, while they decreased in others. It is encouraging to note that there are some decreasi ng trends. The fact that nutrients (especially nitrate) tended to increase is an indication that some land-use management practices warrants reevaluation. But as noted previously, the rela tionship of these apparent decreasing trends may be related to diminishing spring flow. Monitoring The current study revealed an inverse relationship between rock and saline indicators and spring flow. The relationship was observed across the state (Figure 2). Note that changes in spring-water quality often lag behind changes in spring flow. For detail, the smaller charts depicted in Figure 2 have been enlarg ed and can be found in Appendix A. Historically, the WMDs and the USGS ha ve monitored spring-water quality and discharge. With the commencement of the Spri ngs Initiative, FDEP joined in the monitoring efforts. Considerable efforts were made to elim inate inconsistencies in monitoring activities. Unfortunately, at the beginning of the study, the effo rts were not always successful. Specifically, the WMDs, USGS, and FDEP did not always monito r the same analytes, use the same laboratory

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xix analytical methods, or collect fl ow data on the same date as chemical and biological data were collected. In addition, they often sampled at di fferent frequencies. Al l these inconsistencies made statewide comparisons very difficult. The results of this investigation demonstrate that statewide monitoring must continue. For this reas on, it is hoped that, in the future, the state can find ways to minimize monitoring inconsistencies. Recommendations One of the most surprising and most significan t observations of this study was that rockmatrix and saline analytes were increasing almost everywhere in FloridaÂ’s springs, especially during the drought of Sequence C. Saltwater encroachment is a hugely significant issue. Saltwater can restrict water us e and negatively aff ect freshwater ecology, and can adversely affect the long-term term sustai nability of FloridaÂ’s water resources. The relationships among rainfall, recharge, groundwater withdrawals, groundwater quality and levels, plus spring-water flows warrant further research, as does the effects of global climate change. The concentrations of at le ast one nutrient (nitrate) in numerous springs have been excessively increasing since the 1970s (Florida Department of Environmental Protection and Florida Department of Community Affairs, 2002). One of the most visible changes in springwater quality has been the increase in nuisance algae and invasive ex otic aquatic plants. What is the relationship between the increases in nutrients and the nuisance plants? Further research is needed. In addition, land-use management practi ce modifications are needed in order to reverse the increasing trends. It is beyond the scope of this study to elaborate on the management strategies. For a detailed discu ssion of many of the available stra tegies, an excellent reference is: Protecting FloridaÂ’s Springs Land Use Planning Strategies and Best Management Practices (Florida Department of Environmental Prot ection and Florida Department of Community Affairs, 2002). Spring-water quality is sensitive to changes in spring flow and to aq uifer water levels. They represent excellent natural sampling locati ons for monitoring saline incorporated into a statewide saltwater encroachment monitoring network. It is r ecommended that, to the extent practical, springs should be incorporated into a statewide saltwater encroachment monitoring network. The results of the spring monitoring could then potentially be e used to supplement well monitoring networks that are used fo r saltwater encroachment purposes. Although the monitoring of springs and wells is critical for the sustainability of FloridaÂ’s water resources, not all analytes of concern are sampled. Synthetic organic, other supplementary analytes (supplementals), as well as biological indicators, should be included on the monitoring lists. It should be understood that supplementals are expensive to collec t and analyze, and for these reasons, they can only be sampled on a low frequency basis. It should also be noted that supplemental monitoring is often determined by s ite-specific issues. For example, pesticides may only be detected at certain times of the ye ar or in certain locales , determined by land use conditions. Supplementals such as pesticides , synthetic organic compounds, and trace metals should occasionally be sampled.

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xx Figure 2. Inverse relations hip of flow to rock and salinit y indicator concentrations. Darker lines represent water levels (whether by stage or spring flow); light er lines represent saline or rock-matrix indicators (sodium or alkalinity). Time axes vary. The graphs indicate reciprocity between decreases in water levels and increas es of salinity, regardless of location in the state. FloridaÂ’s spring-water chemistry sh ows a high sensitivity to changes in flow (See Appendix A for enlarged versions of inset charts). Wakulla Spring (Well 67) Alapaha River Rise Fannin g S p rin g Homosassa No. 3 Poe Spring Chassahowitzka No. 1 Juniper Springs

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xxi It is critical that evaluations of spring wa ter and groundwater be cl early disseminated to the public as efficiently as practical. One effici ent method is the use of indices. Stock exchange indices have been used in the financial co mmunity for many years. Groundwater quantity indices are used by the Edwards Aquifer Authority in Texas. As an example, the authority use real-time water levels in the Bexar County Index well as an index for the entire county. During dry times, as water levels fall, water restrict ion measures may be i nvoked by the authority. When water levels rise, the restrictions are lif ted (Edwards Aquifer Au thority, 2006). There are several potential indices that could be developed for use in Florida. If one or more indices were developed, they have the potential to become very useful in informing the public about the status of our springs. However, in order to be viable, buy-in by both the public and scientific communities are essential. Hopefully, indices will be adopted in the future. It is essential that technical reports rega rding the results of analyses be generated frequently and in a relatively short time frame. It is acknowledged that it takes a considerable amount of time for an initial report to be genera ted. However, after the initial report, the lag time between sample collection and report generati on should reduce consid erably. In addition, subsequent reports using similar interpretativ e methods could employ computer programs to create “boiler plate” reports as quickly as an alytical data are received from a laboratory. Standardized spring and well sampling throughout the stat e is a critical need. If standardization is achieved, analyses of trends in the future will be much easier to conduct. This in turn will make the resulting interpretations more comprehensive, and the dissemination of the interpretive results will be more me aningful to the public. Specific aspects of the standardization effort include: core and supplemental water-qu ality analytes and indi cators, data reporting, sampling and laboratory quality assurance, data management, data analysis, and assessment reporting, Recommendation Synopsis Research Determine the relationships between increases in nut rients and nuisance plants/algae Determine the best land-use management practice needed in order to reverse increasing nutrient trends Improve our understanding of the relationships among: (1) ra infall, (2) recharge, (3) groundwater withdrawals, (4) groundwater quality and levels, and (5) spring-water quality and discharge Develop a “spring environm ental health” report card. Monitoring Recognize the importance of springs in saltwater encroachment monitoring and incorporate spring monitori ng into that effort

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xxii Add supplemental analytes to spri ng monitoring lists on a periodic basis Develop spring water-quality and quantity interpretative reports on a regular basis Adopt area-wide randomized spring sampling on a periodic basis in order to produce a synoptic report of all springs in Florida Institute multi-agency coordination to increase monitoring efficiency. Topics for discussion should include: • core and supplemental water quality analytes and indicators • possible development of a “spr ing environmental health” index • possible implementation of the random sampling of springs • sampling and laboratory quality assurance • data management • data analysis • assessment reporting

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BULLETIN NO. 69 1REGIONAL AND STATEWIDE TRE NDS IN FLORIDAÂ’S SPRING AND WELL GROUNDWATER QUALITY (1991-2003) by Rick Copeland (PG #126), Neal A. Doran, Aaron J. White, Sam B. Upchurch INTRODUCTION Florida is blessed with some of the most spectacular springs in the world. There are estimated to be over 700 springs in the state. People have been attracted to our springs since before Florida became a state. From a scientific perspective, some of FloridaÂ’s springs have been sampled for over a century. The FGS published its first Springs of Florida bulletin (Ferguson et al., 1947), which documented the chemical and flow data of th e major springs. The bulletin was revised in 1977 (Rosenau et al., 1977) and a new bulletin was generated in 2004 (Scott et al., 2004). In each revision, additional chemical data were presented. Unfortunately, as beautiful as the springs are, not all is well. As FloridaÂ’s population cont inues to grow, water-use and land-use changes are reflected in our spring water. The quantity and quality of spring water are both changing, and at least some of the change s are directly related to human activities. Since the 1940s FloridaÂ’s population has gr own from about two million to about 18 million in 2000. This means that Florida has in creased its population by a rate of about 600 people per day for those 60 years. In fact, between the years 2000 and 2005, the net rate of increase has been over 700 peopl e per day (U.S. Census Burea u, 2006). In the year 2000, Floridians withdrew 3.14 billi on gallons of groundwat er daily (Marella and Berndt, 2005). Marella and Berndt (2005) indicated that ag riculture and public supply accounted for over 82 percent of the groundwater use. Based on these data, each person used over 150 gallons per day of groundwater. It is not surprising that an extensive increase in water use has followed FloridaÂ’s population growth. Neith er is it surprising that there ha s been a noticeable decline in the discharge of many of Florid aÂ’s springs and that the intensive land-use changes have been followed by a noted deteriorations in spring-water quality. Scott et al. (2004) mentioned that one of the most notable deteriorati ons has been the increase in nutri ent concentrations in spring water. While nutrients such as nitrogen and phosphorous are required by aquatic organisms for growth and reproduction, when the concentrations are found to be higher than natural levels, problems can arise. Since the 1970s , concentrations of nitrate, a soluble form of nitrogen, have been found to be increasing in a number of Florid a springs (Florida Springs Task Force, 2000). Over the past several decades, flows in Flor idaÂ’s springs are declin ing and water quality is degrading. The primary chemicals of concer n are nutrients, including soluble forms of nitrogen and phosphorus. In order to improve and prot ect our springs, the Florida Sp rings Task Force (2000) made a series of recommendations to the Governor of Florida. One was that Florida should implement spring monitoring programs in order to detect a nd document long-term trends in water quality. In addition, it was recommended that the state should condu ct research in order to determine the

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FLORIDA GEOLOGICAL SURVEY 2 cause-and-effect relationship between land-use and water-management activities, and the resulting changes in springwater quality and quantity. As a result of the Florida Spring Task Fo rce’s first recommendation, the FGS was asked to evaluate historical spring data in order to detect and document trends in spring-water quality and quantity. This document repor ts the findings of analyses fo r trends in springs, using data from the Springs Initiative of FDEP, the WM Ds, and the USGS spring sampling programs. ACKNOWLEDGEMENTS The authors wish to acknowledge a number of individuals and to thank them for their assistance. From the Florida Department of Environmental Protection, Division of Environmental Assessment and Restoration, Bureau of Waters hed Management, we would like to thank Gail Sloane and Jay Silvanima for suppl ying the authors with data from the TV Network and their miscellaneous assistance on numerous occasions. Laura Morse assisted in supplying quality assurance information. Debra Harring ton, Rick Hicks, Gary Maddox, Jay Silvanima, Chris Sedlacek and Paul Hansard (now with th e Colorado School of Mines) supplied numerous editorial comments during the course of the proj ect. From the FGS, we would like to thank Doug Calman, Rick Green, Tom Greenhalgh, Harley Means, Frank Rupert, and Tom Scott for their many helpful editorial comments. We would also like to acknowledge the e fforts of numerous people from the water management districts who supplied us with spri ng data and constructiv e comments regarding the document. In particular the authors would like to thank Kris Barrios, Angela Chelette, Tony Countryman, Kevin De Fosset, Tom Pratt, and Ni ck Wooten, from the Northwest Florida Water Management District (NWFWMD); Ron Ceryak and David Hornsby of the Suwannee River Water Management District (SRWMD); and Ron Basso, Eric DeHaven, David DeWitt, Joe Haber, Robert Peterson, and Robe rta Starks from the SWFWMD. We would like to thank Brian Katz and Stuart Tomlinson of the USGS. Both individuals supplied data and other informati on that was invaluable to the pr oject. We would like to thank Dr. Xu-Feng Niu of the Florida State University, De partment of Statistics, for contributing to the section regarding statistical me thodologies and to Rich Smith, a graphic designer, who assisted with making of many of the figures. FLORIDA’S SPRINGS Scott et al. (2004) presented an excellent overview of Flor ida’s springs. Although they did not specifically evaluate trends, the au thors described hundreds of Florida’s springs, including a description of thei r water quality. In doing so they described many aspects that control the water quality and quantity of groundwat er. With this in mind, their work can be considered a precursor to the present trend analysis document. With the authors’ permission, much of the following introduction from the sections labeled “Florida’s Springs” to “Differences in Spring and Well Water Quality” are paraphrased from their work, “Springs of Florida.”

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BULLETIN NO. 69 3 Many terms relating to hydrogeology and springs may be unfamiliar to the reader. For this reason a glossary of terms is found in Appe ndix B1. In addition, Appendix B2 (online at http://www.uflib.ufl.edu/ufdc/?b=UF00095137 ) elaborates on the sources of the analytes discussed in this report, along with the probable causes for the trends observed. Other appendices (C, E, F2,H, I, J, K, L, and M) can also be found at the online site. Spring-water discharge comes primarily from th e Floridan aquifer system, which is also the state’s principle source of groundwater. The springs provide a “window” into the aquifer, allowing for a measure of the health of the aquife r. Chemical and biological constituents that enter the aquifer through recharge processes may negatively affect the water quality in aquifers, as well as the flora and fauna of springs and spri ng runs. The declines in water quality can be directly attributed to Florid a’s increased population and changi ng land-use patterns (Florida Springs Task Force, 2000). Classification of Springs Springs are most often classified on the amount of flow or discharge of water. The flowbased classification listed in Ta ble 1 is taken from Meinzer ( 1927) (Table 1). One discharge measurement is all that is required to place a sp ring into one of eight magnitude categories. However, it should be understood th at each spring exhibits a va riable discharge, depending upon rainfall, recharge and groundwater withdrawals within their recharge areas. This can result in a spring being classified as a first magnitude spring at one point in time and a second magnitude at another. In the past, a spring assigned a magn itude when it was first described and continued with that magnitude designation even though the discharge may have changed considerably over time. To alleviate this confusion, the FG S (Copeland, 2003) adopted a system using the historical median of the flow measurements to classify a spring’s magnitude. Using the new system along with the Meinzer system, a spring’s magnitude is now based on the median value of all annual median discharge measurements fo r the period of record. Of the over 700 springs inventoried by the FGS, there are 33 first-magnitude spring s, 191 second-magnitude, and 151 third-magnitude springs. Most are located in th e northern portion of th e state (Figure 3). Table 1. Spring Magnitude. Discharge Magnitude Metric Units English Units 1 2.832 cms 100 cfs ( 64.6 mgd) 2 0.283 to 2.832 cms 10 to100 cfs ( 6.46 to 64.6 mgd) 3 0.028 to 0.283 cms 1 to 10 cfs ( 0.646 to 6.46 mgd) 4 0.0063 to 0.028 cms 100 gpm to 1 cfs ( 100 to 448gpm) 5 0.631 to 6.308 lps 10 to 100 gpm 6 0.063 to 0.631 lps 1 to 10 gpm 7 0.473 to 3.785 lpm 1 pint/min to 1 gpm 8 < 0.473 lpm < 1 pint/min cms = cubic meters per second lps = liters per second cfs = cubic feet per second pint/min = pints per minute mgd = million gallons per day lpm = liters per minute gpm = gallons per minute

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FLORIDA GEOLOGICAL SURVEY 4 Figure 3. Locations of FloridaÂ’s springs (From Scott et al., 2004). A second spring classification system is also in use. The Florida Spring Classification System (Copeland, 2003) (Table 2) is based on an assumption that karst activities have influenced almost all springs in Florida. U nder this system, all springs in Florida can be classified into one of four cate gories, based on the spring's point of discharge. Is the point of discharge a vent or is it a seep and is the point of discharge located onshore or offshore? Since all springs are either vents or seeps, the classi fication can be simplified into the following categories. A spring vent is defined as an opening that concentrates groundwat er discharge to the Earth's surface, including the bottom of the ocea n. The opening is signifi cantly larger than the average pore space of the surroundi ng aquifer matrix. A vent is o ccasionally considered to be a cave, and groundwater flow from this type of vent is typically turbulent. On the other hand, a spring seep is composed of one or more small openings in which water discharges diffusely (or "oozes") from the groundwater environment. Th e diffuse discharge originates from the intergranular pore spaces in the aquifer matri x. Flow from seeps is typically laminar.

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BULLETIN NO. 69 5 Offshore Springs Springs occur both onshore and offshore in Fl orida. Currently, littl e is known about the offshore, or submarine springs, with the excepti on of the Spring Creek Group—the largest spring group in Florida, averaging more than one billion gallons of water discharged per day (maximum flow estimated at more than two billion gallons of water per day [Rosen au et al., 1977; Lane, 2001]). Offshore or submarine springs (Figure 4) are known to exist off Florida's Atlantic and Gulf of Mexico coastlines. These springs are most common in the offshore portion of Florida from Crystal Beach Spring (Figure 4, Spring No. 7) to Bear Creek Spri ng (Figure 4, Spring No. 1). Offshore springs have also been identified o ff the northeastern and sout hwestern parts of the Florida and the western panhandle (Rosenau et al., 1977) (Figure 4). Wa ter-quality data from some of these springs indicate that , at best, the water is brackish. There are anecdotal reports of "fresh water" flowing from Florida’s offshore springs. Table 2. Florida's Spring Classification System. (From Copeland, 2003) SPRINGS Onshore Offshore Vent Onshore Vent Examples Karst spring Resurgence (River Rise) Estavelle (intermittent resurgence or exsurgence) Subaqueous riverine vent Subaqueous lacustrine vent Sand boil Offshore Vent Examples Offshore karst spring Unnamed offshore vent Offshore estavelle vent Seep Onshore Seep Examples Subareal riverine seep Subaqueous lacustrine seep Offshore Seep Examples Unnamed offshore seep Offshore estavelle seep

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FLORIDA GEOLOGICAL SURVEY 6 Figure 4. Offshore Springs (From Rosenau et al., 1977). Spring Recharge Basins In addition to the awareness of increasing tren ds in contaminants such as nitrate over the past several years (Figure 5), there has also b een an increased awareness on the drainage basins that supply water to FloridaÂ’s gr oundwater and springs. The amount of water and the nature and concentrations of chemical constituents that di scharge from springs are functions of the geology, hydrology, weather conditions and land uses within the spring recharge basin. This type of basin, often referred to as a springshed, consists of those areas within groundwater and surfacewater basins that contribute to the discharge of the spring (Dehan, 2002; Copeland, 2003). The springshed consists of all areas where water can be shown to cont ribute to the groundwater flow system that discharges from the spring of inte rest. Karst systems frequently include sinking streams that transmit surface water directly to the aquifer; the r echarge basin may include surface water drainage basins that bri ng water into the spring drainage from outside of the groundwater basin.

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BULLETIN NO. 69 7 Figure 5. Median nitrate concentr ations in 13 selected first-magnitude springs. Springs are Alexander, Chassahowitzka Main, Fanning, Ichetucknee, Jackson Blue, Madison Blue, Manatee, Rainbow, Silver, Silver Glen, Volu sia Blue, Wakulla, and Wacissa #2 (From Scott et al., 2004). OVERVIEW OF THE HYDROGEOLOGY OF FLORIDAÂ’S GROUNDWATER Florida enjoys a humid, subtropical climate throughout much of the state (Henry, 1998). Rainfall, in the region of the major springs (Fig ure 1), ranges from 127 cm (50 inches) to over 152 cm (60 inches) per year. As a result of the climat e and the geologic fram ework of the state, Florida has an abundant supply of fresh groundwate r. Scott (2001) estimated that more than 8.3 billion cubic meters [2.2 quadrillion (2.2 x 1012) gallons] of freshwater are contained within FloridaÂ’s aquifers. However, only a very small percentage of freshwater is available as a renewable resource for human consumption. The Florida peninsula is the exposed portion of the broad Florida Platform. The Florida Platform, as measured at the 200 meter (more than 600 ft) below sea level contour, is more than 483 km (300 miles) wide. It extends more than 240 km (150 miles) westward under the Gulf of Mexico, and more than 113 km (70 miles) unde r the Atlantic Ocean. The present day Florida peninsula is less than one ha lf of the total platform. The Florida Platform is composed of a thic k sequence of variably permeable carbonate sediments, limestone and dolostone, lying on olde r igneous, metamorphic and sedimentary rocks. The Cenozoic carbonate sediments may exceed 1,220 m (4,000 ft) thick. A sequence of sand, silt and clay with variable amounts of limestone a nd shell overlie the car bonate sequence (see Scott et al, 1991 and Scott, 1992b for discussion of th e Cenozoic sediment sequence and the geologic

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FLORIDA GEOLOGICAL SURVEY 8 structure of the platform). In portions of the we st-central and north-centr al peninsula and in the central panhandle, the carbonate rocks, predominantly limestone, occur at or very near the surface. Away from these areas, the overlying sand, silt and clay sequences become thicker. As the rocks sediments compacted and were subjected to other geologic forces, fractures formed. These fractures allowed water to move more freely through the sediments and provided the template for the development of Florida's many cave systems. There are three major aquifer systems in Florida, the Floridan, the intermediate and the surficial aquifer systems (Southeastern Geol ogical Society, 1986; Scott et al., 1991). The Floridan aquifer system (FAS) occurs within a thick sequence of permeable carbonate sediments (see Miller, 1986 and Berndt et al., 1998 for discussi on of the FAS). In some areas, it is overlain by the intermediate aquifer system (IAS) and the intermediate confining unit (ICU) which consists of carbonates, sand, silt and clay. The surficial aquife r system (SAS) overlies the IAS (or the FAS where the IAS is absent), and is composed of sand, shell and some carbonate. The vast majority of Florida's springs result from di scharge from the Upper Fl oridan aquifer system (UFAS), a subdivision of the FAS as discussed by Miller (1986). Typical natural recharge to the FAS originat es as rainwater. As the acidic rainwater percolates downward to the FAS, it is made slightly more acidic by carbon dioxide from the atmosphere and organic acids in the soil. Once in the FAS, the groundwater dissolves portions of the limestone and enlarges naturally occu rring fractures. The dissolution enhances the permeability of the sediments and forms cavities and caverns. Sinkholes are formed by the collapse of overlying sediments into the cavities. Occasionally, the collapse of the roof of a cave creates an opening to the land surface. See La ne (1986) for a description of sinkhole types common in Florida. Recharge to the FAS occurs over approximate ly 55 percent of the state (Berndt et al., 1998). Recharge rates vary from less than 2.54 cm (one inch) per year to more than 25.4 cm (10 inches) per year. Water entering the upper portion of the FAS eventually discharges from a spring. The water has variable residence times. Katz et al. (2001) and Katz (2004) found that water flowing from larger springs had a mean groundwater residence time of more than 20 years and may reflect the mixing of older and younger waters. Florida's springs occur primarily in the nor thern two-thirds of the peninsula and the central panhandle where carbonate rocks are at or near the land surface. Most of these springs produce water from the UFAS which consists of se diments that range in age from Late Eocene (approximately 36 38 million years old [my]) to mid-Oligocene (approximately 33 my). Miocene to Pleistocene sediments (24 my to 10,000 years) often are exposed in the springs. The geomorphology of the state, coupled with the geologic framework, controls the distribution of springs. The springs occur in areas where karst f eatures (for example, sinkholes and caves) are common, the potentiometric surf ace of the FAS is high enough and the surface elevations are low enough to allow groundwater to flow at the surface. Springs generally occur in lowlands near rivers and streams. There are a number of springs known to flow from vents within river channels and many mo re are thought to exist. Hornsby and Ceryak (1998) identified many newly recognized springs in the channels of the Suwannee and Santa Fe Rivers. Springs

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BULLETIN NO. 69 9 that have yet to be described have been f ound within the Apalachicol a River between Gadsden and Jackson Counties (H. Means, Florida Ge ological Survey, pers onal communication, 2004). Weather and climatic events affect the appear ance of spring water. For example, during periods of higher than normal precipitation, such as hurricanes, some springs may reverse flow. When this occurs, stream water flows into th e aquifers. During these times, spring water often has a dark appearance because of the presence of tannins from surfacewater sources. Once stream levels drop enough, the dark waters agai n reverse flow. When this occurs, discharge becomes much clearer. Dryer periods also affect the appearance of springs . For example, during 1998 2002, Florida experienced a major drought w ith a rainfall deficit in places totaling more than 127 cm (50 in) (Verdi et al., 2006). The resulting reduction in recharge from the drought, along with the normal withdrawals, caused a lowering of the potentio metric surface in the FAS. Many first magnitude springs e xperienced a significant flow re duction. Some springs ceased flowing completely. The appearance of the spri ngs also changed as river and lake levels declined reducing the size of the spring-wa ter body and exposing sediments along the banks. QUALITY OF GROUNDWATER AND SPRING WATER Natural Factors Affecting Groundwater and Spring-Water Quality Most of the Florida land mass is a peni nsula that is surro unded by saltwater. R elict saltwater also underlies the entire state. The reason for this is that the Florida Platform consists of carbonate rocks that were de posited in a shallow ocean. At the time of deposition, saltwater existed in their intergranular pore spaces. Gradually over geologic time, sea level was lowered relative to its position when the carbonate sediments were deposited. Through compaction and down warping of sediments on both sides of the Plat form, a series of complex fracture patterns developed. The patterns are often reflected at land surface and have actually influenced the pathways of many of Florida's streams. Over geologic time, as sea level lowered, th e central portion of the Florida Platform was exposed to the atmosphere. As rainfall percol ated downward it eventually replaced the upper portion of saltwater in the developing aquifers w ith a freshwater “lens.” Today, the irregularly shaped “lens” is generally thickest in the cent ral portion of the state, where it is over 610 m (2,000 ft) thick (Klein, 1975). It becomes narrow to ward Florida's coastline. The base of the “lens” is typically a transitional rather than a sharp boundary. Groundwater in the deeper portion of the “lens”, and along the coasts , is mixed with saltwater and ha s relatively high concentrations of saline indicators such as sodium (Na), chloride (Cl), and sulfate (SO4). Water discharging from Florida's aquifer syst ems and springs has its primary source from rainfall. Much of the rainfall reaching land surface flows overland to surfacewater bodies, evaporates, or is transpired by plants. However, a portion of th e rainfall percolates downward through the sediments, or enters sinkholes, where it recharges the aquifers. During its travel downward from land surface to the water table, a nd during residence within Florida's aquifer systems, many factors affect the water chemistry.

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FLORIDA GEOLOGICAL SURVEY 10 A long residence time may allow sufficient tim e for chemical reactio ns between the water and the aquifer rock. As such, water chemistr y reflects the composition of the aquifer rock. Typical residence times range from less than se veral days (in secondary produced caverns and sinkholes) to centuries (Hanshaw et al., 1965). A second factor affecting groundw ater chemistry is flow pat h, which is the length and depth of the path that the gr oundwater follows as it flows th rough an aquifer (Upchurch, 1992). In general, shallow, short flow paths (which are characteristic of the SAS) result in shorter residence times for chemical reactions to take place. Consequently, the total dissolved solid (TDS) content is less than in longer flow-path syst ems. If the flow path is long (on the order of tens of kilometers), such as commonly occurs in the FAS, reactions between rock and water become more probable and the TD S content of the water would be greater as a result of continued rock-water chemical reactions. Because of the residence time and the flow paths of the groundwater within an aquifer, the quality of spring water is typically reflective of the interactions of the major rock types in the aquifer and the groundwater itself. A third factor which is of particular intere st is intergranular po rosity (pores through which water passes between the individual rock ma trix grains). Even though Florida's aquifers have large, secondary cavernous pores spaces, mo st of the pores tend to be small (Upchurch, 1992). Fortunately, whenever the por es are very small, they act as filters for microbes, small organic substances, and clay minerals. In general, this results in naturally filtered groundwater that is very pure and desirable for both dri nking water and recreation. Unfortunately, some pollutants not always removed and our aquifers can become contaminated. Differences in Springand Well-Water Quality The processes controlling the water quality in wells is very similar to those controlling spring-water quality with at least one major difference. Wells are often drilled to production zones as close to land surface as is economical. This is the situation for the wells used in this study, which are for the most part monitoring we lls. Monitoring wells tend be shallow (median depth 80 feet (24 m ) (Appendix C, online). Most water in these shallow wells represents young, recently recharged water. On the other hand, because springs are major discharge points, spring-water can be considered to be an integrat or of water from the entire springshed. Spring water is a mixture of young, shallow, freshly rech arged water and older water from the deeper portions of the aquifer. For this reason, spring wa ter tends to be older th an the relatively shallow water found in the monitoring wells used in this study. Indicators of Groundwater and Sp ring-Water Quality Problems Spring water, while it resides in the aquifer, is considered to be groundwater. However, once spring water exits from the spring onto the ear th's surface, it is cons idered to be surface water. Because of this change, the question ar ises whether regulators should apply groundwater or surfacewater quality standards to the water. Primary and secondary standards with maximum contaminant limits (MCLs) may exist for an anal yte while the water is considered groundwater, but differ for surface water; or vice versa. Drinking water st andards are protective of human

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BULLETIN NO. 69 11 health while surface water criteria are protective of aquatic biota. Although several analytes fall into this category, Nitrate (NO3 + NO2 as N), and hereafter abbreviated NO3, is a good example. Based on drinking water criteria, nitrate has a gr oundwater threshold value of 10 mg/L (Florida Department of Environmental Protection, 1994). However, no numeric nitrate criteria exist for surface water, other than Class I surface water whic h is used for drinking water. The FDEP is currently developing criteria for spring water. Until legal numeric criteria are established for nitrates, it should be unde rstood that any reference to thres hold values in the following text simply infers potential water-quality problems. One of the more disturbing aspects about Florida's groundwater quality has been the documented steady increase of nitrate over th e past several decades (Jones et al., 1996; Champion and DeWitt, 2000; Means et al., 2003). An example is displayed in Figure 5 (From Scott et al., 2004). It shows that nitrate concentrations have a gr eater than 19-fold increase in nitrate concentrations in 13 se lected first-magnitude springs (Alexander, Chassahowitzka Main, Fanning, Ichetucknee Main, Jackson Blue, Madi son Blue, Manatee, Rainbow Group composite, Silver Main, Silver Glen, Volusia Blue, Waku lla, and Wacissa #2 Springs) between the 1970s and 2000. The natural background nitrate concentrations in Florida groundwater are less than 0.05 mg/L (Upchurch, 1992). During the 2001-2002 time fr ame, the FGS sampled 125 spring vents. Of the 125 spring vents sampled, none had nitr ate concentrations ex ceeding the 10 mg/L threshold for Class I surface and drinking water. Fifty-two of the spring vents sampled had nitrate concentrations exceeding 0.50 mg/L (42 pe rcent) and 30 (24 percent) had concentrations greater than 1.00 mg/L. Thus, over 40 percent of the sampled springs had at least a ten-fold increase in nitrate concentra tions above background and approxima tely one quarter of them had at least a 20-fold increase. The elevated nitrate concentrations may adversely affect the aquatic ecosystem in springs and spring runs. Further res earch is still needed and is currently being sponsored by the Springs Initiative Program. The FDEP is aware of the nitrate issues and has worked with other governmental agencies to develop a series of steps to reduce nitrate concentrations in groundwater and springs in the middle Suwannee River Basin where many of Florida's springs are located (Copeland et al., 2000). The FDEP Bureau of Watershed Management and the Florida Department of Comm unity Affairs are active in coordinating the development of spring protection measures. Another groundwater quality conc ern is the influence of sali ne water. Several springs have concentrations of chloride (Cl; a saline indicator) exceeding th e 250 mg/L threshold for drinking water. Springs with this type of wate r tend to be located along Florida's coast and along the St. Johns River. The ultimate source of the salin e indicators is from naturally occurring saline water within the FAS (Klein, 1975), or from sea water near FloridaÂ’s coasts. When the concentrations of saline indi cators are increasing, it may be the result of: (1) natural circumstances such as drought, (2) the consequent upconing of groundwater within the FAS, or (3) lateral intrusi on of salt water due to incr eased groundwater pumping. Enterococcus and total coliform bacteria represent a third concern. It is generally believed that these bact eria originate in fecal matter from warm-blooded animals (Center for Disease Control, 2004). Total coliform concentrations in several springs has exceeded the

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FLORIDA GEOLOGICAL SURVEY 12 drinking water standard of four colonies per 100 ml (Flo rida Department of Environmental Protection, 1994). However, it has b een determined that these bact eria can complete their normal life-cycle outside of warm-blooded animals, especi ally in environments found in parts of Florida (Fujioka and Byappanahalli, 2004), thus the concen trations of fecal colifo rm may not necessarily represent a direct link to warm-blooded animal pathogens. Further research is needed before definitive conclusions can be made regarding the source of fecal bacteria. Another concern is concentrations of enterococcus and fecal coliform bacteria with regards to swimming. The Florida Department of Health has set beach sw imming standards and advisory thresholds for both organisms. To date, exceedances of the standa rds and thresholds in springs have not been a problem. Nevertheless, many residents swim in spring runs and these bacteria are a concern. SPRING SELECTION PROCESS Very little spring-water quality sampling, mo stly by the USGS, occurred until the 1940s. In 1947, the FGS published its first edition of “Spr ings of Florida” (Fergus on et al., 1947) which documented the water quality in the major springs of Florida. The document was revised in 1977 and many previously undocumented springs were sa mpled (Rosenau et al., 1977). It should also be noted that during the 1970s, the three norther n water management districts were formed. They were the NWFWMD, the SRWMD, and the (S aint Johns River Water Management District (SJRWMD). Within a few years, these WMDs, al ong with the USGS and th e already established SWFWMD, occasionally co llected spring-water quality samp les. By the 1990s, the NWFWMD, SRWMD, SJRWMD, and SWFWMD had establishe d periodic to regular sampling, often with the assistance of the USGS, of sp rings within thei r jurisdiction. Partially due to the sampling efforts of the WM Ds, in the 1990s it became apparent that the water quality in some of Florida’s spring s was deteriorating. For this reason, in 1999 the Secretary of the Florida Department of Enviro nmental Protection directed the formation of a multi-agency Florida Springs Task Force to provide recommendations for the protection and restoration of Florida’s springs. In late 2000 the Task Force made recommendations for the preservation and restoration of Florida’s sp rings to the Secretary, and in 2001 the Florida Legislature passed the Florida Spri ngs Initiative. The Initiative authorized funds for FDEP to begin investigating the status of Florida springs a nd develop strategies for protecting them. As a result of the Initiative, the f our WMDs, FDEP, and the FGS have cooperated to monitor Florida’s springs. The Springs Initiative has been responsible for the collection of spring-water quality since 2001. Beginning with that year, much of the data used in this report were obtained from Springs Initiative-sponsored samples. Methods of ev aluating the data used in this report can be used in the future to analyze the spring data curre ntly being generated as a result of the Springs Initiative. In the meantime, data of spring-water quality collected as part of WMD spring sampling programs were used for th is interpretative report. The FGS requested spring data from each of th e four northern WMDs in order to analyze spring-water quality and quantity for trends. The districts delivered data to the FGS in 2002 and 2003. It was soon discovered the WMDs had only sporadically sampled their springs through

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BULLETIN NO. 69 13 the 1980s. However, beginning in the early 1990s each district had begun to sample springs in a semi-consistent manner. Even though data do exis t for many springs, only 58 springs (Figure 6) were ultimately included in th e analysis; one from the NWFWMD, 14 from the SRWMD, 15 from the SJRWMD, and 28 from the SWFWMD. Selection was determined based on the consistency of the data. As a working definitio n, we considered consistency to be the longest string of data in terms of time along with the greatest number of an alytes. We also wanted the largest number of springs to be in cluded that met our concept of consistency. With these criteria in mind we determined that the time period from January 1991 through December 2003 represented the time in which the most consistent data existed for the gr eatest number of springs. We realize that there are several springs that have decades of data. We also realize that since commencement of the Springs Initiative, many spri ngs now have data, but the time sequences are short. As a result, our data interpretations are valid only for the 1991-2003 time frame. A discussion of analytes eval uated and frequencies of sampli ng will be discussed later. Figure 6 displays the location of the included springs in the analyses. A list of the names of springs, along with location inform ation, can be found in Appendix D. WELL SELECTION PROCESS In 1983, the Florida Legislature passed the Water Quality Assurance Act (Florida Statutes, 1983, Chapter 403.063). As a result, FDEP, with the assistance of the five water management districts, plus several counties (A lachua, Broward, Collier, Lee, Miami-Dade, and Palm Beach) established extens ive groundwater monitoring networks. The purpose was to document both ambient groundwater quality c onditions (Background Network) and to detect changes in FloridaÂ’s groundwater quality resultin g from the effects of various land uses and potential sources of contamination (Very Intens e Study Area Network [Scott et al., 1991]). Both networks were in operation unt il 2000. A major subdivision of the Background Network was the Temporal Variability (TV) Network. The TV Ne twork consists of a series of strategicallylocated wells scattered throughout the state that ar e sampled on a monthly to quarterly frequency. Beginning in 1996, FDEP began a major rede sign of its water resource monitoring efforts. The purpose of the redesign was to characterize the environmental conditions of FloridaÂ’s water resources and to determine if those conditions are changing over time. The revised network (The Status Netw ork) became operational in early 2000. A detailed description of the Status Network is presen ted by Copeland et al. (1999). Throughout the redesign process, the TV Network only had minor m odifications. The stated purpose of the redesigned network is to evaluate temporal variabili ty of FloridaÂ’s groundwater quality and to determine whether concentrations of the sampled analytes are in creasing or decreasing over time. The TV Network consists of 46 wells (Figure 7); 25 wells mon itor confined groundwater and 21 wells monitor unconfined groundwater. The wells tap each major aquifer system and are scattered throughout each of FloridaÂ’s five WMDs. As can be seen in Figure 7, some of the well locations represent

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FLORIDA GEOLOGICAL SURVEY 14 Figure 6. Location of springs analyzed in this report. (A list of the spring names can be found in Appendix C.)

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BULLETIN NO. 69 15 Figure 7. Location of Temporal Variability Network (TVN) wells. (A list of well identifiers can be found in Appendix D.)

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FLORIDA GEOLOGICAL SURVEY 16 clusters of wells. Wells that monitor confined ground water are sampled quarterly. Wells that monitor unconfined groundwater are sampled monthly. With respect to the WMDs, the NWFWMD has eight wells, the SRWMD has 10 wells, the SJRWMD has nine wells, th e SWFWMD has 11 wells, and the SFWMD has eight wells in the TV Network that had significant data for an alyses. A list of well names can be found in Appendix D, along with we ll construction data. METHODS This report uses a relatively simple methodology to determine the condition of spring and groundwater quality. Most analyses boil down to the single straightforward question, “ are conditions getting better, getti ng worse, or remaining the same ?” Though this report is based upon several statistical procedures, all address this single question. With this simple objective in mind, additiona l elaboration is requi red to expand upon the connection with actual statistical tests and methods. First, si nce “better” and “worse” are subjective and qualitative questions, an approach that will quantify them is needed. Thus, a somewhat more objective and quantitative form of the above question becomes, “ for the 19912003 period of record, are the indicators d ecreasing, increasing, or remaining the same? ” This frames the question of quality in the terms of changing quantities between two end-points (i.e., the start and finish of a time peri od of interest); changes in quanti ties, such as flow and loading, can be objectively tested in a variety of ways. In order to test quantities, the last remaini ng questions are: (1) wh ich quantities and, (2) over what period of time? These further condi tions must be defined. The first question is which quantities? For this report, as many indicators as possible were tested. This allowed the authors to ask questions of the largest possible scale; limiting the number of indicators only limits the possible number of observations and maximizing the number of observations allows the most comprehensive view of changes that might be of concern. Second, for the quantities examined an increase or decrease in concentr ation must be addressed over a time frame . Therefore, in order to maximize the effectiveness of the analysis, the l ongest possible time seri es was chosen for as many springs as possible. In summary, the choice was for the longest possible time frame for data with the highest quality, for as many indi cators possible, and for as many springs as possible . Laboratory and collection met hodologies have varied over th e last several decades in the state of Florida. Variations include not onl y differences among WMDs, but even use of different laboratories by the sa me district, changes within la boratories, incomplete sampling intervals due to varying purposes and other reasons. Because of this , the earliest starting point for which data quality could be uniformly assumed to be high (in this cas e 1991) was chosen; this created the longest possible time series for anal ysis (1991-2003) for as many springs as possible. Regarding the second question, for this report, we chose trend analysis to evaluate a given time series (between 1991 and 2003) for lin ear trends. Note that Urquhart and Kincaid (1999) mentioned that trends may deviate from st rict linearity. Nevertheless, they mentioned

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BULLETIN NO. 69 17 that if a trend is present, a linear trend will be present, regardless of the type of mathematical structure of the trend, e.g. cyclic , episodic, or a stair-step look. For this report, we were not only interested in detecting the presence of a trend we were also interested in a statistical method that was relatively inse nsitive to missing sampling points (e.g., gaps in data series), outliers, and, data th at seldom had normal (G aussian) distributions. Based upon these reasons, our choice for analysis was the non-parametric, Mann-Kendall (MK) test for trends. Discussions of the MK test and other statistical procedures used in the study, including the correspon ding assumptions, are found in Appendix E. Our last clarification involves interpretation of trends; n ot all increases are bad nor are all decreases good. For example, a decrease in nitrate is desirable and is considered to be good. On the other hand, a long-term decrease in flow is not desirable, since it may indicate an overuse of the resource. Thus, it can be considered to be ba d. Another example, an increase or decrease in pH may not be considered to be good (if it is extr eme), since this analyte is best defined by an optimal middle range; being far outside that range on either side is bad. The point is that change, in one direction or another, can be tested and the result ha s implications regarding the improvement or degradation of the system in question. Definition of Trends Natural systems in general undergo two main t ypes of change: cyclic and linear (A and B, top of Figure 8). Cyclic change is common in nature. Two common examples of cyclic changes include diurnal and seasonal ch anges. Natural changes can al so be linear, moving conditions from one state to another without re turning to the original state. The focus of this report is to document linear trends in water qu ality and quantity. It is also assumed that trends in certain analytes are most likely an thropogenic, rather than natural in origi n. In this case, three possible linear trend scenarios can be test ed. In each case, a chemical component of a groundwater system (whether spring or well) can be plotted as a concentration against time (Figure 8, bottom). The first scenario (on the left) is that the system is increasing in concentration for a particular analyte (for which the symbol, “+”, will be used in this report). One case could be phosphorus. Over a period of interest, change of concentration can be tested at a specific leve l of confidence (e.g., at a 95 percent confiden ce level, or an level of 0.05). This means that by the end of the time period, the concentration was high enough to warra nt the designation of being higher than expected by chance fluctuation alone. Such valu es are marked as being highly unlikely to have occurred unless notable changes to the system were introduce d. In the opposite case (on the right), the concentration could have decreased significantly (represented by “-”). Such a trend suggests a substantial change to the physical environment and w ould therefore be recorded. The third scenario (middle chart) is that neither case was observed. As will be detailed below, this is not a positive statement affirming uniform conditions for the system in question; rather it is a general category for all conditions not classified within the former two situations. This is a default option and it is likely that a number of valid trends that could escape detection and be included in this scenario.

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FLORIDA GEOLOGICAL SURVEY 18 Figure 8. Illustration of three op tions for water-quality trends. Trends can either increase (+), decrease (-), or otherwise cannot be confirmed. Depending on the analyte, the interpretation is that the system is getting better, getting worse, or remaining the same. Taking the example of phosphorus, if the trend is increasing, the situation is getting worse. If the trend is decreasing, it is getting better. Finally, if neither, nothing can be confirmed. All analyses in this report are assigned to one of these three observations. Problems with Trends Trend analyses were largely straightforward and posed few problems. Visual analysis of time series plots showed that the majority of significant trends were ba sed on a large amount of data that indeed demonstrated an obvious tendency. However, seve ral exceptions arose and their handling is addressed in the following sections. “Remaining the Same” – Possibility of Missed Trends The last case scenario in the phrase “getting better, getting worse or remaining the same ” leaves a question as to the identity of the la st category. Note that the last observation— “…remaining the same”—cannot be addressed sta tistically. It is , therefore, considered the alternative case to the situa tion of an increasing or decr easing trend. Because of this “…remaining the same” amounts to a catch-all for all remaining observations (i.e., trends that neither increased nor decreased). Though simple in principle, a clarifica tion should be stated. Within this last category re mains interesting, important, and valuable information—cycles, interesting structure, nonlinear trends, or other phenomena. More problematic, it is likely the analyses conducted here “missed” a number of trends (due to the st rict confidence limit). Increasing Trend (+) Unable to confirm Decreas ing Trend (-) 3 observations for trends: Variable Time 0510152025 -6 -4 -2 0 2 4 6 Time (years)Concentration (ug/L) B. Cycle A. Cycle 0510152025 0 10 20 30 Time (years)Concentration (ug/L) A. Trend B. Trend

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BULLETIN NO. 69 19 However, it is important to state once again that the purpose for this study was neither to find all the trends possible, nor to find the largest number of trends; rather, the purpose was to identify all the trends that could be confidently, statis tically labeled as suc h. Other studies employing greater power (i.e., ability to detect more tr ends) could, and probably should, be conducted. But since this is the first such statewide analysis of water-quality trends, the goal was to minimize the number of false trends—while maximizing the number of true tr ends—in order to get the best picture of where the clearest problems exist. Outliers Statisticians often encounter data that lies outside of an expected range of values. The reasons for this may include data transmission errors, failed laboratory analyses, contaminated samples, and sometimes accurate data record ing unusual situations—causes are not always visible to analysts. This report was no exception. Technically, there are really only two ways of dealing with such data. One is to set arbitrar y guidelines in advance a nd handle the data in accordance. This may include removing outliers that occur above or below a certain accepted range, e.g. adjust the data. The other approach is to include all outliers in the dataset and analyze the data regardless. The rationale is that well-maintained data so metimes records outliers but, with sufficient data, the effects will be minimal. This report chose the latter option and included all data in all analyses—none were discarded. Their presence was accounted for and accommodated in several ways. The first was simply by the choice of analysis. Nonparametric statistics are relatively insensitive to the influence of extreme data points (outliers). A large number of “bad” data points can still influence even a nonparametric analysis. Cross-checking results and examining raw data can assist with this j udgment. In order to compare and check the influence of outlying data, every nonparametric statis tical trend test [the Mann-Kendall (MK) will be di scussed later] result was checked against a linear regression (parametric test) of the same data. Further, both analyses were co nducted with different statistical packages: Minitab (Minitab, 2003) for MK and SPLUS (S-PLUS, 2003) for cross checking regression analyses. Visu al examination of each individual time series was conducted to corroborate the results of the statistical tests; suspicious data sets were re-analyzed. Inspections revealed that in the vast majority of cases, reported statistical trends were composed of time series that showed clear visual trends . Comparison of MK results to linear regressions (though parametric) showed surprising similarit y. Not only did the non-parametric MK results closely match the parametric analyses, but both were surprisingly unaffected by outliers; thus providing strong confirmation that both the data was of high quality and that it gave robust signals. Detection Levels Though the data used in these analyses were the best available in terms of quality assurance, other factors had to be considere d. The analysis of outliers demonstrated that consistency of data handling, laboratory repor ting, and subsequent quality assurance was good. Yet an additional issue surfaced in the plotted time series: the affect of laboratory detection limits. For statistical purposes, if a sample’s concentration was below the laboratory’s method detection limit, it was considered to be the de tection limit. For example, where improvements in

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FLORIDA GEOLOGICAL SURVEY 20 laboratory methodologies over time lowered the mi nimum detection value for several analytes, trend analyses detected significant downward tre nds where no such trend existed. Indeed, a number of time series plots revealed that a nu mber of trends—statisti cally significant by MK tests—were actually the artifact of such “stair step” patterns trending down over time (Figure 9). All data series, therefore, were checked visu ally for such spurious results. Those data series found exhibiting such results were remove d from consideration in the final analyses. These were assigned the designati on “DL” (detection level) in result tables (e.g., “plus-minus” charts which will be discussed later); trends created by detection level artifacts were removed from further analysis. Figure 9. Example of a spurious trend. Detection limit changes can generate the appearance of false tren ds. All time series for all analytes were visually checked for aberant results since visual inspection was necessary to identify artifacts. 2/12/199011/8/19928/5/19955/ 1/19981/25/200110/22/2003 Date 0.00 0.05 0.10 0.15 0.20F (mg/L) Well 1943: Example of Detection Limits

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BULLETIN NO. 69 21 Sparse Data The quantity and consistency of existing data varied widely depending on sampling agency, analyte, and location of springs or wells. Given the amount of data used for the time series studied herein, a distinction should be made concerning how the quantity of data affected its quality . First, all reported analyses had sufficient da ta for time series analysis. Sufficient data constituted a minimum of 10 points for the entire series. Many so ftware packages would not generate statistical results without a minimum set of points—which was often 10 values. At the same time, there is a difference between what constitutes a sufficient amount of data and how that (sufficient) quantity is structured through time. The former issue concerns whether an analysis could be conducted while the latter has implications for the reliability of the interpretation. On one end of the spectrum, some locations only had 10 values, while at the other some had in excess of 100 values. As it tu rns out, considering both springs and wells, the median number of data for the 1991-2003, Sequence A, time frame was 38. Long-term, consistent data collection is an ideal situation for analysis. However, most data sets were between the extremes of a lot or too little. Much of the data used here can be described by the term “sparse data” which we use to mean there are not very many data points in the time sequence but there were a minimum of ten. Often the spring data were collected for some other purpose than for time-series analysis having little structure at all. This results in “messy data.” Messy or disorderly data include s missing values, outliers, transcription errors, or extreme and skewed results. Simply stated, a high proportion of time sequences have varying amounts of missing data. The missing data hinders reliable data interpre tation. One example of “messy data” is nitrate concentrations at Wakulla Spring (Figure 10). An example is as follows. Suppose a large number of data points exist at the beginning of the ti me series, nothing in the middle, and one point at the opposite end of the se ries. Also, suppose a trend is detected. The problem with such a trend is that although is stat istically valid, it may be entirely dependent upon the single point at the one end of the series. If such a trend is labeled valid, then poor judgment was used. The best interpretation for a trend exists when there is an abundance of points sampled consistently for the longest period of time. Time gaps in data series were the most common problem. In a number of cases data collected early in the time series were followed by one or more data colle ction gaps of varying temporal duration. Such trends are dependent upon the connection of two (occasionally more) clusters of data. Though the trends may be valid, they are not ideal; this example underscores the necessity for sampling agencies to implement consistent collection plans over the long term. Though the data can often be used, its utility can be challenged, or c onsidered suspect. The reason is that the value of any individual data poin t is a function of the number and reliability of nearby data points to which it can be compar ed over the long term. Da ta that are sparse, inconsistently collected, or have large time gaps ar e substantially less valuab le than a consistent,

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FLORIDA GEOLOGICAL SURVEY 22 Figure 10. Example of sporadic, unsystematic, and incomplete sampling. Only seven points we re collected in the final eight years of this Wakulla Spring study. Sparse, inconsiste nt sampling after 1994 meant the trend seen here was dependent on relatively few points collected in 2000. Though the trend is statistically valid, this is an excellent illustration of the need for consistent longterm data collection. Ironically, though budget issues are often responsible for gaps in sampling, note that missing data greatly reduces the value of points remaining. Note no data were obtained after 2001 even though Sequence A continued through 2003. well-documented time series. Sparse data collecti on was a significant issue in several notable springs. For example the trend for nitrate at Waku lla Spring for Sequence A included a six-year “gap” (1994-2000) during which th ere was only one sample coll ected. Although th e statistical conclusion that nitrate concentrations at Wakulla were decreasing is valid (to be discussed later), with the lack of data during the 1994-2000 time frame, some may doubt the interpretation of a decreasing trend. Incomplete data sets existed for many analyt es and indicators. Time series for some analytes (e.g., iron) only had a handful of points over the 13 years. For such very small sets, trend analysis was meaningless and these were excluded from analysis. Other analytes had ANALYTES AND INDICATORS A total of 48 chemical constituents and indicators, with a period of record 1991-2003, were analyzed for this study. A list of analyt es and their correspondi ng STORET codes can be found in Appendix F. Data were obtained from several di fferent sources. The state water management districts offered the most info rmation, followed by FDEP and the USGS. Each agency used their respective sa mpling and analysis procedures under whatever gu idelines that were being followed for that part icular period of time. This comp licated the statistical analyses. However, identification of useful data led to a fi eld of 48 different analytes of water quality with

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BULLETIN NO. 69 23 a temporal span of 13 years . Table 3 lists, in alphabetical orde r by column, all of the analytes examined in this study. Table 3. Analyte and Indicator List. Analyte/Indicator Color Depth to Groundwater Total Chloride Dissolved Alkalinity Dissolved P hosphorus Total Dissolved Solids Dissolved Calcium Dissolved Phosphate Total Fluoride Dissolved Chloride Dissolved Sulfate Total Kjeldahl Nitrogen Dissolved Fluoride Dissolved Strontium Total Magnesium Dissolved Iron Enterococci Bacteria Total Nitrate Dissolved Potassium Fecal Coliforms Total Nitrate Nitrite Dissolved Magnesium Mean Daily Flow Total Organic Carbon Dissolved Manganese pH Total Phosphorus Dissolved Sodium Residuals Total Phosphate Dissolved Ammonia Specific Conductance, Field Total Potassium Dissolved Nitrate Specific Conductivity, Lab Total Strontium Dissolved Nitrate, Nitrogen Temperature Total Sulfate Dissolved Nitrate Nitrite Total Al kalinity Turbidity (Hatch Meter) Dissolved Organic Carbon Total Bicarbonate Turbidity, Field Sampling Dissolved Oxygen Total Calcium Water Level (feet relative to mean sea level) Sample Collection and Laboratory Analyses Because many different agencies and laboratories were used to collect and analyze groundwater samples, unwanted variability was pot entially introduced that affected the trend analyses. At a minimum, potential variability was introduced by: (1) different sampling personnel, techniques and equipment, (2) sample tr ansport from the field to the laboratory, (3) environmental and laboratory contamination, (4) concurrent use of several analytical laboratories, and (5) varying me thods of reporting results. For additional information on the analytes, in cluding abbreviations and units for those 27 analytes that had detectable trends, see Table 4 . Spring and well water samples were collected

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FLORIDA GEOLOGICAL SURVEY 24Table 4. Analytes and Indicators Displaying Trends Analyte Abbreviation Unit of Measure Alkalinity Alk mg/L Ammonia/Ammonium NH3 or NH4 mg/L Calcium Ca mg/L Chloride Cl mg/L Discharge or flow – cfs or cubic feet per second (ft3/sec); one cfs = 0.028 cubic meters per second Dissolved Oxygen DO mg/L Fluoride F mg/L Iron Fe µg/L and mg/L Magnesium Mg mg/L Nitrate as N NO3 or NO3 + NO2 mg/L Nitrogen (total) N mg/L Orthophosphate as P PO4 mg/L pH – – Potassium K mg/L Sodium Na mg/L Specific Conductance SC S/cm at 25 ºC Stage – feet above datum Strontium Sr µg/L Sulfate SO4 mg/L Temperature (of water) Temp ºC Total Dissolved Solids TDS mg/L Total Kjeldahl Nitrogen TKN mg/L Total Organic Carbon TOC mg/L Total Phosphorus P mg/L Total Suspended Solids TSS mg/L Turbidity Turb NTU (Current)* JTU (Historic) Water Level/Stage WL(msl) feet above mean level (1988) *JTU and NTU are approximately equivalent, though not identical msl = mean sea level (National Geodetic Vertical Datum, 1988) by several agencies and a private company for th e SRWMD. Regarding sp rings, the agencies include the SRWMD (plus its subcontractor), the SJRWMD, the SWFWMD , and the USGS. For wells, samples were collected by the NWFWMD, the SRWMD and its subcontractor, the

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BULLETIN NO. 69 25 SJRWMD, the SWFWMD, the SFWMD, and the FDEP. In addition, multiple analytical laboratories were used to process the samples. For the 1991-2003 time sequence, spring sampling and analyses faced all of the potential aforementioned problems. During the same time peri od, especially during th e early days of the operation of the TV Network, well monitoring encountered many of the same problems that spring monitoring encountered. The TV Netw ork is operated by the FDEP and by the mid 1990s, the FDEP reduced a considerable portion of unwanted variability by adopting a policy of using a standardized sampling pr otocol, a standardized method of sample transport, a single analytical laboratory, and a standard set of anal ytical methods and reporting protocols. It is hoped that one day, spring monitoring throughout Florida will also adopt similar protocols that will reduce variability. In spite of the potential variability, not all is negative. For all water samples and data used in this report, each corres ponding sampling agency and/or analytical laboratory has an individually-approved quality a ssurance/quality control (QA/QC ) plan on file with FDEP. Regarding QA/QC, the contact for each WMD, FD EP, and the USGS are found in Appendix G. It should be noted that by 2001, in an effort to achieve standardization, the FDEP adopted a recommended method for spring-water quality sampling. An overview of the protocols is found in Scott et al. (2004). The TV Network is managed by the Watershed Monitoring Section (WMS) of the FDEP. It recent ly produced an overview of its well water sampling protocols (Florida Department of Envi ronmental Protection, 2003). Analytes used in this study Multiple agencies collected water-quality samples for th is publication; however one agency may have sampled one analyte, while anot her agency sampled a similar analyte that was closely related to the first. This was quite co mmon for the analytes nitrate, ammonia, phosphate, phosphorus, magnesium, sodium, potassium and chloride. Most often, the difference was between the collection of the dissolved (filtered sa mple) and total (unfiltered sample) form of the analyte. It would be preferable if sufficient data in both the disso lved and total forms of these analytes were available. Unfortunately, it was no t always the case. It was decided to combine the total and dissolved forms becau se of the importance placed on nutrients in order to obtain a time series with a sufficient number of data valu es. We do not recommend this procedure in the future because it would be better to use one or both of the forms in conducting statistical analyses. In the recommendations section (discussed later) we recommend a more consistent set of analytes be used in the future. Neverthele ss, for this study, we occasionally used a combined surrogate form of nitrate, ammonia, phosphate , phosphorus, magnesium, sodium, potassium and chloride. We did this solely for the purpose of obtaining a sufficient amount of data necessary for data analyses. Grouping of Analytes For convenience, and in an effort to better understand groundwater quality trends, the analytes (or indicators) were di vided into several groups. They are: (1) Field, (2) Rock-matrix

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FLORIDA GEOLOGICAL SURVEY 26 or Rock, (3) Saline or Saltwat er, (4) Nutrient, and (5) Other analytes. However, because of occasional chemical complexities, many analytes are grouped into more than one category. Table 5 lists them by group. Note that analytes in the table only refer to those that displayed trends. A detailed description of eac h analyte is found in Appendix F. Table 5. Analyte Groups Field Rock-Matrix (Rock)* Saline or saltwater Nutrient Other Discharge Alk Ca Ca and Mg TSS DO Ca Cl K Turb pH F K N TOC SC Fe Na NH3 and NH4 Temp K SC NO3 or NO3 + NO2 WL(msl) or Stage Mg SO4 PO4 and P PO4 and P TDS SO4 SC WL(msl) or Stage TKN SO4 TOC Sr *Light gray indicates common rock and saline-related indicators while dark gray shows common nutrient analytes. Descriptions of Analyte Groups Each analyte represents a measur e or variable that can be us ed to assist in judging the overall health of FloridaÂ’s groundwat er. Field analytes such as di scharge, water level, and flow describe quantity, but they can also greatly affe ct quality. The rock analytes suggest upconing of water from deep within FloridaÂ’s aquifers. The saline analytes suggest intrusion or upconing of water from the deep portions of our aquife rs, and the nutrient analytes are those that stimulate biological growth or are present as a direct result of biological activity. Field Analytes Field analytes represent a gr ouping for convenience. Measur ements of field analytes were conducted prior to collecting samples for laboratory anal yses. The analytes in this group that were used for trend analyses include: discharge (or flow), dissolved oxygen (DO), pH, specific conductance (SC), water temperature (Tem p), and water level [water level relative to mean sea level (msl) based on the North Am erican Vertical Datu m (NGVD) of 1988)]. Rock-Matrix Analytes Rock-matrix analytes are those indicative of the rocks making up an aquifer. Because of natural rock weathe ring, water that has had a long residence time in an aquifer system has a

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BULLETIN NO. 69 27 greater probability of having a high concentra tion of dissolved rock matrix material. Rock indicators include: alkalinity (Alk), calcium (C a), magnesium (Mg), plus to a lesser extent, fluoride (F), iron (Fe), pH, potassium (K), strontium (Sr), sulfate (SO4), and SC. Since phosphate and phosphorus are often f ound in the mineral fluorapatite , the latter two analytes are also included in the ro ck-matrix group. Saline or Saltwater Analytes Saline analytes are those associ ated with salts within either connate water or seawater. Connate waters are those waters trapped within th e sediments at the time of their deposition. Since the original sediments were deposited in a marine environment, the pore spaces contain very old saltwater. Saline analytes are obvi ously also found in the seawater located along Florida’s coasts. The major difference is the age of water. High c oncentrations of saline analytes are often an indication of horizontal saltwater encroachment. However, they can also be an indication of encroachment of highly mineralized water from th e deeper portion of Florida’s aquifers, below the fresh-water “lens”. The encr oachment can be caused by the depletion of the less dense fresh-water “lens” during a very dr y period (e.g. a drought), or by the upconing of connate water during periods of heavy groundw ater withdrawals. Pumping of groundwater increased during dry periods and th is process exacerbated the appare nt intrusion process. Saline analytes include: calcium, chloride, potassium, sodium (N a), specific conductance, sulfate, and total dissolved solids (TDS). Nutrient Analytes Nutrients represent naturally occurring compounds or elements that are essential for the growth of living organisms. However, if found in high concentratio ns, over-enrichment of nutrients (eutrophicat ion) in a body of surface water can lead to an overgrowth of plant life (including algae) and possibly a loss of dissolved oxygen. For th is report, nutrient analytes include: organic carbon, phosphate, phosphorus, a series of nitrogen related species, and to a lesser extent, Mg, Ca, K, and sulfur in the form of sulfate. The nitrogen related species include nitrogen, ammonia, total kjeldahl nitrogen, nitrate, and nitrite. Other Analytes Analytes in the “other” category do not fit in any of the other four categories. They represent a miscellaneous group. For trend anal yses, the analytes incl uded in this group are suspended solids, and turbidity. DATA The original data were from several sources . The data used for the trends analyses discussed in this document ar e in Appendix H (online).

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FLORIDA GEOLOGICAL SURVEY 28 Data Sources The majority of the water-quality data from the springs were collected and analyzed by the water management districts. The data for wells were obtained from the FDEP Watershed Monitoring Section. Data Verification The analysis of the data was verified severa l times with processes including internal and external reviews in addition to repeat analyses by each author. The internal review consisted of audits performed by two of the authors (N. Dora n and A. White). These audits included handeye verification of every analysis figure for accu racy. Repeat calculatio ns were performed and compared with the first value made using new va lues calculated from the original data. When errors were found, the data were r ecalculated by at least two of the co-authors and then replaced. The external verification was conducted through multiple meetings with WMD staff. During these meetings many of the actual samplers a nd initial compilers of th e data were present. Two rounds of discussion took place; once before this document was comp iled and again as it neared completion. These meetings lasted for several hours and many comments were made on procedures and verification policies. Each concer n was subsequently addressed and is exhibited in the subsequent sectio ns of this document. Data Preparation Preparing the data for analysis included a ddressing the problems of seasonality, missing values, duplicate data, censored data and detect ion limits. The data variation caused by seasonal cycles increases the difficulty of detecting long-te rm trends. This problem can be alleviated by removing the cycles before applying tests or by using tests unaffected by the cycles (Gilbert, 1987). Missing values (i.e., samples that were never collected) cause their own special difficulties for analysis. For example, suppose 12 monthly water samples were scheduled to be collected from a selected well in a given year. Suppose that for a variety of reasons, only 10 were actually collected. Thus, the well had tw o missing values for each indicator sampled. Unless otherwise stated for the statistical analyses , missing values were treated as if they were never collected. For example, if only 10 samples were collected, then descriptive statistics were based on 10, instead of 12 samples. Duplicate data resulted from two samples collected from the same spring or well consecutively. The two samples were then labeled as representing two different sampling events and sent to a laboratory for analyses for the same set of analytes. The purpose of duplicates is to evaluate the internal precision of a laboratory. For statistical analyses, it was decided that the primary sample, collected first in the time sequence, would be used. The second duplicate sample was only used for quality assurance evaluations.

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BULLETIN NO. 69 29 The minimum detection level for analytes from analytical laboratories can cause environmental data to be censored. That is, the distributions are truncated at their lower ends near the laboratory detection level. As stated ear lier, for statistical analys es, all data reported as “Below Detection Level (BDL)” were arbitrarily set at the detection level. In addition, it should be noted that for a given analyte, over the peri od of record, the labora tory detection levels changed, giving multiple detection limits. Time Sequences Data for analyses were segmented into three time sequences: Sequence A (1991-2003), Sequence B (1991-1997), and Sequence C (1998-2003). The first sequence spanned the entire sampling period, January 1, 1991 to December 31, 2003. The two smaller time sequences were used to assist in identifying and evaluating sh orter-term trends (five to six years). Within the time sequences, each analyte needed to have a minimum of 10 data points in order for any statistics to be pe rformed. In addition to the minimu m number of 10 data points, it was arbitrarily decided that for Sequence A at least three data points from Sequence B and at least three data points from Sequence C needed to be present. If Sequence A lacked this additional criterion, then no analys es were performed on the sequen ce. As an example, suppose a spring had 15 data points, 12 in Sequence C and three in Sequence B. An analysis for trend was conducted for Sequence A, and C, but not B. If a spring only has 14 data points, 12 in Segment C and two in Segment B, then no analyses was performed for Sequence A nor Sequence B. However, the sta tistical analysis was conducted for Sequence C. A question arises, are only three data poi nts sufficient to represent the time Sequence B or C within Sequence A? It certainly is not desirable and is an example of “messy” data. This situation was considered to be sufficient for trend analyses because this study represented the first statewide analyses for trends. Fortunate ly, this was not a common situa tion and, hopefully in the future, available data will be less “messy.” Data Used for Analyses and Explanation of Appendices All data presented in this report represent a collaborative effort among the five water management districts, the U.S. Geological Survey and the Florida Geological Survey for spring data, plus Alachua, Palm Beach, Broward, Miami-Dade , Lee, and Collier Counties for well data. This is significant since each sampling agency ha s their own agenda resulting in different reasons for the collection of a particular analyte. Resultant data for both springs and wells can be found in Appendix H (online). The appendix contains the actual concentrations for the analytes measured. The state is broken down into three regions, Northwest, Central, and Sout h Florida. Within each regional folder, the data are placed in their respective WMD. Missing data we re noted with an asterisk. In the folder, the results of the MK analyses along with the corr esponding n (number of data points) and the Sen Slope (SS) for each spring and we ll (to be discussed later) can also be found. The format is similar to that within the data folder. Finally, plus/minus charts (to be discussed later) are also included.

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FLORIDA GEOLOGICAL SURVEY 30 The data in the statistical analysis folder are temporal data. A numerical value of -9999 was included to maintain the order of the spread sheet. A value of -9999 can either mean that data are missing or it can mean th at there are an insufficient number of samples to perform the statistical analyses (procedures to be discussed later). The remaining data were placed in tables. The tables cont ain the following information: (1) the identification (ID) that names the spring (or well), (2) its location in latitude and longitude, (3) the time sequence, (4) the dates fo r which samples were obtained, (5) a p-value for significant increase, (6) a p-value for significant d ecrease, (6) the total number of samples within the sequence, (7) the calculated SSs, and (8) the trend results. With regards to the results, the tables indicate whether there was a significant increase (UP), decrease (DOWN), or no evidence of trend. Throughout this report an upward trend will be designated with either an up arrow ( ) or a plus sign (+). A downward trend will either be designated with a down arrow ( ) or a negative sign (-). INFORMATION GOALS AND DA TA ANALYSIS PROTOCOLS Information Introduction The purpose of data analyses was to document water-quality trends in FloridaÂ’s springs and wells for the period 1991 2003. Prior to evaluation, a list of information goals was developed. The goals were then turned into spec ific questions for which statistical procedures could be used in an attempt to answer them. The questions are listed be low and are followed by a discussion of the statistical procedures used in this report. A more de tailed discussion of all statistical procedures used in th is report can be found in Appendix E.1 (online) and E2 (online). Minitab Release 14 (Minitab, 2003) and S-PLUS 6.2 Professional Edition (S-PLUS, 2003) were used for all analyses. The six questions were: 1. What were the statistical distribu tions for each of the sampled analytes? 2. For Sequence A (the longest time sequence) , for each analyte, and for each spring or well, was seasonality present? 3. For each sequence, for each analyte, and for each spring or well, were linear time series trends present? 4. If trends were present, what were their slopes? 5. For springs or wells with detectable tr ends, were they spatially related? 6. If evidence was found to indicate that the degrading trends were man-induced, what are plausible solu tions and recommendations? Overview of Statistical Analyses Procedures Descriptive Statistics Descriptive statistics were produced for each analyte at each spring and well (station) for the longest time sequence. The descriptions can be found in Appendix I (online). For each

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BULLETIN NO. 69 31 sampled station for Sequence A, the tables list the analyte (or indicator), the measurement unit, the number of samples collected, the number of samples with concentrations below the laboratory detection level (BDL), the minimum value, the first, second and third quartiles, and the maximum value. The first, second and th ird quartiles (Q1, Q2, and Q3) correspond to the 25th, 50th (median), and 75th percentile respectively. An example of the descriptive statistics is presented in Table 6. For a given analyte, the reported minimum concentration value in the table often reflected the minimum detection level reported by the analytical laboratory. Table 6. Example of Descriptive Statistics Table (Sequence A; January, 1991 – December, 2003) Analyte Meas. Unit Num. Samp. Num. BDLs Min Value Q1 Value Median Value Q3 Value Max. Value NO3 mg/L 30 7 0.05 0.09 1.00 2.00 10.30 PO4 mg/L 29 4 0.05 0.10 0.10 0.15 1.30 Kruskal-Wallis, Mann-Whitney, and Wilcoxon Rank Sum Tests Seasonality can be thought of as periodic fluctuations or cycles. As an example, Figure 11 displays monthly water temperatures for an imaginary well during the 1992 calendar year. Not surprisingly the temperature is highest du ring the summer and lowest during the winter months, indicating that for temperatur e there exists a one year cycle. DateTemp (Deg C) 1/1/1993 11/1/1992 9/1/1992 7/1/1992 5/1/1992 3/1/1992 1/1/1992 22.6 22.5 22.4 22.3 22.2 22.1 22.0 21.9 Monthly Water Temperatures(Calendar Year 1992) Figure 11. Monthly water temperatures plotted over the 1992 calendar year for an imaginary well. Cycles are not restricted to calendar years. They can occur over vi rtually any length of time. Figure 12 displays an example of a cycl e longer than one year. In the example, the concentration of an imaginary analyte has a six year cycle or season. Depending on the variable of interest, it may or may not have been influe nced by cycles whose fre quencies are longer than

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FLORIDA GEOLOGICAL SURVEY 32 13 years; Sequence A was 13 years in length (1991–2003). It is difficult to make that determination of the cycle’s in fluence on the analyte. With this in mind, the authors were concerned with the influence of shorter term cycles on Sequence A. Since water samples were collected on a quarterly and mont hly basis while springs were sa mpled either on a quarterly or quasi-quarterly fashion, it was de cided to determine if cycles in those frequencies were present in the data. Figure 12. Example illustration of seasonality with a six-year cycle. For each spring or well for Sequence A, the pr esence of seasonality for each sampled analyte was determined using a Kruskal-Wallis (K W) test (Hollander and Wolfe, 1973; Gilbert, 1987). Quarterly and monthly seas onality tests were conducted be cause stations were generally sampled quarterly and occasionally monthly. It should be noted that m onthly seasonality tests could only be conducted if samples were collected on a monthly or quasi-monthly basis. For the most part, monthly samples were only collected fo r 24 of the 46 wells and only for field analytes. On the other hand, quarterly samples were obtain ed on the remaining wells and quasi-quarterly samples were collected on most of the springs . The quasi-quarterly sampling by the WMDs and the arbitrary seasonal breakdown was as follows : (1) December February, (2) March May, (3) June August, and (4) September November. It should be noted that as we conducted the analyses for trends, we found that , based on the four arbitrary seasons, most analytes did not display significant seasonality. We recognize that in the future, with the acquisition of additional data and with additional trend analyses, a better breakdown may be discovered. Nevertheless, for this analysis exercise, the KW test was used to compare the distribution of two or more populations (seasons) by indirectly comparing their median values during each season as defined by this study. If we had defined only two seasons, the KW test is equivalent to a Mann-Whitney (MW) test (Conover, 1999). Both tests are discusse d in greater detail in A ppendix E. It should also be noted that the results of the MW test are identical to another very similar test; the

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BULLETIN NO. 69 33 Wilcoxon rank sum test (WT) (Conover, 1999). The WT test was occasionally used during this study because some of the statistical software used included the WT test rather than the MW test. Conover (1999) discusses the WT test in detail. Resu lts of the WT test are identical with those of the MW test. Consider a situation in which one wants to determine if two populations have the same statistical distributions for a gi ven season and samples are theref ore obtained for each season. For the MW test, the null hypothesis is that the median of the tw o populations are the same while the alternate hypothesis is that they are not. The two samples are combined into a single ordered sample from smallest to highest . Each observation is then a ssigned a rank with out regard to which sample it originally came from. The sum of the ranks assigned to those values from one of the populations is then generated. If the rank sum of the corres ponding population is very small (or very large), there is an indication th at the values from one population tends to be smaller (or larger) than the values from the other. If so, the di stributions of the two populations are not equal. If the rank sums of the two populations are not equa l, neither are their medians. Returning to the KW test, it compares the di stribution of more than two populations (e.g., seasons). For this report, each test was tw o-sided. The null hypothesi s is that the median concentration of an analyte sampled in any se ason is equal to the median of the remaining seasons. The alternate hypothesis is that the median concentrati on for at least one season is not equal to the others. Under the latter scenario, it is assumed that seasonality does exist. For quarterly data, tests were conduc ted assuming that each quarter was a season. For monthly data sets, tests were conducted assuming that each m onth was a season. The level of significance was preset to = 0.05. For example, 38 temperature samples were collected at Weeki Wachee Main Spring for time Sequence A. However, data were not avai lable for the period 1991 through most of 1993. Data were available for the 1993-2001 time frame. All samples were sampled on a quarterly basis; nine in each of seasons (1), (2), and (4), plus ten in season (3). The KW test compared the median values for each of the four seasons and, based on the test, it was concluded that the median of at least one season did not equal the other medians. Thus, it was concluded that quarterly seasonality does exist for the spring with respect to temperature. Since monthly data were not available, no conclusion could be made regarding monthly seas onality. Results for these analyses are found in Appendix J (online). Deseasonalized Data If seasonal cycles were present in the data, the data were deseasonalized using a method presented by Intelligent Decision Technologies ( 1998). Although most measurements of central tendency used in this report pertain to the me dians, means were used (Sen, 1968) in the deseasonalization transformation equation (Intelligent Decisions Technologies, 1998). The Sen method subtracts the mean of the correspondi ng season from each datum and then adds the overall average (mean) of the se quence back to the or iginal datum. For example, suppose 10 years of quarterly data were collected at a site for chloride. Suppose the overall mean of the data for the 10 year period was 1.0 unit while the mean of the winter quarter was 0.2 mg/L. Now

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FLORIDA GEOLOGICAL SURVEY 34 suppose a concentration for a particular winter quarter sample was 1.2 mg/L. In mg/L, the corresponding transformed, des easonalized datum becomes: x = (original) – [seasonal (w inter) mean] + (overall mean) = (transformed x ) x = 1.2 mg/L – 0.2 mg/L + 1.0 mg/L = 2.0 mg/L. Mann-Kendall Test Gilbert (1987) stated that th e Mann-Kendall (MK) test can be viewed as a nonparametric test for zero slope of th e linear regression of time-ordered da ta versus time. Given that it is a nonparametric technique, it does not depend on an assumption of a particular underlying distribution. The test identifies correlations in data through temporally ranking the data and then determining the number of times the concentratio n goes up or down relative to the previous time step. It only uses the relative magnitudes of th e data rather than their measured values. Data reported as trace or below the mini mum detection level (MDL) were used by assigning a common value that was smaller than, or equal to, the smallest measured value in the data set. For this report, below detection leve l (BDL), was assigned an arbitrary value equal to the detection le vel (DL). Once the seasonality tests were completed (results found in Appendix J), each analyte was tested for a linear tr end using the MK test ( = 0.05) for each time sequence. A macro program was used for the analysis while work ing within Minitab [Appendix E.1 (Online)]. However, if data were insufficient (n < 10), the MK test was not conducted. For this exercise, we always used a one-sided test. The reason was that we had a preconceived idea as to whether or not a downward (or upward) trend was an i ndication that conditions were getting worse (or better). The results of the MK tests are found in Appendix K (online). Seasonal Kendall Test A common test used in the analyses of time series is the Seasonal Kendall (SK) test (Gilbert, 1987). It is an adoption of the MK test, and can be used if there is seasonality in the data. The SK test is the techni que of choice. Unfortunately, it has a set of requirements that were not obtainable. Miller et al. (2004) mentioned that the test requires that the percentage of censored data (e.g. data reported as BDL) be no more than about five percent. In addition, Miller stated that there should only be one censo ring level. This latter requirement was not obtainable because our data were obtained from ag encies operating independently of each other. The agencies used multiple laboratories with multiple detection levels, which amounted to multiple censoring levels. Thus, the SK test was not used in this investigation. In the future, as better and more consistent data are obtaine d, the SK test is th e recommended test. Sen Slope If a trend was found to exist for either nonseasonal or seasonal data, its corresponding slope was determined using a Sen Slope (SS) estimator (Sen, 1968; and Gilbert, 1987). The estimator measured the median difference betw een successive concentr ation observations over

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BULLETIN NO. 69 35 the time series. The SS was used only to measure the magnitude of the slope . It was not used as a hypothesis test. Results are f ound in Appendix K (online). Sign Test For each analyte exhibiting a trend, a map showing the location of the corresponding station was created. In additi on to statistical evaluations, visual estimates were made as to whether clusters of corresponding up ward or downward trends existe d. Associations with depth, land use, and other relationships were evaluated. The last statistical proc edure used was the sign test (Sullivan, 2004). The sign test is a relatively simple procedur e to conduct. It was used to determine if a significant number of stations demonstrated upward or downward trends over a geographical region. Note that on e spring in the SWFWMD was not used in the analyses. The reason will be disc ussed later. As an example, suppose during Sequence A, 29 of the 57 springs displayed an upward trend for nitrate. Can it be conc luded that there exists an upward statewide trend? What if 40 (or 45) of the springs demonstrated upward trends? If one thinks of the causes of trends in individual stations as be ing random processes, we could expect about half of the springs to have upward trends, while about half should have downward trends. On the other hand, if a large proportion of the springs had upward trends, we might be suspicious that one or more phenomena were affecting springs and causing the upward trends over a region. Finally, if an extremely large proportion of the springs demons trated upward trends, we would become even more confident that the phenomena were aff ecting the upward concen trations over a region. For the sign test, one assigns a (+) value if there is and an upward trend and a (-) value if there is a downward trend. Sulliv an (2004) stated that zeros add not hing to the test and therefore should be eliminated from further analysis. Th us, all springs demonstrating no trend were assigned a value of zero (0) and were eliminated from further analyses . The test simply compares the proportion of + values to the – values. For this exercise, was preset to 0.05 for the level of significance for these evaluations. Caveats and Assumptions It should be noted that this study was not set up as a designed experiment. We took existing data and attempted to evaluate them. As a consequence, there were many less-thanperfect situations that we needed to address in order to conduct the statistical analyses related to this project. Whenever one takes existing data which were originally collected with a variety of goals in mind and attempts to ev aluate them with a new set of objectives, problems should be expected. For example, R.A Fisher, a sta tistician sometimes referred to as the “ Father of Modern Statistics ” (Sullivan, 2004), once stated, “To call in the statistic ian after the experiment is done may be no more than asking him to pe rform a postmortem examination: he may be able to say what the experiment died of.” This quote is appropriate for our study. We faced many unpleasant situations with rega rd to the data analyses. One of the major sources of problems pertai ned to the assumptions of the statistical procedures [see Appendix E (online)]. Gene rally these tests assumptions are: (1) the

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FLORIDA GEOLOGICAL SURVEY 36 measurements are mutually independent, (2) th e observations are random, (3) the populations are continuous, and (4) the scales or measurement ar e at least ordinal. For the sign test, the assumptions are slightly differen t: (1) the stations are mutually independent, (2) the measurement scale is at least ordinal, and (3) if the probable outcome of a sign is (+) or (-), for one station, the same is true for all other stations. With the exception of the independenc e issue, the assumptions were valid. The issue of dependency will be addressed during the discussion of the results of the study. RESULTS The trend results of every spring and well for each analyte can be found in Appendix K. What follows is a set of examples from selected springs and wells. Our purpose is to give the reader a generalized idea about the behavior of analytes duri ng the study period. Although some discussion regarding the causes of trends at an individual spring will be discussed, the emphasis of this report is on regional and statewide trends . A discussion regarding the possible sources of the analytes and the most probably causes of trends can be found in Upchurch (1992) and Appendix B2. The trend results are divided in to both springs and wells by water management district. There were no springs analyzed in the SFWMD. Thus springs were geographically divided into the NWFWMD, SR WMD, SJRWMD, and SWFWMD. A note is needed regarding the relationship between time-series figures and Sequences. If sufficient data were available, time series analyses were generated for each Seque nces A, B, and C. However, if data were missing for the front or back end of the Sequence, the corresponding figures still cover the entire sequence. As an example, the first series di scussed is for magnesium in Wakulla Spring during Sequence A (1991-2003). Unfortunately, no data exis ts for the last two years of the sequence. Nevertheless, the figure displays th e entire sequence. This is true for all time series discussed. Springs Northwest Florida Water Management District In the NWFWMD, only Wakulla Spring (Figure 13) had sufficient data for analyses for this study. Wakulla was sampled through a piece of tubing placed into a major conduit of the spring. Thus, the samples are considered spring-w ater samples. However, for years, the FDEP has, for administrative purposes, considered the tubing to be a well (Well 67 in the Temporal Variability Network). Since FDEP considers the station to be a we ll and the fact that the tubing taps a spring vent, the station for this report was analyzed both as a spring and a well. Stage data were collected at the spring vent, and stag e was used in lieu of water levels. Rock and Saline Analytes , Nutrients, and Flow Rock-matrix analytes included cations such as calcium and magnesium. Wakulla Spring shows an increase in dissolv ed magnesium over time Seque nce A (1991-2003). Increases in magnesium and conductivity are illustrated in Figure 14. The time series for magnesium at Wakulla, like many analytes, showed inconsistent sampling over the period of record. In this case the time period from 1994 to 2000 contained only one point. For the given data, the MK

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BULLETIN NO. 69 37 Figure 13. Location of Wakulla Spring within the NWFWMD. test confirmed an increasing tr end (p < 0.05). For almost every time-series figure, the median value of the second half of the sequence was compared to median of the first half, using the Wilcoxon rank sum test (WT). This enabled us to not only determine the slope of the trend, but to also better evaluate magnitude of change during the time series. There was a significant change over the period of record (p < 0.05). Whet her by analysis of trends, or comparison of two halves of the time sequence, the latter half of the st udy revealed elevated values of dissolved magnesium. The missing data from the intervening years in the magnesium time series (Figure 14, top) appear to be accounted for in the time series for specific condu ctance (SC) (Figure 14, bottom). Wakulla Spring showed a clear increase in SC over time. The probable causes for the increases in magnesium and SC, along with the decrease in flow, will be discussed later on a districtwide and statew ide perspective. Figure 15 (top) displays a trend for nitrate-ni trite concentrations in Wakulla Spring for the 1991-2003 time frame. The time series show s noticeable data gaps from 1995 to 2000 and again during 2001-2003. In the Wakulla Basin, Chelet te et al. (2002) indi cated that there are several significant sources of nutri ents. These include effluent from a large spray field, fertilizer application, and numerous onsite waste disposal treatment sites (OSTDS) within the basin, and up-gradient of the spring. Fortunately, it appears, since 1991, the amount of nitrate has significantly decreased. Nitr ate in the form of dissolved nitr ate-nitrite declined (Figure 15, top).

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FLORIDA GEOLOGICAL SURVEY 38 Figure 14. Increasing rock analyt es at Wakulla Spring. Magnesium (top) and specific conductance (SC) (bottom) have upward trends (p < 0.05). Te sts include MK for time series trends, (WT) on sequences B and C (first and second half of study), plus SS calculations on the rates of changes.

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BULLETIN NO. 69 39 Figure 15 . Decreasing nitrates and water levels at Wakulla Spring. Dissolved nitrate (top) and water levels (bottom) had significant trends. Tests (p = 0.05) included MK and WT. WT compare medians of the first and second halves of the study. (1.0 m = 3.3 ft)

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FLORIDA GEOLOGICAL SURVEY 40 MK and WT tests indicate that whether by trend analysis or comparison of the first and second half of the time sequences, concentrations of ni trogen decreased. Loper et al. (2005) suggested that the decreasing nitrate concentr ations were due to lowered con centrations of effluent from a large spray field located within 16 km (10 mi) of the spring. Figure 15 (bottom) illustrates a significant drop in stage level . Suwannee River Water Ma nagement District Figure 16 displays the locations of the 15 sp rings located in the Suwannee River Water Management District (SRWMD) used in this report. The spring names and the abbreviations are found in Table 7. Figure 16. Location of springs within the SRWMD.

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BULLETIN NO. 69 41 Table 7. Suwannee River Water Ma nagement District Spring Names and Abbreviations. Spring Abbreviation Spring Abbreviation Alapaha Rise ALR Poe Spring POE Gilchrist Blue Spring GIL Blue Ruth/Little Sulfur Springs RLS Fanning Spring FAN Rock Bluff Spring RKB Hart Spring HAR Royal Spring ROY Hornsby Spring HOR Suwannee Blue Spring SBL Lafayette Blue Spring LBS Telford Spring TEL Little River Spring LRS Troy Spring TRY Manatee Spring MAN Many of the springs are located along the Su wannee River, along a se ction of the river which is roughly perpendicular to the coast, at least in its lower stretch. Numerous trends were noted along an approximate south to north, or lower to upper, river direction. (Specific results are found in Appendix K). Rock-Matrix and Saline Analytes Alkalinity, calcium, magnesium, sodium and specific conductance in creased strongly in the SRWMD over Sequence A. Increases were partic ularly strong in the latter half of the study (Sequence C). Increasing trends were dominant for several analytes. Magnesium and sodium had significant increases in eight of 14 springs with no decreases. Calcium increased in nine springs. Examples of increases in the rock indicators are shown in Fi gures 17-20. Figures 17 and 18 illustrate trends in calcium for four springs over Sequence A while Figures 19 and 20 demonstrate patterns for magnesium for four springs over Sequence A or C, depending on the spring. Note that for many of the time-series figures that compared two stations, the vertical scales do not coincide. By keep ing the vertical scales constant , occasionally the variability of one graph became so small that you could not see it . In the end, we decide d it was better to use inconsistent vertical and to em phasize variability over time. Changes in calcium in springs for the lower Suwannee River are similar to changes in springs farther north. Fanning Spring (FAN) and G ilchrist Blue Spring (GIL Blue) illustrate two of the nine springs that exhibited and increase in calcium (Figure 17). In addition to calcium, FAN showed significant increases in all rock-mat rix and saline indicators including alkalinity, chloride, potassium, magnesium, sodium, and speci fic conductance. The time series plot in Figure 17 shows a gradual increase in calcium from 60 mg/L in 1995 to approximately 80 mg/L in 2003; the gradual increase had a low varian ce around the best fit line. When data for sequences B and C were compared, Sequence C da ta had clearly higher medians (WT test pvalue, <0.0001, illustrated by box plots in inset fi gure in bottom corner). Like FAN, calcium concentrations in GIL Blue increased. The in itial concentration was about 50 mg/L and ended with 65 mg/L; both springs increased in concentr ation by approximately 20 mg/L. GIL Blue also had many other analytes with upw ard trends that mirrored FAN: alkalinity, chloride, magnesium, sodium, and specific conductance. Springs farther north (Figure 18) had similar looking trends to those springs located farther sout h (Figure 17), although the overall tr ends in other analytes were different. Suwannee Blue Spring (SBL) and Troy Spring (TRY) together ha d increases in only

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FLORIDA GEOLOGICAL SURVEY 42 Figure 17. Increasing rock analytes at Fanning and Gilchrist Blue Springs . Fanning (top) and Gilchrist Blue Springs (bottom) had significant increases in calcium. Tests (p < 0.05) included MK for for trend, WT on Sequences B and C, plus SS calculations on the rate of change. Beginning and ending sampling dates for the two springs are not the same. B C MK p-value =0.0005 SS = 0.2694 WT p-value =0.0563 nA = 8 nB = 33 12 40 45 50 55 60 65 1993199419951996199719981999200020012002 Date 40 45 50 55 60 65T-Ca (mg/L) Gilchrist Blue Spring Time Sequence A (1991-2003)MK p-value =0.0005 nA= 10 nB = 40 WT p-value <0.0001 SS =0.2694 1/1/19955/22/199710/11/19993/1/20027/21/2004 Date 0 20 40 60 80T-Ca (mg/L) Fanning Springs Time Sequence A (1991-2003) 12 0 20 40 60 80 B C

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BULLETIN NO. 69 43 Figure 18. Increasing rock analytes at Suwannee Blue and Troy Springs. Suwannee Blue (top) and Troy Spring (bottom) had significant increases in calcium. Tests (p < 0.05) included MK for trend, WT on Sequences B and C, plus SS calculations on the rate of change. Beginning and ending sampling dates for the two springs are not the same. 12 40 50 60 70 1 2 B C MK p-value <0.0001 SS = 0.2565 WT p-value <0.0001 nA = 23 nB = 24 4/1/199712/4/19988/8/20004/12/200212/16/2003 Date 40 50 60 70T-Ca (mg/L) Suwannee Blue Spring Time Sequence A (1991-2003) 11/8/19928/5/19955/1/19981/25/200110/22/2003 Date 30 40 50 60 70T-Ca (mg/L) Troy Spring Time Sequence A (1991-2003)MK p-value <0.0001 SS = 0.1782 WT p-value =0.0006 nA = 18 nB = 42 12 30 40 50 60 70

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FLORIDA GEOLOGICAL SURVEY 44 Figure 19. Increasing rock analytes at Manatee and Hart Springs. Manatee (top) and Hart Springs (bottom) had significant increases in magnesium. Test s (p < 0.05) included MK for trend, WT on the first (1) half and th e second (2) half of both time series. Beginning and ending sampling date for springs are not the same. MK p-value =0.0017 SS = 0.066667 WT p-value =0.006 n1 = 9 n2 = 9 5/1/19964/12/19983/24/20003/5/20022/15/2004 Date 3.5 4.0 4.5 5.0 5.5 6.0T-Mg (mg/L) Hart Springs Time Sequence C (1998-2003) 12 4.0 4.5 5.0 5.5 6.0 A B 6/1/199510/1/19972/2/20006/5/200210/6/2004 Date 4 5 6 7 8T-Mg (mg/L) Manatee Spring Time Sequence A (1991-2003)MK p-value <0.0001 SS = 0.0351 WT p-value <0.0001 n1 = 22 n2 = 22 12 0 2 4 6 B C

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BULLETIN NO. 69 45 Figure 20. Increasing rock analytes at Poe and Lafayette Blue Springs. Poe (top) and Lafayette Blue Spring (bottom) had significant increases in magnesium. Tests (p < 0.05) included MK for trend, WT on the first and second half of both series, and SS calculation on rate of change. Beginning and ending sampling dates for the springs are not the same. 6/26/19974/2/19991/7/200110/15/20027/22/2004 Date 2 4 6 8 10T-Mg (mg/L) Poe Spring Time Sequence C (1998-2003) 8/11/19959/11/199710/13/199911/13/200112/16/2003 Date 8 10 12 14 16T-Mg(mg/L) Lafayette Blue Spring Time Sequence A (1991-2003) 1 2 MK p-value <0.0001 SS = 0.0745 WT p-value =0.0082 n1=22 n2=22 12 8 10 12 14 16 1 2 12 4 5 6 7 8 9 10 MK p-value <0.0001 SS = 0.0830 WT p-value <0.0001 n1=22 n2=22

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FLORIDA GEOLOGICAL SURVEY 46 calcium, magnesium and sodium. Unlike FAN and GIL Blue, SBL and TRY exhibited no trends in alkalinity, chloride, potassium , or specific conductance. Toward the south, Manatee (MAN) and Hart (HAR) (Figure 19) began the time series with approximately four mg/L of magnesium; by the conclusion of th e series, they were at six to seven mg/L. Further north, Poe Spring (Poe) (Fi gure 20) began at about four mg/L in 1998 and rose to about 10 mg/L in late 2002. Lafayette Blue Springs (LBS) (Figure 20)( began at about eight mg/L in 1998 and rose to about 14 mg/L in 2001. Flow The SRWMD consistently collected flow or di scharge data at specific spring vents during the same day that they collected water sample s from their springs. However, the SRWMD did not begin collecting discharge data until the 1997-1998 time frame. During Sequence C, for the SRWMD, flow ra tes decreased significa ntly in 10 of 14 springs. There was not an increase in flow ra te in any of the spri ngs during the same time sequence. In addition, the degree of decrease in flow was sometimes severe. Figures 21-24 illustrate the trends for eight springs starting at the lower end of the Suwannee River and moving inland and northward. Springs at the lowest end of the Suwa nnee River included Fanning (FAN) and Hart (HAR) Springs (Figure 21). Both springs show substa ntial drops in flow levels. By the end of the period of record, flow was reduced to approximately half the levels seen at the beginning of the time series. FANÂ’s highest recorded flows were near 120 cubic feet per second (cfs), but ended near 50 cfs. HARÂ’s highest record ed flow was approximately 90 cfs and fell to near 40 cfs at the end fo the time series. Upstream from these springs are Rock Bluff (RKB) on the Suwannee and Hornsby (HOR) Springs on the Santa Fe River (Figure 22). Both displayed even sharper declines in flow. Rock Bluff went from a high of 50 cfs to under 20; flow was reduced to zero cfs briefly in 2001. Hornsby showed an even stronge r decline: over 200 cfs was m easured in 1998 and the flow reduced to zero cfs during a period starting in early 2000. This was followed by a small recovery of flow rate in 2003. Poe Spring, on the Santa Fe River, and Litt le River Sulfur Spring (LRS) on the middle Suwannee region had strong declines in flow rate (F igure 23). Poe Spring recorded discharges of 60 to 80 cfs near the beginning of the time series but declined to near 20 cfs by the end. LRS began the time series with a flow rate near 90 cfs and ended near 20. D ecline in flow at LRS closely followed a regression line fit to the date (Figure 23, bottom). Troy (TRY) and Telford (TEL) Springs both ha d downward trends in flow. Though flow at Troy was approximately three times higher than Telford (Figure 24) there was a slight increase in flow in mid-1998 followed by a decrease for both springs in early 2000, and then another slight increase in flow occurred in late 2001. Overall, both springs seem to show that flow was reduced by at least half, with LR S indicating a reduction in flow by a third at the end of the time series.

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BULLETIN NO. 69 47 Figure 21. Decreasing flow at Fanning and Hart Springs. Between 1998 and 2001 Fanning (top) and Hart Springs (bottom) had significant decreases in flow. Tests (p < 0.05) in cluded MK for trend, WT, plus an SS calculation on rate of change. Ov er the period of record, flow at both springs was re duced significantly. Beginning and ending sampling dates are not the same. [One cfs equals 0.028 cubic meters per second (cms).] 6/12/19965/13/19984/12/20003/13/20022/11/2004 0 20 40 60 80Flow (cfs) Hart Springs Time Sequence C (1998-2003)MK p-value <0.0001 SS =-3.2411 WT p-value =0.0012 n1=9 n2=9 12 0 20 40 60 80 1 2 1/1/19975/10/19989/16/19991/22/20016/1/2002 Date 20 40 60 80 100 120Flow (cfs) Fanning Springs Time Sequence C (1991-2003)MK p-value <0.0001 SS =0.2773 WT p-value =0.0002 n1 =11 n2 = 11 Fanning Springs Time Sequence C (1998-2003) Hart Springs Time Sequence C (1998-2003)

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FLORIDA GEOLOGICAL SURVEY 48 Figure 22. Decreasing flow at Rock Bluff and Hornsby Springs. Rock Bluff (top) and Hornsby Springs (bottom) had significant decreases in flow. Tests (p < 0.05) included MK for trend, WT, plus an SS calculation. For both Rock Bluff and Horn sby, flow reduced dramatically. Hornsby Springs flow s topped for a period after late 2000. Beginning and ending sampling dates are not the same. (One cfs = 0.028 cms) 1/1/199710/2/19987/2/20004/2/20021/1/2004 Date 0 10 20 30 40 50Flow (cfs) Rock Bluff Springs Time Sequence C (1998-2003)MK p-value <0.0001 SS =-1.0039 WT p-value =0.0001 n1 =14 n2 =14 12 0 10 20 30 40 50 1 2 1/1/199711/5/19989/8/20007/13/20025/16/2004 Date 0 100 200 300Flow (cfs) Hornsby Spring Time Sequence A (1991-2003) 12 0 100 200 300 MK p-value =0.0003 SS=-3.4692 WT p-value =0.0006 n1= 17 n2 = 17 1 2 Rock Bluff Springs Time Sequence C (1998-2003) Hornsby Spring Time Sequence C (1998-2003)

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BULLETIN NO. 69 49 Figure 23. Decreasing flow at Po e and Little River Springs. Poe (top) and Little River Springs (botto m) had significant decreases in flow. Tests (p < 0.05) include d MK for trend, WT, plus an SS calculation on rate of change. For both Poe and Little River flow reduced to about one third by the end of the series. Beginning and ending sampling dates are not the same. (One cfs = 0.028 cms) Little River Spring Sequence A (19912003) Poe Spring Sequence A (19912003)

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FLORIDA GEOLOGICAL SURVEY 50 Figure 24. Decreasing flow at Troy and Telford Springs . Troy (top) and Telford Springs (bottom) had significant decreases in flow. Tests (p < 0.05) included MK for trend, WT, plus an SS calculation on rate of change. Over the period of record, flow at both Troy and Telford was reduced by half. Beginning and e nding sampling dates are not the same. (One cfs = 0.028 cms) 1/1/19978/9/19983/17/200010/23/20016/1/2003 Date 50 90 130 170Flow (cfs) Troy Spring Time Sequence A (1991-2003)MK p-value <0.0001 SS=0.1782 WT p-value =0.0221 n1 = 13 n2 =13 12 50 70 90 110 130 150 170 B C 1/1/19978/1/19983/1/20009/30/20015/1/2003 Date 10 20 30 40 50Flow (cfs) Telford Spring Time Sequence A (1991-2003)MK p-value <0.0001 WT p-value =0.1547 SS =-0.6674 n1=15 n2=15 12 10 20 30 40 50 B C

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BULLETIN NO. 69 51 Nutrient Analytes Nutrients in the SRWMD had more complex patterns than the patterns of either the salinity indicators or flow. While some nutrient tre nds were very strong, others were not as clear. Of the 15 springs in the SRWMD, TKN increased significantly in nine springs (with no decreasing trends). Nitrate appeared to decrea se (downward trend in six springs, while it increased in three springs). At the same time, other nutrients—phosphorus and phosphate specifically—appeared to increase. For phosphorus, there were five springs with increasing trends and only one spring indica ting a decrease; for phosphate th ere were four springs with increasing trends and only one sp ring with a decreasing trend. The FDEP has a maximum nitrate standard of 10 mg/L for groundwater and Class I surface water before considering th e water impaired. Both water standards are directed toward maintaining drinking water quality (Florida De partment of Environmen tal Protection, 1994). Currently, there is not a standard that is directed toward changes and concentrations of biota in surface water. However, FDEP has established a non-legal threshold for nitrate and phosphorus for surface water (Florida Department of Environmental Protection, 2004) . The thresholds were based on a statewide evaluation of chlorophyll con centrations in lakes. The groundwater-surface water relational assessment (SRA) limit is 0.45 mg/L for nitrate. Groundwater nitrate concentrations exceeding the 0.45 mg /L limit suggest that there is a potential for adverse affects on aquatic organisms in the spring runs. Technically , the threshold level a pplies only to surface water and there is a need to es tablish a groundwater to surface water interaction for the threshold to be relevant. Since springs represent an in teraction between groundwater and surface water, we used the threshold level for comparative purposes. Figures 25 and 26 represent examples of changes in nutrients in springs of the SRWMD. Figure 25 is an example of a decreasing nitrate trend. Nitrate signif icantly decreased from 1998-2003 fo r Poe Spring. For comparative purposes the SRA was chosen as a fixed reference and is the gray line in Figure 25. Poe Spring exceeded the SRA recommendations prior to 1999, but then declined to levels below the SRA. Possible reasons for the decline in nitrate in th e Suwannee Basin will be discussed later. While nitrate often decreased in the SRWM D, TKN rose significan tly. Phosphorus also exhibited some increasing concentrations. To tal phosphorus at Poe Spring (Figure 26) almost doubled from 1999 to 2003. Phosphorus and phosphate both increased at several springs. An even greater number of upward trends, however, we re seen for TKN. Figure 26 (bottom) shows an increase in TKN at Lafayette Blue Spring ov er the study period. The plot also illustrates some of the differences between nutrient and sali ne trends. While saline and rock-matrix analyte plots give evidence of clear increases, trend lin es for nutrient plots were sometimes less well defined and potentially not as strong. Figure 26 shows a sign ificant upward trend for total phosphorus (MK test, p < 0.05) though the p-valu e of 0.0443 does not indicate such a strong increasing trend; data for the first and second ha lf of the time sequen ce were not significantly different (WT p-value = 0.3633). The potential cau ses of nutrient and ot her trends will be discussed later.

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FLORIDA GEOLOGICAL SURVEY 52 Figure 25. Decreasing nitrates at Poe Spring. The horizontal line represents The FDEPÂ’s SRA limit for total nitrat e (0.45 mg/L). Levels exceeded recommended SRA limit prior to late 1999 but since then were significantly lower. 7/1/19974/1/19981/1/199910/ 1/19997/1/20004/1/20011/ 1/200210/1/20027/1/2003 Date 0.0 0.4 0.8 1.2T-NO3[N] (mg/L) Poe Spring Time Sequence C (1998-2003)SRA Value = 0.45 mg/L MK p-value <0.0001 SS =-0.0090 WT p-value <0.0001 n1= 22 n2 = 23 12 0.0 0.4 0.8 1.2 1 2

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BULLETIN NO. 69 53 Figure 26. Increasing nutrient analytes at Poe and Lafayette Blue Springs. Poe (top) and Lafayette Blue (bottom) illustrate two increasing nutrients in the SRWMD: one for phosphorus and the other for TKN. Poe shows a clear increase in phosphorus while TKN at Lafayette Blue illustrates one of the many increasing TKN trends in SRWMD springs. Beginning and ending sampling dates for these springs are not the same. 1/1/19956/18/199712/5/19995/22/200211/7/2004 0.0 0.1 0.2 0.3 0.4TKN (mg/L) Lafayette Blue Spring Time Sequence A (1991-2003) 12 0.0 0.1 0.2 0.3 0.4 MK p-value = 0.0443 SS = 0.0012 WT p-value = 0.3633 nB = 6 nC = 41 B C 5/1/19971/30/199910/30/20007/31/20025/1/2004 0.04 0.06 0.08 0.10 0.12 0.14T-P (mg/L) Poe Spring Time Sequence C (1998-2003) 12 0.04 0.06 0.08 0.10 0.12 0.14 MK p-value <0.0001 SS = 0.0007 WT p-value = 0.0001 n1= 22 n2 = 23 1 2

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FLORIDA GEOLOGICAL SURVEY 54 St. Johns River Water Management District The springs located in the St. Johns River Water Management District (SJRWMD) and used in this report are found in Figure 27. Spring names and abbrev iations are found in Table 8. Figure 27. Location of Springs within the SJRWMD.

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BULLETIN NO. 69 55 Table 8. St. Johns River Water Management District Spring Names and Abbreviations Spring Abbreviation Spring Abbreviation Alexander Spring Alexander Salt Springs Salt Apopka Spring Apopka Sa nlando Springs Sanlando Fern Hammock Springs Fern Silver Glen Springs Silver G Juniper Springs Juniper Starbuck Spring Starbuck Miami Spring Miami Sweetwater Spring Sweetwater Palm Spring Palm Volusia Blue Spring Vol Blue Ponce De Leon Spring PDL Wekiwa Spring Wekiwa Rock Spring Rock The SJRWMD only had a few trends in co mparison to the other WMDs. Calcium, strontium, fluoride, and pH increased in a si gnificant number of spri ngs over time Sequence A, while phosphate levels decreased. With respec t to individual springs , Miami, Palm, Sanlando, and Wekiwa Springs had at least eight analytes with increasing trends over Sequence A, while Volusia Blue Spring (Vol Blue) an d Sweetwater Spring decreased in at least eight analytes over the same time sequence. Alexander and Silver Gl en (Silver G) Springs each had seven or fewer analytes showing any trend (positive or negati ve). Sequence B had no districtwide trends. During Sequence C fluoride and pH increased in a large number of springs while flow decreased at many locations. Rock-Matrix and Saline Analytes Increasing trends were associat ed with rock-matrix analytes. Strontium, calcium, pH and fluoride increased over Sequence A. Nine springs had significant increases in calcium and pH while one spring had a decreasing trend for thes es analytes. Both fluoride and strontium increased in 10 springs and decr eased in one. Within Sequence A, only Sequence C showed trends for fluoride, pH and flow. Thus, majo r changes for the SJRWMD , like other districts, occurred during 1998 to 2003. Figures 28-30 depict increases in rock-matrix analytes for three springs in Seminole and Orange Counties. Alkalinity an d strontium suggest changing ch emistries. Both analytes increased in Palm, Sanlando, a nd Wekiwa Springs. All plots s how trends closely fitting an increasing best-fit line. Starting at about 116 mg/L for alkalinity, Palm Springs increases to about 126 mg/L. Sanlando Springs begins at about 130 mg /L and increases to approximately 150 mg/L. Strontium at Sanlando Springs began around 60 g/L and ended over 90 with little variation in the upward trend. Wekiwa Spring st arted at a higher level (near 100 g/L) and ended the time series at about 140 g/L. Wekiwa Spring is also unique in showing an a pparently quick increase in concentration between 1993 a nd 1995. Palm Springs differed from the other two springs in having strontium concentrations at the start of the study three to four times higher than the other two springs.

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FLORIDA GEOLOGICAL SURVEY 56 Figure 28. Increasing rock analytes at Palm Springs. Alkalinity (top) and st rontium (bottom) increased signi ficantly over Sequence A. Tests (p < 0.05) included MK for trend, WT on sequences B and C, plus an SS calculation. Beginning and ending dates for the springs were not the same.

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BULLETIN NO. 69 57 Figure 29. Increasing rock analytes at Sanlando Springs. Alkalinity (top) and s trontium (bottom) increased significantly over Sequence A. Tests (p < 0.05) included MK for trend, WT on sequences B and C, plus an SS calculation on rate of change. Beginning and ending sampling dates for these springs were not the same.

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FLORIDA GEOLOGICAL SURVEY 58 Figure 30. Increasing rock analytes at Wekiwa Spring. Alkalinity (top) and st rontium (bottom) increased signi ficantly over Sequence A. Tests (p < 0.05) included MK for trend, WT on sequences B and C, plus an SS calculation. Beginning dates for these springs were not the same.

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BULLETIN NO. 69 59 Nutrient Analytes There were fewer nutrients trends in the SJRWMD than in other WMDs. For example, both phosphorus and TKN demonstrated few to no changes (no increases or decreases for phosphorus, no increases and two d ecreases for TKN). Nitrate show ed no clear trend direction. For example, in the seven springs showing trends for nitrate, three increased and four decreased. With respect to nutrients, only phosphate showed consistent tre nds across the district. Eleven springs decreased in phosphate while no springs increased. Figure 31 shows two phosphate trends, which also are cons idered to be Rock-matrix analytes. Phosphate levels for both Palm and St arbuck Springs fell by nearly half of the initial concentrations. Phosphate at Palm Springs (top figure) began the time se ries at approximately 0.15 mg/L and dropped to about 0.09 in 2002. Values from the end of the time series, 2002 to 2003, suggest a rise in concentrat ions. Starbuck levels began n ear 0.17 mg/L and fell to about 0.12 mg/L. Similar to Palm Springs, Starbuck appears to record a rise in concentrations near the end of the time series in 2003. Southwest Florida Water Management District Figure 32 shows the locations of the springs in the SWFWMD. Table 9 displays the corresponding spring abbreviations. Note that after analyses of spring data, th e SWFWMD notified the authors and told us that they now question the validity of using Boyette Spring data. They now believe it receives a significant portion of its water from a nearby sinkhole (< 1 kilometer away) and much of the receiving water is dairy waste (Morrison, 2000). Since the i ndividual spring analyses were already completed, we decided to keep the spring in the analys es. However, because of the point-source dairy contamination, Boyette Spring data were rem oved from both di strictwide and statewide analyses. The SWFWMD springs had strong trends in rock-matrix, salin e and nutrient indicators. Similar to the SRWMD, rock-matrix and saline indicators rose significantly. Unlike the SRWMD, nutrient indicators showed different t ypes of trends. Differences in behavior of nutrients between the SRWMD and SWFWMD sugge st regional differences exist between these two areas. Similarities in rock-matrix and saline trends between the SRWMD and SWFWMD suggest these trends extend beyond district boundaries. Some sp rings showed more changing chemistries than others. Betty Jay, Boyette, an d Tarpon Hole Springs had many analytes with increasing trends. Buckhorn Main and Hidden Rive r No. 2 Spring had a nu mber of decreasing trends. Those showing no trends among the an alytes studied during time Sequence A included Boat, Bobhill, Rainbow Swamp N o. 3, and Wilson Head Springs. Rock-Matrix and Saline Analytes Strong increases in both rock-m atrix and saline analytes were evident in springs in the SWFWMD during time Sequence A. Analytes wi th increasing trends include bicarbonate,

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FLORIDA GEOLOGICAL SURVEY 60 Figure 31. Decreasi ng phosphate concentrations at Palm and Starbuck Springs. Palm (top) and Starbuck Springs (bottom) illustrate the most Sharply decreasing nutrien t (phosphate) in the dist rict. Both springs show Substantial reductions since the beginning of the time series, with a potential increase at the end of the series. Note samples were not collected until 1995. 199519961997199819992000200120022003 Date 0.08 0.10 0.12 0.14 0.16 0.18T-PO4 (mg/L) Palm Springs Time Sequence A (1995-2003) 12 0.08 0.10 0.12 0.14 0.16 0.18 MK p-value < 0.0220 SS = -0.0013 WT p-value < 0.0081 nb = 6 nc = 19 B C 12 0.10 0.12 0.14 0.16 0.18 MK p-value < 0.0096 SS = -0.0013 WT p-value < 0.0218 nb = 6 nc = 20 B C 11/8/19928/5/1995 5/1/19981/25/ 200110/22/2003 Date 0.11 0.13 0.15 0.17 0.19T-PO4 (mg/L) Starbuck Spring Time Sequence A (1991-2003)

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BULLETIN NO. 69 61 Figure 32. Location of springs within the SWFWMD.

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FLORIDA GEOLOGICAL SURVEY 62Table 9. Southwest Florida Water Managemen t District Spring Names and Abbreviations Spring Abbreviation Spring Abbreviation Betty Jay Spring Betty Jay Hunters Spring Hunters Boat Spring Boat Lithia Main Spring Lithia Main Bobhill Spring Bobhill Magnolia Spring Magnolia Boyette Spring* Boyette Pump House Spring Pump House Bubbling Spring Bubbling Rainbow No. 1 Spring Rainbow No. 1 Buckhorn Main Spring Buckhorn Main Rainbow No. 4 Spring Rainbow No. 4 Catfish Spring Catfish Rainbow No. 6 Spring Rainbow No. 6 Chassahowitzka No. 1 Spring Chassahowitzka No. 1 Rainbow Bridge Seep Rainbow Bridge Seep Chassahowitzka Main Spring Chassahowitzka Main Rainbow Swamp Spring No. 3 Rainbow Swamp No. 3 Hidden River Head Spring Hidden River Head Salt Spring Salt Hidden River No. 2 Spring Hidden River No. 2 Tarpon Hole Spring Tarpon Hole Homosassa No. 1 Spring Homosassa No. 1 Trotter Main Spring Trotter Main Homosassa No. 2 Spring Homosassa No. 2 Weeki Wachee Main Spring Weeki Wachee Main Homosassa No. 3 Spring Homosassa No. 3 Wilson Head Spring Wilson Head calcium, chloride, potassium, magnesium, sodi um, conductivity, sulfate, strontium, and total dissolved solids. Of these, incr eases strongly attributable to ro ck chemistries were bicarbonate and strontium. Chemistries suggesting a rise in salinity included sodium and total dissolved solids. Analytes in common to both groups in cluded calcium, chloride, potassium, magnesium, specific conductance, and sulfate (which showed strong increases). Similar to other districts, Sequence B had very few trends. The majority of the influence for these increases occurred during time Sequence C. Figures 33-35 represent increasing trends for chloride. Chloride had the most frequent number of trends in th e SWFWMD (increased in 18 springs and decreased in only two). It was closely matched to sodium (increased in 16 sp rings, decreased in two). The following figures depict the chloride trends from several springs in the norther n SWFWMD along the Gulf Coast. Springs occur from north to south along the Gulf Coast. Figure 33 includes two springs from southern Marion County, one of the north ernmost counties in SWFWMD. These springs, Rainbow No. 6 and Bubbling Springs, increased in chloride concentrati ons, both springs show a steady increase during the years of Sequence A. Both springs began with 3.0-4.0 mg/L of chloride and ended the time series with approximatel y 5.0-6.0 mg/L. For a couple of springs just to the south in Citrus County, the increase in chloride was more dramatic (Figure 34). Hunt ers Spring (top) began the time se ries with approximately 50 mg/L of chloride. Values rose quickly at one point, more than doubling, and then declined. Trotter Main (bottom) showed a similar pattern, though with shar per changes. Tr otter Main had values of approximately 50 mg/L near the start, as did Hunters, but then increased to nearly 250

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BULLETIN NO. 69 63 Figure 33. In creasing saline analytes at Ra inbow and Bubbling Springs. Rainbow No. 6 (top) and Bubbling Springs (bottom) had significant increases in chloride. Tests (p < 0.05 ) included MK for trend, WT on sequences B and C, plus an SS calculation on rate of change. Beginning and ending dates for these springs are not the same. 1995199619971998199920002001 2002 2003 Date 2.5 3.0 3.5 4.0 4.5 5.0 5.5D-Cl (mg/L) Rainbow No. 6 Spring Time Sequence A (1991-2003) 1994199519961997199819992000200120022003 Date 4.0 4.5 5.0 5.5 6.0 6.5D-Cl (mg/L) Bubbling Spring Time Sequence A (1991-2003)MK p-value = 0.0002 SS = 0.0321 WT p-value < 0.0001 nb = 16 nc = 23 MK p-value = 0.0002 SS = 0.0417 WT p-value = 0.0014 nb = 13 nc = 23

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FLORIDA GEOLOGICAL SURVEY 64 Figure 34. Increasing saline analytes for Hunters and Trotter Main Springs. Hunter (top) and Trotter Main Springs (bottom) had significant increases in ch loride. Tests (p < 0.05) included MK for trend, WT on sequences B an d C, plus an SS calculation on rate of change. Beginning and ending dates for these springs are not the same. 199519961997199819992000200120022003 Date 10 30 50 70 90 110D-Cl (mg/L) Hunter Spring Time Sequence A (1991-2003)MK p-value = 0.0005 SS = 1.5802 WT p-value = 0.0033 nb = 12 nc = 20 12 5 7 9 11 13 15 17 B C 199519961997199819992000200120022003 Date 0 50 100 150 200 250D-Cl (mg/L) Trotter Main Spring Time Sequence A (1991-2003)MK p-value < 0.0001 SS = 0.1133 WT p-value = 0.0009 nb = 15 nc = 23

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BULLETIN NO. 69 65 Figure 35. Increasing saline analytes for Weeki Wachee and Bobhill Springs. Weeki Wachee (top) and Bobhill Springs (bottom) had significant increases in chloride. Tests (p < 0.05) included MK for trend, WT on sequences B and C, pl us an SS calculation on rate of change. 199519961997199819992000200120022003 Date 5 6 7 8D-Cl (mg/L) Weeki Wachee Sequence A (1991-2003) 199519961997199819992000200120022003 Date 5 7 9 11 13 15 17D-Cl (mg/L) Bobhill Spring Time Sequence A (1991-2003)MK p-value < 0.0001 SS = 0.0457 WT p-value < 0.0032 nb = 15 nc = 23 MK p-value < 0.0001 SS = 0.1133 WT p-value < 0.0009 nb = 14 nc = 19

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FLORIDA GEOLOGICAL SURVEY 66 mg/L at one point—a five-fold increase. Figure 35 depicts chloride concentrations at Weeki Wachee and Bobhill Springs. Weeki Wachee began th e time series with only about 6.0 mg/L of chloride and ended with a concentration of a bout 8.0 mg/L. Bobhill Spring began about 5.0 mg/L and ended with about a 9.0 mg /L chloride concentration. Flow Historic data suggested possible declines si milar to the SRWMD. Homosassa No. 1 flow levels declined for the years 1996-2003 (Figure 36). Longer-term tr ends are depicted in Figure 37, which further illustrates declines in flow. Si nce the 1960s, average y early flow for Rainbow Springs has declined (dark gray line indicates a timeline for Sequence A). WT tests between the first and second half of the data series show a difference between the two data series. However, for data representing time Sequence A, results do not indicate a significant difference. This suggests that trends on the scale of this study (i.e ., 13 years) may sometimes be missed in spite of being part of a larger change (e.g. 40 years of data ). In this case, declin es in flow rate were evident beginning in the 1960s. Long-term flow in Weeki Wachee Springs flow data (Figure 37, bottom) has an equally interesting pattern. Although no regression is disp layed, flow data going back to 1904 displays a rise until the 1960s, followed by a de cline until the present. Gray line s illustrate th e time line for Sequence A and that for post-1960. The range in fl ow during this time appears to be two-fold (100 to 250 cfs). Such a pattern may reveal that s hort-period trends may be part of longer-term cycles for groundwater; implications of this will be addressed later. Nutrient Analytes Nitrate increased strongly (19 springs w ith upward trends, only one down), while ammonia, phosphate, phosphorus, TKN, and tota l organic carbon showed little indication of trends. Since TKN, phosphorus, and total orga nic carbon decreased somewhat (though not significantly) it seems to indicate that nitrate-nitrogen alone s howed the strongest increase for SWFWMD. All other analytes showed little change or even evidence of a slight decline. Also unlike patterns seen in the rock and saline indi cators, nitrate increased during both sequences B and C. This is in contrast with the rock an alytes which showed str ongest activity during Sequence C. Figure 38 and 39 illustrate nutrient trends and their variability for SWFWMD. Hunter and Magnolia Springs (Figure 38), illustrate clear in creases in nitrate over Sequence A. Nitrate increases occurred regardless of initial concentr ations at the beginning of the time series. For example, Hunter Spring (top) had a consistent increase from a low initial value (about 0.25 mg/L) to just under the SRA th reshold of 0.45 mg/L. Hunter re mained under the SRA value for the time period. Magnolia Spring showed a rate of increase similar to Hunter (SS = 0.0046 and 0.0042, respectively). However, Magnolia began th e time series with a higher starting value (about 0.35 mg/L). The trend for Magnolia crosse d over the SRA threshold (Figure 38, bottom, gray line marks SRA value). Similarly Weeki Wachee (Figure 39, top), began the time series with a value near 0.45 mg/L and increased to 0.8 mg/L by the end of the time sequence. All three springs had similar rates of change yet differe d in their initial concentrations of nitrate.

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BULLETIN NO. 69 67 Figure 36 . Decreasing flow at Homosassa No. 1 Spring. Flow rates declined significantly from 1996 to 2003. (One cfs = 0.028 cms) Overall, TKN showed little activity (one tre nd up, four down for Sequence A). Figure 39 (bottom) shows a trend in TKN fo r Boyette Spring. It started with relatively low initial values and was followed with a rapid increase in 1998. Values went fr om near 0.5 mg/L to over 3.0 mg/L in short period of time. Field Analytes Only two Field analytes demonstrated de creasing trends over Sequence A, pH and temperature. The analyte pH increased in one spring and decreased in 10 , while temperature did not increase in any springs but decreased in eight. Like rock analytes, and unlike the consistent rise in nitrate, the trends for pH largely occurred in Sequence C. Wells The wells used for this study are a subdivi sion of FDEPÂ’s Background Network, referred to as the Temporal Variability (TV) Network. Although independe nt of springs, it was believed that evaluating trends in wells would shed insight as to the ch emical behavior of FloridaÂ’s groundwater. Decreasing tr ends in water levels and pH were often obser ved. Because of the drought, the lowering of water levels was predic table. However, the decrease in pH was unexpected. Plausible reasons for the d eclines will be discussed later. 1/2/19961/2/19981/2/20001/2/20021/2/2004 Date 40 60 80 100 120Flow (cfs) Homosassa No. 1 Spring Flow 12 40 60 80 100 120 LR p-value < 0.0001 n = 2879 WTp-value < 0.0001

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FLORIDA GEOLOGICAL SURVEY 68 Figure 37. Long-term flow trends at two SWFWMD springs. Rainbow (top) and Weeki Wachee Springs (bottom) show historic changes. For Rainbow, points represent average flow per year. Altho ugh no regression line on the graph, Weeki Wachee data since 1904 (bottom) showed a rise until about 1960 followed by a subsequent fall. Dark gray lines represent time line for Sequence A. (One cfs = 0.028 cms) 1960s to Present 3/30/1905 8/15/1932 1/1/1960 5/19/1987 Date 100 150 200 250Flow (cfs) Weeki Wachee Flow (1904-2003) 1991-2003 Present study time line 1960 1970 1980 1990 2000 Year 500 600 700 800 900Flow (cfs) Rainbow Springs Average Flow (1965-2003) 12 500 600 700 800 900 12 500 600 700 800 900 1991-2003 Present study time line

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BULLETIN NO. 69 69 Figure 38. Increasing nitrates at Hunters and Magnolia Springs. Hunter (top) and Magnolia Springs (bottom) illustrate the most actively increasing nutrient trend in the district (nitrate). Hunters increase remained below the the SRA (0.45 mg/L). Magnolia SpringÂ’s increase in nitrate began below the SRA and ends above it; thus it crosses a recommended limit. Beginning and ending dates for these springs were not the same. 2/12/199011/8/19928/5/19955/1/19981/25/200110/22/2003 Date 0.20 0.25 0.30 0.35 0.40D-NO3NO2 (mg/L) Hunter Spring Time Sequence A (1991-2003)R2 = 0.6173MK p-value < 0.0001 SS = 0.0046 WT p-value = 0.0001 nb = 12 nc = 20 12 0.2 0.3 0.4 0.5 B C 199519961997199819992000200120022003 Date 0.30 0.35 0.40 0.45 0.50D-NO3NO2 (mg/L) Magnolia Spring Time Sequence A (1991-2003) SRA Value =0.45 mg/LMK p-value < 0.0001 SS = 0.0042 WT p-value = 0.0001 nb = 13 nc = 23 12 0.30 0.35 0.40 0.45 0.50 1 2

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FLORIDA GEOLOGICAL SURVEY 70 Figure 39. Increasing nutrient analytes at Weeki Wachee and Boyette Springs. Weeki Wachee (top) shows a clear increase in nitrate in Sequence A. Most of the time series for Sequence A included values above 0.45 mg/L. Boyette (bottom) illustrates an unusual trend in TKN. TKN values sometimes rose suddenly over a very short period of time in 1998. SWFWMD staff indicated the source of the TKN was probably from a nearby dairy waste lagoon. Beginning and ending dates for these springs were not the same. 8/5/19955/1/19981/25/200110/22/2003 Date 0.4 0.5 0.6 0.7 0.8D-NO3NO2 (mg/L) Weeki Wachee Time Sequence A (1991-2003) SRA Value = 0.45mg/LMK p-value < 0.0001 SS = 0.0055 WT p-value = 0.0111 n1 = 15 n2 = 23 12 0.4 0.5 0.6 0.7 0.8 B C 2/12/199011/8/19928/5/19955/1/1998 Date 0 1 2 3D-TKN (mg/L) Boyette Spring Time Sequence A (1991-2003)MK p-value = 0.0005 SS = 0.0100 WT p-value = 0.0002 nb = 27 nc = 22 12 0 1 2 3 B C

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BULLETIN NO. 69 71 Northwest Florida Water Management District Northwest Florida wells (Figur e 40) showed a lowering of water levels for Sequence A (six of eight wells were down, w ith no increasing trends). Other anal ytes that had trends were as follows. The analyte pH decreased in four wells , while none of the eight increased. Sodium and sulfate increased (four increased in eight wells, none decreased). Figure 40. Location of wells within the NWFWMD. Changes in sequences B and C reflected t hose in Sequence A. For Sequence B water level fell (six of eight wells had decreasing levels, while none increased). Several wells also showed increases in sodium (increased in four wells, decreased in none) and conductivity (increased in five wells, decreased in none). Unlike springs, where the main influences on the chemistries occurred during Sequence C, the only notable analyte in well data demons trating a change was pH. The analyte decreased in six of eight wells stud ied (and increased in none). Water Levels and pH Figures 41and 42 illustrate several of these tr ends. The association of water level and pH suggest a relationship between th e two analytes and will be disc ussed later. A drop in water levels occurred in both unconf ined and confined wells. Confined aquifer Well 312 (Figure 42) showed a 5 m (15 ft) decline over the period of record.

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FLORIDA GEOLOGICAL SURVEY 72 Figure 41. Decreasing pH and water levels in NW FWMD wells (#91 and #129). Tests (p < 0.05) included MK for trend, WT on sequences B and C, plus an SS calculation on rate of change. 1991199219931994199519961997199819992000200120022003 Date 2 3 4 5 6 7 8pH 1 6 11 16WL (msl)Well 91 Time Sequence A: pH and WL pH WL.msl. 12 2 3 4 5 6 7 8 12 1 6 11 16 pH MK p-value = 0.0010 nb = 80 nc = 66 WT p-value = 0.0028 SS =-0.0016 Water Level MK p-value < 0.0001 nb = 81 nc = 54 WT p-value < 0.0001 SS = -0.0161 pH MK p-value = 0.0158 nb = 53 nc = 36 WT p-value = 0.0001 SS = -0.0012 Water Level MK p-value < 0.0001 nb = 53 nc = 24 WT p-value < 0.0001 SS = -0.0466 12 5.0 5.4 5.8 6.2 12 4 6 8 10 12 1991199219931994199519961997199819992000200120022003 Date 5.0 5.4 5.8 6.2pH 4 6 8 10 12WL (msl)Well 129 Time Sequence A: pH and WL pH WL

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BULLETIN NO. 69 73 Figure 42. Decreasing pH and water levels in NWFWMD wells (#131 and #312). Tests (p < 0.05) included MK for trend, WT on sequences B and C, plus an SS calculation on rate of change. Water level is in feet above mean seal level. (One m = 0.3048 ft) Water Level MK p-value < 0.0001 nb = 81 nc = 35 WT p-value < 0.0001 SS = -0.0893 1991199219931994199519961997199819992000200120022003 Date 3.5 4.0 4.5 5.0 5.5pH 14 15 16 17 18 19 20WL (msl)Well 131 Time Sequence A: pH and WL pH WL (msl)pH MK p-value < 0.0001 nb = 53 nc = 66 WT p-value = 0.0004 SS = -0.0030 Water Level MK p-value < 0.0001 nb = 52 nc = 55 WT p-value < 0.0001 SS = -0.0187 12 3.5 4.0 4.5 5.0 5.5 12 14 15 16 17 18 19 20 1991199219931994199519961997199819992000200120022003 Date 45 50 55 60 65 70WL (msl) Well 312 Time Sequence A: WL WL (msl) 12 45 50 55 60 65 70

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FLORIDA GEOLOGICAL SURVEY 74 Suwannee River Water Ma nagement District The locations of the SRWMD TV wells are displayed in Figure 43. Decreasing water level trends were observed in th e SRWMD. Temperature rose in Sequence C (six increased and none decreased). Trends in Sequence A suggested the same pattern as in northwest Florida: declines in water level and pH. Figure 43. Location of wells within the SRWMD. Water Levels and pH Over the period of record, water level and pH trends looked similar to other districts. As two examples (Figure 44) of unconfined wells (Wells 1943 and 2465), a drop in water level appeared to be accompanied by a decrease in pH. Note that Well 2465 had rapidly declining water levels but a relatively slower change in pH. The water level decreased approximately 5 m (15 feet) by the end of the st udy. Confined groundwat er showed similar patterns. Figure 45 shows water level and pH falling simultaneously for wells 2585 and 2675. In Well 2585, the water level drop is a minimum of 3 m (15 ft); some points in the early time series have substantially higher water level values [18 m (60 ft)] and sugge st the difference was even greater. By far the most extreme water level differen ce was recorded was Well 2675. From a high point of 27 m (90 ft) msl in 1994, water levels fell to approximately 9 m (30 ft) by 2003. This is nearly 18 m (60 ft) difference is due to its locati on near the Alapaha River. Local karst feature create differences in water levels in response to rainfall. Like other wells in the district, Well 2675 experienced a decline in pH.

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BULLETIN NO. 69 75 Figure 44. Decreasing pH and water levels in SRWMD wells (#1943 and #2465). Both wells are confined. Tests (p < 0.05) included MK for trend, WT on seque nces B and C, plus an SS calcula tion on rate of change. Note the beginning sampling dates for wells are not the same. (One m = 0.3048 ft.)

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FLORIDA GEOLOGICAL SURVEY 76 Figure 45 . Decreasing pH and water leve ls in SRWMD wells (#2585 and #2675). Both wells are confined. Tests (p < 0.05) included MK for trend, WT on sequences B and C, plus SS calculations. Note beginning and sampling dates for wells are not the same. (One m = 0.3048 ft.) St. Johns River Water Management District Figure 46 displays the location of TV Network wells in the SJRWMD. The trends for the wells shown in Figure 46 in the SJRWMD were slightly different from both the NWFWMD and

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BULLETIN NO. 69 77 Figure 46. Location of wells within the SJRWMD. the SRWMD. There were fewer wells with decreasing waters levels in the SJRWMD. However, decreases in pH were similar to the other WM Ds. The greatest proportion of decrease was in specific conductance. During Sequence A, zero increased while five decreased. During Sequence B one increased and five decreased, and during Sequence C, two increased while five decreased. Along with specific c onductance, rock analytes such as calcium and alkalinity showed decreases for Sequence A. A number of wells showing an increase in temperature, both in Sequences A (seven increased, one d ecreased) and Sequence C (five increased, two decreased). In Sequence C, incr eases in temperature and dissolv ed oxygen were notable. This occurred while pH was decreasing (none in creased, four wells decreased). Water level had an unclear direction (four wells in creased and only one decreased). Unlike other districts, pH decreased in many wells while wate r level tended to increase during Sequence C. Rise in temperature was often seen alongsid e a drop in specific conductance. Figure 47 shows both unconfined and confined groundwater (wells 1417 and 1763, respectively). Figure 48

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FLORIDA GEOLOGICAL SURVEY 78 Figure 47. Temperature and specific conductance in SJRWMD wells (#1417 and #1763). Tests (p < 0.05) included MK for trend, WT on sequences B and C, plus an SS calculation on rate of change.

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BULLETIN NO. 69 79 Figure 48. Temperature a nd specific conductance in SJRWMD well (#1762). Tests (p < 0.05) included MK for trend, WT on sequences B and C, plus an SS calculation on rate of change. shows the same type of figure for confined groundwater (Well 1762). All wells start with different initial temperature and specific c onductance. Well 1417 temperature starts around 22º C and ends over 23º C. In a similar way, confined groundwater (Well 1763) starts near 22º C but ends slightly higher. Though the slope is signif icant, a WT test between segments B and C showed no significant differences (p-value 0.6739) , indicating the amount of increase was less. At the same time, another confined well (Well 1762; Figure 48) had a clear temperature increase, starting near 24º C and ending near 26º C. Specific conductance had clearl y decreasing trends while temperature rose. Well 1417 began with greater than 400 S/cm specific conductance but e nded with just above 300 (Figure 48, top). Slightly more attenuated downward trends are present in the confined water (wells 1763 and 1762). Well 1763 showed trends within the range of 630 to a bout 600—all within 30 S/cm. Well 1762 had a drop in specific conductance that was also over a relatively modest range of 760 700 S/cm (Figure 48). Southwest Florida Water Management District The SWFWMD wells (Figure 49) had the least amount of change among the WMDs. There were only a few cases worth noting. For Time Sequence A, six of 10 wells had temp

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FLORIDA GEOLOGICAL SURVEY 80 Figure 49. Location of wells within the SWFWMD. perature trends. Of these, five of six increased. Sequence B had four increases with no decreases in temperature. Time Sequence C showed some small changes, probably in relation to changes water levels. Although three downw ard water-level trends were observed for Sequence A (with no upward trends), Sequence C had four increases in water level (none decreased). This was

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BULLETIN NO. 69 81 reflected in the number of downward trends for specific conductance (one increased, five decreased). Like wells in the northern part of the st ate, water levels a nd pH often decreased significantly in a number of places in the SWFWMD . Figure 50 illustrates de clining water levels and pH for two SWFWMD unconfined groundwater wells. Water level decreased at Well 996. At the same time, WT tests did not affirm di fferences between Sequence B and C water levels. The decreasing water level-trend was probably caused by the drought which occurred during Sequence C (low points are visi ble after the year 2000), but re covered after 2001. Thus, the overall reduction in water levels was relati vely small, when viewed from Sequence A (insignificant difference in the WT test). In contrast, Well 1087 had a significant reduction in water level and in pH. Well 707 (confined; Figure 51 ), along with wells 99 6 and 1087 (unconfined), demonstrated declining water levels that matche d trends toward the thr ee previously discussed WMDs. As with the other WMDs, a decrease in pH appeared to accompany the fall in water levels. The pH levels in Sequences B and C in Well 707 indicated the lack of verifiable difference between the time sequences (WT test) although a MK test de tected a significant downward slope for pH. On the other hand, signif icant declines in wate r levels were observed. As with the unconfined groundwater, confined Well 707 showed a reduction in water level during the drought in 2000. The sim ilarities in water-level change s in the SWFWMD and in the northern WMDs for springs and wells, suggeste d a statewide cause rather than only local influences. South Florida Water Management District Figure 52 displays the location of the wells in the SFWMD. A small number of trends were present for a variety of an alytes but nothing to suggested strong district-wide changes. The only possible exception was pH. For time Sequence C, of nine wells six registered trends—one increased and five decreased for pH. Examples of decreasing pH levels can be seen in two unconfined groundwater wells: 6490 and 3398 (Figur e 53). The figure also demonstrates that water levels decreased in Well 6490. Relatively higher water levels at the start of the study may account for much of the change (Figure 53, top). The connection between pH and water level will be explored later. However, pH trends around the state were dominantly toward lower values. South Florida was no exception. Districtwide Spring Trends Previously, the discussion has been restricted to defining trends for specific analytes at individual stations (springs or wells). Maps de picting all of the trends for each analyte for each spring or well by water management district can be found in Appendix L (Online). Evaluating individual trends is essential for this st udy. However, looki ng at trends from another scale can often be enlight ening. For example, were there districtwide or statewide areal trends present? The sign test was th e major tool used for the analyses.

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FLORIDA GEOLOGICAL SURVEY 82 Figure 50. Decreasing pH and water levels in SWFWMD wells (#996 and #1087). Tests (p < 0.05) included MK for trend, WT on sequences B and C, plus an SS calculation on rate of change. (One ft = 0.305 m) pH MK p-value = 0.0442 nb = 84 nc = 64 WT p-value = 0.1617 SS = -0.0002 1991199219931994199519961997199819992000200120022003 Date 40 42 44 46 48WL (msl) WL (msl)Well 996 Time Sequence A: WLWater Level MK p-value = 0.0434 nb = 86 nc = 64 WT p-value = 0.0616 SS = -0.0040 12 40 42 44 46 48 2/12/199011/8/19928/5/19955/1/19981/25/200110/22/2003 Date 5.5 6.0 6.5 7.0 7.5 8.0pH 88 90 92 94 96WL (msl)Well 1087 Time Sequence A: pH and WL pH WL (msl)Water Level MK p-value = 0.0023 nb = 84 nc = 64 WT p-value < 0.0001 SS = -0.0096 12 5.5 6.0 6.5 7.0 7.5 8.0 12 88 90 92 94 96

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BULLETIN NO. 69 83 Figure 51. D ecreasing pH and water levels in SWFWMD well (#707). Water levels an d pH for Southwest confined groundwater (Well 707). Tests (p < 0.05) included MK for trend, WT on sequences B and C, plus an SS calculation on rate of change. Wakulla Spring is the only spring in the NW FWMD to have sufficient data for trend analyses. If only one station is present, a distri ctwide analysis for tre nds, based on the sign test, is not possible (Gilbert, 1987). For these reasons, and because Wakulla Spring is located only about 24 km (15 miles) to the SRWMD border, we included Wakulla Spri ng with the SRWMD. In addition, the SFWMD had no spring with suffi cient data for analyses. Thus, districtwide trends could only be conducted for the SRWMD (16 springs including Wakulla), the SJRWMD (14 springs), and the SW FWMD (27 springs). Recall (p. 59) that the after the delivery of Boyette Spring water quality data, the SWFWMD declassified Boyette as a spring. B ecause of the point-source dairy contamination, Boyette Spring data were removed from both dist rictwide and statewide analyses. Also, recall (p. 35) that the statistical test used to evaluate the presence of areal trends was the sign test (Appendix E). As used in this study, the sign test compares the pro portions of significantly increasing trends to significantly decreasing tr ends. The sequences in which were unable to confirm a trend, or those with insufficient da ta were not used for the sign tests. 2/12/199011/8/19928/5/19955/1/19981/25/200110/22/2003 Date 6.5 6.9 7.3 7.7 8.1pH 0 10 20 30WL (msl) pH WL (msl)Well 707 Time Sequence A: pH and WLpH MK p-value = 0.0045 nb = 82 nc = 34 WT p-value = 0.1627 SS = -0.0008 Water Level MK p-value = 0.0001 nb = 82 nc = 33 WT p-value = 0.0223 SS = -0.0592 12 6.5 6.9 7.3 7.7 8.1 12 0 10 20 30

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FLORIDA GEOLOGICAL SURVEY 84 Figure 52. Location of wells within the SFWMD.

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BULLETIN NO. 69 85 Figure 53. Decreasing pH an d water levels in SFWMD wells (#6490 and # 3398). SFWMD unconfined groundwater shows downward trends. Tests (p < 0.05) included MK for trend, WT, plus an SS calculation on rate of change. 1991199219931994199519961997199819992000200120022003 Date 6.2 6.7 7.2 7.7 8.2pH 0 2 4 6WL (msl)Well 6490 Time Sequence A: pH and WL pH WLpH MK p-value < 0.0001 nb = 80 nc = 66 WT p-value = 0.0002 SS = -0.0012 Water Level MK p-value = 0.0488 nb = 81 nc = 66 WT p-value < 0.1353 SS = -0.0014 12 6.2 6.7 7.2 7.7 8.2 12 0 2 4 6 9/13/199910/17/200011/21/200112/26/2002 Date 6.8 7.0 7.2 7.4pH Well 3398 Time Sequence C: pHpH MK p-value = 0.0001 n1 = 23 n2 = 23 WT p-value = 0.0002 SS = -0.0050 12 6.6 6.8 7.0 7.2 7.4

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FLORIDA GEOLOGICAL SURVEY 86 Districtwide Spring Trends in Suwann ee River Water Management District The individual spring trends for Sequence A in the SRWMD (incl uding Wakulla Spring) are displayed in Table 10. Flow had a significa nt decreasing trend while calcium, magnesium, sodium, total kjeldahl nitrogen (TKN), and temp erature each had upward districtwide trends (Table 11). Notice that for the sign test disc ussions, the symbol “+” indicates of an upward trend, “-” designates a downward tr end, and a blank indicates no dis cernable trend. The two far right columns of Table 10 summarize the total nu mber of pluses and minuses for the respective analyte. Table 11 summarizes the analytes disp laying districtwide trends using the sign test, along with corresponding p-values. For Sequence B (Table 12), there were no obs ervable trends. Trends in Sequence C (Table 13) were similar to those in Sequence A. Table 14 summarizes Sequence C. Flow decreased, while calcium, ma gnesium, sodium, phosphorous and total kjeldahl nitrogen, had upward trends. Total organic ca rbon had a downward trend. Districtwide Spring Trends in St. Jo hns River Water Management District Spring trends for the SJRWMD are shown in Table 15. For Sequence A (Table 16) calcium, fluoride, pH, and strontium each had up ward trends while orthophosphate (or simply phosphate) had a downward trend. As with the SR WMD, no districtwide trends were observed for Sequence B (Table 17) within the SJRWMD. However, for Sequence C (Tables 18 and 19), flow had a downward trend while pH and fluoride had upward trends. Districtwide Spring Trends in Southwes t Florida Water Management District Individul spring trends fo r the SWFWMD are displayed in Table 20. For Sequence A (Table 21), bicarbonate (related to alkalinity), calcium, chloride , magnesium, nitrate, potassium, sodium, specific conductance, strontium, sulfat e, and total dissolved solids, each had upward districtwide trends. The analyt es pH and temperature had downwa rd trends. Unfortunately, flow data were only available from three gaging stat ions within the SWFWMD. For this reason, there were insufficient data to make conclusions regarding districtwide flow trends. During Sequence B (Table 22), fluoride and nitrate each had an upward trend whereas phosphorus had a downward trend (Table 23). As with Sequence A, there existed insufficient data to determine significant flow trends during Sequence B. Sequence C was similar to Sequence A in term s of trends (Table 24). Bicarbonate, calcium, chloride, magnesium, nitrate, potassi um, specific conductance, sodium, strontium, sulfate, and total dissolved solids showed upwar d trends while pH had a downward trend (Table 25). Again there were insufficient data to dete rmine districtwide trends in flow. However, during Sequence C, three gaging stations did have sufficient data and all three of these sites demonstrated downward trends (Table 26).

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BULLETIN NO. 69 87Table 10. Spring Trends in the SRWMD (plu s Wakulla Spring), Sequence A (1991-2003). (+ = trend, blank = no evidence of trend, = trend) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 + Alk + + + + 4 0 Ca + + + + + + + + + + 10 0 Cl + + + + + + 4 1 DO + + 2 9 F + + 2 0 Flw* 0 11 K + + 2 2 Mg + + + + + + + + + 9 0 Na + + + + + + + + + 9 0 NH3 DL + DL + DL DL DL DL DL DL DL 2 0 NO3** + + + 3 7 P + + + + + 5 1 PO4 + + + + 4 1 pH + + + + + 5 1 SC-lb + + + + + + + 7 2 SO4 + + + + 4 1 TKN + + + + + + + + + 9 0 Temp + + + + + + + 7 0 TOC + + 2 1 Trb + + + 3 1 All analytes total unless otherwise stated * Inferred from stage data. **NO3 = NO3 + NO2 as N (total) DL = Influenced by cha nging laboratory met hod detection level. 1. Wakulla Spring (NWFWMD) 9. Suwannee Blue Spring 2. Manatee Spring 10. Royal Spring 3. Fanning Spring 11. Telford Spring 4. Hart Spring 12. Lafayette Blue Spring 5. Rock Bluff Spring 13. Alapaha River Rise 6. Little River Spring 14. Gilchrist Blue Spring 7. Ruth/Little Sulfur Springs 15. Poe Spring 8. Troy Spring 16. Hornsby Spring Table 11. SRWMD (plus Wakulla Spring ) Districtwide Trends based on sign tests, Sequence A. Analyte + Trend Direction P-Value Ca 10 0 Up 0.001 Mg 9 0 Up 0.002 Na 9 0 Up 0.002 TKN 9 0 UP 0.002 Temp 7 0 Up 0.008 Flow 0 11 Down 0.001

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FLORIDA GEOLOGICAL SURVEY 88 Table 12. Spring Trends in the SRWMD (p lus Wakulla Spring) Sequence B (1991-1997). (+ = trend, 0 = no evidence of trend, = trend) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 + Alk + + + 3 0 Ca + 1 0 Cl 0 1 DO 0 1 F 0 0 Flw* 0 1 K 0 1 Mg + + + 3 1 Na + + + 3 0 NH3 + 1 0 NO3** 0 0 P 0 3 PO4 0 3 pH 0 1 SC-lb + + + + 4 0 SO4 + 1 1 TKN DL DL DL DL 0 1 Temp + + + + 4 0 TOC 0 0 Trb + DL DL DL 1 3 All analytes total unless otherwise stated SC-lb = Specific Conductance (laboratory) a * Inferred from stage data. DL = Influe nced by changing laboratory me thod detection level. **NO3 = NO3 + NO2 as N (total) 1. Wakulla Spring (NWFWMD) 9. Suwannee Blue Spring 2. Manatee Spring 10. Royal Spring 3. Fanning Spring 11. Telford Spring 4. Hart Spring 12. Lafayette Blue Spring 5. Rock Bluff Spring 13. Alapaha River Rise 6. Little River Spring 14. Gilchrist Blue Spring 7. Ruth/Little Sulfur Springs 15. Poe Spring 8. Troy Spring 16. Hornsby Spring

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BULLETIN NO. 69 89Table13. Spring Trends in the SRWMD (plus Wakulla Spring), Sequence C (1998-2003). (+ = trend, 0 = no evidence of trend, = trend) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 + Alk + + 2 2 Ca + + + + + + + + + + + 11 0 Cl + + + + + + 6 2 DO + + 2 8 F + + + + + 5 0 Flw* 0 9 K + + + + + + + 7 1 Mg + + + + + + + + + + + + + 13 0 Na + + + + + + + + + + + + 12 0 NH3 +D + +D + +D +D +D +D +D +D +D +D +D 2 0 NO3** + + 2 9 P + + + + + + + + + 9 0 PO4 + + + + + + + 7 1 pH + + + 3 2 SC-lb + + + + + + + 7 4 SO4 + + + + + + 6 3 TKN + + + +D + + + + + +D + + +D 10 0 Temp + + + + 4 0 TOC + 1 9 Trb + + + + + 5 0 All analytes total unless otherwise stated * Inferred from stage data. **NO3 = NO3 + NO2 as N (total) D = DL = Influenced by changing laboratory method detection level. 1. Wakulla Spring (NWFWMD) 9. Suwannee Blue Spring 2. Manatee Spring 10. Royal Spring 3. Fanning Spring 11. Telford Spring 4. Hart Spring 12. Lafayette Blue Spring 5. Rock Bluff Spring 13. Alapaha River Rise 6. Little River Spring 14. Gilchrist Blue Spring 7. Ruth/Little Sulfur Springs 15. Poe Spring 8. Troy Spring 16. Hornsby Spring Table 14. SRWMD (plus Wakulla Sp ring) Districtwide Trends based on sign tests, Sequence C. Analyte + Trend Direction P-Value Flow 0 9 Down 0.002 Ca 11 0 Up <0.001 Mg 13 0 Up <0.001 Na 12 0 Up <0.001 P 9 0 Up 0.002 TKN 10 0 Up 0.001 TOC 1 9 Down 0.003

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FLORIDA GEOLOGICAL SURVEY 90Table 15. Spring Trends in th e SJRWMD, Sequence A (1991-2003). (+ = trend, 0 = no evidence of trend, = trend) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 + Alk + + + + + + 6 1 Ca + + + + + + + + + 9 1 Cl + + + + + 5 3 F + + + + + + + + + + 10 0 Flw + + + 3 3 K 0 1 Mg + + + + + + + 7 2 Na + + + + + 5 3 NO3* + + + 3 4 P 0 0 PO4 -DL 0 11 pH + + + + + + + + + 9 1 SCfld + 1 6 SO4 + + + + + + + + 8 5 TKN 0 2 Temp + + 2 0 TDS + + + + 4 2 Sr + + + + + + + + + + 10 1 Analytes are total rather than dissolv ed except for Apopka Spring. SC-fld = Specific Conductance field *NO3 = Depending on spring, nitrate could be in the form of: (1) D NO3 + NO2 (as N), (2) D NO3 (as N) or T NO3 (as N) combined; (3) T NO3 + NO2 (as N) combined, or (4) T NO3 (as N) DL = Influenced by changing laboratory method detection level. 1. Alexander Spring 9. Rock Springs 2. Apopka Spring 10. Sanlando Springs 3. Volusia Blue Spring 11. Salt Springs 4. Fern Hammock Springs 12. Silver Glen Springs 5. Juniper Springs 13. Starbuck Spring 6. Miami Spring 14. Sweetwater Spring 7. Palm Springs 15. Wekiwa Spring 8. Ponce de Leon Spring Table 16. SJRWMD Districtwide Trends Based on Sign Tests, Sequence A. Analyte + Trend Direction P-Value Ca 9 1 Up 0.011 F 10 0 Up 0.001 PO4 0 11 Down <0.001 pH 9 1 Up 0.011 Sr 10 1 Up 0.001

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BULLETIN NO. 69 91Table 17. Spring Trends in the SJRWMD, Sequence B (1991-1997). (+ = trend, 0 = no evidence of trend, = trend) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 + Alk + 1 4 Ca + 1 1 Cl + + 2 1 F + + 2 0 Flw + + + + + 5 0 K + + 2 0 Mg + 1 1 Na + + 2 1 NO3* 0 1 P 0 5 PO4 0 0 pH 0 4 SCfld + 1 5 SO4 + + 2 0 TKN + 1 1 Temp + 1 0 TDS + + 2 4 Sr + + 2 1 Analytes are total rather than di ssolved except for Apopka Spring. *NO3 = Depending on spring, nitrate could be in the form of: (1) D NO3 + NO2 (as N), (2) D NO3 (as N) or T NO3 (as N) combined; (3) T NO3 + NO2 (as N) combined, or (4) T NO3 (as N) DL = Influenced by changing laboratory method detection level. 1. Alexander Spring 9. Rock Springs 2. Apopka Spring 10. Sanlando Springs 3. Volusia Blue Spring 11. Salt Springs 4. Fern Hammock Springs 12. Silver Glen Springs 5. Juniper Springs 13. Starbuck Spring 6. Miami Spring 14. Sweetwater Spring 7. Palm Springs 15. Wekiwa Spring 8. Ponce de Leon Spring Note: No Sequence B districtwide trends were observed in the SJRWMD.

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FLORIDA GEOLOGICAL SURVEY 92Table 18. Spring Trends in the SJRWMD, Sequence C (1998-2003). (+ = trend, 0 = no evidence of trend, = trend) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 + Alk + + + + 4 0 Ca + + + 3 1 Cl + + + + + + 6 4 F + + + + + + + 7 0 Flw 0 8 K + 1 0 Mg + 1 1 Na + + 2 1 NO3* + 1 1 P 0 3 PO4 pH + + + + + + + + + + 10 0 SCfld + 1 1 SO4 + + + 3 3 TKN 0 2 Temp + + + + 4 0 TDS 0 2 Sr + + + 3 1 Analytes are total rather than di ssolved except for Apopka Spring. *NO3 = Depending on spring, nitrate could be in the form of: (1) D NO3 + NO2 (as N), (2) D NO3 (as N) or T NO3 (as N) combined; (3) T NO3 + NO2 (as N) combined, or (4) T NO3 (as N) DL = Influenced by changing laboratory method detection level. 1. Alexander Spring 9. Rock Springs 2. Apopka Spring 10. Sanlando Springs 3. Volusia Blue Spring 11. Salt Springs 4. Fern Hammock Springs 12. Silver Glen Springs 5. Juniper Springs 13. Starbuck Spring 6. Miami Spring 14. Sweetwater Springs 7. Palm Springs 15. Wekiwa Spring 8. Ponce de Leon Spring Table 19. SJRWMD Districtwide Trends Based on Sign Tests, Sequence C. Analyte + Trend Direction P-Value Flow 0 8 Down 0.008 pH 0 10 Up 0.001 F 7 0 Up 0.008

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BULLETIN NO. 69 93Table 20. Spring Trends in the SWFWMD, Sequence A (1991-2003). (+ = trend, blank = no evidence of trend, = trend) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Bicarb*1 + + + + + + + + + + + Ca + + + + + + Cl + + + + + + + + + F + + + Flw K + + + + + + + + + Mg + + + + + + + + + Na + + + + + + + + NH3 -D -D -D -D -D NO3*2 + + + + + + + + + P*3 PO4 pH + SC-fld + + + + + + + + SO4 + _ + + + + + + + Sr + + + + + + + + + TDS + + + + + + Temp TKN -D + -D -D -D -D T-N TOC + -D -D -D -D -D -D Fe*3 -D -D -D -D Bicarb* = Only WMD to sample bicarbonate was SWFWMD. Other WMDs sampled alkalinity. NO3* = D-NO3+NO2 as N. Fe*3 = Only WMD to sample D-Fe was SWFWMD D = DL = Influenced by changing laboratory method detection level. 1. Betty Jay Spring 8. Chassahowitzka Main Spring 2. Boat Spring 9. Chassahowitzka No. 1. Spring 3. Bobhill Spring 10. Hidden River Head Spring 4. Boyette Spring 11. Hidden River No. 2 Spring 5. Bubbling Spring 12. Homosassa No. 1 Spring 6. Buckhorn Main Spring 13. Homosassa No. 2 Spring 7. Catfish Spring 14. Homosassa No. 3. Spring

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FLORIDA GEOLOGICAL SURVEY 94Table 20. Spring Trends in the SWFWMD, Sequence A (continued). Analyte 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Bicarb*1 + + + + + + + + Ca + + + + + + Cl + + + + + + + + + F + Flw K + + + + + + + + + Mg + + + + + + + Na + + + + + + + + NH3 -D -D -D -D NO3*2 + + + + + + + + + + P*3 PO4 + pH SC-fld + + + + + + + SO4 + + + + + + + Sr + + + + + + + + + TDS + + + + + + + + Temp TKN -D -D T-N TOC -D -D -D -D -D -D -D Fe*3 -D -D -D -D -D Bicarb*1 = Only WMD to sample bicarbonate wa s SWFWMD. Other WMDs sampled alkalinity. NO3*2 = D-NO3+NO2 as N. Fe*3 = Only WMD to sample D-Fe was SWFWMD D = DL = Influenced by changing laboratory method detection level. 15. Hunter Spring 22. Rainbow Swamp Spring No. 3 16. Lithia Spring Major 23. Rainbow Bridge Seep Spring 17. Magnolia Spring 24. Salt Spring 18. Pump House Spring 25. Tarpon Hole Spring 19. Rainbow No. 1 Spring 26. Trotter Main Spring 20. Rainbow No. 4 Spring 27. Weeki Wachee Main Spring 21. Rainbow No. 6 Spring 28. Wilson Head Spring Table 21. SWFWMD Distri ctwide Trends Based on Sign Tests, Sequence A*. Analyte + Trend Direction P-Value** Bicarb 19 0 Up <0.001 Ca 12 1 Up 0.002 Cl 18 1 UP <0.001 Flow NA NA NA NA K 18 1 Up <0.001 Mg 16 0 Up <0.001 Na 16 1 Up <0.001 NO3 19 0 Up <0.001 pH 1 9 Down 0.011 SC 15 1 Up < 0.001 S04 15 2 Up 0.001 Sr 17 0 Up <0.001 TDS 14 0 Up <0.001 Temp 0 8 Down 0.004 * After evaluation of individual springs, staf f at the SWFWMD declassified Boyette Spring as a spring. As a consequence, Boytte data were no t used for evaluations of districtwide or statewide trends. ** Trends suspected of being influenced by changing laboratory detection levels are not included.

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BULLETIN NO. 69 95Table 22. Spring Trends in th e SWFWMD, Sequence B (1991-1997). (+ = trend, blank = no evidence of trend, = trend) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Bicarb*1 + + Ca Cl + F + + + + + Flw K + + Mg + + Na + NH3 NO3*2 + + + + P*3 PO4 pH + SC-fld + + SO4 + + Sr TDS + Temp + TKN T-N TOC -D Fe*3 + + Bicarb*1 = Only WMD to sample bicarbonate wa s SWFWMD. Other WMDs sampled alkalinity. NO3*2 = D-NO3+NO2 as N. Fe*3 = Only WMD to sample D-Fe was SWFWMD D = DL = Influenced by changing laboratory method detection level. 1. Betty Jay Spring 8. Chassahowitzka Main Spring 2. Boat Spring 9. Chassahowitzka No. 1. Spring 3. Bobhill Spring 10. Hidden River Head Spring 4. Boyette Spring 11. Hidden River No. 2 Spring 5. Bubbling Spring 12. Homosassa No. 1 Spring 6. Buckhorn Main Spring 13. Homosassa No. 2 Spring 7. Catfish Spring 14. Homosassa No. 3. Spring

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FLORIDA GEOLOGICAL SURVEY 96Table 22. Spring Trends in the SWFWMD, Sequence B (continued). 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Bicarb*1 + Ca Cl + F + + + + + + Flw K Mg Na + + NH3 NO3*2 + + + + P*3 PO4 pH + SC-fld + + SO4 + Sr TDS + Temp TKN + T-N TOC -D -D -D -D Fe*3 + Bicarb*1 = Only WMD to sample bicarbonate was SWFWMD NO3*2 = NO3+NO2 as N. Fe*3 = Only WMD to sample D-Fe was SWFWMD D = DL = Influenced by changing laboratory method detection level. 15. Hunter Spring 22. Rainbow Swamp Spring No. 3 16. Lithia Spring Major 23. Rainbow Bridge Seep Spring 17. Magnolia Spring 24. Salt Spring 18. Pump House Spring 25. Tarpon Hole Spring 19. Rainbow No. 1 Spring 26. Trotter Main Spring 20. Rainbow No. 4 Spring 27. Weeki Wachee Main Spring 21. Rainbow No. 6 Spring 28. Wilson Head Spring Table 23. SWFWMD Districtwide Trends Based on Sign Tests, Sequence B. Analyte + Trend Direction P-Value* F 10 0 Up 0.002 Flow NA NA NA NA NO3 8 0 UP 0.008 P 0 8 Down 0.004 * After evaluation of individual springs, staff at the SWFWMD declassified Boyette Spring as a spring. As a consequence, Boytte data were not used for evaluations of districtwide or statewide trends. **Trends suspected of being influenced by changing laboratory detection levels are not included.

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BULLETIN NO. 69 97 Table 24. Spring Trends in the SWFWMD, Sequence C (1998-2003). (+ = trend, blank = no evidence of trend, = trend) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Bicarb*1 + + + + + + + + + + + Ca + + + + Cl + + + + + F + + + Flw K + + + + + Mg + + + + + + + + Na + + + + + + NH3 NO3*2 + + + + + + + P*3 + PO4 pH SC-fld + + + + + SO4 + + + + + Sr + + + + + + + + + + + TDS + + + + + Temp + TKN T-N + TOC + Fe*3 + Bicarb*1 = Only WMD to sample bicarbonate was SWFWMD NO3*2 = NO3+NO2 as N Fe*3 = Only WMD to sample D-Fe was SWFWMD D = DL = Influenced by changing laboratory method detection level. 1. Betty Jay Spring 8. Chassahowitzka Main Spring 2. Boat Spring 9. Chassahowitzka No. 1. Spring 3. Bobhill Spring 10. Hidden River Head Spring 4. Boyette Spring 11. Hidden River No. 2 Spring 5. Bubbling Spring 12. Homosassa No. 1 Spring 6. Buckhorn Main Spring 13. Homosassa No. 2 Spring 7. Catfish Spring 14. Homosassa No. 3 Spring

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FLORIDA GEOLOGICAL SURVEY 98 Table 24. Spring Trends in the SWFWMD, Sequence C (continued). 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Bicarb*1 + + + + + + + + + + Ca + + + + + Cl + + + + + + + F + + Flw K + + + + + + + + + + Mg + + + + + + Na + + + + + + + + NH3 -DL -DL NO3*2 + + + + + + + P*3 PO4 pH SC-fld + + + + + + + SO4 + + + + + + + Sr + + + + + + + + + TDS + + + + + Temp TKN T-N + TOC + Fe*3 + Bicarb*1 = Only WMD to sample Bicarbonate was SWFWMD NO3*2 = NO3+NO2 as N Fe*3 = Only WMD to sample D-Fe D = DL = Influenced by changing laboratory method detection level. 15. Hunter Spring 22. Rainbow Swamp Spring No. 3 16. Lithia Spring Major 23. Rainbow Bridge Seep Spring 17. Magnolia Spring 24. Salt Spring 18. Pump House Spring 25. Tarpon Hole Spring 19. Rainbow No. 1 Spring 26. Trotter Main Spring 20. Rainbow No. 4 Spring 27. Wekki Wachee Main Spring 21. Rainbow No. 6 Spring 28. Wilson Head Spring Table 25. SWFWMD Districtwide Trends Based on Sign Tests, Sequence C. Analyte + Trend Direction P-Value* Bicarbonate 21 0 Up <0.001 Ca 9 0 Up 0.002 Cl 12 0 Up <0.001 Flow NA NA NA NA K 15 0 Up <0.001 Mg 14 0 Up <0.001 Na 14 0 Up <0.001 NO3 14 3 Up 0.006 pH 0 6 Down 0.016 SC 12 0 UP <0.001 SO4 12 0 UP <0.001 Sr 19 0 Up <0.001 TDS 9 0 Up 0.004 * After evaluation of individual springs, staff at the SWFWMD declassified Boyette Spring as a spring. As a consequence, Boytte data were not used for evaluations of districtwide or statewide trends.

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BULLETIN NO. 69 99Table 26. Spring Flow from Three Stations in the SWFWMD. Spring Location Trend Direction P-value Homosassa Springs at Homosassa Down <0.0001 Chassahowitzka River near Chassahowitzka Down <0.0001 Chassahowitzka River Near Homosassa Down <0.0001 For a summary of districtwide trends see Ta ble 27. The table displays the Sequence (A, B, or C) by WMD. It displays the analytes with upward and dow nward trends. In addition, it displays the corresponding p-values . If a p-valu e is less than (significance level preset at 0.05), it is concluded that a trend exists. It should be noted that the lower the p-value, the lower the probability is that the null hypothesis (no trend) is true and, therefore, th e stronger the argument for the existence of a trend. For example, a p-valu e of slightly less than 0.05 indicates that there was slightly less than one in 20 chance th at trend did not exis t. If the p-value was 0.01, then there is only a one in 100 chance of the error occurring. In addition to the authors presetting to be 0.05, they also, arbitrarily, set a p-value of 0.02 as being strong ev idence for a trend. Thus, a pvalue less than 0.05, but greater than or equal to 0.02, was considered to be evidence for a moderately strong trend. A p-value of less than 0.02 is considered to be strong evidence for a trend. Based on this argument, with a few excep tions, p-values in Table 27 represent strong evidence for trends. Table 27. Statewide Spring Trend Summary by WMD and Time Sequence. Light gray boxes indicate saline-related indicators, dark gray nutrient-related indicators. (p-values are from sign tests by the corresponding water management district) Sq SRWMD (including Wakulla Spring) SJRWMD SWFWMD A Up p-val Dwn p-val Up p-val Dwn p-val Up p-val Dwn p-val Ca 0.001 Flow 0.001 Ca 0.011 P04 <0.001 Ca 0.003 Tmp 0.004 Mg 0.002 F 0.001 Bcarb <0.001 pH 0.021 Na 0.002 pH 0.011 Mg <0.001 TKN 0.001 Sr 0.001 Sr <0.001 Tmp 0.008 K <0.001 Na <0.001 Cl <0.001 SO4 0.001 SC 0.001 TDS <0.001 NO3 <0.001 B F 0.002 P 0.004 NO3 0.008 C Ca <0.001 Flow <0.001 pH 0.001 Flw 0.008 Ca 0.002 pH 0.016 Mg <0.001 TOC 0.003 F 0.008 Bicarb <0.001 Na <0.001 Mg <0.001 P 0.002 Sr <0.001 TKN 0.001 K <0.001 Na <0.001 Cl <0.001 SO4 <0.001 SC <0.001 TDS 0.004 NO3 0.013 Bcarb = Bicarb; Dwn = Down; Flw = Flow; Tmp = Temp

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FLORIDA GEOLOGICAL SURVEY 100 Statewide Spring Trends It should be pointed out that bicarbonate was sampled only by the SWFWMD. However, the other WMDs sampled alkalinity. The two species are considered to have sufficient similarities to be considered one analyte (b icarbonate/alkalinity spec ies) for the sign test exercises. Tables 28-30 show analytes with statewide trends for each time sequence. For Sequence A (Table 28), analytes showing upward statewide trends were alkalinity, calcium, chloride, fluoride, magnesium, nitrat e, potassium, specific conductance, sulfate, strontium, and total dissolved solids. Flow was the only analyte with a downward trend. For Sequence B (Table 29), the sign tests reveal ed that nitrate had an upward trend, while phosphorus, and phosphate showed decreasing trends. For Sequence C (Table 30), the sign tests indi cated that alkalinity, calcium, chloride, fluoride, magnesium, nitrate, potassium, specifi c conductance, sulfate, strontium, and total dissolved solids, and total kjeldahl nitrogen eac h had upward trends, while flow and total organic carbon demonstrated downward trends. Except for fl ow, the analytes with statewide trends were the same in Sequence C as they were in Sequence A. No statewide trend determination for flow for Sequence B could be made because of insufficient data. Table 28. Statewide Trends Based on Sign Tests for 57 Springs, Sequence A (1991-2003). Analyte + Trend Direction P-Value Alk 29 0 Up <0.001 Ca 31 2 Up <0.001 Cl 28 5 Up <0.001 F 16 0 Up <0.001 Flow 3 14 Down 0.006 K 20 4 Up 0.001 Mg 32 2 Up <0.001 Na 30 4 Up <0.001 NO3 25 11 Up 0.014 SC* 24 8 UP 0.004 SO4 27 8 Up 0.001 Sr 27 1 Up <0.001 TDS 18 2 Up <0.001 *Specific conductivity SWFWMD and SJRWMD measured specific co nductivity (field); SRWMD measured specific conductivity (lab). Table 29. Statewide Trends Based on Sign Te sts for 57 Springs, Sequence B (1991-1997). Analyte + Trend Direction P-Value NO3 10 1 Up 0.006 P 0 11 Down <0.001 PO4 0 10 Down 0.001

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BULLETIN NO. 69 101 Table 30. Statewide Trends Based on Sign Tests for 57 Springs, Sequence C (1998-2003). Analyte + Trend Direction P-Value Alk 27 2 Up <0.001 Ca 23 1 Up <0.001 Cl 24 6 Up 0.001 F 17 0 UP <0.001 Fl0w 0 19 Down <0.001 K 23 1 Up <0.001 Mg 28 1 Up <0.001 SC* 28 1 Up <0.001 SO4 20 5 Up 0.004 Sr 21 6 Up 0.003 Sr 22 1 Up <0.001 TDS 9 2 Up 0.033 TKN 10 2 Up 0.020 TOC 2 12 Down 0.007 * Specific conductance SWFWMD an d SJRWMD measured specific conductance (field); SRWMD measured specific conductivity (lab). Constrained Version of Statewide Trends A second, more constrained, criterion was also used in the sign test evaluation. For these analyses, in order for an analyte to be considered to have a statewide tren d, not only did it need to show a significant statewide trend based on a sign test, there also needed to be significance in at least two of the three WMDs . Since several springs are located within a common springshed, the areal clustering of these latter springs can po tentially be influenced by springs having highly correlated water chemistries. For Sequence A (Tab le 31), using the more constrained approach, calcium, magnesium, sodium and strontium showed increasing statewide trends while no analyte had decreasing trends. There were insufficient flow data in the SWFWMD and, using the twoWMD criterion, no statewide trend determination could be made for flow. There were no statewide trends for analytes using the constrai ned two WMD criteria for Sequence B. However, for Sequence C, Table 32 indicates that flow d ecreased statewide, whil e calcium, magnesium, sodium, and strontium increased. Because of lack of available space in many of the following tables, abridged abbreviations are assigned to ea ch WMD for both spring and well tables. They are as follows: NWFWMD (NW), SRWMD (S R), SJRWMD (SJ), SWFWMD (SW), and SFWMD (SF). Table 31. Statewide Trends in at Least Two WMDs, Sequence A (1991-2003). (Districtwide in at leas t two WMDs and significant in at least two spring in three WMDs.) Analyte + Sig in WMD Trend Direction P-Value Ca 31 2 SR, SJ, SW Up <0.001 Mg 32 2 SJ, SW Up <0.001 Na 30 4 SR, SW Up <0.001 Sr 27 1 SJ, SW UP <0.001 SR = SRWMD, SJ = SJRWMD, SW = SWFWMD

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FLORIDA GEOLOGICAL SURVEY 102 Table 32. Statewide Trends in at Least Two WMDs, Sequence C (1998-2003). (Districtwide in at least two WMDs an d significant in at least tw o springs in three WMDs.) Analyte + Sig in WMD Trend Direction P-Value Flow 0 19 SR, SJ Down <0.001 Ca 23 1 SR, SW Up <0.001 Mg 28 1 SR, SW Up <0.001 Na 28 1 SR, SW Up <0.001 Sr 22 1 SJ, SW UP <0.001 SR = SRWMD, SJ = SJRWMD, SW = SWFWMD Independence of Springs and Wells According to Conover (1999), a sign test makes three assumptions. First, the measurement scale is at least ordinal within each pair. For this study, each pair may be determined to be a plus, a minus or a tie. Second, the pairs need to be internally consistent. That is, the probability of any one pair being plus (or minus) is the same for all pairs. Third, the pairs of data are considered to be mutually inde pendent bivariate random variables. The three assumptions are discussed in detail in Appendix E. For the analyses in this report, the first two assumptions are readily achieved. However, the third assumption was not always met. Although sampling stations are often considered to be randomly located, and each analyte to be a random variable, it is not always correct to assume that the pairs of da ta are mutually independent. Some of the springs are located within a common sp ringshed. Because of their proximity to one another, the analyte concentration in one spring may (but not necessarily) be highly correlated with other springs within the springshed. Likewise , some of the wells are in clusters; that is, the wells are located next to each other, but tap di fferent aquifers. Like springs, because of their proximity to one another, the concentration in one well may be highly correlated (but not necessarily) with the other wells in the cluster. Note the farther a station is located from a second one, the less likely the two are hi ghly correlated with each other. One way to deal with the proximity problem would be to randomly select one spring from each springshed, or one well from each cluster. This effort will reduce the dependency issue. However, it will also reduce the number of springs and wells available for analyses. Because it was very difficult to find springs and wells with sufficient data for trend analyses, it was not desirable to elim inate sampling stations. Because some of the wells are clusters, dependency due to the close proximity of wells to one another, can be, and probably is, a problem in the evaluation of well water-quality trends. Three clusters of two wells are found in the NW FWMD. Two clusters of three wells and one cluster of two wells are found in the SJRWMD. One cluster of th ree wells and two clusters of two wells are found in the SWFWMD . Finally, two clusters of tw o wells are in the SFWMD. For statewide trends, the best way to combat the problem is to: (1) emphasize analytes with strong trend signals (e.g. p-values < 0.02) a nd (2) emphasize which analytes demonstrate significant trends in, for example, at least three of the five WMDs . Quantifying the effect of dependency can be difficult. However, the strength of the statewide (and districtwide) trend signals (p-values) can assist in evaluating the dependency issue

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BULLETIN NO. 69 103 for this project. Table 33 displays the st atewide plus/minus chart for Sequence A for Alk/Bicarbonate, calcium, magne sium, strontium and fluoride fo r the 57 springs. The table reveals that for Alk/Bicarb, ther e were 29 “+” values and zero “-” values. For Sr, there were 27 “+” values and only one “-”. For both analytes, th e p-values of the sign test were <0.001. Notice in the cells in Table 33 that contains the values 29 for Alk/Bicarb and 27 fo r strontium, there is a 12* in parentheses and an 7** in parentheses resp ectively. The asterisk next to the 12 indicates that if there is no “-” value, one could have as few as 12 “+” valu es and still have a p-value less than 0.001. The double asterisk next to the 7 indicat es that if there is no “-” value, one could have as few as eight “+” values and still have a p-value less than 0.05 (the le vel of significance). Since there were 29 and 27 “+” values for Alk/Bi carb and strontium respectively, it is highly unlikely that dependency is a major factor regard ing whether or not there are statewide trends. Table 33. Selected Statewide Anal yte Results, Sequence A (1991-2003). Analyte + Direction P-Value Alk/Bicarb 29 (12*) (7**) 0 Up <0.001 Ca 31 (16*) (9**) 2 Up <0.001 Mg 32 (16*) (9**) 2 Up <0.001 Sr 27 (12*) (7**) 1 Up <0.001 F 16 0 Up 0.007 * Min. # of + and still have a probab ility value (P-Val) <0.001 with a given number of values ** Min. # of + and still have a pr obability value (P-Val) <0.050 with a given number of values Also in Table 33, note that for the rows co rresponding to calcium and magnesium, there were 31 and 32 “+” values respectively and, for both analytes there were only two “-” values. The single and double asterisks indicate that if th ere were only two “-” values, one could have as few as 16 “+” values and still have a p-value of less than 0.001. One could also have as few as 9 “+” values and still have a p-va lue of less than the significan ce level of 0.05. Since, for each analyte, there were 31 and 32 “+” values respectively, it is highl y unlikely that dependency is a significant issue when stating there are statewide trends for these analytes. Table 27 indicates that the p-values are overw helmingly, on a districtwi de basis, less than 0.02. In addition, most analytes displaying statew ide trends in Tables 28 30 have very low pvalues (generally less than 0.02). Because of the high proportion of extremely strong trend signals (low p-values), the authors conclude that although dependency is an issue to be aware of, it is not a major issue with regard to districtwide and statewide trends fo r springs for this study. Districtwide Well-Water Trends The number of wells with sufficient data for trend analyses varied per WMD between eight and 11. In addition, wells were labele d as withdrawing water from: (1) unconfined groundwater, (2) confined groundwat er, and (3) a combination of both categories (all wells combined). As with any statistical test, the smalle r the sample size, the more difficult it is to find enough evidence to reject a null hypothesis. With the low number of wells per district, evidence supporting districtwide trends wa s rare. Because the unconfined and confined groundwater wells were subdivisions of all wells, finding evidence of districtwide trends for these subdivisions was even more difficult.

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FLORIDA GEOLOGICAL SURVEY 104 Several indications of changing groundwater quality were observed. The basis of the evidence is arbitrary and is as follows. If the number of wells demonstrating trends in one direction exceed those trending in the other di rection by greater than 50 percent, it was considered to be potential (weak) evidence for a districtwide trend. However, the minimum number of wells demonstrating trends in the one direction mu st exceed the number in the opposite, minor, direction by four or more. For ex ample, Table 34 reveals that the number of wells with decreasing trends in water levels [WL(ms l)] is six and that the number with increasing trends is zero. Since the number of decreasing trends (dominant direction) exceeds the number with decreasing trends (minor) direction by at l east four, we made the interpretation that the NWFWMD had a decreasing districtwi de trend in water levels for Sequence A. The criteria was used for unconfined, confined, and the combined categories. In another example, also for Sequence A in the NWFWMD in the combin ed category, dissolved oxygen had downward trends in four wells and one well demonstrat ed an upward trend. Even though there is a dominance of downward trends, the number of wells with downward trends did not exceed the number with upward trends by more than four. Thus, the authors did not consider the existence of a potential downward trend for di ssolved oxygen for the NWFWMD. Evidence of Districtwide Well Water-quali ty Trends – Northwest Florida Water Management District Data from eight wells (six unconfined and two confined) in the NWFWMD were used. For unconfined groundwater for Sequence A, sodium and sulfate showed potential evidence for upward trends, while pH demonstrated potential evidence for downward trends (Table 34). Using the criteria mentioned a bove, with only two wells tappi ng confined groundwater, potential evidence for districtwide trends did not exis t. For the combined category (all), potential evidence for upward trends existed for sodium, sulf ate, and temperature, while pH demonstrated a potential downward trend. In addition, in th e combined category, water levels displayed a significant downward districtwide trend while wate r level above mean sea level (WL[msl]) had a potential increasing trend. Tabl e 35 displays the plus/minus (upward/downward) results for Sequence A for the NWFWMD. It also lists several potential reasons for the changes in water quality and quantity. Table 36 displays the trend results for Se quence B. For unconfined groundwater, sodium had a potential increase. For the combined cate gory, sodium and SC-fld (specific conductance field) increased while water levels decreased (T able 37). For Sequence C (Table 38), the only analyte demonstrating evidence for trends was pH. For unconfined groundw ater, as well as the combined category, it demonstrated a poten tial downward trend (Table 39).

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BULLETIN NO. 69 105 Table 34. Well Trends in the NWFWMD, Sequence A (1991-2003). (+ = trend, blank = no evidence of trend, = trend) Unconfined GW Confined Well Number Well Number Uncon Con Both (All) Analyte 67*1 91 129 131 245 313 243 312 + + + Alk + + + 2 1 1 0 3 1 Ca + + + 3 0 0 0 3 0 Cl + + 2 0 0 0 2 0 DO + 1 3 0 1 1 4 F -DL -DL -DL 0 0 0 0 0 0 Fe 0 0 0 0 0 0 K 0 1 0 0 0 1 Mg + + + 3 0 0 0 3 0 Na + + + + 4 0 0 0 4 0 NH3 0 0 0 0 0 0 NO3*2 -DL + -DL 1 1 0 0 1 1 PO4 0 1 0 0 0 1 pH 0 4 0 0 0 4 SC-f + + + + 3 2 1 0 4 2 SO4 + + + + 4 0 0 0 4 0 TDS 1 0 0 0 1 0 Temp + + + + + 4 0 1 0 5 0 TOC 0 0 0 0 0 0 Trb-l 0 2 0 0 0 2 WL(msl) 0 5 0 1 0 6 Well 67*1 taps conduit of Wakulla Spring. NO3*12 = NO3 + NO2 as N (Dissolved). DL = Trend influenced by changes in laboratory dete ction level; not due to environmental change. Well Number WMD Well ID 67 Wakulla Spring Well 91 Charles Donahue 129 Weller Ave MPZ 131 Weller Ave Shallow 243 Blountstown Floridan 245 Blountstown Surficial 312 USGS 422A NR Greenhead 313 USGS 422B NR Greenhead Table 35. Potential NWFWMD Districtwide Trends, Sequence A. (Note small sample size.) Analyte Confined or Unconfined Direction Comments Na Unconfined Up Lowering WL may be ca use of slight increase in saline analytes. pH Unconfined Down Lowering WL may be cause of decreased pH SO4 Unconfined Up Lowering WL may be cause of slight increase in saline analytes. Temp All Up Increase in air temperature WL(msl) All Down Decrease in rainfall.

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FLORIDA GEOLOGICAL SURVEY 106 Table 36. Well Trends in th e NWFWMD, Sequence B (1991-1997). (+ = trend, blank = no evidence of trend, = trend) Unconfined GW Confined Well Number Well Number Uncon Con Both (All) Analyte 67*1 91 129 131 245 313 243 312 + + + Alk + 1 0 0 0 1 0 Ca + + 2 0 0 0 2 0 Cl + 1 0 0 0 1 0 DO 0 3 0 1 0 4 F -DL -DL -DL -DL 0 0 0 0 0 0 Fe + 1 2 0 0 1 3 K 0 3 0 0 0 3 Mg + + + 3 0 0 0 3 0 Na + + + + 4 0 0 0 4 0 NH3 0 0 0 0 0 0 NO3*2 0 0 0 0 0 0 PO4 0 0 0 0 0 0 pH + 1 0 0 0 1 0 SC-f + + + + + 4 0 1 0 5 0 SO4 + 1 1 0 0 1 1 TDS 0 0 0 0 0 0 Temp + + 1 0 1 0 2 0 TOC 1 0 0 0 0 0 Trb-l 0 0 0 0 0 0 WL(msl) 0 5 0 1 0 6 Well 67*1 taps conduit of Wakulla Spring. NO3*2 = NO3 + NO2 as N (Dissolved). DL = Trend influenced by changes in laboratory detection level; not due to environmental change. Well Number WMD Well ID 67 Wakulla Spring Well 91 Charles Donahue 129 Weller Ave MPZ 131 Weller Ave Shallow 243 Blountstown Floridan 245 Blountstown Surficial 312 USGS 422A NR Greenhead 313 USGS 422B NR Greenhead Table 37. Potential NWFWMD Districtwide Trends, Sequence B. (Note small sample size.) Analyte Confined or Unconfined Direction Comments Na Unconfined, All Up Lowering WL may be cause of slight increase in saline analytes. SC-f All Up Lowering WL may be cause of slight increase in saline analytes. WL All Down Decrease in rainfall.

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BULLETIN NO. 69 107 Table 38. Well Trends in the NWFWMD, Sequence C (1998-2003). (+ = trend, blank = no evidence of trend, = trend) Unconfined GW Confined Well Number Well Number Uncon Con Both (All) Analyte 67*1 91 129 131 245 313 243 312 + + + Alk 0 1 0 0 0 1 Ca + + 2 0 0 0 2 0 Cl + 1 0 0 0 1 0 DO + + 2 3 0 2 2 5 F + 1 0 0 0 1 0 Fe 0 0 0 0 0 0 K + 1 1 0 0 1 1 Mg + + 2 0 0 0 2 0 Na + 1 0 0 0 1 0 NH3 0 1 0 0 0 1 NO3*2 + 1 0 0 0 1 0 PO4 0 1 0 0 0 1 pH 0 4 0 2 0 6 SC-f + + + 2 1 1 0 3 1 SO4 + 1 0 0 0 1 0 TDS + 1 0 0 0 1 0 Temp + + + 2 1 1 0 3 1 TOC 0 1 0 0 0 1 Trb-l + + + 3 0 0 0 3 0 WL(msl) + + 2 3 1 1 2 4 Well 67*1 taps conduit of Wakulla Spring. NO3*2 = NO3 + NO2 as N (Dissolved). DL = Trend influenced by changes in laboratory detection level; not due to environmental change. Well Number WMD Well ID 67 Wakulla Spring Well 91 Charles Donahue 129 Weller Ave MPZ 131 Weller Ave Shallow 243 Blountstown Floridan 245 Blountstown Surficial 312 USGS 422A NR Greenhead 313 USGS 422B NR Greenhead Table 39. Potential NWFMD Districtwide Trends, Sequence C. (Note small sample size.) Analyte Confined or Unconfined Direction Comments pH All Down Possibly higher mixture of younger recharge water near well screen during low water level times.

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FLORIDA GEOLOGICAL SURVEY 108 Evidence of Districtwide Well Waterquality Trends – Suwannee River Water Management District Sufficient data existed for nine wells (five unconfined and four confined) in the SRWMD (Table 40). Only pH and water levels for Se quence A for the combined category had potential trends. They were both downward (Table 41). For Sequence B (Table 42), pH demonstrated a potential downward trend for all wells (Table 43 ). However, For Sequence C (Table 44) specific conductance had a potential upward tr end for unconfined groundwater (Table 45). Water levels potentially decreased for the combined category. No evidence for trends existed for confined groundwater. However, for the combined categ ory, field specific conductance and temperature displayed a potential upward trend, while water levels had a potential downward trend. Table 40. Well Trends in the SRWMD, Sequence A (1991-2003). (+ = trend, blank = no ev idence of trend, = trend) Unconfined GW Confined GW Well Number Well Number Uncon Con Both (All) Analyte 1931 1943 2259 2465 2003 2404 2585 2675 2193 + + + Alk + + 1 1 1 1 2 2 Ca 0 2 0 1 0 3 Cl + + + 2 2 1 0 3 2 DO + + 2 0 0 1 2 1 F -DL -DL 0 0 0 0 0 0 Fe 0 0 0 0 0 0 K -Dr -DL + -Dr -Dr 1 1 0 0 1 1 Mg + 1 0 0 0 1 0 Na + + + 1 2 1 0 3 2 NH3 + 1 0 0 0 1 0 NO3*1 + -DL -DL + -DL 1 3 1 0 2 3 PO4 0 2 0 0 0 2 pH + -Dr*2 1 3 0 3 1 6 SC-f 0 1 0 0 0 1 SO4 + 1 2 0 1 1 3 TDS 0 0 0 0 0 0 Temp + + + 3 1 0 3 3 4 TOC + 1 0 0 0 1 0 Turb(lab) 0 3 0 1 0 4 WL(msl) + 0 4 1 2 1 6 NO3*1 = NO3 + NO2 as N (dissolved) DL = Trend is influenced by changing laborator y detection level; not due to environmental change. Dr*2 = High pH during early portion of time segment, which could possibly be related to well grout. Dr = Drilling fluids may be cause of hi gh concentrations during ear ly period of time segment. Well Number WMD Well ID Well Number WMD Well ID 1943 -111117007 2585 -011011002 2259 -061410003 2675 +021332004 2465 -021231001 2193 -072013001 2003 -101601002 1931 R18T11SEC3101 2404 -030833001 Table 41. Potential SRWMD Di strictwide Trends, Sequence A. Analyte Confined or Unconfined Direction Comments pH All Down High mixture of young, recharge water near well screen during drought. WL (msl) All Down Less rainfall, less recharge, and more pumping of GW

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BULLETIN NO. 69 109 Table 42. Well Trends in the SRWMD, Sequence B (1991-1997). (+ = trend, blank = no ev idence of trend, = trend) Unconfined GW Confined GW Well Number Well Number Uncon Con Both (All) Analyte 1931 1943 2259 2465 2003 2404 2585 2675 2193 + + + Alk + + 1 0 1 0 2 0 Ca 1 0 0 0 1 0 Cl + + 1 0 1 0 2 0 DO + + + 1 0 2 0 3 0 F -DL -DL 0 1 0 0 0 1 Fe 0 2 0 1 0 3 K -Dr -DL -Dr -Dr 0 1 0 0 0 1 Mg + 1 1 0 0 1 1 Na + + 1 0 1 1 2 1 NH3 0 0 0 0 0 0 NO3* -DL -DL -DL 0 3 0 0 0 3 PO4 0 0 0 0 0 0 pH 0 3 0 1 0 4 SC-f + 1 2 0 3 1 5 SO4 0 1 0 2 0 3 TDS 0 0 0 0 0 0 Temp + 1 1 0 2 1 3 TOC 0 0 0 0 0 0 Turb(lab) 0 0 0 0 0 0 WL(msl) + + + + 2 2 2 2 4 4 NO3* = NO3 + NO2 as N (dissolved) DL = Trend influenced by change in laborator y detection level; not due to environmental change. Dr = Drilling fluids may be cause of high concentrations during early period of time segment. Well Number WMD Well ID 1943 -111117007 2259 -061410003 2465 -021231001 2003 -101601002 2404 -030833001 2585 -011011002 2675 +021332004 2193 -072013001 1931 R18T11SEC3101 Table 43. Potential SRWMD Di strictwide Trends, Sequence B. Analyte Confined or Unconfined Direction Comments pH All Down Possibly higher mixture of youn ger, recharge water near well screen during low water level times.

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FLORIDA GEOLOGICAL SURVEY 110Table 44. Well Trends in the SRWMD, Sequence C (1998-2003). (+ = trend, blank = no ev idence of trend, = trend) Unconfined GW Confined GW Well Number Well Number Uncon Con Both (All) Analyte 1931 1943 2259 2465 2003 2404 2585 2675 2193 + + + Alk 0 3 0 0 0 3 Ca + 0 3 1 0 1 3 Cl 0 2 0 0 0 2 DO + + + + 4 1 0 1 4 2 F + + + + 3 0 1 0 4 0 Fe 0 0 0 0 0 0 K + 1 0 0 0 1 0 Mg + 0 1 1 0 1 1 Na + 0 2 0 1 1 2 NH3 + 1 0 0 0 1 0 NO3* + 1 1 0 0 1 1 PO4 + 1 0 0 0 1 0 pH + + 1 1 1 1 2 2 SC(field) + + + + + + 4 1 2 0 6 1 SO4 + + + 2 0 1 0 3 0 TDS 0 2 0 0 0 2 Temp + + + + + + + 4 0 3 0 7 0 TOC + 1 0 0 0 1 0 Turb(lab + 1 1 0 0 1 1 WL(msl) + 1 4 0 3 1 7 NO3* = NO3 + NO2 as N (dissolved) Well Number WMD Well ID 1943 -111117007 2259 -061410003 2465 -021231001 2003 -101601002 2404 -030833001 2585 -011011002 2675 +021332004 2193 -072013001 1931 R18T11SEC3101 Table 45. Potential SRWMD Districtwide Trends, Sequence C. Analyte Confined or Unconfined Direction Comments Temp Uncon, All Up Air temperature in WMD increased. Water temperature may be related. WL(msl) All Down Less rainfall, less recharge, and more pumping of GW. SC(field) Uncon Up Less rainfall, less dilute recharge water Evidence of Districtwide Well Water-quality Trends – St. Johns River Water Management District There were sufficient data for nine wells (three unconfined and si x confined) in the SJRWMD for districtwide trend analyses. Sin ce there were only three wells tapping unconfined groundwater, evidence of districtwide trends fo r this category of well was not achievable.

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BULLETIN NO. 69 111 For Sequence A (Table 46), for combined groundwater, alkalinity, calcium, pH, and specific conductance displayed evidence for do wnward trends while temperature displayed evidence of an upward trend (Table 47). For Sequence B (Table 48), the only evidence for a potential trend (Table 49) was pH (combined, dow nward). For Sequence C (Table 50), the only evidence for trends was in the combined cat egory. Dissolved oxygen had evidence for an upward trend while pH a nd specific conductance di splayed evidence of dow nward trends (Table 51). Table 46. Well Trends in the SJRWMD, Sequence A (1991-1998). (+ = trend, blank = no ev idence of trend, = trend) Unconfined GW Confined GW Well Number Well Number Uncon Con Both (All) Analyte 1417 1764 1781 1420 1674 1762 1763 1779 1780 + + + Alk + 0 3 1 2 1 5 Ca 0 3 0 2 0 5 Cl 0 1 0 2 0 3 DO + + 1 0 1 0 2 0 F -DL -DL -DL -DL 0 0 0 0 0 0 Fe 0 0 0 1 0 1 K -Dr -Dr 0 1 0 1 0 2 Mg + + + 1 2 2 0 3 2 Na + 0 3 1 0 1 3 NH3 + + 1 1 1 0 2 1 NO3* -DL -DL -DL -DL 0 1 0 1 0 2 P04 0 1 0 0 0 1 pH -DL 0 1 0 3 0 4 SC 0 3 0 2 0 5 SO4 + + + 2 1 1 2 3 3 TDS 0 0 0 0 0 0 Temp + + + + + + 2 0 4 1 6 1 TOC -Dr 0 0 0 0 0 0 Turb(lab) 0 1 0 0 0 1 WL(msl) + 1 0 0 1 1 1 NO3* = NO3 + NO2 as N (dissolved). DL = Reason for trend is due to a lowering of the laboratory detection level; not due to environmental change. Dr = Drilling fluids may be cause of relativel y high concentrations during ear ly period of time segment. Well Number WMD Well ID 1417 S-0045 1420 S-0038 1674 R22T10SEC2001 1762 SJ0029 1763 SJ0030 1764 SJ0032 1779 BA0054 1780 BA0055 1781 BA0056 Table 47. Potential SJRWMD Di strictwide Trends, Sequence A. Analyte Confined or Unconfined Direction Comments Alk All Down Generally as WL rose, Alk decreased; Alk low in recharge water. Ca All Down Generally as WL rose, Ca de creased; Ca low in recharge water. pH All Down Generally as pH decreased. ; pH is low in recharge water SC All Down Generally as WL rose, SC decr eased; SC low in recharge water. Temp All Up Air temperature increase.

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FLORIDA GEOLOGICAL SURVEY 112 Table 48. Well Trends in the SJRWMD, Sequence B (1991-1997). (+ = trend, 0 = no evidence of trend, = trend) Unconfined GW Confined GW Well Number Well Number Uncon Con All (Both) Analyte 1417 1764 1781 1420 1674 1762 1763 1779 1780 + + + Alk + 0 1 1 1 1 2 Ca 0 2 0 1 0 3 Cl 0 2 0 0 0 2 DO + 0 0 1 1 1 1 F -DL -DL -DL 0 0 0 0 0 0 Fe + 1 0 0 1 1 1 K -Dr -Dr 0 0 0 2 0 2 Mg 0 2 0 0 0 2 Na 0 1 0 1 0 2 NH3 0 0 0 0 0 0 NO3* -DL 0 0 0 0 0 0 P04 0 0 0 0 0 0 pH 0 1 0 3 0 4 SC + 0 2 1 2 1 4 SO4 + 0 1 1 1 1 2 TDS 0 0 0 0 0 0 Temp + + 0 0 2 1 2 1 TOC 0 0 0 0 0 0 Turb(lab) 0 0 0 0 0 0 WL(msl) + 1 0 0 0 1 0 NO3* = NO3 + NO2 as N (dissolved). DL = Reason for trend is due to a lowering of the la boratory detection level; not due to environmental change. Dr = Drilling fluids may be cause of rela tively high concentrations during early period of time segment. Well Number WMD Well ID 1417 S-0045 1420 S-0038 1674 R22T10SEC2001 1762 SJ0029 1763 SJ0030 1764 SJ0032 1779 BA0054 1780 BA0055 1781 BA0056 Table 49. Potential SJRWMD Di strictwide Trends, Sequence B. Analyte Confined or Unconfined Direction Comments pH All Down Generally pH decreased more in confined than unconfined.

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BULLETIN NO. 69 113Table 50. Well Trends in the SJRWMD, Sequence C (1998-2003). (+ = trend, blank = no ev idence of trend, = trend) Unconfined GW Confined GW Well Number Well Number Uncon Con All (Both) Analyte 1417 1764 1781 1420 1674 1762 1763 1779 1780 + + + Alk 0 2 0 0 0 2 Ca 0 1 0 0 0 1 Cl 0 1 0 0 0 1 DO + + + + 2 0 2 0 4 0 F 0 0 0 0 0 0 Fe 0 0 0 0 0 0 K + 1 2 0 0 1 2 Mg 0 1 0 0 0 1 Na + 1 0 0 0 1 0 NH3 + 1 0 0 0 1 0 NO3* 0 1 0 0 0 1 P04 0 2 0 0 0 2 pH 0 2 0 2 0 4 SC + 1 2 0 3 1 5 SO4 0 1 0 0 0 1 TDS 0 0 0 0 0 0 Temp + + + + 2 0 2 2 4 2 TOC 0 0 0 0 0 0 Turb(lab) + 1 0 0 0 1 0 WL(msl) + + + + 2 0 2 1 4 1 NO3* = NO3 + NO2 as N (dissolved). Well Number WMD Well ID 1417 S-0045 1420 S-0038 1674 R22T10SEC2001 1762 SJ0029 1763 SJ0030 1764 SJ0032 1779 BA0054 1780 BA0055 1781 BA0056 Table 51. Potential SJRWMD Di strictwide Trends, Sequence C. Analyte Confined or Unconfined Direction Comments DO All Up Generally as WL rose; DO high in recharge water. pH All Down Generally pH decreased. SC All Down Generally as WL rose, SC decr eased; SC low in recharge water. Evidence of Districtwide Well Water-quali ty Trends – Southwest Florida Water Management District There were sufficient data for 11 wells (five unconfined and six confined) in the SWFWMD for districtwide trend analyses (Table 52). No evidence of trends was found to exist for wells tapping either unconfined or c onfined groundwater. For the comb ined category (Table 53),

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FLORIDA GEOLOGICAL SURVEY 114 potential evidence existed for upward trends in temperature for Sequence A. The same can be said for Sequence B 9Tables 54 and 55). For Sequence C (Table 56), evidence existed for a downward trend in field specifi c conductance (Table 57). Table 52. Well Trends in the SWFWMD, Sequence A (1991-2003). (+ = trend, blank = no evidence of trend, = trend) Unconfined GW Confined GW Well Number Well Number Uncon Con All (Both) Analyte 736 996 7934 1087 1100 615 707 737 775 997 7935 + + + Alk + + 1 0 1 1 2 1 Ca 0 1 0 2 0 3 Cl 0 1 0 1 0 2 DO 0 0 0 0 0 0 F -DL -DL -DL 0 0 0 0 0 0 Fe + 0 0 1 0 1 0 K + -Dr + -Dr 1 0 1 1 2 1 Mg 0 2 0 1 0 3 Na + 1 1 0 1 1 2 NH3 0 1 0 0 0 1 NO3*1 -DL -DL -DL 0 1 0 1 0 2 PO4 0 0 0 0 0 0 pH + 1 1 0 2 1 3 SC-fld 0 1 0 2 0 3 SO4 -*2 + 0 2 1 1 1 3 TDS 0 0 0 0 0 0 Temp + + + + + 2 0 3 1 5 1 TOC 0 0 0 0 0 0 Trb(lab) 0 1 0 0 0 1 WLmsl 0 2 0 1 0 3 NO3*1 = NO3 + NO2 as N (dissolved). *2 The first two values of SO4 in Well 1087 are extremel y high values, and are questionable. Trend is not present if both are eliminated. DL = Reason for trend is due to a lowering of the laboratory detection level; not environmental change. Dr = Drilling fluids may be cause of relativel y high concentrations during ear ly period of time segment. Well Number WMD Well ID 736 Crewsville SH 996 Claywell Elem SF 7934 Romp 23 Surf 1087 Withla. St. Forest G 1100 Rdge MNR Rmp99x SH-A 615 ROMP 17 SWNN 707 ROMP 23-1 DEEP 737 Crewsville UP Int 775 ROMP TR 8-1 Int 997 Claywell Elem FL 7935 ROMP 23 PZ2 Table 53. Potential SWFWMD Di strictwide Trends, Sequence A. Analyte Confined or Unconfined Direction Comments Temp All Up Possibly related to higher air temperature. Wells 7934, 7935, and 1100 were not sampled un til 1999. Each had upward trends for WL. The upward trend shows up in Sequence C.

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BULLETIN NO. 69 115Table 54. Well Trends in the SWFWMD, Sequence B (1991-1997). (+ = trend, blank = no ev idence of trend, = trend) Unconfined GW Confined GW Well Number Well Number Uncon Con All (Both) Analyte 736 996 7934 1087 1100 615 707 737 775 997 7935 + + + Alk + 0 0 1 1 1 1 Ca 0 0 0 1 0 1 Cl 0 1 0 0 0 1 DO 0 0 0 0 0 0 F -DL -DL 0 0 0 1 0 1 Fe + 1 0 0 0 1 0 K -Dr -Dr -Dr 0 0 0 0 0 0 Mg + + 0 1 2 1 2 2 Na 0 0 0 1 0 1 NH3 0 0 0 0 0 0 NO3*1 -DL 0 0 0 1 0 1 PO4 0 0 0 0 0 0 pH 0 0 0 2 0 2 SC-fld + 0 1 1 1 1 2 SO4 -*2 + 0 1 1 1 1 2 TDS 0 0 0 0 0 0 Temp + + + + 2 0 2 0 4 0 TOC 0 0 0 0 0 0 Trb(lab) 1 0 1 1 2 1 WLmsl + + 1 0 1 1 2 1 NO3*1 = NO3 + NO2 as N (dissolved). *2 The first two values of SO4 in Segment B are extremely high va lues, and are questionable. Trend is not present if both outlie rs are not eliminated. DL = Reason for trend is due to a lowering of th e laboratory detection level; not environmental change. Dr = Drilling fluids may be cause of relativel y high concentrations during ear ly period of time segment. Well Number WMD Well ID 736 Crewsville SH 996 Claywell Elem SF 7934 Romp 23 Surf 1087 Withla. St. Forest G 1100 Rdge MNR Rmp99x SH-A 615 ROMP 17 SWNN 707 ROMP 23-1 DEEP 737 Crewsville UP Int 775 ROMP TR 8-1 Int 997 Claywell Elem FL 7935 ROMP 23 PZ2 Table 55. Potential SWFWMD Dist rictwide Trends, Sequence B. Analyte Confined or Unconfined Direction Comments Temp All Up Possibly related to higher air temperature.

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FLORIDA GEOLOGICAL SURVEY 116Table 56. Well Trends in the SWFWMD, Sequence C (1998-2003). (+ = trend, blank = no evidence of trend, = trend) Unconfined GW Confined GW Well Number Well Number Uncon Con All (Both) Analyte 736 996 7934 1087 1100 615 707 737 775 997 7935 + + + Alk + 1 0 0 0 1 0 Ca 0 0 0 0 0 0 Cl + 1 1 0 0 1 1 DO + 1 1 0 1 1 2 F 0 0 0 0 0 0 Fe 0 0 0 0 0 0 K + 1 1 0 0 1 1 Mg + + 2 0 0 0 2 0 Na 0 0 0 0 0 0 NH3 + 1 1 0 0 0 0 NO3* + 1 0 0 0 0 0 PO4 0 0 0 0 0 0 pH + + 2 0 0 1 2 1 SC-fld + 0 2 1 3 1 5 SO4 + 1 0 0 0 1 0 TDS + 1 0 0 0 1 0 Temp 0 0 0 0 0 0 TOC 0 1 0 0 0 1 Trb(lab) 0 1 0 0 0 1 WLmsl + + + + 2 0 2 0 4 0 NO3* = NO3 + NO2 as N (dissolved). Well Number *1 WMD Well ID 736 Crewsville SH 996 Claywell Elem SF 7934 Romp 23 Surf 1087 Withla. St. Forest G 1100 Rdge MNR Rmp99x SH-A 615 ROMP 17 SWNN 707 ROMP 23-1 DEEP 737 Crewsville UP Int 775 ROMP TR 8-1 Int 997 Claywell Elem FL 7935 ROMP 23 PZ2 Table 57. Potential SWFWMD Districtwide Trends, Sequence C. Analyte Confined or Unconfined Direction Comments SC-fld All Down Slight decrease in SC-fld. Lower in recharge water.

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BULLETIN NO. 69 117 Evidence of Districtwide Well Water-quality Trends – South Florida Water Management District For Sequence A (Table 58), there were suff icient data for six unconfined and three confined wells and there was no evidence of tren ds. For Sequence B (Table 59), again there was no evidence of trends. However, for Sequence C (Table 60), the only evidence for a districtwide trend was for unconfined, and for all wells co mbined, suggesting a downward trend for pH (Table 61). Table 58. Well Trends in the SFWMD, Sequence A (1991-2003). (+ = trend, blank = no evidence of trend, = trend) Unconfined GW Confined GW Well Number Well Number Uncon Con All (Both) Analyte 2793 2872 3109 3398 3490 6490 2873 3108 3433 + + + Alk 0 1 0 0 0 1 Ca 0 1 0 0 0 1 Cl 0 3 0 0 0 3 DO + 1 1 0 0 1 1 F -DL -DL 0 0 0 0 0 0 Fe 0 1 0 0 0 1 K -DL + 1 1 0 0 1 1 Mg 0 1 0 0 0 1 Na 0 2 0 0 0 2 NH3 + 1 0 0 0 1 0 NO3* -DL + 0 1 1 0 1 1 PO4 0 0 0 0 0 0 pH + 1 2 0 1 1 3 SC-fld + 0 1 1 0 1 1 SO4 + 1 1 0 0 1 1 TDS 0 0 0 0 0 0 Temp + 1 2 0 0 1 2 TOC 0 0 0 0 0 0 Trb(lab) 0 2 0 0 0 2 WLmsl + + 1 1 1 1 2 2 NO3* = NO3 + NO2 as N (dissolved). DL = Reason for trend is due to a lowering of the laboratory detection level; not due to environmental change. Well Number WMD Well ID 2793 G-2364 2872 C-00972 2873 C-00973 3108 L-02200 3109 L-02202 3398 PBSS44 3433 POF-0008 3490 KISSPARK 6490 27-3

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FLORIDA GEOLOGICAL SURVEY 118 Table 59. Well Trends in the SFWMD, Sequence B (1991-1997). (+ = trend, blank = no ev idence of trend, = trend) Unconfined GW Confined GW Well Number Well Number Uncon Con All (Both) Analyte 2793 2872 3109 3398 3490 6490 2873 3108 3433 + + + Alk 0 1 0 0 0 1 Ca 0 1 0 0 0 1 Cl 0 3 0 0 0 3 DO + 1 0 0 0 1 0 F 0 1 0 0 0 1 Fe 0 1 0 0 0 1 K + 1 1 0 0 1 1 Mg + 1 1 0 0 1 1 Na 0 2 0 0 0 2 NH3 0 0 0 0 0 0 NO3* 0 0 0 0 0 0 PO4 0 0 0 0 0 0 pH + 1 0 0 0 1 0 SC-fld 0 2 0 0 0 2 SO4 + + 2 1 0 0 0 0 TDS 0 0 0 0 0 0 Temp + 1 2 0 0 1 2 TOC 0 0 0 0 0 0 Trb(lab) 0 0 0 0 0 0 WLmsl + + 1 0 1 0 2 0 NO3* = NO3 + NO2 as N (dissolved). Well Number WMD Well ID 2793 G-2364 2872 C-00972 2873 C-00973 3108 L-02200 3109 L-02202 3398 PBSS44 3433 POF-0008 3490 KISSPARK 6490 27-3

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BULLETIN NO. 69 119Table 60. Well Trends in the SFWMD, Sequence C (1998-2003). (+ = trend, 0 = no evidence of trend, = trend) Unconfined GW Confined GW Well Number Well Number Uncon Con All (Both) Analyte 2793 2872 3109 3398 3490 6490 2873 3108 3433 + + + Alk + + 2 0 0 0 2 0 Ca 0 0 0 0 0 0 Cl + + 2 0 0 0 2 0 DO + 0 0 1 0 1 0 F 0 1 0 0 0 1 Fe 0 0 0 0 0 0 K 0 1 0 0 0 1 Mg 0 1 0 0 0 1 Na + 1 0 0 0 1 0 NH3 + + 2 0 0 0 2 0 NO3* 0 1 0 0 0 1 PO4 + 1 0 0 0 1 0 pH + 0 4 1 1 1 5 SC-fld + 1 2 0 0 1 2 SO4 0 0 0 0 0 0 TDS 0 0 0 0 0 0 Temp + 1 2 0 0 1 2 TOC 0 1 0 0 0 1 Trb(lab) 0 0 0 0 0 0 WLmsl + + 2 2 0 0 2 2 NO3* = NO3 + NO2 as N (dissolved). Well Number *1 WMD Well ID 2793 G-2364 2872 C-00972 2873 C-00973 3108 L-02200 3109 L-02202 3398 PBSS44 3433 POF-0008 3490 KISSPARK 6490 27-3 Table 61. Potential SFWMD Districtwide Trends, Sequence C. Analyte Confined or Unconfined Direction Comments pH Uncon, All Down Generally pH fell during all tim e segments. Possibly related to slight decreases in water levels

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FLORIDA GEOLOGICAL SURVEY 120 Statewide Well Water-quality Trends Table 62 shows analytes with statewide trends for each time sequence for unconfined, confined, and all (combine d) groundwater resources. Table 62. Statewide Groundwater Trends Base d on Sign Tests: Sequences A, B, and C. Sequence A (1991 2003) Groundwater Resource Unconfined GW Confined GW All WL(msl) p-val = 0.019 WL(msl) p-val= 0.004 Turb p-val = 0.004 Turb p-val= 0.002 Ca p-val = 0.035 pH p-val = 0.04 pH p-val = <0.001 Temp p-val = 0.035 Temp p-val = 0.036 Sequence B (1991 1997) Groundwater Resource Unconfined GW Confined GW All None pH p-val = 0.031 pH p-val = 0.039 Sequence C (1998 2003) Groundwater Resource Unconfined GW Confined GW All None None pH p-val = 0.011 Temp p-val = 0.041 For Sequence A, Table 62 reveals that temp erature had an upward trend statewide for unconfined and combined groundwater. For unconf ined groundwater, turbidity and water levels had downward trends while pH trended downward in confined groundwater. For combined groundwater, calcium, temperature, turbidity, wate r levels and pH had downward trends. By defining strong trends as those with p-values of less than 0.02, pH and water levels had strong downward trends for combined groundwater. Du ring Sequence B, pH had downward trends in confined and in the combined groundwater res ources. During Sequence C, pH had a strong downward trend in the combined gr oundwater resources. Temperature had an upward trend. Comparison of Strong Statewide Trends for Groundwater and Spring Water Whereas well water (Table 62) displays strong trends in calcium and several field analytes, Table 63 indicates that rock and saline indicators show strong (p -value <0.02) statewide trends for springs. In Table 63, during Sequence A, flow had a significantly decreasing trend and the following rock-matrix indicators had upward trends: alkalinity, calcium , chloride, fluoride, potassium, magnesium, sodium, specific conductan ce, strontium, sulfate, and total dissolved solids. No rock-matrix or saline indicator had a significant trend durin g Sequence B. Trends during Sequence C were the same as those in Sequence A with one exception. Whereas total

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BULLETIN NO. 69 121 dissolved solids did have a strong significant upward trend during Se quence A, it did not display a significant upward trend during Sequence C. Table 63. Statewide Spring-water Quality Summary for Rock and Saline Indicators. (Only indicators displaying strong significant trends (P-Value < 0.02) Sequence A (1991 2003) Analyte Trend Direction P-Value Flow Down 0.007 Alk Up <0.001 Ca Up <0.001 Cl Up <0.001 F Up <0.001 K Up 0.001 Mg Up <0.001 Na Up <0.001 SC Up 0.007 Sr Up <0.001 SO4 Up <0.001 TDS Up <0.001 Sequence B (1991-1997) No rock or saline indicators displayed a trend. Sequence C (1998-2003) Flow Down <0.001 Alk Up <0.001 Ca Up <0.001 Cl Up 0.002 F Up <0.001 K Up <0.001 Mg Up <0.001 Na Up <0.001 SC Up 0.005 Sr Up <0.001 SO4 Up 0.007 Constrained Version of Statewide Trends A second, more constrained, criterion was also used in the sign test evaluation. For these analyses, in order for an analyte to be considered to have a statewide tren d, not only did it need to show a statewide trend based on a sign test, it also needed to have evidence of a districtwide trend in at least three of the five WMDs. Re garding combined groundwater resources, Table 64 indicates that for Sequence A, calcium, pH, and water levels had downward trends, while temperature had a statewide incr easing trend. All were strong tr ends. The analyte pH had a

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FLORIDA GEOLOGICAL SURVEY 122 significant downward trend during Sequence B wh ile pH had a downward trend and temperature had an upward trend during Sequence C. The pH trend was strong. Table 64. Statewide Trends for at Least Three WMDs: Sequences A, B, and C for Combined Groundwater Resources. Statewide Sequence A ( 1991-2003) Trends in at Least three WMDs Analyte + Eviden ce in WMD Trend Direction P-Value* Ca 3 12 SR, SJ, SW Down 0.016 pH 3 20 NW, SR, SJ, SW, SF Down <0.001 Temp 20 8 NW, SJ, SW Up 0.018 WL(msl) 4 18 NW, SR, SW, Down 0.002 Statewide Sequence B (1991-1997) Trends in at Least 3 WMDs Analyte + Evidence in WMD Trend Direction P-Value* pH 2 10 SR, SJ, SW Down 0.020 Statewide Sequence C (1998-2003) Trends in at Least 3 WMDs Analyte + Evidence in WMD Trend Direction P-Value* pH 5 18 NW, SJ, SF Down 0.006 Temp 15 5 NW, SR, SJ Up 0.021 * In addition to a p-value <0.05, there must be significant trends in at least three of the five WMDs. DISCUSSION Recall that the definition of a constr ained statewide trend was that at the = 0.05 level of significance for springs, analytes al so had to have statistically significant trends using the sign test in two of the three WMD regions [(1) SR WMD plus Wakulla Spring, (2) SJRWMD, and (3) SWFWMD]. For wells, analytes had to have statis tically significant trends using the sign test in three of the five WMDs. Considering the cons trained versions of st atewide trends, Table 65 summarizes the results. For spring-water quali ty, calcium, magnesium, sodium, and strontium had increasing trends during Sequence A and C. In addition, flow had a decreasing trend for Sequence C. For combined groundwater, duri ng Sequence A, temperature increased while calcium, pH, turbidity, and water levels decrea sed significantly. For Seque nce B, pH decreased while for Sequence C, pH decreased and temperature increased. Spring-water quality is considered an integr ator of what affects groundwater during its flow path from the recharge area to the spring di scharge point. Regarding springs, there were no strong rock and saline trends during Sequence B. Because of the highly correlative relationship among the rock and saline indicators during Sequen ce A and C, it indicates that the time period of Sequence C (1998-2003) was the one in which mo st trends developed and is also when the drought occurred. The evidence de rived from well-water quality is not nearly as strong. However, there is supporting evidence. Regard ing well-water quality, no strong trends occurred during Sequence B. The indicator pH had strong decr easing trends in Sequence A and C and a significantly decreasing tre nd during Sequence B.

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BULLETIN NO. 69 123 Table 65. Constrained Statewide Spring and Groundwater-quality Summary. Sequence Springs All GW (Unconfined and Confined) A (1991 2003) Ca Ca Mg pH Na Temp Sr Turb WL(msl) B (1991 1997) pH C (1998 2003) Flow pH Ca Temp Mg Na Sr Major Cause of Statewide Trends: Drought and Consequential Saltwater Encroachment From a districtwide or a statewide perspective, if regional trends di d not exist, one would expect, for a given analyte, a similar number w ould increase as would decrease. However, the results of sign tests in this study, especially on th e statewide scale, indica te that for springs the rock-matrix and the saline indicato rs were the two groups that had the vast majority of area-wide trends for Sequences A and C. In wells, the field indicators, such as temperature, water levels and pH, were the ones that displayed large, area-wi de trends. Districtwide and statewide trends occurred mostly in Sequences A and C, but not very often in Sequen ce B (1991-1997). What are the causes of the rock, saline, and field indicator trends? Are the causes related? Is there one overall reason for the trends, or ar e there a variety of reasons? The most severe portion of the drought occu rred during the 1999-2000 time frame (Verdi et al., 2006). Could the reasons for the area-wide trends be related to the drought? If saline indicators trended upward during the study period, is it an indica tion that Florida experienced saltwater encroachment on a regional and/or statewid e scale? We decided that for this paper, we would differentiate between the terms saltwater encroachment and saltwater intrusion. As modified from Neuendorf et al. ( 2005), saltwater encroachment is defined as the displacement of fresh groundwater by the advance of saltwater due to its greater density. Freeze and Cherry (1979) use the term intrusion as the migration of saltwater into freshwater aquifers under the influence of groundwater development. For our purposes, intrusion indicates a man-induced process , while encroachment makes no such distinction between natural and man-made causes . Because the drought lasted for much of the 13year time frame of the study, we addressed the drought-related questions by reviewing annual weather data for Sequences B and C. We believed that these data could shed light on the behavior of field indicators such as temperature, spring flow, and water level. Temperature was addressed first. Table 66 displays mean annual statewide temperatures and rainfa ll for Sequences B and C, based on data from the Southeastern

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FLORIDA GEOLOGICAL SURVEY 124 Regional Climate Center (2006). Regarding air temperature (Table 66), there were 84 SERCC weather stations in Florida with sufficient da ta to calculate annual means for the 1991-2003 time period. For these stations, the mean temperature for Sequence B was 22.12 ° C (71.81º F) and the mean for Sequence C was 22.23 ° C (72.02 º F), a slig ht increase. Figure 54 depicts the year to year changes in mean temperature. Table 66. Summarized Annual Weather Data in Florida (1991-2003). Category Sequence B (1991 1997) Sequence C (1998 – 2003) Difference (Seq. C Seq. B) Mean Air Temperature (84 Weather Stations) 22.12 ° C (71.81 º F) 22.23° C (72.02 º F) + 0.12 ° C (+ 0.21 º F) Mean Rainfall (88 Weather Stations) 139.64cm/yr (54.98 in/yr) 127.76 cm/yr (50.30 in/yr) +11.89 cm/yr (4.68 in/yr) Regarding rainfall (Table 66), there were 88 stations with sufficient data to calculate annual means. For Sequence B, the mean was 139.64 cm/yr (54.98 in/yr). For Sequence C, the mean was 127.76 cm/yr (50.30 in/yr). Figur e 54 indicates that beginning in 1999 and continuing through 2000, Florida e xperienced a very dry period. It began one year after the beginning of Sequence C. During Sequence C, th ere was a deficit of between 10 and 13 cm/yr (four and five in/yr) of rainfall a nnually relative to Sequence B. With reduced rainfall, there was less recharge to groundwater and, conse quently, spring flow declined. In searching for an explanation for the st atewide trends, the drought and saltwater encroachment can explain virtually all of the rock-matrix and sali ne-indicator trends. Recall that Florida’s fresh groundwater forms a “lens” of freshwater that, because of its lower density, overlies saline water. During periods of abundant rainfall, aquifer rech arge exceeds discharge and the freshwater “lens” increas es in size. However, during the state’s periodic droughts, the rate of aquifer recharge is less than discharge and the “lens” shrinks in size. With less recharge, the potentiometric surfaces of aquifers are lowere d and spring flow declines. As they decline, we believe that younger and freshe r groundwater discharging from sp rings is eventually replaced by deeper and older water. The deeper water c ontains more minerals (transition zone water) because it has been in the aquifer system for a longer period of time. This idea is supported by Upchurch (1992) and Ka tz (2004). Figure 55 illustrates the relative position among sea water, transition water (including both “ outer” and “inner”) and freshwater within the Floridan aquifer system. Note the relationship between “outer ” and “inner” transition water. The “outer” contains a greater proportion of saline indicators, while the “inne r” water contains a greater percentage of rock-matrix analytes. Figure 56 depicts a schematic of possible en croachment before and during a drought. During the drought, aquifer water levels decline, in ferring that the fresh water” lens” decreases in size. Coastal springs, or springs that are tidally influenced, experience lateral encroachment of sea water. Inland springs can also be affected. Encroachment can occur because of the potential replacement of older and denser saline water at the base due to the lowering of the head in the Upper Floridan aquifer system. If the potentiometric surface of the UFAS become less than the aquifers lying below the UFAS, saline water can invade from below.

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BULLETIN NO. 69 125 YearDeg F 2004 2002 2000 1998 1996 1994 1992 1990 73.5 73.0 72.5 72.0 71.5 71.0 Annual Mean Air Temperature in Florida (1991 2003)(From 84 SERCC Weather Stations) YearInches / Yr 2004 2002 2000 1998 1996 1994 1992 1990 60 55 50 45 40 Annual Mean Rainfall in Florida (1991 2003)(From 88 SERCC Weather Stations) Figure 54. Weighted mean temp erature and rainfall data in Florida (1991-2003). Horizontal lines in each time sequence, represent the correspond ing mean values. (1.00 in = 2.54 cm; °C = (5/9)[°F – 32.00.) It should be understood that the confin ing units below the UFAS generally retard the upward encroachment of deep, confined saline water. Nevertheless, because of the drought Sequence B Sequence C Mean = 71.81 Mean = 72.01 Mean = 54.98 Mean = 50.30

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FLORIDA GEOLOGICAL SURVEY 126 during Sequence C, on a statewide basis, we infe r saline encroachment did occur and that the extent varied across the state dependi ng on the severity of the drought. During a drought, there is less surface water runoff. Thus, there is not as much young less-mineralized surface water recharging Florida’s aquifers through swallets and sinks. Again, this is favorable for increasing trends in ro ck and saline indicators in spring discharge. Figure 55. Relative position of rock-matrix and saline analytes in the Upper Floridan aquifer system. Drought Verdi et al. (2006) mentioned that a drought is a time of less-than-normal or expected rainfall. It can be thought of as a period of time when there is insufficient wa ter to support the agricultural, urban or environmen tal needs of a society. They also stated that a hydrological drought is an extended period during which stream flow, la ke, reservoir storage, and groundwater levels are below normal. Referring to a drought, Jackso n (1997) said, “In general, an extended period of dry weather or period of deficient rainfall that may extend over an indefinite number of days. There is not a quantitative standard to determine th e degree of deficiency needed to constitute a drought. Qualitatively, a drought may be defined by its effect as a dry period of sufficient length and severity to cause at least partial crop failu re or having impacted the ability to met normal water demand.”

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BULLETIN NO. 69 127 Figure 56. Fresh groundwater wedge before and during a drought. Top – Saline transition water (hatched) and saline water surround Florida. During normal times, freshwater “lens” is thic ker and spring flow is greater. Bottom Reduction in spring flow reflects freshwater “lens” decrease. Reduction draws in saline water, both laterally and potentially from below. Na Cl K Seawater Spring Flow Water Table High Normal Freshwater Lens Gulf of Mexico Atlantic Ocean Florida Platform (Limestone) Transition Zone Mg Ca SO4 Alk Land Sf Freshwater Lens Na Cl K Seawater Spring Flow Water Table Dro p Reduced Freshwater Lens ( Due to Drou g ht ) Transition Zone Mg Ca SO4 Alk Gulf of Mexico Atlantic Ocean Florida Platform (Limestone) Land Sf Freshwater Lens

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FLORIDA GEOLOGICAL SURVEY 128 According to Henry (1998), the 30-year aver age (1961-1990) rainfall in Florida was just over 53 inches (135 cm) per year . For the 1999 and 2000 time frame, Florida had a deficit of over 30 inches (76 cm), relative to its 30-year mean. Also, since the average rainfall during Sequence C was only 50.30 inches/yr (127.8 cm/yr), Florida was in a drought. In fact, in 2001 the FDEP and the Florida Department of Commun ity Affairs (2002) stated that, at that time, Florida was in the midst of an historical seve re drought. The severity of the statewide drought varied depending on the local precipitation (Appe ndix M, Online). Thus, the severity of the drought and the corresponding saltwater encroach ment also varied across the state. Rock-Matrix and Saline Indicator Evidence in Spring-water Quality In Florida, recharge generally occurs firs t in the uppermost portion of aquifers and recharge water is younger than deeper water. T hus, during times of less recharge as spring flow is reduced, the proportion of older (transition) wa ter increases. The older water is enriched in rock-matrix analytes. The fact that rock and saline indicators demonstrated strong increasing trends across the state (Tables 27-30), while flow had a strong decreasing trend is a compelling argument that Florida’s freshwater “lens” decreased in size and saltwater encroachment did occur during Sequence C. Unfortunately, determining the locations where the actual encroachment took place cannot be determined w ith these sets of data. In the future, better monitoring should allow the state to make these determinations. Rock-Matrix and Saline Indicator Evidence in Well-water Quality Recall that the wells used for th is report are TV wells and that they tend to be relatively shallow. Although the maximum depth of any of the wells used in this study is 1000 feet, 50 percent of the wells are between 57 and 161 feet (17 and 49 m) (Appendix C, Online) and, as previously stated, the median de pth of the wells is 80 feet (24 m). The wells generally tap the upper portion of the corresponding aquifer. Figure 57 is a diagram of an unconfined well. Note the relative position of the well intake zone (well screen) to the water table. Under our hypothesis, gr oundwater just below the water table has the lowest pH. During wet periods (Figure 57, top) , the distance from the intake zone to the water table (static water level) is at its maximu m. During the drought (Figure 57, bottom), the water table was slowly lowered. As it dropped, a greater and greater proportion of groundwater with lower pH found its way into the well intake zone. As the drought continued, water levels, along with pH, decreased. There is no evidence that pH decreased throughout the groundwater column only that th e water table, with the most acidic wa ter, moved downward closer and closer to the well intake zone during the drought. Other explanations can explain the correlation between water level and pH. For example, D. Harrington (FDEP, personal co mmunications) suggested that th e lowering of the water table and subsequent oxidation in the uppermost porti on of the saturation zone during a drought, could lead to a release of reduced sulfur compounds and a subsequent lowering of pH. P. Hansard (Colorado School of Mines, personal communicati ons) supported Harringt on’s interpretation.

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BULLETIN NO. 69 129 Figure 57. Water level and pH relat ionships for a well with a falling water table. Top (Time 1) – the upper portion of the water table gene rally consists of recently recharged, low pH metoric water. Botom (Time 2) heavy pumping and drought conditio ns lower the water table, introducing progressively lower pH water to the well screen. As the water table is lowered, low pH water near the top of the water table moves closer and closer to the well screen.

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FLORIDA GEOLOGICAL SURVEY 130 As water levels decreased, dissolved oxygen could increase in the vicinity of the well. The increases in aerobic microbial respiration c ould increase carbon dioxide content, and consequently lower pH. He noted there did not need be a net change in pH in the entire groundwater column; simply that the zone of maximum respiration (e.g. the water table) got closer to the well screen duri ng the drought. Although the specific s are not totally understood, the hypothesis that the lowering of pH is related to the lowering of water le vels is testable. As Florida fully recovers from the drought, wate r levels and pH values should increase. Table 62 indicates that for combined groundw ater during Sequence A, decreasing trends occurred, not only for both water level and pH, but also for temperature, turbidity and calcium. Groundwater temperature increased statewide, while turbidity and calcium decreased. The most plausible explanation is that groundwater temper ature increased as air temperature increased. Recall that most of the 46 wells were relatively shallow. An inspection of air temperature (Southeast Regional Climate Center, 2006) reveal ed that air temperature increased during Sequence A. An addition, spring wa ter, which is an integrator of the entire springshed, both deep and shallow, had no temperature trends. Regarding turbidity, no districtwide trends were observed and the only statewide trend occurred during Sequence A for combined (unc onfined and confined) groundwater. Appendix B1 indicates that turbidity is a measure of light to pass through a water sample. It is caused by particulate material suspended in the water and colloidal material that hinders light penetration. The source of turbidity is ofte n from surface water that contains high concentrations of humic substances and/or particulate matter, chemical reactions that result in the precipitation of colloidal material and certain forms of pl ankton growth. During the drought, less water originating from land surface can find its way in to wells. Thus, the drought is a plausible explanation for the decreasi ng trends in turbidity. The reason for the decr easing trend in calcium in wells is not fully understood. Calcite precipitation increases with increasing temperature. Thus, the increasing in temperature may be a cause for decreasing calcium concentrations. Paradoxically, increases in carbon dioxide near the well intake zone as water levels decreased (Figure 57) shoul d cause calcite dissolution, and raise calcium concentrations. Mo re research is needed in orde r to fully understand the positive correlation between water levels and calcium concentrations. Regional to Sub-Regional Eviden ce of Saltwater Encroachment In springs, rock-matrix and sa line indicators demonstrated st rong increasing trends across the state (Tables 27-32) while flow had a strong decreasing trend. Together they are compelling arguments that Florida’s freshwater “lens” decr eased in size and saltwater encroachment did occur during Sequence C. Annual mean temperat ure and precipitation data for each station, and for each WMD, are found in Appendix M (Online) . The data were used to calculate the weighted statewide means (weighted by the number of stations in each WMD) for rainfall used in the time series plots in Figure 58.

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BULLETIN NO. 69 131 YearInches / Yr 2004 2002 2000 1998 1996 1994 1992 1990 65 60 55 50 45 40 Variable SWFWMD NotSWFWMDSWFWMD Compared to Remainder of Florida Figure 58. Weighted mean annual rainfall during Sequence A. An inspection of rainfall data in Appendix M (Online) for each of the WMDs indicates that the rainfall deficit during Sequence C was le ss in the SWFWMD than the other regions of Florida. For this discussion, consider the SWFWMD (and surrounding area) to be a “donut hole” and the remaining WMD areas to be a “donut.” A comparison of the “donut hole” to the “donut ” is found in Table 67. The table reveals that the weighted mean annual temperature in the SWFWMD “donut hole” for Sequence B was 22.59 ºC (72.66 ºF), whereas in Se quence C, it was only 22.56 °C ( 72.61 ºF), a decrease of (0.03 ºC (0.05 ºF). During Sequence B, the weighted mean annual rainfall in the “donut hole” was 131.55 cm/yr (51.79 in/yr) while the rainfall decreased to 131.50 cm/yr (51.77 in/yr) for Sequence C, a decrease of only 0.05 cm/yr (0.02 in/yr). Table 67. Annual Weather Data, four WM Ds Compared to SWFWMD (1991-2003). Sequence WMD Mean Annual Sequence B Sequence C Difference (Seq. C Seq. B) Temp 22.59 °C (72.66 º F) 22.56 °C (72.61 º F) 0.03 °C (0.05 º F) SW “Donut Hole” Rain 131.55 cm/yr (51.79 in/yr) 131.50 cm/yr (51.79 in/yr -0.05 cm/yr (0.02 in/yr) Temp 22.01 °C (71.61 º F) 22.17 °C (71.90 º F) + 0.16 °C (+ 0.29 º F) NW, SR, SJ, SF “Donut” Rain 142.60cm/yr (56.14 in/yr) 126.42 cm/yr (49.77 in/yr) 6.37 in/yr (16.18 cm/yr)

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FLORIDA GEOLOGICAL SURVEY 132 Consider the “donut.” It had different weather conditions, rela tive to the “donut hole.” For the “donut”, during Sequence B, the temp erature averaged 22.01 °C (71.61 º F) and for Sequence C, the mean temperature was 22.17 ºC ( 71.90 ºF), an increase of 0.16 ºC (0.29 ºF). Regarding precipitation, during Sequence B, the “donut” averaged 142.60 cm/yr (56. 14 in/yr) of rain, and during Sequence C, it averaged only 126.42 cm/yr (49.77 in/yr), a deficit of 16.18 cm/yr (6.37 in/yr). Interestingly, during the worst of th e drought (1999-2000) the SWFWMD “donut hole” region suffered severely (Verdi et al., 2006). As it turns out the SWFWMD region was also dryer during Sequence B, relative to the rest of the state (Figur e 58). Nevertheless, during the last two years of Sequence C, it recovered and actually had a more normal rainfall than the remainder of Florida (Figure 58). Now consider each WMD. If one subtracts the mean rainfall during Sequence C from the mean of Sequence B at each rain station, then Tabl e 68 indicates that the nu mber of rain stations in the NWFWMD with an increase in rainfall was one, while the number with decreasing rainfall was eight. Using a sign test, the correspondin g p-value was 0.020, and thus, there existed a downward trend in annual mean rainfall for the NWFWMD. The table also indicates that downward trends existed in the SRWMD, the SJRWMD, and the SFWMD. However, no trend was present in the SWFWMD “donut hole.” To re iterate, in terms of rainfall, for Sequence C, the SWFWMD suffered severely during the worst part of th e drought (1999-2000) but only suffered mildly, relative to the rest of Florid a, if one considers the entire 1998-2003 Sequence C time frame. Table 68. Summarized rainfall, Sequence C minus Sequence B. WMD + P-Val Trend NWFWMD 1 8 0.020 Down SRWMD 0 11 <0.001 Down SJRWMD 2 19 <0.001 Down SWFWMD 12 10 0.416 No Trend SFWMD 6 19 0.007 Down Number of stations in which rainfall in Sequence C > than same station in Sequence B = + Number of stations in which rainfall in Sequence C than same station in Sequence B = (Source: Southeast Regional Climate Center, 2006) In spite of the relatively mild affect of decreased rainfall during the entire duration of Sequence C, there were many indications that th e spring-water quality within the “donut hole” suffered severely. Table 27 displays the analytes with trends for each of the three time sequences for springs. Note the discussion that follows may be indi cative that the severe affect denoted earlier may not have had time to revers e. On the other hand, it may indicate that saline encroachment (or even intrusion) was a problem during Sequence C. Recall that during Sequences A and C, we cons ider increasing trends in saline and rockmatrix indicators, along with decreasing trends in spring flow and water levels, to be an indication of a decreasing volume of fresh water in Florida’s aq uifers and an indication of

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BULLETIN NO. 69 133 saltwater encroachment. As spring flow decrea sed, spring discharge water was replaced with older, more mineralized water. The statew ide changes in groundwat er quality, along with statewide decreases in aquifer potentiom etry, support this perspective. For the following analysis consider Wakulla Spring to be part of the SRWMD. If one only considers saline (including flow) and ro ck-matrix indicators for Sequence A in the SRWMD (plus Wakulla), flow decreased while ca lcium, magnesium, and sodium increased. For the SJRWMD, calcium, fluoride, and strontium increased. However, for the SWFWMD, ten rock and saline analytes had increasing trends . They were calcium, bicarbonate, magnesium, strontium, potassium, sodium, chloride, sulfate, sp ecific conductance, and total dissolved solids. During Sequence C, strong trends were obser ved in seven saline indicators in the SWFWMD: strontium, potassium, sodium, chlori de, sulfate, specific conductance, and total dissolved solids had upward trends . In addition, three rock indicators: calc ium, bicarbonate, and magnesium had upward trends. Suff icient spring flow was only ava ilable at three stations in the SWFWMD (Homosassa Springs, Chassaho witzka River near Chassahowitzka, and Chassahowitzka River near Homosassa Springs) . Flow was observed to decrease (see Homosassa and Chassahowitzka Springs in Tabl e 26 and Appendix K). Data from only three springs are insufficient to estimate a regional trend. However, it is plausible, that if additional spring flow data were available, they would demonstrate that significant downward trends in spring flow in the SWFWMD did occur. The increasing trends in saline and rock indi cators indicate that salt-water encroachment occurred during Sequence C. Although data suggest s that encroachment was most severe in the SWFWMD, because the concentrati ons of saline analytes increa sed almost everywhere in the state during the drought, it is an in dication that encroachment occurr ed on a statewide scale. The 1998-2002 drought was one of the worst histor ical droughts to aff ect Florida (Verdi et al, 2006. In order to make up for the drought, groundwater pumpi ng increased (Verdi et al., 2006). Because an increase in groundwater pumpi ng occurred during one of worst droughts, it is likely that human-induced saline intrusion took place. On a statewide scale, the extent and severity of the intrusion is difficult to quantify. However, within the northern portion of the SWFWMD, a water budget and a regional groundwater flow model indicated that the affect of groundwater withdrawals was less than 2.0% of the a ffect due to the loss of recharge because of decreased rainfall (Ron Basso, personal communicati ons). Nevertheless, intrusion should be a concern. If another drought of this magnitude occurs, depending on the amount of increased pumping, it could potentially have adverse affect s on the long-term sustai nability of FloridaÂ’s groundwater resources. Groundwater Withdrawals The Florida Department of Environmental Pr otection (2008) stated that water use in Florida will increase as Flor idaÂ’s population grows. The population in 1990 was officially 12,937,926. In 2000 it was 15,982,378 and by 2003 it was 16,713,149 (U.S. Census Bureau, 2006). Over those 14 years, it grew by 3,775,223, an increase of over 730 people per day.

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FLORIDA GEOLOGICAL SURVEY 134 According to Marella and Berndt (2005), Fl orida’s groundwater withdrawals for all water use categories (agriculture, publ ic supply, commercial/industria l, recreation, domestic, and power generation) in 2000 exceeded 3.1 billion gallons per day. Of those categories, agriculture and public supply accounted for over 82 percent. If divided evenly amongst the population, in 2000, over 190 gallons per day (gpd) of groundwater were used by each person of the state. Since Florida’s population is growing by 730 peopl e per day and each new person is using over 190 gpd, then the demand for grou ndwater increases by more th an 135,000 gpd or by more 50 million gallons per year. Because of the lack of precipitation, in an effort to make up for the lack of rain, the pumping of groundwat er typically increased during droughts. Thus during Sequence C the drought, the increased population and the in crease in consumption of groundwater each had a negative impact on both the quantity and quality of Florida’s gr oundwater resources. Groundwater Summary Groundwater quantity and quality data indicate s that during Sequence C, Florida suffered from natural saltwater encroachment during the drought. The ability to quantify the extent and severity of the encroachment problem on a statewide basis is not possible at this time due to lack of sufficient data. The drought caused a dec line in recharge which in turn lowered the potentiometric surfaces in Florida’s aquifers fo llowed by a decrease in spring flow. This was exacerbated by: (1) the increased pumping of groundwater during the drought and (2) the increased demand for groundwater because of th e increased population. The consequence of the drought and the increased pumping of groundwater wa s saltwater encroachment. It is indicated by decreasing trends in spring flow and increasing trends in the c oncentration of rock and saline indicators. A return of normal rainfall should greatly help in reversing the process. In the future, spring monitoring and trend analyses should identify any changes. In addition, water conservation practices, along with minimum flow s and levels (MFLs) (Florida Statutes,1983, Chapter 373.042) being established by the WMDs s hould mitigate the affect of future droughts. Nevertheless, the monitoring of population growth, pumping of groundwater, per capita water use, as well as water quality and quantity, are also needed in order to properly manage our water resources. Miscellaneous and Important Issues Falling Well Water Levels – A Districtwide and Statewide Problem in Wells Well-water level trends were consistent with what was seen in spring flow. The most common single trend seen among wells was a simu ltaneous decrease in water level and pH. Trends were seen in both confined and unconf ined wells and both limestone and siliciclastic aquifers. This suggested the cause transcended lo cal aquifer or rock-matrix characteristics. A physical linkage between water level and pH can be established, at leas t for the shallow wells used in this study, by referring ag ain to Figure 57. Recall that we lls penetrate the overlying rock to the point of an intake zone marked by a we ll screen. The drought or excessive groundwater withdrawal lowered the water table in relation to the intake zone. An explanation for the drop in

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BULLETIN NO. 69 135 pH, in conjunction with the fall of the water ta ble, involves the water ch emistry near the top of the water table. Since decreases in groundwater levels prog ressively allow greater volumes of lower pH water into the well screen, this creates the obs ervation—over time—that pH is dropping. Therefore, the statewide lowering in well water levels corresponds to drops in pH. Thus, the chemical and physical trends in well water during the drought may simply reflect the increasing proximity of the upper portions of the water table to the well screen. A second statewide trend observed in the sh allow wells was an increase in water temperature. For Sequence A, increasing trends in temperature were observed on a statewide scale for unconfined groundwater but not for confined groundwater (Table 62). Increasing trends were evident in some districts (e.g., SRWMD) but not in others (e.g., SJRWMD and SWFWMD). There are several plausi ble explanations for the trends. The first involves the type of pumps used. Grundfos Redi-flo 2 pumps were the well pump most often used. These submersible pumps need well water to cool the pu mp motors. Samplers, particularly for large wells during sample collection, observed the wa rming of water. In comparison, peristaltic pumps were also used (e.g. for shallow wells less than 25 feet deep) and fo r springs. For these pumps, samplers did not observe altered water temperatures. It is not likely that pump heating was the ca use of increased distri ctwide and statewide temperature trends. The heating of water is not the same as the creation of an upward trend in a time series. In order for a trend to be observed, it would require not only that water be heated within the individual pump but that the amount of heat added by the pump each year increased steadily over all parts of the state . Spring temperatures increased in some places but not in others. Peristaltic pumps, not submersible pumps, were used for shallow wells and springs. They do not require cooling. If well-water temperature rose as an artifact of the collection methodology then a separate explanation is needed to explain why temperat ure rose in springs, which were sampled with different equipment. Both shallow well and sp ring temperature increases were observed in the SRWMD. On the other hand, peristaltic pumps were also used in th e SWFWMD, and, as it turned out, spring-water temperatures typi cally decreased while well-water temperature increased. Another possibility is that the trends are statistical artifacts such as “aliasing.” Aliasing is a result of sampling over a time inte rval that is longer than the dura tion of cycles of the variable of interest. Figure 59 depicts cy clic variations of water levels . The cycle is approximately 7 days in length. If sampling occurs at intervals that are less than 7 days, a cyclic pattern will be detected, even if it is not the “true” 7-day cycl e. By setting the sampling interval at the same period as the cyclicity, the cycles are not detected. In fact, with a 7-day cycle, the starting day of the week has a profound consequence on the apparent behavior of the data. Starting sampling on Day 1 (Monday) results in an a pparent increase in water levels over time. Starting sampling on Day 3 (Wednesday) results indicate an apparent negative trend in water levels. Clearly, there is an important relationship between the period of sampling and the pe riod of the cyclicity. This issue is important for all analytes in trend analysis since it can involve any trends. The danger is that, in a time series short enough, one limb of the false cycle can appear as an

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FLORIDA GEOLOGICAL SURVEY 136 upward or downward trending curve. The key problem with this explanation is that the results of the aliasing are cycles, not trends. As such, it is equally likely to sample in such a way that a false upward or downward trend is generated. Figure 59. Example of aliasing. Regarding water temperature, one s hould see an equal probability of up and down trends in water temperature. However, if both upwar d and downward tendencies are equally likely then it requires a second explanation to understand why trends so often tend in the same direction; or to say it another way, it is not that trends are going up but that so many are going up. The sign tests (Table 49) reveal that the majority of trends descri bed here were predominately up. The simplest explanation for increased temperature is that a single cause is responsible for the widespread singular trends. It appears that the most plausible explanati on for increasing well water temperature is an increase in air temperature. Table 67 indicates that the mean air temperature across most of Florida was about 0.29 F (0.16 C) higher during Sequence C ( 1998-2003) relative to Sequence B (1991-1997). For the shallow wells, it is possibl e that localized air te mperature increases are responsible for increasing water temperature.

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BULLETIN NO. 69 137 Nitrogen and Phosphorus Nutrients—Regi onal and Local Problem in Springs Several nutrient trends in springs were anal yzed for the four water management districts providing spring data. Nitrates (in various forms), phosphorus, phosphate (or ortho-phosphate), TKN and ammonia were the most common. Thes e can be grouped as nitrogen and phosphorus and will be addressed separately fo r each water management district. Nitrate concentrations have increased in nor thern Florida springs for over 30 years. The data analyzed for Wakulla Spring indicates a downward trend for the 1991 2003 time frame, yet the spring has a longer history of nitrate in creases (Figure 60). From the 1970s to the early 1990s, nitrate concentrations in Wakulla Spring rose from approximately 0.2 mg/L to over 1.0 mg/L. Increases in nitrogen trends are typica lly due to specific land use inputs. The most common inputs are from fertilizer application, septic tanks, animal excrement, golf courses, and wastewater treatment facilities (F lorida Spring Task Force, 2000). Nutrient transport is a complex process. Nitrat e and other nutrients wash into aquifers and undergo large-scale mixing with groundwat er (Martin and Gordon, 1997). Analyte concentrations in springs follo wing storms change as a functi on of epikarst (upper weathered karst) flushing. Nitrate concentratio ns increase as a result of this effect. Changes in concentration are often seasonal (Katz, 2000; Boyer et al., 1999). DateNO3 + NO2 as N (mg/L) 1/1/2005 1/1/2000 1/1/1995 1/1/1990 1/1/1985 1/1/1980 1/1/1975 1/1/1970 1.1 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 Nitrate Concentrations in Wakulla Spring(1972 2003) Figure 60. Nitrate Concentrations in Wakulla Spring between 1972 and 2005. Nitrogen in the Northwest Flor ida Water Management District One on-going study is taking place at a wastewater treatment f acility (WWTF) spray field located approximately 10 miles from Wakulla Sp ring. Wastewater has been noted to change

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FLORIDA GEOLOGICAL SURVEY 138 concentrations of a number of analytes includi ng chloride, nitrogen, pho sphorus, organic carbon, coliform bacteria, sodium, and potassium (Elder et al., 1985). Depending on the analyte and the percent of organic material pres ent, soil and underlying rock matrices can absorb much of the material introduced. Spray-field monitoring we lls have documented changes in both chloride and nitrate-nitrogen concentrati ons. Chloride has been noted to increase from 3 to 15 mg/L while nitrate-nitrogen climbed from 0.5 to 4 mg/L in nearby wells (Elder et al., 1985). The association of combined increases in nitrate and chloride has also been reported in ot her parts of the country (e.g. Ogallala Aquifer, Texas; Hudak, 2002). Weki wa Springs in the SJRWMD appear to have a similar wastewater input problems. Septic tank are sometimes referred to as on site waste disposal systems (OSWDS). Their leachate plus lawn fertilization seem to be the most likely source of the nitrogen (Toth and Fortich, 2002). Studies of Leon and Wakulla Counties have doc umented six main nitrogen sources were identified: atmospheric deposition, wastewat er treatment facilities, OSWDSs, commercial fertilizers, livestock and sinking streams (Chelette et al., 2002). Of these sources, there are both inorganic and organic sources of nitrogen, either of which could be introduced in dissolved or particulate form. Forms of nitrogen can be classifi ed as either dissolved inorganic, particulate inorganic, dissolved organic, a nd particulate inorganic. The exact contribution of each of these forms is difficult to establish. Actual amounts of nitrogen contri buted from these sources have been documented with varying accuracy. WWTF contributions are well established, whereas data from OSWDS are more difficult to acquire. Re gardless of the exact contribution, the overall contribution of WWTF a nd OSWDS comprise the majority of nitrogen inputs into the environment. They deliver, respectively, 550 and 800-2,400 kg-N/ha-yr (Chelette et al., 2002). Though atmospheric deposition of nitrogen is subs tantial, it is disperse d over wider areas and comprises approximately 4-5 kg-N/ha-yr (tot al of wet and dry deposition combined). Based on Chelette et al. (2002), much of the nitrogen fertilizers applied to the landscape is sequestered or returned to the atmosphere; only a fracti on becomes part of groundwater. Nitrogen is a highly reactive element and its chemi cal pathways are difficult to establish. It can be sequestered in vegetation, lake-bottom sedime nts, the subsurface, or it can return to the atmosphere. In spite of the small proportion of nitrogen actually ente ring groundwater, total nitrate discharging from Wakulla Spring at least doubled ove r the last 25 years. Agricultural sources have been document ed through isotopes and water ages. Many springs have complex flow paths with older and younger flow paths converging within springs. Isotopic studies indicate a vari ety of water ages in northe rn Florida springs. Nitrate concentrations are negatively correlated to age of spring water and the nitrate originates from varying proportions of inorganic (fertilizers) and organic-N (anima l wastes) sources (Katz et al., 1999b; Toth, 1999). Close correlation of nitrate trends in some Fl orida counties to county-wide fertilizer sales underscores this relationshi p (Chelette et al., 2 002; Katz et al., 1999b). Another factor in localization is underlying geology and soil. Even within agricultural areas nutrients may show up in groundwater in greater or less proportion based on underlying geology, soil conditions, and preferential flow pa ths within aquifers. One study in Florida illustrates this for nitrate in surface water an d groundwater. In the northwestern portion of the state the Dothan soils are plenthitic (iron hard pan) with a shallow perched water table (Day,

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BULLETIN NO. 69 139 1997). These conditions result in less nitrate percolating into the aquifer, al though greater concentrations of nitrate may be concentrated in surface runoff. Other soils in the panhandle can provide a suitable environment for nitrate to persist and eventua lly find its way into groundwater. Bowman (1991) also indicated that soil types can affect nitrate input into groundwater. Our study shows that nitrate has been trending downw ard in Wakulla Spring significantly during the 1991-2003 period (Figure 60). The time series includes gaps. Howe ver, both MK trend results and WT tests of Sequence B and C data confirm a drop in the latter half of the series. These results suggest that a moderate improvement ma y have occurred. Loper et al. (2005) suggested that the improvements are due to decreased efflue nt concentrations at the spray field. At the same time, the highly elevated starting point of the time series in 1991 (1.0 mg/L), as compared to 0.2 mg/L in 1972, was the product of severa l decades of a strong rise (Figure 60). Nitrogen in the Suwannee River Water Management District The SRWMD was the only district to provide flow data on the days that nutrient samples were collected. This allowed an examination of flow-related loading fo r the analytes. Of the nutrient analytes examined for the SRWMD, th e only one having a distri ctwide trend was TKN (nine increased and zero decreased). At the same time, other nutrient anal ytes suggest increases and decreases. Nitrate decreased in six springs (and increased in only three), while phosphorus increased in five and phosphate increased in four (with each only decreasing in one spring). At least four explanations exist that can possi bly explain the decrease in nitrate. First, since the latter half of the time series was a drier period, it is possible that less nitrate became available to groundwater as a result of decreased precipitation or a possible reduction in fertilizer applications during the dry period. Second, dur ing the dry period, the soil may have stored nitrogen. Under both of these scenarios, when the current dry period ends, nitrate trends in springs will be expected to incr ease. Third, efforts by the local WMDs to conserve on the rates of fertilizer application were succ essful. Under this scenario, wh en the dry period ends, in all likelihood, nitrate concentra tions in springs will continue to decline. Fourth, during the drier times, spring discharge is reduced. Reduced flow creates an appearance of lower nitrate concentration in the springs. For example, fl ow-adjusted trends and flow/concentration plots revealed a different behavior between nitrate-nitrogen and T KN over the period of record. Figures 61-64 compare and contrast flow-adjusted trends. Flow adjustments were derived in two ways. The figures include plots of: (1) the product of flow volumes and nutrient concentrations against time and log-log plots of nutrient concentration as a function of the flow. The figures contrast different springs with a variety of trend directions. Troy Spring (Figure 61, top) demonstrates an inverse relationship over time fo r flow-adjusted nitrate, while the log-log plot (Figure 61, bottom) shows a positive relationship exists between nitrate concentrations (vertical axis) and flow (horizon tal axis). Figure 62 (top) displays no apparent flow relationship over time for flow-adjuste d trend for TKN for Troy Spring, while Figure 62 (bottom) reveals that TKN concentration (vertical axis) has an inverse relationship with flow (horizontal axis). Figur e 63 (Hornsby Spring) shows a negativ e relationship over time for flow-adjusted nitrate (top), but demonstrates a positiv e relationship regarding th e log concentration of nitrate versus the log of flow (bottom). In Fi gure 64 (top) there is a pos itive relationship over

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FLORIDA GEOLOGICAL SURVEY 140 Figure 61. Flow adjustment for Nitrate in Troy Spring. Flow-adjusted nitrate (top) show s a clear decline over time, while the log of nitrate plotted against log of flow (bottom) shows a clear positive association. 102 6789FLOWCFS4 10-1.0 6 7 8 9 2 3TKN 5/1/19989/13/19991/25/20016/9/2002 Date 0 500 1000 1500 2000 2500Flow (cfs) * NOXN-Tot (mg/L) Troy: Flow-Adjusted Nitrogen 102 6789Flow (cfs) 100.0 2 3NOXN-Tot (mg/L)

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BULLETIN NO. 69 141 Figure 62. Flow adjustment for TKN in Troy Springs. Flow adjusted TKN shows little change ov er time while the log of flow versus the log of TKN (bottom) is slightly negative. 102 6789FLOW (CFS) 10 -1.0 6 7 8 9 2 3TKN 5/1/19989/13/19991/25/20016/9/2002 Date 0 20 40 60 80Flow (cfs) * TKN (mg/L) Troy: Flow-Adjusted TKN

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FLORIDA GEOLOGICAL SURVEY 142 Figure 63. Flow adjustment for nitrate in Hornsby Spring. Flow adjusted nitrate-nitrite (top) over time shows a clear decline over time. The log of nitrate plotted against log of flow (bottom) shows a positive association. 5/1/19989/13/19991/25/20016/9/200210/22/2003 Date 0 500 1000 1500 2000Flow (cfs) * NOXN-Tot (mg/L) Hornsby: Flow-Adjusted Nitrogen 101102 234567823456782345Flow (cfs) 100.0 3 4 5 6 7 8 9NOXN-Tot (mg/L)

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BULLETIN NO. 69 143 Figure 64. TKN versus time and log of TKN versus log of flow in Hornsby Spring . TKN shows a drop with a sudden rise at the end of the time series (top). However, there is very little relationship between the log of flow and the log of TKN (bottom). 12/17/19965/1/19989/13/19991/25/20016/9/200210/22/2003 Date 0 100 200 300 400 500TKN (mg/L) Hornsby: Flow-Adjusted TKN 101102 234567823456782345Log Flow (cfs) 10-1.0100.0 6 7 8 9 2 3 4 5 6 7 8 9Log TKN (mg/L)

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FLORIDA GEOLOGICAL SURVEY 144 time for TKN. However, there is a slightly negative relationship be tween the log of TKN compared to the log of flow (bottom). Hornsby Sp ring had the sharpest decr ease in flow of all SRWMD springs and actually stopped flowi ng during portions of the study period. Figures 61-64 suggest that redu ced spring flow was responsible for apparent decreases in nitrate concentrations and increases in TKN concen trations. Because in all cases, whether nitrate concentration is increasing, decreasing, or show ing no trend, nitrate concentrations closely follow flow amounts in the springs. This flow-depe ndent behavior is one pl ausible explanation of the decreasing nitrate trends in the Suwannee District; nitrate conc entrations may have fallen in some springs simply as a function of reduced flow. One clear observation revealed by flow adju stments is how the two forms of nitrogen differ for the SRWMD. TKN showed a clearly different pattern th an nitrate-nitrogen. For Troy Spring (Figure 61, top) nitrate loading decreased over time. However, as a function of flow, nitrate correlated pos itively with flow (Figure 61, bottom) . On the other hand, TKN slightly increased over time (Figure 62, top), but had an inverse relationship with flow (Figure 62, bottom). Hornsby Spring was similar to Troy Spri ng. Nitrate loading (Figure 63, top) decreased over time and it correlated posi tively correlated with flow (Figure 63, bottom). TKN concentrations increased over time (Figure 64, top), but TKN had an insignificant correlation with flow (Figurer 64, bottom). As with the other two springs, nitrate loading at Fanning Spring (Figure 65, top) decreased during the drought, and nitrate concentrations were correlated positively with flow (Figure 65, bottom). With regard to TKN, its loading increased over time (Figure 66, top), and TKN was inversely correlated with flow (Figure 66, bottom). Table 69 summarizes nutrient relationships for several springs in the SRWMD. The table contains summary data for Troy, Hornsby, and Fa nning Springs (already discussed), plus Little River, Telford, and Ruth/Little Sulfur (RLS) Sp rings. For each of these selected springs, the table contrasts the relationships among concentrat ion, loading, time, and flow for both nitrate and TKN. At the bottom of the table is a summary. Nitrate concentrations and nitrate loading generally decreased over time. Nitrate concentrations were positively related to flow. As flow decreased during the drought, nitr ate concentrations generally decreased. Since nitrate concentrations are dependent on flow, as rainfa ll returns to normal, nitr ate concentrations may begin to increase, because of th e increased spring flow. TKN behaved differently. TKN concentratio ns generally increased over time, while TKN loading generally decreased. TKN concentrations were inversely (negatively) related to flow. As flow decreased during the drought, TKN concentrations generally increased. These results raised questions concerning the different sources and chemical behaviors of both forms of nitrogen. It is clear that nitrat e closely followed the flow amounts—at least for these selected springs in the Suwannee Distri ct. However, TKN shows an almost inverse relationship with flow. Since TKN is a combination of both NH3 and organic nitrogen, a possible explanation is that the sources of the or ganic nitrogen in TKN we re from either highly organic water originating from swamps or from agriculture a nd/or waste water sources.

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BULLETIN NO. 69 145 Figure 65. Flow adjustment for nitrate in Fanning Spring. Flow adjusted nitrate-n itrite shows a sharp rise followed by a decline over time (top). The log of nitrate-nitrite plotted against log of flow (bottom) shows a positive relationshiship. 102 456789Flow (cfs) 3 4NOXN-Tot (mg/L) 3/27/19975/1/19986/5/19997/9/20008/13/2001 Date 500 1000 1500 2000 2500Flow (cfs) * NOXN-Tot (mg/L) Fanning: Flow-Adjusted Nitrogen

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FLORIDA GEOLOGICAL SURVEY 146 Figure 66. Flow-Adajustment for TKN in Fanning Spring. TKN shows nearly no flow -adjusted trend over time (top). Plotted against the log of flow versus the log of TKN shows an inverse negative reationship with flow (bottom). 12/17/19965/1/19989/13/19991/25/2001 Date 0 40 80 120Flow (cfs) * TKN (mg/L) Fanning: Flow-Adjusted TKN 102 456789Log Flow (cfs) 10-1.0 4 5 6 7 8 9 2 3 4 5 6Log TKN (mg/L)

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BULLETIN NO. 69 147 Table 69. Relationships among Concentration and Loading of Nitrate and TKN versus Time and Flow in Selected Springs in the SRWMD Spring Reference Nitrate or TKN Loading or Concentration Versus Time or Flow Relationship + , 0, or Troy Table 10 Nitrate Concentration Time 0 Table 10 TKN Concentration Time 0 Figure 62 Nitrate Loading Time Figure 62 TKN Loading Time 0 Figure 62 Nitrate Concentration Flow + Figure 62 TKN Concentration Flow Hornsby Table 10 Nitrate Concentration Time Table 10 TKN Concentration Time 0 Figure 63 Nitrate Loading Time Figure 63 TKN Loading Time + Figure 63 Nitrate Concentration Flow + Figure 63 TKN Concentration Flow 0 Fanning Table 10 Nitrate Concentration Time + Table 10 TKN Concentration Time + Figure 64 Nitrate Loading Time 0 Figure 64 TKN Loading Time 0 Figure 64 Nitrate Concentration Flow + Figure 64 TKN Concentration Flow Little River Table 10 Nitrate Concentration Time Table 10 TKN Concentration Time + Appendix M Nitrate Loading Time Appendix M TKN Loading Time Appendix M Nitrate Concentration Flow + Appendix M TKN Concentration Flow Telford Table 10 Nitrat e Concentration Time Table 10 TKN Concentration Time + Appendix M Nitrate Loading Time Appendix M TKN Loading Time Appendix M Nitrate Concentration Flow + Appendix M TKN Concentration Flow Ruth/Little Sulfur Table 10 Nitrate Concentration Time + Table 10 TKN Concentration Time + Appendix M Nitrate Loading Time Appendix M TKN Loading Time Appendix M Nitrate Concentration Flow + Appendix M TKN Concentration Flow Overall for springs above Reference Nitrate or TKN Loading or Concentration Versus Time or Flow Relationship + , 0, or Table 10 Nitrate Concentration Time Table 10 TKN Concentration Time + Appendix M Nitrate Loading Time Appendix M TKN Loading Time Appendix M Nitrate Concentration Flow + Appendix M TKN Concentration Flow

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FLORIDA GEOLOGICAL SURVEY 148 During 2003, a relatively wet year, large amou nts of organic debris, originating from swamps or other sources, possibly entered th e groundwater regime though swallets and were simply flushed through the springs. However, there is another possibi lity for increasing TKN trends. Since NH3 showed little activity in the SRWMD, changes in organic nitrogen are possibly responsible for increased trends. Orga nic material found within the deeper and older Avon Park Formation is a possibl e source of organic nitrogen a nd, by extension, TKN. During the drought, deeper organic-rich groundwater, originating from the Avon Park Formation, may have found its way to the springs. The mechanis m for transporting the olde r water to springs is analogous to that controlling the increases of ro ck and saline analyte concentrations during a drought. In either scenario, it a ppears that nitrogen from organi c sources found their way into the SRWMD groundwater during the period of record wh ile nitrate concentrat ions were controlled by spring flow. Nitrogen in the St. Johns River and Southw est Florida Water Management Districts There were no observed district wide nutrient trends in the SJRWMD. However, nutrients were a large problem in the SWFWMD. Nineteen springs showed upward tr ends in nitrate and only one had a downward trend. In compar ison, phosphorus and phosphate trends (to be discussed shortly) were suggestiv e of a slight improvement. Unlike the SRWMD, flow data were sparse for the SWFWMD and loading could not be determined. This disparity (dominant upward trends in SWFWMD for nitrate but relative ly inactive [or improving] phosphorus trends) provided another good example of the “patchy” nature of nutrient trends in the state. Much has been said about the SWFWMD’s nitrate problems (C hampion and DeWitt, 2000; Champion and Starks, 2001; Jones and Upchur ch, 1994; Jones et al., 1996; Jones et al., 1997). These earlier works provide explanations for what is seen in this study. The following springs had upward nitrate trends during th e period of record: Boat, Buckhorn Main, Chassahowitzka No. 1, Chassahowitzka Mai n, Hidden River Head, Hidden River No. 2, Homosassa (Nos. 1, 2 and 3), Hunter, Magnolia, Pumphouse, Rainbow (No. 1 and 6), Rainbow Bridge Seep, Salt, Tarpon Hole, Trotte r Main, and Weeki W achee Main Springs. Marion County Marion County includes the Rainbow Springs Group; the fourth largest spring group system in Florida. Data were analyzed for Rainbow No. 1, Ra inbow No. 4, Rainbow No. 6, Rainbow Swamp No. 3, and Rainbow Bridge Seep. Rainbow Springs Group Rainbow Springs Group, like many other springs in the SWFWMD, had nitrate concentrations well above that of the natural Floridan aquifer system value (<0.05 mg/L). The main source of nitrate in the group was primarily derived from inorganic s ources of nitrate, in particular inorganic fertilizers a pplied to pastures near the springs . Thus the nitrates represent a local flow system (Champion and Starks, 2001; Jones, et al., 1996).

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BULLETIN NO. 69 149 Citrus County Citrus County has several spring groups: King’s Bay, Homosassa, and Chassahowitzka Springs Groups. Springs included Chassahowitz ka No. 1, Chassahowitzka Main, Hidden River Head, Hidden River No. 2, Homosassa Numbers 1-3, Hunter, Pumphouse, and Trotter Main Springs. King’s Bay Springs Group The King’s Bay Springs Group is the second larg est system in Florida. Tarpon Hole and Hunter Springs are part of this group. Freshwater springs were locat ed on the east side of the bay while springs with brackish wate r were found in the central a nd western portions. As of 2001, flow in the springs was only 75 percent of th e historical average (Champion and Starks, 2001). Water quality in the King’s Bay Springs Gr oup is tidally influenced. TDS and chloride concentrations change with tides . This suggests that, even at lo w tide, the springs are strongly influenced by the coastal transition zone. Most nitrate input was from inorganic sources, most likely inorganic fertilizers applie d to golf courses and residential properties near the springs. Thus, the nitrates are indicative of a lo cal flow system (Jones and Upchurch, 1994). Homosassa Springs Group The Homosassa Springs Group, in western Ci trus County, had several springs with upward nitrate trends: Homosassa , Trotter Main, Pumphouse, and Hidden River Head. Like the King’s Bay Group, the Homosassa Springs Group show s an influence from the coastal transition zone (Jones et al., 1997). Like the King’s Bay Springs Group, Ho mosassa Springs Group nitrates were derived primarily from inorganic sources of nitrate—inorganic fe rtilizers applied to residential and golf course turf gr ass near the springs. Again, the nitrates represent a local flow system. Chassahowitzka Springs Group Like the King’s Bay and Homosassa Groups , Chassahowitzka Springs Group varies between fresh and brackish and is tidally influe nced. TDS and chloride concentrations varied greatly, showing a coastal transition zone influen ce even at low tide (Jones et al., 1997). Nitrate concentrations were generally below 0.6 mg/L but varied among individual springs in the group. Mixing of coastal transition zone waters and variations in Floridan aquifer system nitrate concentrations were sources of variations. Most nitrat e was derived from i norganic sources, such as inorganic fertilizers applied to residential and golf c ourse grass near the sp rings (Jones et al., 1997). Hernando County Hernando County included two spring group s: Weeki Wachee and Aripeka Springs Groups. Springs included Boat, Ma gnolia, Salt, an d Weeki Wachee.

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FLORIDA GEOLOGICAL SURVEY 150 Weeki Wachee Springs Group This group lies within western Hernando Count y, southwest of Brooksville and is located inland of the brackish water to the west. Week i Wachee Main Spring had increasing nitrates. As with other SWFWMD springs , the sources of nitrate are probab ly inorganic fertilizers applied to golf and residential lawns in the vicinity of the springs (Jones, et al., 1997). Boat Springs, Bobhill, and Magnolia Springs These springs are located southwest of th e Weeki Wachee Springs Group in Hernando County. Average discharge for thes e springs is relativel y low (Rosenau, et al., 1977). As with other SWFWMD springs, TDS and ch loride concentrations range from fresh to brackish with proximity to the coast. TDS and chloride concen tration changes suggest the group is influenced by the coastal transition zone. The sources of nitrat es are possibly inorganic fertilizers applied to residential and golf course lawns near the springs. Hillsborough County The only sampled springs in Hillsborough County were Lithia Spring and Buckhorn Springs. The only spring with incr easing nitrate was Buckhorn Spring. Lithia Spring and Buckhorn Spring Unlike most of the other springs, Lithia and Buckhorn Springs exhibit little change in TDS or chloride. They are not affected by the higher salinities of the transition zone. The high amounts of nitrate in Lithia and Buckhorn Spri ngs are derived from an inorganic source— inorganic fertilizers applied to citrus within the vicinity of the springs (Jones and Upchurch, 1994). Summary of the Nitrate Problem in Spring Water Originally, the land around th ese springs consisted of pine forest, hammock forests and scrub (Champion and Starks, 2001; and Wolfe, 1990). This natural setting was eventually replaced by agricultural deve lopment such as livestock pa stures, row crops and citrus. Additionally, the last several decades have included urban and commercial development. These developments included many residential units and golf courses. Studies at the SWFWMD have concluded that during the last 25 years, nitrate from inorganic fe rtilizers has leached into the Upper Floridan aquifer and is now dischargi ng from the springs. Popul ation within SWFWMD has been projected to increase to 4.6 million by 2010 (Champion and Starks, 2001). With nitrate already leaching into th e FAS, and development ongoing, the ni trate increases wi ll continue for the foreseeable future. Phosphorus in Spring Water by Water Management District Phosphorus is strongly correlated with underlyi ng phosphatic rock formations in Florida, predominately from the Hawthorn Group (Scott et al., 1991). The unusually high phosphorus

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BULLETIN NO. 69 151 contents of streams and lakes deriving water drained from phosphatic areas have long been studied (Odum, 1953). Other potential sources of increased phos phorus in springs involve industry and wastewater. Naturally high phosphorus concentrations occur in surface waters in some parts of the state, but can be elevated in other areas by municipal wastewat er and phosphate mining. Because the removal of phosphorus is not often a ddressed in wastewater treatment, it is an important source of contamination. Although some facilities may have the ability to treat for phosphorus, most onsite wastewater treatment and sewage treatment faci lities do not prevent introduction of phosphorus into the environment. Suwannee River Water Ma nagement District Wakulla Spring is the only spring that was evaluated in the NWFW MD and for Wakulla Spring, phosphorus was not an issue. For the SR WMD, flow-adjusted tr ends for phosphorus and phosphate were examined. Figu res 67-75 compare flow-adjuste d trends among springs that show varying trends in phosphorus and phosphate. Overall, the response of phosphate is more similar to that of TKN than nitrate-nitrogen for the SRWMD. Figures 67 and 68 are examples of the relationship between flow and analyte concen trations in a spring (Troy) for phosphorus and phosphate. Time series of the flow-adjusted anal ytes show little eviden ce of temporal trends (Figures 67, top and 68, top). Log-log plots of concentration and flow (Figures 67, and 68, bottom) show only slight rela tionship between: (a) flow and phosphorus, or (b) flow and phosphate concentrations. Ruth/Little Sulfur (RLS) Spring shows a sli ght decrease in the log of concentration versus the log of flow (Figures 69, top and 70, top) for both analyt es. However, it has slightly decreasing phosphorus and phosphate flow-adjusted tre nds over the period of record (Figures 69, bottom and 70, bottom). Fanning Spring (Figures 71 a nd 72) shows a slightly different picture. Flow-adjusted concentrations for both phosphoru s and phosphate decrease after 1998 [(Figures 71 (top) and 72 (top)]. However, phosphorus concen trations increase w ith flow (Figure 71 bottom), while phosphate concentrations decrease s lightly over time (Figure 72, bottom). Little River Spring (Figure 73) has decreasing phosphorus and phosphate flow-adj usted trends over the period of record (Figures 73, t op and 74 top). The log of phos phorous and the log of phosphate (Figure 73 bottom and 74, bottom) both decrease with the log of flow. However, like TKN, both phosphorous and phospha te also showed nega tive relationships between the log of the concentration and the log of the flow. An explana tion for these trends is suggested when these plots are compared to one of the few examples of a decreasing phosphate trend in the SRWMD. Hornsby Spring showed a strong decrease in flow-adjusted phosphate (Figure 75, top), with an increa se at the end of the time se ries. The strong downward trend reflects the rapid reduction in flow within Hornsby Spring over the ti me series. A log-log plot of concentration against flow (Figure 75, bottom) shows a positive increase, unlike the other springs. When phosphate decreased, flow also decr eased. The implications are that, like TKN, phosphorus-based nutrients increased at a rate fast er than flow decreased. This is why trends

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FLORIDA GEOLOGICAL SURVEY 152 Figure 67. Flow adjustment for phosphorus in Troy Spring . phosphorus (top) show little declines over time while the log of phosphorus has a negative relationship to the log of flow. Phosphate (bottom) shows a slight negative trend over time while the log of phosphate has little to no relationship to the log of flow. 102 6789Flow (cfs) 3 4 5 6T-Phosphorus (mg/L) [x 10-2] 5/1/19989/13/19991/25/20016/9/2002 Date 5 15 25 35Flow (cfs) * P (mg/L) Troy: Flow-Adjusted Phosphorus

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BULLETIN NO. 69 153 Figure 68. Flow-adjustment for phosphate in Troy Spring. Phosphate (top) shows a slight negative trend over time while the log of phosphate has little to no relationship to the log of flow (bottom). 12/17/19965/1/19989/13/19991/25/20016/9/2002 Date 0 5 10 15 20 25Flow (cfs) * o-PO4 (mg/L) Troy Flow-Adjusted Phosphate 102 6789Log Flow (cfs) 10-2.00 6 7 8 9 2 3 4 5Log o-PO4 (mg/L)

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FLORIDA GEOLOGICAL SURVEY 154 Figure 69. Flow adjustment for phosphorus in Ruth/Little Sulfur Springs . Phosphorus (top) shows slight decline over time. The log of phosphorus (bottom) has a slightly negative relationship to the log of flow (bottom). 12/17/19965/1/19989/ 13/19991/25/20016/9/2002 Date 0 1 2 3 4 5Flow (cfs) * P (mg/L) RLS Flow-Adjusted Phosphorus 10-1.0100.0101.0 23456723456723Log Flow (cfs) 10-1.0 4 5 6 7 8 9Log P (mg/L)

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BULLETIN NO. 69 155 Figure 70. Flow adjust ment for phosphate in Ruth/Little Sulfur Springs . Flow-adjusted phosphate declines over time (top). The log of phosphate has has possible negative relationship to the log of flow (bottom). 12/17/19965/1/19989/13/19991/25/20016/9/2002 Date 0 1 2 3Flow (cfs) * PO4 (mg/L) RLS Flow-Adjusted Phosphate 10-1.0100.0101.0 23456723456723Log Flow (cfs) 10-1.00 2 3 4 5 6 7 8 9Log o-PO4 (mg/L)

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FLORIDA GEOLOGICAL SURVEY 156 Figure 71. Flow-adjustment for phosphorus in Fanning Spring. Phosphorus declines after 1998 (top). The log of phosphorus has a positive relationship to the log of flow (bottom). 12/17/19965/1/19989/13/19991/25/2001 Date 11 15 19 23Flow (cfs) * T-P (mg/L) Fanning: Flow-Adjusted Phosphorus 102 456789Flow (cfs) 10-1.0 6 7 8 9 2T-Phosphorus (mg/L)

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BULLETIN NO. 69 157 Figure 72. Flow adjustment for phosphate in Fanning Spring. The flow adjusted phosphate shows an incr ease through 1998 and then a decline (top). However, the log of phosphate shows a slight decline with the log of flow (bottom). 12/17/19965/1/19989/13/19991/25/2001 Date 11 16 21 26 31 36Flow (cfs) * o-PO4 (mg/L) Fanning: Flow-Adjusted Phosphate 102 456789Log Flow (cfs) 10-1.00 5 6 7 8 9Log o-PO4 (mg/L)

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FLORIDA GEOLOGICAL SURVEY 158 Figure 73. Flow adjustment for phosphorous in Little River Spring. Flow adjusted phosphorous declines over time (top). However, the log of phosphorus declines with a decline in the log of flow (bottom). 12/17/19965/1/19989/13/19991/25/20016/9/2002 Date 5 9 13Flow (cfs) * Phosphorus (mg/L) LRS: Flow-Adjusted Phosphorus 102 234567892Log Flow (cfs) 10-2.00 2 3 4 5 6 7 8Log Phosphorus (mg/L)

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BULLETIN NO. 69 159 Figure 74. Flow adjustment for ph osphate in Little River Spring. Phosphate (top) shows a decline over time while the log of phosphate has a negative relationship to the log of flow (bottom). Relationship of concentration to flow shows a stronger decline than at other springs. 12/17/19965/1/19989/13/19991/25/20016/9/2002 Date 2 4 6 8 10 12Flow (cfs) * o-PO4 (mg/L) LRS: Flow-Adjusted Phosphate 102 23456789Log Flow (cfs) 10-2.00 9 2 3 4Log o-PO4 (mg/L)

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FLORIDA GEOLOGICAL SURVEY 160 Figure 75. Flow adjustment for phosphate in Hornsby Spring. One of the few ex amples of a decreasing phosphate trend in the SRWMD. Flowadjusted ph osphate shows a pronounced dec line over time with a large increase at the end (top). The log of phosphate as a function of the log of flow (bottom) shows an association. This pattern is the opposite of what is seen with the majority of the SRWMD sp rings where increasing phosphate tr ends correspond to a negative relationship with the log of flow. 1/1/199711/14/19989/27/20008/10/20026/23/2004 Date 0 50 100 150 200Flow (cfs) * o-PO4 (mg/L) Hornsby: Flow-Adjusted Phosphate 10-1.0100.0101.0102.0 23456234562345623456Log Flow (cfs) 10-1.0 7 8 9 2Log o-PO4 (mg/L)

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BULLETIN NO. 69 161 with decreasing concentrations (like phosphate at Hornsby Spring) show positive relationships with flow: the concentrations were almost en tirely dependant on flow, and the concentrations were decreasing. A reduction in flow may have actually masked a number of otherwise upward trends in nutrient analyte concentrations. This would mean that the actual number of nutrient increases may be greater than this report is able to document and it is likely the trends recorded here underestimate the true number of increases. A second explanation for reduction in phosphate has been noted in other states. Trend analyses in water quality of North Carolina no ted a significant reduction in phosphate following the 1988 state-wide ban of phosphate use in deterg ents. Trend analyses s how reductions from the time period of 1983 to 1995 (Childress et al., 1998) . Similar reductions in phosphate detergent, or improvements in wastewater treatment, coul d also result in downward phosphorus trends in Florida. The most plausible explanation we can postula te includes a hypothesi s that explains the selective nutrients, plus rock and saline anal yte trends. TKN and phosphorus-based nutrients increased at a rate faster than flow decreased. The phosphorus tr ends may simply be additional observations of the shrinking of Florida’s fres hwater “lens” and the uptake of older water inferred across the state. Several seemingly unr elated trends (e.g. salinity, pH, phosphorus) are simultaneously answered by this single explanat ion making it the preferre d, but not necessarily the correct, option. More work is need ed to fully understand this observation. St. Johns River and Southwest Fl orida Water Management Districts The SJRWMD had no increasing phosphate tre nds with 11 decreasing trends, while the SWFWMD had no increasing trends w ith five decreasing trends. Po ssibly related to this is the observation that the SJRWMD also witnessed nine springs showing significantly increasing pH values, with only one spring show ing a decrease. Odum (1953) obs erved that surface waters in Florida, such as streams, often have high conc entrations of phosphorus a nd low pH values. On the other hand, we observed that springs have hi gh pH values, relative to surface waters, and often contain less phosphorus conc entrations than streams. Odum (1953) suggested a controlling role for pH in the solubility of phosphorus in natural surface water c onditions. Based on these observations, the decreasing trends observed for phosphate and phosphorus may actually reflect an increasingly larger volume of deeper wate r components comprising spring-water because of the drought. Such deeper water would be both hi gher in pH and lower in phosphorus. With the exception of the SRWMD, nearly every phosphorusrelated trend in the state is downward. This explanation has the advantage of being consistent with the clearly observed statewide increase in rock and saline indicators. Thus, if older and deep er-sourced water is disc harging at springs, then it would create both a strong incr ease in rock and sali nity trends, which are clearly documented, as well as the decrease in phosphorus seen here.

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FLORIDA GEOLOGICAL SURVEY 162 Comparison of Coastal to Inland and Tidal to Non-Tidal Springs Most trends observed in this study were for rock-matrix and saline analytes and most were caused by the drought. By closely examining the trends displayed in this report, it became obvious that the magnitude of change for spring s located near the coas t during the drought was greater than for inland springs. However, did coas tal springs have proporti onally more increasing trends than did inland sp rings? Did tidal springs have propor tionally more increasing trends than did non-tidal springs? An inspection of Figures 13, 16, 27, and 32 reveals that for some spring, it is easy to determine as to whether they are in land or not. Others are not so ea sy to identify. For example, in the SJRWMD, almost all springs in this report are lo cated very near the St . Johns River, which parallels the coast (Figure 27). For this reason, SRJWMD spri ngs were not used in this evaluation. Wakulla Spring in the NWFWMD (Figure 13) is lo cated near the coast and was easily categorized as being a coastal spring. For the SRWMD, the Suwannee River flows roughly perpendicular to the coast (Figure 16 ). Based on this observation, the authors categorized the first seven spri ngs, beginning at the mouth of the Suwannee River as being coastal. All other SRWMD springs were placed into the inland category. Staff at the SWFWMD categorized their spri ngs for us. The spring categorizations for both WMDs are found in Table 70. Table 70. Inland and Coastal Springs within the SRWMD and the SWFWMD SRWMD (including Wakulla Spring) SWFWMD Coastal Springs Inland Springs Coastal Springs Inland Springs MAN ALR Betty Jay Bobhill FAN LBS Boat Boyette HAR TEL Chassahowitzka No. 1 Bubbling RKB SBL Chassahowitzka Main Buckhorn LRS ROY Hidden River Head Catfish RLS GIL Blue Hidden River No. 2 Lithia TRY POE Homosassa No.1 Rainbow No. 1 Wakulla (NWFWMD) HOR Homo sassa No.2 Rainbow No. 4 Homosassa No.3 Rainbow No. 6 Hunters Rainbow Swamp No. 3 Magnolia Rainbow Bridge Seep Pump House Weeki Wachee Main Salt Wilson Head Tarpon Hole Trotter Main Once the springs were categorized, a two-sa mple proportion test (Sullivan, 2004) was used to determine whether the pr oportion of springs w ith upward trends was the same for both coastal and inland springs. Data from Sequence C were used. Each test was conducted for each of the rock-matrix and the saline indicators at a significance level of 0.05. The null hypothesis

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BULLETIN NO. 69 163 was that the proportions of upwar d trends were the same for bot h coastal and inland springs, while the alternate hypothesis was th at they were not the same. The results are found in Table 71. The table li sts the analyte in the first column. The second, third, and fourth columns contain the nu mber of coastal spri ng trending upward, the number trending downward and th e proportion of springs trending upward for coastal springs. Columns five, six, and seven lists the number of inland springs trending upward, the number trending downward and the proportion of springs tr ending upward for inland springs. Finally, the right-hand column (column 8) displa ys the p-values for each test. All of the p-values are greater than 0.05. Based on this ev aluation, there are insufficient data to conclude that the propor tion of coastal springs were diffe rent from inland springs during Sequence C. For the springs showing trends for the rock-matrix and saline analytes, greater than 90% of the trends were increasing. This was true regardless of be ing associated with coastal or inland springs. Table 71. Comparison of Coastal and Inland Springs for Upward Trends During Sequence C, excluding the SJRWMD Analyte Coastal U Coastal D Prop C UInland U Inland DProp I U P-value Alk 13 0 1.000 12 2 0.857 0.488 Ca 16 0 1.000 17 0 1.000 1.000 Mg 20 0 1.000 18 0 1.000 1.000 Cl 14 1 0.933 15 2 0.882 1.000 F 1 0 1.000 5 0 1.000 1.000 K 15 1 0.938 10 0 1.000 1.000 Na 19 0 1.000 18 1 1.000 1.000 P 9 2 0.812 5 3 0.625 0.603 PO4 8 0 1.000 3 1 0.750 0.333 SC 14 5 0.736 15 2 0.882 0.408 SO4 11 3 0.786 14 2 0.875 0.642 I = Inland, C = Coastal The results of Table 71 repres ent a geographic comparison (coa stal versus inland). Some individuals at the SWFWMD expressed a concern th at not all coastal springs listed in Table 70 were tidally influenced. They requested a compar ison of tidal versus nontidal springs. The two right-hand columns in Table 70 represent coasta l and inland springs in the SWFWMD. All of their coastal springs are tidally influenced, wher eas their inland springs are not. Data from the springs listed in the two right -hand columns of Table 70 were used to produce Table 72. The results in Table 72 list the analytes in th e first column. The second, third, and fourth columns contain the number of tidal springs trending upward, the number trending downward and the proportion of springs trending upward for tidally-influenced spri ngs. Columns five, six, and seven lists the number of non-tidal springs trending upward, the num ber trending downward and the proportion of springs trending upward for non-tidally in fluenced springs. Finally, the right-hand column (column 8) displa ys the p-values for each test.

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FLORIDA GEOLOGICAL SURVEY 164 Table 72. Comparison of Tidal and Non-Tidal Springs for Upward Trends During Sequence C in the SWFWMD Tidal U Tidal D Prop T U Non-Tidal U Non-Tidal D Prop Non-Tidal U P-Val Bicarb 12 0 1.000 9 0 1.000 1.000 Ca 6 0 1.000 3 0 1.000 1.000 Mg 8 0 1.000 6 0 1.000 1.000 Cl 6 0 1.000 6 1 0.857 0.857 F 1 0 1.000 3 0 1.000 1.000 K 7 0 1.000 8 0 1.000 1.000 Na 6 0 1.000 8 0 1.000 1.000 P 1 2 0.333 0 3 0.000 1.000 SC 7 0 1.000 5 0 1.000 1.000 S04 8 0 1.000 4 0 1.000 1.000 Sr 10 0 1.000 9 0 1.000 1.000 TDS 4 0 1.000 6 0 1.000 1.000 Note that all of the p-values listed in Ta ble 72 are greater than 0.05. Since many of the tidal springs in Table 72 are the same as the coas tal springs listed in Tabl e 70, it is not surprising that the results in Table 71 and Ta ble 72 are similar. Note that the sample size is small. Note also that unlike the other analytes, phosphorous had decreasing trends. In spite of phosphorous, based on this evaluation, there is insufficient data to conclude that the proportion of upward trends for tidal springs were different from non-tid al springs. For the springs showing trends in the rock-matrix and saline analytes, greater than 90% of the trends were increasing. This was true regardless of being associated with tidal or non-tidal springs. Global Factors Influencing FloridaÂ’s Groundwater Reasons for the trends in FloridaÂ’s groundwat er may range from small-area (large-scale) to large-area (small-scale). For those utilizing FloridaÂ’s resources, severa l large-area influences need to be discussed. Global Long-Term Cycles: Atlantic Multidecadal Oscillation The Atlantic Multidecadal Oscillation (AMO) is a term used to describe long-term changes in sea surface temperature (SST) of the No rth Atlantic Ocean. Cycles of cool and warm ocean temperatures are quasi-periodic lasti ng between 60-80 years (Kerr, 2000, 2005). The AMO is driven by ocean-scale changes in the Atlantic, most likely associated with thermohaline circulation. For Florida, these changes have been observed to be particularly strong (Sutton and Hodson, 2005). An AMO warm phase delivers more precipitation, while a cool phase may be marked by drought. For southern Florida, inflow into Lake Okeechobee can change by 40 percent between extremes (Figure 76, top). It s hould be noted that a similar observation between the AMO and surface water-flows in the SWFW MD have been observe d (Southwest Florida Water Management District, 2004). Figure 76 (top) displays change s in North Atlantic SST as a function of time. The period prior to 1920 had relatively low temperatures . Between 1920 and 1960 the SST increased. It decreased from 1960 to about 1970, and then subse quently it rose again. The effects of the

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BULLETIN NO. 69 165 Figure 76. Atlantic Multidecadal Oscillation and Florida spring flow. The Atlantic Multidecadal Oscillation (AMO, top panels) compared to long-term changes in Florida's sp ring flow (bottom). Top shows North Atlantic sea surface temperature (SST, °C) since 1900. Top lower panel shows effects of the positive AMO on the rainfall and correspondin g flow into Lake Okeechobee. Bottom chart is the log of flow against time for two large Florida springs: Silver Springs and Weeki Wachee Springs. The lines (smoothed spring flow) increase until 1960 (marked) and decline thereafter. Flow from the springs align with AMO patterns during past century. (National Oceanic and Atmospheric Administration [2006b]).

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FLORIDA GEOLOGICAL SURVEY 166 positive AMO were reflected in southern Florida rainfall and inflow into Lake Okeechobee. Figure 76 (bottom) shows spring flow for Silver and Weeki Wachee Springs, two major springs in Florida with long term flow da ta. It shows the log of flow over time. A semi-arbitrary line, drawn at 1960, marks a divide between a period of relative increases in spring flow and subsequent declines. The dividing line closely corresponds to AMO patterns, sugges ting this is a strong influence for Florida springs. AMO cycles are influenced by other oceanogr aphic anomalies (McC abe et al., 2004). More than half of the spatia l and temporal variance of th e multidecadal drought frequency over the conterminous US is related to the Pacifi c Decadal Oscillation (PDO) and AMO together. These droughts also influenced Florida’s groundwater. Kerr (2000, 2005) indicates that the recent drought impacts over the United States (1996, 1999-2002) were associated with North Atlantic warming (positive PDO) and northeastern and tropical Pacific cooling (negative PDO). It is believed that the positive AMO since 1995 (i.e., warm North Atlantic SST) may continue. Because of this, changes in the PDO have important implications for the state of Florida. In mid1998, the PDO became negative until 2002 when both PDO and AMO became positive. A positive AMO and a negative PDO (e.g., 1998) can result in a drought similar to that suffered by Florida in the 1950s. However, a positive AMO and a positive PDO can also cause a drought (e.g., the drought Florida went through in the 1930s ). Thus, if the PDO remains positive while the AMO continues to be positive, a decade-long , 1930s-type drought is a possibility (McCabe et al., 2004). The authors indicated this has important impli cations for water resource planners, particularly in the more arid southwestern portions of the US. At the same time, results of analyses in this report show a clear affect on Florida groundw ater by the same climaticallyGlobal Short-Term Cycles: El Niño and La Niña In addition to the longer-term global change s seen in the AMO and PDO the time period encompassed two additional significant events: back -to-back years of an extreme El Niño and an extreme La Niña. For background, El Niño is an oscillation of tropical Pacific oceanatmospheric interactions. The usual effects of El Niño are increased rainfall and flooding or drought and wildfire—varying depending on loca tion around the Pacific Basin. Under normal conditions, trade winds blow west ward across the tropical Pacific, pushing back the warmer overlying surface water (Figure 77, middle panel). Th is creates a slightly higher sea surface in the western (compared to the eastern) Pacific. The temperature in the western Pacific can also be about 8°C warmer than the eastern. This allows c ooler, nutrient-rich deeper water off the coast of South America to upwell. Rainfall is commonly less over the cooler east ern waters during this period. However, during El Niño, trade winds are re duced and there is a decrease in the depth of the thermocline in the western Pacific. Warmer water then moves east and caps the cooler, normally upwelling water, in the east. This crea tes a band of warm water across the Equatorial Pacific (Figure 77, bottom panel). As a result, more rainfall and flooding occur in places such as Peru. La Niña is something of a reverse of El Niño. It is charact erized by atypically cold water temperatures in the Equatorial Pacific (compare d to the warm water characterizing El Niño). A band of cold water is observed to stretch along the Equator during La Niña (Figure 77, top panel). El Niño and La Niña ar e the opposite ends of the El Ni ño-Southern Oscillation (ENSO) cycle. El Niño is sometimes the warm phase of ENSO while La Niña is the cold phase.

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BULLETIN NO. 69 167 Figure 77. Sea surface temperature, La Nia, and El Nio . Sea surface temperatures for La Nia, normal, and El Nino conditions in the Equatorial Pacific (top, center, and bottom respectively). Note strong difference between 1997 (bottom) and 1998 (top). Cooler and warmer water are indicated by light and dark, respectively. The years 1997-1998 were the divide between Time Sequence B (1991-1997) and Time Sequence C (1998-2003) [From National Oceanic and Atmospheric Administration (2006a)].

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FLORIDA GEOLOGICAL SURVEY 168 Without respect to this knowledge, this st udy was broken into time sequences that reflected the timing of the events: Sequence B (1991-1997) ended with El Niño and Sequence C (1998-2003) began with La Niña. Analysis of h undreds of individual time series bridging these time sequences revealed that 1998 was a visible br eak-point in the data, analogous in geology to a stratigraphic “marker bed.” This means that data from various springs and wells could sometimes be referred to common visible time series “excursions” ar ound that approximate period of time. This raises the possibility th at, although Florida was under the influence of a longer-term decline in water quantity (Figure 77), the cons equence of these shorter-duration perturbations were more strongly felt. Brief but substantial excursions in anal yte values – whether upward or downward – probably contribute a greater infl uence on the overall trend lines than do more subtle, long-term influences. Thus, excursions in 1997-1998 and dr ought are likely the cause behind most of the trends in this report. Earlier years of the study included a weak La Niña (1994-1995). This was followed by a very strong El Ni ño, occurring in 1997. Immediately following this was a strong La Niña (cold) event in 1998. These extreme y ears were followed a severe statewide (and national) drought in 2000. Acid Rain One possible explanation for the decrease in well-water pH over the study period was acid rain. Acid rain is often th e product of sulfur, carbon, or nitrogen oxide s that result from industry, burning coal, or combustion of othe r materials. During the investigation, it was suggested that lower well-water pH values si mply reflected increasing airborne chemical pollutants in Florida’s precipitation. If this were true a time series of pH values in Florida rainfall should show a decreasing trend. Figure 78 reveal s that this was not the case. The figure plots the mean monthly rainfall pH values for seven rainfall stations from around Florida (Appendix M). The rainfall means showed no significant trends over time, though standard deviation decreased slightly. The drought resu lted in less rainfall. This should result in a reduction in the pH standard deviation, not an increase. Implications of Future Low Rainfa ll and Increasing State Water Demands The AMO cycle seen in Figure 76 is approx imately a 60-year cycle with 30 years of increased rainfall followed by 30 years of decrease d rainfall. Since little is known about these cycles, the accurate modeling of future rainfall ch anges is not currently possible. At the same time, with a state that is growing so rapidly in population as Florida, water demand increases are inevitable. Regardless of current lack of ability to understand larger-scale dr iving factors in water quantity, the influence on statewide water res ources created by AMO/PDO and El Niño/La Niña may soon prove to be important. For the sake of illustration, a simple scenario can be posited. If one can assume a cycle is 60-years long (something which cannot be predicte d in advance) and one can assume that the increase began in 2004, this would mean a welcomed 30-year increase in rainfall. At the current rate of growth of more than 700 people per day, an increased volume of wa ter would relieve state water needs and possibly reduce or reverse incr easing concentrations of both rock and salineindicators in spring water. However, once the cy cle reached its high point, a decline in rainfall

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BULLETIN NO. 69 169 2/12/199011/8/19928/5/1995 5/1/19981/25/200110/22/2003 Date 4.4 4.6 4.8 5.0 5.2Mean pH (s.u.) Average Meteoric pHAverage From Seven Statewide Stations Figure 78. Average monthly pH from seven atmospheric rain stations (19912003). will follow for the next 30 years. The concern is that Florida would no l onger have its current 18 million residents, but millions more. By 2010, it is estimated that the population will be over 19 million and, by 2030, it will be 29 million (Clous er, 2006; McGovern, 2004). Once rainfall declines begin, the amount of recharge will be less, and because of FloridaÂ’s increased population, the demand for groundwater will increase. FloridaÂ’s springs can be expected to have substantially lower amounts of flow, and, unless appropriate, long-term su stainability measures are incorporated into public policy, th e quality of spring water will decline. Implications Regarding Long-Term Sustainability Alley et al. (1999) stated that groundwater sustainability is the development and use of groundwater in a manner that can be maintain ed for an indefinite time without causing unacceptable environmental, economic or social c onsequences. Scott (2001) estimated that more than two quadrillion gallons of potable groundwater exist within FloridaÂ’s aquifer. They also believed that in order to determine the outlook for sustaining FloridaÂ’ s groundwater resources, four questions needed to be addressed: What is the level of infrastructu re development and population growth that is supportabl e by the stateÂ’s water resources? Should mineralized waters be consider ed as part of a sustainable water supply? How much impact on the environment is acceptable? How do we balance ecological sustai nability with human needs and economic growth?

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FLORIDA GEOLOGICAL SURVEY 170 Scott (2001) also indicated that once the removal of water exceeds the recharge, “mining” of the groundwater occurs. At that point, Florida’s groundwater is no longer sustainable. With Florida’s growing population, what ar e reasonable solutions? Scott and Schmidt (2000) mentioned that mineralized water can be converted to fresh water through reverse osmosis (RO) processes and surface water can be used to supplement groundwater supplies. However, they pointed out that both potential solutions present their own set of problems and they proposed a set of subsequent questions: Does the inclusion of these waters in the sustainable supply create a false sense of security? Should aquifer storage and recovery (ASR) water be a portion of the sustainable water supply? Should growth management and e nvironmental stability rely on RO and ASR waters? Is it wise to allow growth management and environmental decisions to be based on expensive altern ative water supplies or is that simply avoiding the “natural” limitations? These are very serious questions that the citi zens of Florida will face in the very near future. Analyses from this report suggest that salt-water encroachment may already be occurring and as our population con tinues to grow, we are mo re susceptible than ever to droughts. We need to commence addressing these issues now. If the AMO theory is correct, we may be fortunate and have a 30-year “wet” period in store for us. If so, we may have additional time to address the sustainability issue. If it is incorrect, we need to address the issue now.

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BULLETIN NO. 69 171 REFERENCES Alley, W.M., Reilly, T.E., and Franke, O.L., 1999, Sustainability of Ground-water Resources: U.S. Geological Survey Circular 1186, 79 p. Baker, A.E., Cichon, J.R., Arthur, J.D., and Ra ins, G.L, 2002, Florida aquifer vulnerability assessment: Geological Society of America Abstracts with Programs, v. 34, no. 6, p. 346. Berndt, M. P., Oaksford, E. T ., and Mahon, G. L., 1998, Groundwater; in Fernald, E. A., and Purdum, E. D., eds., Water Resources Atlas of Florida: Tallahassee, Florida State University, p. 38-63. Berube, M.S., and Boyer, M., eds., 1985, Amer ican Heritage Dictionary: Boston, Houghton Mifflin Co., 1568 p. Bowman, K. R., 1991, Protection of groundwat er quality through land-use regulations: Lexington, Midwest Groundwater Conference, v. 36, p. 90-91. Box, G. E. P., and Jenkins, G. M., 1976, Times se ries analysis, forecas ting and control: San Francisco, Holden-Day Inc, 575 p. Boyer, J. N., Fourqurean, J. W., and Jones, R. D., 1999, Seasonal and long-term trends in the water quality of Florida Bay (1989-1 997): Estuaries, v. 22, no. 2B, p. 417-430. Brockwell, P. J., and Davis, R.A., 1991, Time series: theory and methods: New York, SpringVerlag, 577 p. Bruland, G.L., Bliss, C.M, Grunwald, S., Come rford, N.B., and Graetz, D.A., 2008, Soil nitratenitrogen in forested vers us non-forested ecosystems in a mixed-use watershed: Geoderma, v. 148, no. 2, p. 220-321. Center for Disease Control, 2004, Center for Disease Control: http://ncidd/dbmd/diseaseinfo (January, 2004). Champion, K. M., and DeWitt, D. J., 2000, Origin of nitrate in groundwater discharging from Crystal Springs, Pasco Count y, Florida: Brooksville, Southwest Florida Water Management District Report, 191 p. Champion, K. M., and Starks, R., 2001, The hydrol ogy and water quality of springs in WestCentral Florida: Brooksville, Southwest Fl orida Water Management District, 149 p. Chelette, A., Pratt, T., and Katz, B., 2002, Nitr ate loading as an indicator of nonpoint source pollution in the Lower St. Marks-Wakulla Ri vers watershed: Northwest Florida Water Management District, Water Re sources Special Report 02-1, 138 p.

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FLORIDA GEOLOGICAL SURVEY 172 Childress, C. J. O., and Bathala, N., 1998, Water-qua lity Trends for streams and reservoirs in the research triangle area of North Carolina , 1983-95: U.S. Geological Survey WaterResources Investigations Report 97-4061, 18 p. Cleveland, W. S., and Devlin, S., 1988, Locally we ighted regression analysis by local fitting: Journal of the American Statis tical Association, v. 83, p. 596-640. Clouser, R. L., 2006, Issues at th e rural-urban fringe: will Flor ida be prepared for 2030?: http://edis.ifas.ufl.edu/FE661 (January, 2003). Conover, W. J., 1999, Practical nonparametric sta tistics: New York, John Wiley and Sons, 584 p. Cooper, H. H., 1964, A hypothesis c oncerning the dynamic balance of fresh water and salt water in a coastal aquifer: U.S. Geologica l Survey Water Paper 1613-C, 12 p. Copeland, R. E. ed., 2003, Florida spring classification system and spring glossary: Florida Geological Survey Special Publication 52, 17 p. Copeland, R., Upchurch, S., Summers, K., Jani cki, P., Hansard, P., Paulic, P., Maddox, G., Silvanima, J., and Craig, P., 1999, Overview of the Florida Department of Environmental Protection's integrated water resource monitori ng efforts and the desi gn plan of the Status Network: Tallahassee, Florida Department of Environmental Protection, Ambient Monitoring Section, 41 p. Copeland, R., Hornsby, D., and Smith, D., 2000, Monitoring the effects of implementing best management practices in a rural wa tershed in north-c entral Florida, in Conference Proceedings of the National Water Mon itoring Conference--Monitoring for the Millennium, Austin, p. 89-100. Day, C. D., 1997, Nitrate concentrations in soil s and shallow groundwater near an agricultural field in Santa Rosa County, Florida [Master's thesis]: Hattiesburg, Un iversity of Southern Mississippi, 124 p. DeHan, R. S., 2002, Workshop to develop blue pr ints for the management and protection of Florida springs--Proceedings, Ocala, FL., May 8-9, 2002, Florida Geological Survey Special Publicati on 51, Compact Disk. Driscoll, F. G., 1996, Groundwater and wells : St. Paul, Johnson Division, 2nd ed., 1089 p. Edwards aquifer authority, 2007, Water levels and spring flow rates, J17 index well live update: http://edwardsaquifer.org/pages/J17RealTime.asp (January, 2007). Elder, J. F., Hunn, J. D., and Calhoun, C. W., 19 85, Wastewater applicati on by spray irrigation on a field southeast of Tallahassee, Florida; effects on groundwater quality and quantity, 1980-82: U.S. Geological Survey Water-Re sources Investigations 854-4006, 41 p.

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BULLETIN NO. 69 173 Ferguson, G. E., Lingham, C. W., Love, S. K., and Vernon, R. O., 1947, Springs of Florida: Florida Geological Survey Bulletin 31, 196 p. Field, M. S., 1999, A lexicon of cave and karst terminology w ith special reference to environmental karst hydrology: Washington, D.C., Environmental Protection Agency, Office of Research and Developmen t, U S EPA/600/R-99/006, 195p. Florida Department of Envir onmental Protection, 1994, Groundwater guidance concentrations: Tallahassee, Florida Departme nt of Environmental Protec tion, Division of Water Facilities, Bureau of Drinking Water and Groundwater Resources, 53 p. __________, 2003, Watershed Monitoring Section Status and Temporal Variability Monitoring Networks Sampling Manual, December 2003: http://www.dep.state.fl.us/water /monitoring/docs/SamplingManual.pdf (January, 2004) __________, 2004, Integrated water quality assessmen t for Florida: 2 004 305(b) Report and 303(d) List Update: http://dep.state.fl.us/water /docs/2004_Integrated_report.pdf (June 2005) __________, 2008, Learning from the drought, Annual st atus report on regional water supply planning, Florida Department of Envi ronmental Protection report, 16 p. Florida Department of Environmental Protection and Florida Department of Community Affairs, 2002, Protecting Florida's springs--land use pl anning strategies and best management practices: Tallahassee, Florida Departme nt of Environmental Protection, 124 p. Florida, Statutes, 1983, Chapter 403.063: Water quality assurance act. Florida Administrative C ode, 1996, Rule 62-22.200(3). Florida Springs Task Force, 2000, Florida's spri ngs: Strategies for prot ection and restoration: Tallahassee, Florida Department of Environmental Protection, 63 p. Freeze, R. A., and Cherry, J. A., 1979, Groundwat er: Englewoods Cliffs, Prentice-Hall, 604 p. Fujioka, R. S., and Byappanahalli, M. N., 2004, Proceedings and report--Tropical water quality indicator workshop, August 2003: Manoa, Un iversity of Hawaii at Manoa Water Resources Research Center, Special Report SR-2004-01. Gilbert, R., 1987, Statisti cal Methods for E nvironmental Pollution Moni toring: Agincourt, Van Nostrand Reinhold, 313 p. Hanshaw, B. B., Back, W., and Rubin, M., 19 65, Radiocarbon determinations for estimating groundwater flow velocities in centr al Florida: Science, v. 148, p. 494-495.

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FLORIDA GEOLOGICAL SURVEY 174 Helsel, D., and Gilroy, E., 1997, Applied environmental statistic s class notes, Short Course Presented to the Florida Departme nt of Environmental Protection. Hem, J. D., 1985, Study and interpretation of the chem ical characteristics of natural water: U. S. Geological Survey Water-Supply Paper 2254, 263 p. Henry, J. A., 1998, Weather and Climate: in Fernald, E. A., and Putnum, E. D., eds., Water Resources Atlas of Florida: Tallahass ee, Florida State University, p. 16-37. Hollander, M., and Wolfe, D., 1973, Nonparametric Statistical Methods: New York, John Wiley and Sons, 503 p. Hornsby, D., and Ceryak, R., 1998, Springs of the Suwannee River Basin in Florida: Live Oak, Suwannee River Water Management Distri ct Water Resources Report 99-02, 178 p. Hudak, P. F., 2002, Associations between rural la nd uses and groundwater quality in the Ogallala Aquifer, Northwest Texas: Groundwate r Monitoring & Remediation, v. 22, p. 117-120. Huntoon, P.W., 1995, Is it appropriate to apply por ous media groundwater circulation models to karst aquifers?: in El-Kadi A.I ed., Groundwater Models for Resources Analysis and management: Boca Raton, Lewis Publishers, p. 339-358. Intelligent Decision Technologies, 1998, WQSTAT-PLU S statistical software userÂ’s guide: Longmont, Intelligent Decisi ons Technologies, Inc., 46 p. Jackson, J. A., ed., 1997, Glossary of geology: Al exandria, American Geological Institute, 789 p. Johnson, R.H, and Bush, P.W, 1986 , Summary of the hydrology of th e Floridan aquifer system in Florida and in parts of Georgia, South Ca rolina, and Alabama: U. S. Geological Survey Professional Paper 1403-A, 105p. Jones, G. W., and Upchurch, S. B., 1994, Origin of nutrients in groundwa ter discharging from the Lithia and Buckhorn springs: Brooksvill e, Southwest Florida Water Management District Report, 209 p. Jones, G. W., Upchurch, S. B., and Champion, K. M., 1996, Origin of nitrate in groundwater discharging from Rainbow Springs, Marion County, Florida: Brooksville, Southwest Florida Water Management District Report, 155 p. Jones, G. W., Upchurch, S. B., Champion, K. M., and DeWitt, D. J., 1997, Water-Quality and Hydrology of the Homosassa, Chassahowitz ka, Weeki Wachee, and Aripeka Spring Complexes, Citrus and Hernando Counties, Fl orida--Origin of Incr easing Nitrate Concentrations: Brooksville, Southwest Florida Water Management Di strict Report, 167 p.

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BULLETIN NO. 69 175 Katz, B. G., 2000, A multi-tracer a pproach for determining sources of nitrate contamination of groundwater and springs, Lafaye tte County, Florida: U.S. Ge ological Survey Open-File Report 2000-204, 82 p. Katz, B. G., 2004, Sources of nitrate contamination and age of water in la rge karstic springs of Florida: Environmental Geology, v. 46, p. 689-706. Katz, B. G., Bohlke, J. F., and Hornsby, H. D., 1999a, Use of chemical and isotopic tracers to assess sources and chronology of nitrate contam ination in spring waters, northern Florida: Geological Society of America Abstr acts with Programs, v. 31, no. 7, p. 331. Katz, B. G., Hornsby, H. D., Bohlke, J. K., and Mokray, M. F., 1999b, Sources and chronology of nitrate contamination in spring waters , Suwannee River Basin, Florida: U. S. Geological Survey Water-Resources Investigations Report 99-4252, 54 p. Katz, B. G., Bohlke, J. K., and Hornsby, H. D ., 2001, Timescales for nitrate contamination of spring waters: Chemical Geology, v. 179, p. 167-186. Kerr, R. A., 2000, A North Atlantic climate pacemaker for the centuries: Science, v. 288, p. 1984-1986. __________, 2005, Atlantic climate pacemaker for mille nnia past, decades hence?: Science, v. 309, p. 43-44. Klein, H., 1975, Depth to base of potable water in the Floridan aquife r (revised): Florida Geological Survey Map Series 42. Lane, B. E., 1986, Karst in Florida: Florida Ge ological Survey Spec ial Publication 29, 100 p. __________, 2001, The Spring Creek submarine spri ngs group, Wakulla County, Florida: Florida Geological Survey Sp ecial Publication 47, 34 p. Loper D. E., Landing, W. M, Pollman, C. D., and Chan Hilton, A. B., 2005, Degradation of water quality at Wakulla Springs, Florida: assessment and recommendations, report of the Peer Review Committee on the Workshop, solving water pollution problems in the Wakulla Springshed of North Florida, Worksh op held on May 11 13, 2005, Tallahassee, FL.: http://aquacomm.fcla.edu/978/ (January, 2003). Maddox, G., and Lloyd, J.M., Introduction, in Scott, T. M., Lloyd, J. M., and Maddox, G. L., eds., 1991, Florida's Groundwater Qualit y Monitoring Program--Hydrogeological Framework: Florida Geological Surv ey Special Publication 32, 97 p. Marella, R. L., and Berndt, M. P., 2005, Water w ithdrawals and trends from the Floridan aquifer system in the southeastern United States, 1950-2000: U. S. Geological Survey Circular 1278, 20 p.

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FLORIDA GEOLOGICAL SURVEY 178 Southwest Florida Water Management Distri ct, 2004, Florida River Flow Patterns and the Atlantic Multidecadal Oscillation: Brooksvill e, Ecological Evaluation Section, draft Report, 80 p. Southwest Florida Water Manage ment District, 2005, Di strict water management plan, Public Input: Brooksville, draft report, March 2005, Appendix C, Definitions, p. C1-C6, 76 p. Spechler, R.M., 2001, The relation between structure and saltwate r intrusion in the Floridan aquifer system, northeastern Florida: in Kuniansky, E.L. U.S. Geological Survey Karst Interest Group Proceedings, Water-Resources Investigations Report 014011, p. 25-29. Sullivan, M., 2004, Statistics--Informed decision s using data: Upper Saddle River, Prentice Hall/Pearson Education, 823 p. Sutton, R. T., and Hodson, L. R., 2005, Atlantic O cean forcing of North American and European summer climate: Science, v. 309, p. 115-118. Toth, D. J., 1999, Water quality and isotope concen trations from selected springs in Florida: Geological Society of America Abstr acts with Programs, v. 31, no. 7, p. 374. Toth, D. J., and Fortich, C., 2002, Nitrate concen trations in the Wekiwa groundwater basin with emphasis on Wekiwa Springs: Palatka, St. Johns River Water Management District Technical Publication SJ2002-2, 76 p. Tsay, R. S., 2002, Analysis of Financial Time Series: New York, John Wiley & Sons, 450 p. U. S. Census Bureau, 2006, State and County Quickfacts Florida Quickfacts: http://quickfacts.census.gov/qfd/states/12000.html (December, 2006). U.S. Environmental Protection Agency, 1989, Sta tistical analysis of groundwater monitoring data at RCRA facilities, interim final guidance: Washington, U.S. Environmental Protection Agency, Office of Solid Waste Management Division, 352 p. Upchurch, S. B., 1992, Quality of water in Florida's aquifer systems, in Maddox, G. L., Lloyd, J. M., Scott, T. M., Upchurch, S. B., and Cope land, R., eds., Florida' s groundwater quality monitoring program--Background hydrogeochemist ry: Florida Geological Survey Special Publication 34, p. 12-63. Urquhart, N. S., and Kincaid, T. M., 1999, Designs fo r detecting trend from repeated survey of ecological resources: Journal of Agricultural, Biological, and Environmental Statistics, v. 4, p. 404-414. Verdi, R.J., Tomlinson, S.A., and Marella, R.L., 2006, The drought of 1998-2002: Impacts on FloridaÂ’s hydrology and landscape: U.S. Geological Survey Circular 1295, 34 p. Wolfe, S. H., 1990, An ecological characterization of the Florida Springs Coast: Pithlachascotee to Waccasassa Rivers: Tallahassee, Florida Fish and Wildlife Service Biological Report 90-21, 334 p.

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BULLETIN NO. 69 179 APPENDIX A. RELATIONSHIPS AMONG SPRING FLOWS, ROCK, AND SALINITY INDICAT OR CONCENTRATIONS FOR SELECTED SPRINGS 2/12/199011/8/19928/5/19955/ 1/19981/25/200110/22/2003 Date 41 43 45 47 49 51T-Alk (mg/L) 5 7 9 11 13Flow (cfs)Juniper Springs Time Sequence A (1991-2003) T-Alk (mg/L) Flow (cfs) Figure A1 . Juniper Springs – Alkalinity versus flow. 2/12/199011/8/19928/5/19955/1/19981/25/200110/22/2003 Date 4.0 4.4 4.8 5.2 5.6Na (mg/L) 4 5 6 7Stage (feet)Wakulla Spring Time Sequence A (1991-2003) Na (mg/L) Stage (feet) Figure A2. Wakulla Spring – Sodium versus stage.

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FLORIDA GEOLOGICAL SURVEY 180 12/17/19965/1/19989/13/19991/25/20016/9/200210/22/2003 Date 1 3 5 7 9 11Na (mg/L) 200 400 600 800Flow (cfs)Alapaha River Rise Time Sequence A (1991-2003) Na (mg/L) Flow (cfs) Figure A3 . Alapaha River Rise – Sodium versus flow. 3/23/19948/5/199512/17/19965/1/19989/13/19991/25/20016/9/2002 Date 2 3 4 5 6 7Na (mg/L) 40 60 80 100 120Flow (cfs)Fanning Spring Time Sequence A (1991-2003) Na (mg/L) Flow (cfs) Figure A4. Fanning Spring – Sodium versus flow.

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BULLETIN NO. 69 181 12/17/19965/1/19989/13/19991/ 25/20016/9/200210/22/2003 Date 4 6 8 10 12T-Na (mg/L) 20 40 60 80Flow (cfs)Poe Spring Time Sequence A (1991-2003) Na (mg/L) Flow (cfs) Figure A5. Poe Spring – Sodium versus flow. 3/23/199412/17/19969/13/19996/9/2002 Date 100 200 300 400 500Na (mg/L) 60 70 80 90 100 110 120Flow (cfs)Homosassa No. 3 Time Sequence A (1991-2003) Na (mg/L) Flow (cfs) Figure A6. Homosassa No. 3 Spring – Sodium versus flow.

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FLORIDA GEOLOGICAL SURVEY 182 8/5/19955/1/19981/25/200110/22/2003 Date 0 100 200 300 400Na (mg/L) 40 50 60 70 80Flow (cfs)Chassahowitzka No. 1 Time Sequence A (1991-2003) Na (mg/L) Flow (cfs) Figure A7. Chassahowitzka No. 1 Spring – Sodium versus flow.

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BULLETIN NO. 69 183 APPENDIX B. GLOSSARY OF TER MS AND POSSIBLE CAUSES OF TRENDS APPENDIX B1. GLOSSARY (Modified from Poucher and Copeland, 2006) alluvial sinkhole – An alluvial sinkhole is an ancient or relict sinkhole (paleosinkhole) that has been filled with soil and/or sediment. It may or may not have a surficial expression. See also paleosinkhole and relict sinkhole (SDII Global Corporation, 2002). artesian – A modifier that describes a condition in wh ich the potentiometric surface is above the elevation of the top of the aquifer (Modified from Field, 1999). It is synonymous with confined . aquifer – A body of soil, sediment, or rock that is satur ated with water and sufficiently permeable to allow production of water from wells (SDII Global Corporation, 2002). blind valley – A stream valley that terminates abruptly at a sinkhole, swallow hole, or swallet (where the stream disappears underground) (SDII Global Corporation, 2002). caliche – See duricrust . cave – A natural underground opening or series of openi ngs and passages large enough to be entered by an adult person (Modified from Monroe, 1970). cavern – A cave or conduit system with larger than aver age size that has been cr eated by the dissolution of limestone or other soluble rock (SDII Global Corporation, 2002). cavernous porosity – A pore system having large, cavernous openings; the lower size limit, for field analysis, is practically set at approximately th e smallest opening that an adult person may enter (Field, 1999). "chimney" sink – A cover-collapse sinkhole that forms near a vertical shaft or “chimney”, typically developing where bedrock is near land surface. These features are common in the Gainesville area of Florida (Modified from SDII Global Corporation, 2002). collapse sinkhole – A type of sinkhole formed by collapse of the cover materials (soil, sediment, or rock) into an underground void created by the dissolution of limestone or dolostone. See rockcollapse sinkhole and cover-collapse sinkhole (SDII Global Corporation, 2002). conduit; karst conduit – Large dissolutional voids, including enlarged fissures and tabular tunnels. In some usage, it is restricted to voids that are water-filled. Conduits may include all voids greater than 10 mm (one cm) in diameter, but another classification scheme places them between arbitrary limits of 100 mm to 10 m. Whichever valu e is accepted in a particular context, smaller voids are commonly termed subconduits (Field, 1999). conduit flow; karst conduit flow – Undergroundwater flow within c onduits. Conduit flow is generally turbulent, but can also be laminar (Field, 1999). confined – See artesian . cover – Materials consisting of soil, sediment, or rock that overlies the soluble rock (limestone, dolostone etc.) in a karst terrane. In Florida, the cover includes the sand and clay deposits that overlie the

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FLORIDA GEOLOGICAL SURVEY 184limestone (Modified from SDII Global Corporation, 2002). cover-collapse sinkhole – A sinkhole formed by cover materials (sand, clay, etc.) raveling into a void in the underlying limestone (Modified from SDII Global Corporation, 2002). cover-subsidence sinkhole – A collapse sinkhole that forms when the upper surface of the limestone is dissolved away, and the cover materials slowly subside to occupy the space once occupied by limestone. Voids may not be well developed in cover-subsidence sinkholes because of the continued downward movement of cover materials. See also solution sinkhole and sag depressions (SDII Global Corporation, 2002). diffuse flow – Groundwater flow conditions that are genera lly slow-moving, may be laminar (Reynolds number much less than 1.0), has uniform discharge, and a slow response to storms (Modified from Field, 1999). discharge – The rate of flow at a given instant in terms of volume per unit of time (Modified from Neudendorf et al., 2005). It is synonymous with flux. doline – A bowlor funnel-shaped hollow in limestone topography, ranging in diameter from few meters to a kilometer, and in depth up to sever al hundred meters (Modified from Monroe, 1970). A doline is synonymous with sinkhole . dolostone – A sedimentary rock composed predominantly of the mineral dolomite (Ca,Mg(CO3)2). While soluble, dolostone is less likely to contain well-developed karst features than limestone (Modified from SDII Global Corporation, 2002). duricrust – A deposit of precipitated minerals, mainly calcite , formed in the soil or near-surface layers in arid or semi-arid zones at the horizon where a scendant capillary water evaporates and salts held in solution are deposited. In Florida, seasonal ra infall and intense evaporation may form similar semi-concreted soils within the epikarst (Modified from Field, 1999). epikarst – 1 . The zone of weathering that penetrates the upper surface of a limestone stratum. Weathering of limestone results in development of rubble, fine-grained, carbonate-rich silt, clay, and karren (including pinnacles and valleys in th e limestone rock surface) (Modified from SDII Global Corporation, 2002). 2 . An intensely dissolved zone consisting of an intricate network of intersecting roofless, dissolution-widened fissu res, cavities, and tubes dissolved into the uppermost part of the carbonate bedrock. The dissolution features in the epikarst zone are or ganized to move infiltrating water laterally to down-gradient seeps and springs or to collector st ructures such as shafts that conduct the water farther into the subsurface (Huntoon, 1995). estavelle – 1 . A spring that reverses flow because of relativ e changes in the elevation of groundwater potentials and stream stage (SD II Global Corporation, 2002). 2 . An intermittent spring resurgence or exsurgence, active only in wet seas ons (Modified from Field, 1999). Generally, an estavelle is located near streams or rivers. When the water level of the stream is high (e.g. during flood stage), surface water directly recharges the aquifer. exsurgence – A spring or seep in karstic terrane not clearly connected with swallets (or ponors ) at a higher level (Field, 1999).

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BULLETIN NO. 69 185fissure – Any discontinuity within the rock mass that is either initially open or capable of being opened by dissolution to provide a route for water movement. Fissures in this sense, applied generally in karst, therefore include the primary sedimentary bedding planes as well as tectonic faults and joints. More specifically, the term has been used to describ e voids with an average width dimension of 10 to 100 mm (Modified from Field, 1999). fracture – Cracks formed in soils, sediment or rocks by natural stresses. In Florida, many fractures have been developed to relieve stress caused by Earth tides (SDII Globa l Corporation, 2002). It is synonymous with joint . fracture trace – A confirmed pattern observed through remote sensing (areal photography or satellite imagery) that owes its origin to jointing or fr acturing in the underlying soils, sediments, or bedrock. See photolineament (SDII Global Corporation, 2002). grotto – A cave chamber or room preceded by a narrower passage (Modified from Field, 1999). joint – See fracture. karren – Features that develop on the upper surface of a lim estone or other soluble rock as it is weathered These features are prevalent in the Quilin area in China and in western Ireland. In Ireland they are sometimes referred to as burren. In Flor ida, karren are usually buried under the cover materials and consists of pinnacles and depressions in the rock surface. The depressions may or may not be related to sinkhole activity (M odified from SDII Global Corporation, 2002). karst – A term describing landforms that have been modifi ed by dissolution of soluble rock (limestone or dolostone) (Modified from SDII Global Corporation, 2002). karst terrane – A terrane, generally underlai n by limestone or dolostone, in which the topography is chiefly formed by the dissolution of rocks, a nd which may be characterized by sinkholes, sinking streams, closed depressions, subterrane an drainage, and cav es (Copeland, 2003). karst window – 1 . A depression opening that reveals portions of a subterranean flow, or the unroofed portion of a cave (a vertical window). 2 . An opening in natural limestone walls formed by the joining of subterranean karst grottos as a resu lt of dissolution processes (a horizontal window). Both terms are modified from Field (1999). Note also that the Florida Springs Nomenclature Committee believes that flow through an exposed conduit in the aquifer is different from flow onto the Earth’s surface. For this reason, the Florida Springs Nomenclature Committee does not consider a karst window to be a spring. It is an exception to the definition of a spring (See spring ). karstic aquifer – An aquifer containing soluble rocks with a permeability structure that includes abundant interconnected conduits dissolved from the host rock. The interconnected conduits are organized and faci litate the circulation of fluid in the downgradient direction wherein the permeability stru cture evolved as a consequence of dissolution by fluid (Modified from Huntoon, 1995). laminar flow – Flow in which the head loss is proportional to the first power of velocity. Water flowing in a laminar manner will have streamlines that remain distinct and that flow direction at every point remains unchanged with time. Da rcy’s Law strictly applies under laminar flow conditions only (Modified from Field, 1999).

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FLORIDA GEOLOGICAL SURVEY 186limestone – A sedimentary rock primarily composed of the mineral calcite (CaCO3). Limestone is soluble and often develops karst features when w eathered (Modified from SDII Global rp., 2002). magnitude – See Spring magnitude . nonartesian A condition in which the upper surface of the zone of saturation forms a water table under atmospheric pressure. The term is synonymous with unconfined (Field, 1999). offshore spring – The point of discharge of the spring is seaward of the mean low-tide level (Copeland, 2003). onshore spring – The point of discharge of the spring is landward of the mean low-tide level (Copeland, 2003). overflow stream – A stream valley that is down gradient of a swallow hole, swallet, or blind valley and that carries water only when the recharge capacity of the swallow hole is exceeded. In Florida, the term is sometimes used to identify an overflow, or paleo-overflow, stream valley (Modified from SDII Global Corporation, 2002). paleokarst – This term describes either an ancient karst terrane or the presence of features associated with an ancient karst terrane. The term is used to describe old sinkholes and other karst features that are no longer actively forming. In west-central Florida, the term is used to refer to sinkholes that formed decades to millions of years ago a nd are no longer active (Modified from SDII Global Corporation, 2002). paleosinkhole – An ancient sinkhole that is no longer active. See relict sinkhole and alluvial sinkhole (SDII Global Corporation, 2002). photolineament – A natural linear feature on the land surface that has been identified from areal photographs or other images. Photolineaments ar e identified by alignments within or between lakes and wetlands, sinkholes, stream segments, so ils, and vegetation patterns. Photolineaments are also known as photolinears . Note that photolinears may or may not represent geologic features, so the term is not synonymous with fracture trace. See fracture trace (Modified from SDII Global Corporation, 2002). pipe – In karst terminology, it is a semi-circular condu it through which water and soil can pass. Pipes are often nearly vertical and they have steep (nearly vertical) sides (SDII Global Corporation, 2002). polje – A large flat-bottom sinkhole complex formed by the coalescence of several smaller sinkholes. Poljes are flat-bottomed because of subsequent sedimentation, usually in a lake. Payne’s Prairie in Alachua County is an example (Modified from SDII Global Corporation, 2002). ponor – Hole in the bottom or side of a closed de pression through which water passes to or from an underground channel (Field, 1999). It is synonymous with swallow hole . raveling – Raveling is the process by which water transpor ts soil particles downward into cavities in the underlying strata. Because sand is typically damp and the grains are angular, in Florida they do not easily ravel without moving water. Because of their cohesiveness, clay-rich strata are more difficult to ravel than sandy soils (SDII Global Corporation, 2002).

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BULLETIN NO. 69 187relict sinkhole – A relict (or relic) sinkhole is an ancient sinkhole that is no longer active. It may be expressed as a sinkhole lake, depression in the land surface, or loose soils in the subsurface. See paleosinkhole and alluvial sinkhole (Modified from SDII Global Corporation, 2002). resurgence – re-emergence of groundwater through a karst f eature, a part or all of whose waters are derived from surface inflow into ponors at higher levels (Modified from Field, 1999). river rise – see resurgence (Field, 1999). rock-collapse sinkhole – A collapse sinkhole formed when the limestone, or other soluble rock, cavern ceiling fails and collapses into a void (Modi fied from SDII Global Corporation, 2002). rubble – In the context of karst, rubble describes the gravel-like debris that forms as limestone is weathered (Modified from SDII Global Corporation, 2002). sag depression – A sag depression is often the surficial manifestation of a solution or cover subsidence sinkhole. As the underlying bedrock is dissolved away, the cover materials slowly sag, creating a depression. Owing to the shallow water table, sags often become small, circular wetlands (SDII Global Corporation, 2002). sand boil – A spring in which the vent has been filled in with sand. Spring discharge continuously suspends the sand particles that cover the spri ng. Thus the spring has a “boiling” appearance (Copeland, 2003). seep – 1 . To move slowly through small openi ngs of a porous material (Field, 1999). 2 . With regard to springs in Florida, a seep is also a noun that infe rs one or more small openings in which water discharges diffusely (“oozes”) from the groundwat er environment. Discharge is from intergranular pore spaces in the matrix and flow is typically laminar (Copeland, 2003). seepage – The infiltration or percolation of water through rock or soil to or from the Earth’s surface and is usually restricted to the very slow movement of groundwater (Field, 1999). sink – See sinkhole . sinkhole – A landform created by subsidence of soil, sedimen t, or rock as underlying strata are dissolved by groundwater. Sinkholes can form by collapse into subterranean voids created by dissolution of limestone or dolostone or by subsidence as th ese strata are slowly dissolved away (Modified from SDII Global Corporation, 2002). siphon – 1 . In speleology, a cave passage in which the ceiling dips below a water surface (Monroe, 1970). 2 . A flooded cave passage. A gallery (conduit) in the form of a “U” with water moving only under pressure when the siphon is co mpletely filled (Field, 1999). 3 . Site and origin of an intermittent spring; section of a flooded cave or sump flooded passage (Field, 1999). soil piping – Laterally limited, vertical areas of loose soil often caused by downward vertical movement of the soil (raveling). See pipe (Modified from SDII Global Corporation, 2002). solution sinkhole – Sinkhole formed by the slow subsidence of soil or sediment as the upper surface of the underlying, water-soluble sediment or rock is removed by dissolution. See cover-subsidence sinkhole (SDII Global Corporation, 2002).

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FLORIDA GEOLOGICAL SURVEY 188source aquifer – The aquifer from which the water in a spring originates (Copeland, 2003). spring – A point where underground water emerges ont o the Earth’s surface (including the ocean bottom). The image of a trickle of water springing from a hillside hardly matches that of a vast cave pouring forth a river, but both are called springs. Springs may be exsurgences or resurgences, depending upon the source of their wate r. They may also be part-time exsurgences and part-time resurgences. In some usages, “spring” is restricted to the water that outflows; in other usages, the word can refer to the water, the outlet, or the locality of the outflow (Field, 1999). Note that the Florida Springs Nomenclatu re Committee believes that flow through an exposed conduit in an aquifer is different from flow onto the earth’s surface. For this reason, the Florida Springs Nomenclature Committee does not cons ider a karst window to be a spring. It is an exception to the definition of a spring. spring boil – Variable discharge from a spring in which hy drostatic pressure is great enough to cause a turbulent discharge (Modified from Field, 1999). spring complex – See s pring group . The Florida Springs Nomenclature Committee encourages the use of spring group and discourages the use of this term. spring group – A collection of individual spring vents and seeps that lie within a discrete spring recharge basin (or springshed). The individual vents and seeps of onshore spring groups almost always share a common spring run, or a tributary to the run. Spring group vents and seeps are often spread over an area of several square miles. It should be emphasized th at the term spring group will be restricted to those vents and seeps that discharge a well-define d spring recharge basin. The spring vents or seeps within a springshed may be referred to as springs. As an example, the Rainbow Springs Group will include several spring vents that drain the Rainbow Springs Group basin, and discharge into the Rainbow River spring run. Note that a spring recharge basin is defined only by potentiometric data and not by chemical or other physical characteristics of the spring discharge. However, chemical and additional physical data can, and should, be used to better define individual spring vent basins within a spring grou p basin. This type of mapping was conducted for the Rainbow Springs Group in Marion County by Jones et al. (1996). All springsheds have not been mapped. Therefore, if a springshed is not mapped, then it is acceptable to use the term “springs” to refer to multiple vents discharging into a common spring run. spring magnitude – A category based on the volume of flow from a spring per unit time. spring pool – A small body of water, either artificia lly impounded or naturally occurring, that encompasses one or more spring vents. It contains spring discharge that flows into a spring run. It contains spring discharge that flows into a spring run (The Florida Springs Nomenclature Committee, 2003). spring recharge basin – Those areas within groundwater and surfacew ater basins that contribute to the discharge of the spring. The position of the divi de is orthogonal to is opotential lines (Copeland, 2003). It is synonymous with springshed . Note that the position of the recharge basin boundary is time dependent. That is, the boundary is representative of a “snapshot” in time, rather than permanent. Thus, the boundaries of springsheds are dynamic and vary as a result of a changing potentiometric surface. If a spring is found to drain one springshed during times of high potentiometry, and another basin during low

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BULLETIN NO. 69 189times, then the spring should be connected with two spring basins in the spring database (Copeland, 2003). Whenever practical, descriptive asp ects of the recharge basin should be noted in the spring database. The following are examples. The rela tive recharge to groundwater within the basin should be noted. Those portions of the basi n where confined and unconfined groundwater conditions exist should also be recorded. Finally, groundwater vulnerability within the springshed should be noted if possible. A potenti al tool to predict vulnerability is the Florida Aquifer Vulnerability Assessment (FAVA) model (Baker et al., 2002). spring run – 1 . A body of flowing water that originates from a karst spring (Field, 1999). 2 . A stream (river, creek, etc.) whose primary (>50 percent) source of water is from a spring, springs, or spring group (The Florida Springs Nomenclatu re Committee 2003). For example, the Wakulla River, where the predominant source of water is from Wakulla Spring, is a spring run. However, farther down stream, where surface water tributaries, contribute 50 percent or greater of the flow, the Wakulla River is no longer considered a sp ring run. A detailed hydrogeologic (e.g., the collection of discharge and seepage data) study may be needed in order to identify boundaries of a spring run (The Florida Springs Nomenclature Committee, 2003). spring seep – See seep . spring vent – See vent . springs – Multiple spring vents or seeps located in proximity to each other. The usage of this term is discouraged, but for pragmatic reasons, it cannot be entirely dropped. For example, several vents may discharge into a common spring run and the collection of scientific data (e.g. water samples or disch arge measurements) cannot be obtained from individual vents located in the run. However, it may be practical to obtain a composite water sample or composite flow measurement representing several vents. Under this situation, the term springs is acceptable. However, a list of each vent or seep represented by the composite sample should be recorded by the sampler, and ultimat ely placed into the spring database (Copeland, 2003). steephead – A deeply cut valley, generally short, terminati ng at its upslope end in an amphitheater, at the foot of which a stream may emerge; e.g., ocean, lake, river, or stream (Field, 1999). springshed – See spring recharge basin . subaqueous spring – A spring that discharges below the surface of a water body (Field, 1999). The term implies a pre-existing receiving surfacewater body and is synonymous with submerged (Poucher and Copeland, 2006). submerged – See subaqueous . submarine spring – See offshore spring . swallet – See swallow hole . swallow hole – A place where water disappears underground in a limestone region. A swallow hole gen

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FLORIDA GEOLOGICAL SURVEY 190erally implies water loss in a closed depression or blind valley, whereas a swallet may refer to water loss into alluvium at a streambed, even though there is no depression (Field, 1999). tidal spring – A spring whose discharge is controlled by tid al cycles. Near the coast, tidal springs may alternately discharge saline and fresh water. In land, the pattern of fresh water discharge may simply reflect tidal changes in the potentiome tric surface (SDII Global Corporation, 2002). turbulent flow – The flow conditions in which inertial fo rces predominate over viscous forces and in which head loss is not linearly related to velocity . It is typical of flow in surfacewater bodies and subsurface conduits in karst te rranes, provided that the conduits have a minimum diameter of approximately 2-5 mm, although some research sugg ests that 5-15 mm may be more appropriate (Modified from Field, 1999). trace – See overflow stream (SDII Global Corporation, 2002). uvala – Large, complex sinkholes with irregular bottoms, formed by the coalescence of several smaller closed depressions. The bottom of an uvala is characterized by multiple sinkholes and an irregular bottom (Modified from SDII Global Corporation, 2002). unconfined – See nonartesian . vent – An opening that concentrates groundwater dischar ge at the Earth’s surface, including the bottom of the ocean. The spring point of discharge is significantly larger than that of the average pore space in the surrounding rock and is often consider ed a cave or fissure. Flow from the opening is mostly turbulent (Copeland, 2003).

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BULLETIN NO. 69 191 APPENDIX B2. Origins of Temporal Trends in Florida’s Groundwater (Online at http://www.uflib.ufl.edu/ufdc/?b=UF00095137 ) APPENDIX C. Well CONSTRUCTION AND LOCATION DATA (Online) APPENDIX D. SPRING LOCATIONS Spring County Latitude/ Longitude Spring County Latitude/ Longitude NWFWMD Wakulla Spring Wakulla 30.234/ -83.086 SJRWMD SRWMD Alexander Spring Lake 29.072/ -81.569 Alapaha Rise Hamilton 30.427/ -83.086 Apopka Spring Lake 28.559/ -81.675 Gilchrist Blue Spring Gilchrist 29.820/ -82.678 Fern Hammock Springs Marion 29.175/ -81.701 Fanning Spring Levy 29.578/ -82.932 Juniper Springs Marion 29.175/ -81.706 Hart Spring Gilchrist 29.666/ -82.948 Miami Spring Seminole 28.702 -81.436 Hornsby Spring Alachua 29.840/ -82.588 Palm Spring Seminole 28.835 -81.443 Lafayette Blue Spring Lafayette 30.115/ -83.223 Ponce De Leon Spring Volusia 29.125 -81.355 Little River Spring Suwannee 29.986/ -82.963 Rock Spring Orange 28.748 -81.495 Manatee Spring Levy 29.480/ -82.974 Salt Springs Marion 29.351 -81.733 Poe Spring Alachua 29.815/ -82.644 Sanlando Springs Seminole 28.681 -81.388 Ruth/Little Sulfur Springs Suwannee 29.996/ -82.023 Silver Glen Springs Marion 29.207 -82.047 Rock Bluff Spring Gilchrist 29.789/ -82.915 Starbuck Spring Seminole 28.689 -81.384 Royal Spring Suwannee 30.073/ -83.071 Sweetwater Spring Marion 29.210 -81.653 Suwannee Blue Spring Suwannee 30.081/ -82.931 Volusia Blue Spring Volusia 28.939 -81.332 Telford Spring Suwannee 30.107/ -82.834 Wekiwa Spring Orange 28.712 -81.460 Troy Spring Lafayette 30.006/ -82.997

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FLORIDA GEOLOGICAL SURVEY 192 APPENDIX D (continued) SWFWMD Spring County Latitude/ Longitude Spring County Latitude/ Longitude Betty Jay Spring Citrus 28.690 -82.592 Pump House Spring Citrus 28.789 -82.584 Boat Spring Hernando 28.430 -82.653 Rainbow No. 1 Spring Marion 29.094 -82.433 Bubbling Spring Marion 29.093 -82.430 Rainbow No. 4 Spring Marion 29.094 -82.433 Buckhorn Main Spring Hillsborough 27.884 -82.299 Rainbow No. 6 Spring Marion 29.085 -82.424 Catfish Spring Citrus 28.891 -82.595 Rainbow Swamp Spring No. 3 Marion 29.094 -82.433 Bobhill Spring Hernando 28.435 -82.641 Rainbow Bridge Seep Marion 29.094 -82.433 Boyette Spring Hillsborough 27.854 -81.274 Salt Spring Citrus 29.094 -82.615 Chassahowitzka No. 1 Spring Citrus 28.709 -82.571 Tarpon Hole Spring Citrus 28.891 -82.591 Chassahowitzka Main Spring Citrus 28.709 -82.572 Trotter Main Spring Citrus 28.874 -82.582 Homosassa No. 1 Spring Citrus 28.792 -82.585 Weeki Wachee Main Spring Hernando 28.789 -82.569 Homosassa No. 2 Spring Citrus 28.792 -82.585 Wilson Head Spring Sumter 28.510 -82.316 Homosassa No. 3 Spring Citrus 28.792 -82.585 Hidden River Head Spring Citrus 28.769 -82.583 Hidden River No. 2 Spring Citrus 28.769 -82.584 Hunters Spring Citrus 28.887 -82.588 Lithia Main Spring Hillsborough 27.861 -82.228 Magnolia Spring Pasco 28.428 -82.649

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BULLETIN NO. 69 193APPENDIX E. STATISTICS (Online) Appendix E1. Statistical Methodologies (Online) Appendix E2. Macro Codes for Mann-Kendall Tests and Sen Slopes (See Accompanying CD) APPENDIX F. ANALYTES Appendix F1. Analyte Descriptions Field Analytes Field analytes represent a grouping of convenien ce. Most were obtained prior to collecting collecting samples for laboratory analyses. The analytes in this group that were used fortrend analyses include discharge (or flow), dissolved oxygen, pH, specific conductance (SC), water temperature, and water level (msl). Discharge – Discharge, or spring flow , is controlled by groundwater levels in the aquifers and generally changes slowly in res ponse to fluctuations in potentiometry. Discha rge is measured in cubic feet per second or gallons per day. For trend analyses, disc harge is referred to as flow. Dissolved Oxygen (DO) – Oxygen readily dissolves in water. The source of oxygen can be atmospheric or biological. Typically, springs th at discharge water from deep aquifer sources have low dissolved oxygen concentrations. On the other hand, in sh allow groundwater the dissolved oxygen content is relativ ely high. This is due to a greater exposure to the atmosphere and an increase in biological activity. pH – Measures the acidity or alkalinity of water. It is defined as the negative log of the activity of the hydrogen ion in a solution. Values range between zero and 14. A low pH (below seven) represents acidic conditions, and a high pH (above seven) represents alkaline conditions. A pH of seven indicates the water is neutral. As ra indrops form they inco rporate dissolved carbon dioxide, forming weak carbonic acid. The resulting ra in has a low pH. In Florida, as rainwater passes through soil layers it incorporates organic acids and the acidity increases. When acidic water enters a limestone aquifer, the acids react with calcium carbonate in the limestone and dissolution occurs . Generally, most spring-water falls within a pH range of seven to eight. During heavy ra in events, spring-water can drop in pH as tannic acids from nearby surface waters are flushed into the spring system. It should be noted that sampled river rises tend to have a lower pH than the clearwater spring systems due to the surfacewater component of the river rise water. The pH in well water generally falls within the six to eight range.

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FLORIDA GEOLOGICAL SURVEY 194 Specific Conductance (SC) – Specific conductance is a measure of the ability of a substance, in this case groundwater, to conduc t electricity at 25 ºC. The c onductance is a function of the amount and type of ions in the water. Th e units are microsiemens per centimeter ( S/cm ). Instead of measuring SC in the field, some sampling agencies had their laboratory measure SC. For trend analyses, SC in the field (S C-field) was preferred. However, in order to generate sufficient data for time sequences A, B, and C, laboratory SC (SCL) was used if SCfield was unavailable. One sampling agency us ed the term field condu ctance [cond(field)] for SC-field. For trend analyses, the abbreviation SC is used. Note that it includes SC-field, and SCL. Stage – The stage is the height of a water surface above an arbitrarily established datum plane. For this report, stage is conve rted water level above the Na tional Geodetic Vertical Datum (NGVD) of 1927 (South Florida Water Mana gement District, 2005), or approximately mean seal level (msl). It is often used in spring monitoring. Water Level – In a well, the variable water level is considered to be the distance from a measuring point located close to land surface downw ard to the groundwater surface. In data files, it is sometimes recorded as the depth to water and abbr eviated (DtoH2O). Although it is convenient to measure water levels in this manner and store them in a data base, interpreting how water levels change over time can be somewhat confusing. For exam ple, if potentiometric levels of an aquifer decrease over time due to a dr ought, potentiometric leve ls will drop. However, water levels as the reported in a data base will increase (the distance from land surface to the groundwater surface will increase). In order to avoid this confus ion, for this report, all water level data were converted to its elevation, re lative the NGVD datum of 1927, or approximately mean sea level. Thus, when levels in groundwater decrease, water level data decrease. For this report, the converted water level data is used and is abbreviate d WL(msl) water le vel relative to mean sea level. Water Temperature (Temp or T) – Geologic material is characteristically a good insulator. Rocks and sediments tend to buffer changes in the temperature (Temp) of groundwater. Thus, groundwater temperature does not vary much a nd tends to reflect th e average annual air temperature in the vicinity of sp rings or wells. In Florida, groundwater temperatures generally range from 68°F to 75°F (20° C to 24° C), plus or minus several tenths of a degree. It plays a role in chemical and biological act ivity within the aquifer and can assist in determining residence time of the water in the aquifer. Rock-Matrix Analytes Because of natural rock weathering, water that has had a long residence time in an aquifer system has a greater probability of having high con centration of rock matrix material. Thus rockmatrix analytes are those indica tive of the rocks making up an aqui fer. For this report, rock indicators include alkalinity, calcium, magnesium, plus to a le sser extent, fluoride, iron, pH, potassium, strontium, sulfate, and specific conductance.

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BULLETIN NO. 69 195 Alkalinity (Alk) – In the presence of acids, alkalinity results from of the dissociation of calcite (or aragonite) (CaCO3) and dolomite (CaMg (CaCO3)). The two minerals are the major mineral constituents in carbonate aquifers, such as the FAS and the Biscayne Aquifer. Upon dissolution, carbonate (CO3) and bicarbonate (HCO3) are the two resulting predomin ant chemical species. In most natural systems, in the pH range of 6.4 to 10.3 at 25 ºC, bicarbonate is the major anion. As such, bicarbonate is the dominant constituent of alkalinity of the water. This is the situation regarding alkalinity in Florid a. Depending on the laboratory, either total alkalinity or bicarbonate (Bicarb) was measured. For the pur pose of trend analyses, the two analytes are considered to be very similar to each other and the term alkalinity will represent either constituent. Calcium (Ca ) – Calcium and magnesium (Mg) are the dominant cations in the carbonate aquifers in Florida and are the major minera ls that constitute limestone and dolostones respectively. The Floridan aquifer system is composed of calcite and dolomite. Calcium is released upon the weathering carbon ate rocks. It is also released upon the weathering of gypsum and anhydrite. Gypsum is occasi onally found in the inte rmediate aquifer system and Upchurch (1992) indicated that both are co mmon at the base of the Floridan aquifer system in the Avon Park and Oldsmar Formations. Both dissolved calcium (D-Ca) and total Ca (T-Ca) were sampled. Occasionally, a sampling agency altern ated between the two species. For trend analyses, whenever possible, D-Ca was used and was the species of choice. However, both species were lumped together into a surrogate analyte (simply calcium) and were treated as if they were the same species. Fluoride (F) – Hem (1985) indicated that a source of fluor ide is the mineral fluorapatite. This mineral is commonly found in the Hawthorn Group of the IAS (Olson, 1972). Both dissolved fluoride (D-F) and total fluoride (T-Fe) were sa mpled. For trend analyses , whenever possible, DF was used and was the species of choice. Iron (Fe) – Three common sources of iron (Fe) in Flor ida’s groundwater are the: (1) oxidization of the mineral pyrite, (2) oxidation of organic compounds, and (3) dissolution of iron oxide and silicate minerals (Upchurch, 1992). It is generally more prevalent in th e SAS and the IAS than the FAS. Both dissolved iron (D-Fe) and tota l iron (T-Fe) were sampled. For trend analyses, whenever possible, D-Fe was used. Magnesium (Mg) – Due to chemical similarities, many of the factors that govern the distribution of calcium in Florida aquifer systems can also be applied to magnesium. The intermediate aquifer system’s Hawthorn Gr oup contains significant sources of magnesium, including magnesium-rich clays (Upchurch, 1992). The FAS al so contains abundant dolomite which is the major source of Mg in Florida’s aquifer systems. Both dissolved magnesium (D-Mg) and tota l Mg (T-Mg) were sampled. Occasionally a sampling agency alternated between the two species. For trend analyses, whenever possible, DMg was used and was the species of choice. Howe ver, both species were lumped together into a surrogate analyte (magnesium) and were treat ed as if they were the same species.

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FLORIDA GEOLOGICAL SURVEY 196 Potassium (K) – In Florida’s groundwater, potassium is primarily derived from sea water (Upchurch, 1992). Therefore, coas tal regions, where the fresh wate r/salt water transition zone is present, typically contain the highe st K concentrations. Other sources are drilling fluids in newly installed wells , clay minerals, and in fertilizers. Both dissolved (D-K) and total (T-K) potassium were sampled. For trend analyses, wh enever possible, D-K was used. pH – s previously stated, when acidic water enters a limestone aquifer, the acids react with calcium carbonate (CaCO3) in the limestone and dissolution occurs. In Florida, pH often has a direct inverse relationship with the concentrat ions of Ca, Mg, and Alk. For example, during heavy rain events, spring-water and shallow gr oundwater can drop in pH as acidic surface water recharges the aquifer systems. Specific Conductance (SC) – Because it is a meas ure of electrical conductance at 25 º C, and because it a good indicator for the dissolution of limestones and dolostones, SC is a good rockmatrix indicator. Strontium (Sr) – Strontium is relatively uncommon in Flor ida’s aquifer systems. However, it occasionally substitutes for calcium (Upc hurch, 1992) in the in the carbonate (CO3) matrix of carbonate aquifers. It is more pr evalent in the older, deeper, a nd more saline portion of the FAS. The dissolved (D-Sr) and the total (T-Sr) sp ecies were sampled. Whenever possible, the dissolved form was used for trend analyses. Sulfate (SO4) – Sulfate is commonly found in aquifer waters in Florida and has several sources. The two most common sources are from seawat er and the dissolution of gypsum and anhydrite (naturally occurring rock types within Florida's aquifer systems). Sulfate is often used as a soil amendment to acidif y soils, and, thus, is associated with agricultural activities . Finally, disposal and industrial waste activities release sulfate to groundwater. Salt-Water (or Saline) Analytes Salt-water analytes are those associated with salts from either connate or seawater. Connate waters are those waters trapped within th e sediments at the time of their deposition. Since the original sediments were deposited in a marine environment, the pore spaces contain very old salt water. Salt-water analytes are obviously also found in the seawater located along Florida’s coasts. The major difference is the ag e of water. High concentrations of salt-water analytes are often an indication of horizontal salt water intrusion. However, it can also be an indication of intrusion of highly mineralized water from the deeper portion of the Florida’s fresh water “lens.” The intrusion can be caused by the depletion of the less dense fresh water “lens” during very dry period (e.g. a droug ht), or by the upconi ng of connate water during periods of heavy groundwater withdrawals. It should be noted that the pumping of groundwater increased during dry periods and exacerbated th e intrusion process. For this report, saline analytes include calcium, chloride, potassium, sodium, specific conduc tance, sulfate, and total dissolved solids (TDS). Calcium – In addition to it predominance as a rock-matrix indicator, calcium can also be considered an indicator of salt-water intrusion. As previously stated, calcium can be released

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BULLETIN NO. 69 197 into Florida’s groundwater from the weathering of gypsum and anhydrite found at the base of the Floridan aquifer system. If calcium concentra tions are found to be increasing, in conjunction with sulfate, it can be an indication that the ol der and deeper water from the base of the freshwater “lens” is finding its way into the shallowe r portions of Florida’s groundwater systems. If this occurs, there is the potential that increases in the concentration of other salt water indicators will follow. Chloride (Cl) – Chloride is the most abundant constituen t in seawater. Groundwater and springwater that are tidally influenced may have high chloride concentrations. Other sources for Cl in Florida are from rainfall via marine aerosols from the ocean, and as a by-product of waste. Chloride is chemically conservative a nd reacts very little with groundwater. Potassium – K is primarily derived from sea water. However, it can be introduced into groundwater via fertilizers. Other sources are from drilling fluids in newly installed wells and from clay minerals. Sodium – In Florida, sodium (Na) in groundwater ha s several sources. Th e major source is the mixing of seawater with fresh water. Two ot her, but relatively minor, sources are marine aerosols and the weathering of sodium-beari ng minerals like feldspars and clays. Thus, to a very minor degree, sodium can also be considered a rock analyte. However, for this report is considered a saline analyte. Both di ssolved sodium (D-Na) and total sodium (T-Na) were sampled. The species D-Na was pr eferred for trend analyses. Specific Conductivity – Because it is a measure of electri cal conductance, and because highly mineralized water has high SC values, it is a good indicator of saline conditions. Sulfate – Because of its source (gypsum and anhydrite), SO4 is considered to be a rock indicator. However, as previously stated, sulfate can be released into Florid a’s groundwater from the weathering of gypsum and anhydrite found at the base of the Floridan aquifer system and, because seawater is also an important source of su lfate in coastal areas, sulfate is an excellent salt water indicator. Total Dissolved Solids (TDS) – TDS are primarily derived from the dissolution of carbonate rocks in Florida’s aquifers. They also orig inate from saline and connate marine water. Nutrient Analytes These analytes represent compounds or elemen ts that are essentia l for the growth of living organisms and occur naturally. However, if found in high concentr ations, they can cause the over-enriching of a body of surface water (eut rophication), leading to an overgrowth of plant life (including algae) and possibl y a loss of dissolved oxygen. For th is report, nutrient analytes include phosphate, phosphorus, a se ries of nitrogen related speci es, and to a lesser extent, Mg, Ca, K, and sulfur (in the form of sulfate). The nitrogen related speci es include nitrogen, ammonia, total kjeldahl nitrog en, nitrate, and nitrite.

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FLORIDA GEOLOGICAL SURVEY 198 Calcium – Since calcium is an essential nutrient and is a major ingredient in fertilizers, it is included in the nutrient analyte category. Magnesium – As with calcium, magnesium is an essentia l nutrient and is a major ingredient in fertilizers. Thus, it is include d in the nutrient analyte category. Nitrogen (N) – For this report, the monitored nitrogen sp ecies is total nitrogen. The amount of ammonia, nitrate, nitrite, a nd organic nitrogen, when summed, gives the total nitrogen (T-N) content of groundwater. For groundwater, the major sources are fertilizers and animal excrement. Ammonia and ammonium – Nitrate is one member of a sequence of related nitrogen compounds that includes nitrogen gas (N2), nitrite or nitrogen dioxide gas (NO2) and other oxides, ammonia and ammonium (NH3, NH4), a number of other inorganic and organic compounds (Upchurch, 1992). The gaseous phases exist in the atmosphere and in soil atmospheres but are not of importance in the sa turated zones of aquife rs. Ammonia gas also escapes into the atmosphere. Thus, ammonia is present in groundwater in the form of ammonium (NH4) because of the prevalent pH conditions and reduction-oxidation potentials. A source of the nitrogen can be from fertilizers and animal excrement. Nitrate and Nitrite – Nitrate (NO3) and nitrite (NO2) are both found in Florida’s well water and spring water. In terms of abundance, in oxidizi ng environments, nitrate dominates significantly over nitrite. For this reason, nitrat e is not often measure by itself. Rather, it is measured as part of a nitrate species. The monitored species of n itrate are dissolved nitrate plus nitrite as N (DNO3 + NO2), dissolved nitrate as N (DNO3), total nitrate plus nitrite as N (T-NO3+NO2), and total nitrate as N (T-NO3). The concentrations of all of these analytes are considered to be measures of nitrate. Nitrate contamination recently has become a problem in both well water and spring water. Nitrate often originates from fertilizer s, septic tanks and animal waste that enter the aquifer in the spring recharge area. Nitrate, bein g a nutrient, encourages algal and aquatic plant growth in spring water, which may lead to eutr ophication of the spring run or associated water body. Nitrite, which is much less of a problem, can originate from sewage and other organic waste products.56 Organic Carbon – Natural and non-naturally occurring or ganic carbon are present in varying concentrations in spring-water in Florida. Th e primary source of natu rally occurring organic carbon is humic substances (decaying plant materi al). Synthetic organic carbon represents a minor component. The species sample d was total organic carbon (TOC). Phosphate (PO4) – Phosphate, as monitored, is orthophosphate . It is an essential nutrient and occurs in groundwater in Florida. Unfortunatel y, an excess of phosphate can cause run-away plant growth and the eutrophication of surface waters. The mineral fluorapatite found in the Hawthorn Group in the IAS is pos sibly the most important sour ce of phosphate in groundwater in Florida. However, other sources include orga nic and inorganic ferti lizers, animal waste,

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BULLETIN NO. 69 199 human waste effluent and industria l waste. Both dissolved (D-PO4) and total (T-PO4) orthophosphate were sampled. The species D-PO4 was preferred for trend analyses. Phosphorus (P) – Total phosphorus (T-P) is the species of phosphorus monitored in springwater by the water management di stricts of Florida. It includes the total of several oxidation states that range from P3to P5-. Phosphorus can originate fr om the mineral fluorapatite. However, it is a component of sewage. Its presence can cause the eu trophication of surface water. Potassium – Since K is a major ingredient in fertilizers, it is included in the nutrient analyte category. Sulfate – Since SO4 is an ingredient in fertilizers, it is included in the nutr ient analyte category. Total Kjeldahl Nitrogen (TKN) – Total kjeldahl nitrogen is a measure of the sum of the ammonia nitrogen and organic nitrogen in th e groundwater sample. The ammonia nitrogen, mainly occurring as ammonium (NH4), occurs in trace amounts in groundwater. Organic nitrogen originates from biologi cal sources including sewa ge and other waste. It is also found naturally in the Avon Park Formation toward the base of the UFAS (Appendix B2). Other Analytes Analytes in the “Other” category do not f it in the other four. They represent a miscellaneous group. For trend analyses, the analytes included in this group are suspended solids, and turbidity. Suspended Solids – These refers to the tota l amount of solid material suspended in the water column. As opposed to turbidity, total suspended solids (TSS) do not take into account the light scattering ability of the water. TSS are filtered out of a water sample. Turbidity (Turb) – Turbidity is a measure of the colloidal suspension of tiny particles and precipitates in spring water. High turbidity wate r impedes the penetration of light and can be harmful to aquatic life. Most Florida springs discharge water low in turbidity.

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FLORIDA GEOLOGICAL SURVEY 200 Appendix F2. Analyte Li st with STORET Codes Analytes Abbreviated STORETID Number Analyte Units Description Bicarb 29801 Bicarbonate Mg/L ALKALINITY,WATR,DISS.,FIX END PT,LAB,AS CACO3, MG/L Color 81 Color PT-CO COLOR,APPARENT(UNFILTER ED SAMPLE) PLAT-COB UNITS Cond(field) 94 Specific Conductanc e, Field MICRO MHO SPECIFIC CONDUCTANCE,FIELD (UMHOS/CM @ 25° C) D-Alk 4255 Dissolved Alkalinity mg/L BICARBONATE ALKALINITY(CAC03),DISSOLV ED,WATER D-Ca 915 Dissolved Calcium mg/L CALCIUM, DISSOLVED (MG/L AS CA) D-Cl 941 Dissolved Chloride mg/L CHLORIDE, DISSOLVED IN WATER D-F 950 Dissolved Fluoride mg/L FLUORIDE, DISSOLVED (MG/L AS F) D-Fe 1046 Dissolved Iron mg/L IRON, DISSOLVED (UG/L AS FE) D-K 935 Dissolved Potassium mg/L POTASSIUM, DISSOLVED (MG/L AS K) D-Mg 925 Dissolved Magnesium mg/L MAGNESIUM, DISSOLVED (MG/L AS MG) D-Mn 1056 Dissolved Manganese mg/L MANGANESE, DISSOLVED (UG/L AS MN) D-Na 930 Dissolved Sodium mg/L SODIUM, DISSOLVED (MG/L AS NA) D-NH3 608 Dissolved Ammonia mg/L NITROGEN, AMMONIA, DISSOLVED (MG/L AS N) D-NO3 618 Dissolved Nitrate mg/L NITRATE NITROGEN, DISSOLVED (MG/L AS N) D-NO3(N) 620 Dissolved Nitrate, Nitrogen mg/L NITRATE NITROGEN, TOTAL (MG/L AS N) D-NO3NO2 631 Dissolved Nitrate Nitrite mg/L NITRITE PLUS NITRATE, DISS. 1 DET. (MG/L AS N) DO 299 Dissolved Oxygen mg/L OXYGEN, DISSOLVED, ANALYSIS BY PROBE

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BULLETIN NO. 69 201 Appendix F2 (Continued) Complete Analyte Descriptions continued Analytes Abbreviated STORET ID Number Analyte Units Description DOC 681 Dissolved Organic Carbon mg/L CARBON, DISSOLVED ORGANIC (MG/L AS C) D-P 666 Dissolved Phosphorus mg/L PHOSPHORUS, DISSOLVED (MG/L AS P) D-PO4 671 Dissolved Phosphate mg/L PHOSPHORUS, DISSOLVED ORTHOPHOSPHATE (MG/L AS P) D-SO4 946 Dissolved Sulfate mg/L SULFATE, DISSOLVED (MG/L AS SO4) D-Sr 1080 Dissolved Strontium g/L STRONTIUM, DISSOLVED (UG/L AS SR) DtoH2O 72109 Depth to Groundwater FR MPFT DEPTH TO WATER LEVEL FROM A MEASURING POINT (FEET) Entero 31649 Enterococci Bacteria NO/100ML ENTEROCOCCIME-MF Fcol 31616 Fecal Coliforms NO/100ML FECAL COLIFORM,MEMBR FILTER, M-FC BROTH, 44.5 C Flow (cfs) 60 Mean Daily Flow cfs FLOW, STREAM, MEAN DAILY CUBIC FEET PER SECOND (CFS) pH 406 pH SU PH, FIELD, STANDARD UNITS Resid 530 Residuals mg/L RESIDUE, TOTAL NONFILTRABLE (MG/L) SCL 95 Specific Conductivity MICRO MHO SPECIFIC CONDUCTANCE (UMHOS/CM @ 25° C) T-Alk 411 Total Alkanity mg/L ALKALINITY, TOTAL (MG/L AS CACO3 T-Ca 916 Total Calcium mg/L CALCIUM, TOTAL (MG/L AS CA) T-Cl 940 Total Chloride mg/L CHLORIDE, TOTAL IN WATER TDS 70300 Total Dissolved Solids mg/L RESIDUE, TOTAL FILTRABLE (DRIED AT 180C), MG/L Temp 10 Temperature û C TEMPERATURE, WATER (DEGREES CENTIGRADE) T-F 951 Total Fluoride mg/L FLUORIDE, TOTAL (MG/L AS F) T-K 937 Total Potassium mg/L POTASSIUM, TOTAL MG/L AS K)

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FLORIDA GEOLOGICAL SURVEY 202 Appendix F2 (Continued) Complete Analyte Descriptions continued Analytes Abbreviated STORET ID Number Analyte Units Description TKN 623 Total Kjeldahl Nitrogen mg/L NITROGEN, KJELDAHL, DISSOLVED (MG/L AS N) T-Mg 927 Total Magnesium mg/L MAGNESIUM, TOTAL (MG/L AS MG) T-Na 929 Total Sodium mg/L SODIUM, TOTAL (MG/L AS NA) T-NO3 615 Total Nitrate mg/L NITRITE NITROGEN, TOTAL (MG/L AS N) T-NO3NO2 630 Total Nitrate Nitrite mg/L NITRITE PLUS NITRATE, TOTAL 1 DET. (MG/L AS N) TOC 680 Total Organic Carbon mg/L CARBON, TOTAL ORGANIC (MG/L AS C) T-P 665 Total Phosphorus mg/L PHOSPHORUS, TOTAL (MG/L AS P) T-PO4 650 Total Phosphate mg/L PHOSPHATE, TOTAL (MG/L AS PO4) T-SO4 945 Total Sulfate mg/L SULFATE, TOTAL (MG/L AS SO4) T-Sr 1082 Total Strontium g/L STRONTIUM, TOTAL (UG/L AS SR) Turb 76 Turbidity (Hatch Meter) HACH FTU TURBIDITY, HACH TURBIDIMETER (FORMAZIN TURB UNIT) Turb(field) 82078 Field Sampling of Turbidity NTU TURBIDITY, FIELD NEPHELOMETRIC TURBIDITY UNITS, NTU WL 82545 Water Level (from sea level) ft WATER LEVEL RELATIVE TO MEAN SEA LEVEL (FEET)

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BULLETIN NO. 69 203APPENDIX G. QUALITY ASSURANCE (QA) OFFICER CONTACT INFORMATION Spring Data Agency Contact Telephone Address NWFWMD QA Officer 850-539-5999 81 Water Management Dr. Havana, FL 32333-4712 SRWMD QA Officer 386-362-1001 9225 County Road 49 Live Oak, FL 32060 SJRWMD QA Officer 386-329-4500 4049 Reid Street, P.O. Box 1429 Palatka, FL 32178-1429k SWFWMD QA Officer 813-985-7481 7601 US Highway 301 Tampa, FL 33637 USGS J. Michael Norris Chief National Stream Gaging Project 603-226-7847 or 1-888-275-8747 U.S. Geological Survey National Center 12201 Sunrise Valley Dr., M.S. 415 Reston, VA 20192 Well Data FDEP QA Officer Watershed Monitoring Section 850-245-8517 2600 Blairstone Road Tallahassee, FL 32399 APPENDIX H. DATA FROM SPRINGS AND WELLS (Online) APPENDIX I. DESCRIPTIVE STATISTICS (Online) APPENDIX J. SEASONALITY RESULTS (Online) APPENDIX K. MANN-KENDALL TESTS AND SEN SLOPE RESULTS (Online) APPENDIX L. DISTRICTWIDE MAPS (Online) APPENDIX M. RAINFALL AND TEMPERATURE DATA (Online) APPENDIX N. ATMOSPHERIC DEPOSITION STATION INFORMATION (Data available from http://nadp.sws.uiuc.edu/sites/sitemap.asp?state=fl ) Site ID Site Name Latitude Longitude County Elevation (m) FL03 Bradford Forest 29.9747 N 82.1981 W Bradford 44 FL05 Chassahowitzka National Wildlife Refuge 28.7494 N 82.7494 W Citrus 3 FL11 Everglades National ParkResearch Center 25.39 N 80.68 W Dade 2 FL14 Quincy 30.5481 N 84.6008 W Gadsden 60 FL23 Sumatra 30.1111 N 84.9919 W Liberty 14 FL32 Orlando 28.5923 N 81.1903 W Orange 21 FL41 Verna Well Field 27.38 N 82.2839 W Sarasota 25 FL99 Kennedy Space Center 28.5428 N 80.6444 W Brevard 2

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1 Appendix B2. Origins of Temporal Trends in FloridaÂ’s Groundwater Interpretation When There Is A Pattern of Analyte Origin in Groundwater Increasing Trends Decreasing Trends Alkalinity (Alk) The primary natural source of alkalinity is dissolution of rock materials. In limestone aq uifers, the reaction of recharging water with calcite in the limestone is: H2O + CO2 + CaCO3 Ca+2 + HCO3 -. Where saline water encroachment is not a problem, HCO3 is the primary source of alkalinity and the dominant anion in Florida springs. 1. The proportion of conduit flow is decreasing and diffuse flow is increasing 2. Relative contribution of water held in storage in the aquifer is increasing because of longer residence times and more opportunity to react with the host aquifer 3. A connection with the surface that allowed rapid recharge may be less efficient 4. A new, more alkaline water source has been added to the flow system 1. Conduit flow is becoming more important than diffuse flow 2. Relative contribution of water held in storage in the aquifer is decreasing because of increased rapid recharge 3. A new, more acidic water source has been introduced Ammonia/Ammonium (NH3/NH4) Ammonia/ammonium is generally not detectable in natural groundwater. Small quantities may be present near decaying organics in a chemically redu cing environment. Where these analytes are reported, the sources are typically fertilizer, animal wastes, or industrial effluent. Many fertilizers contain ammonium either as ammonium nitrate, urea, or some other ammonium compound. Animal wastes (human and other) also contain ammonium and urea [(NH2)2CO]. In animal wastes and some fertilizers, much of the ammonia degasses into the atmosphere rather than entering the groundwater system. 1. Increased use of or change in formulation of fertilizers 2. New sources of waste disposal in springshed 3. Changes in waste management in springshed (new septic tanks, landfills, feedlots, etc.) 4. Increase in drainage of wetlands or natural sources of chemically reduced nitrogen 5. Decrease in the reduction/oxidation potential of the groundwater that causes an increase in nitrate reduction 1. Decreased use of or change in formulation of fertilizers 2. Reduction in the sources of wa ste disposal in springshed 3. Changes in waste management in springshed (septic tanks, landfills, feedlots, etc.) 4. Decrease in drainage of wetlands or na tural sources of chemically reduced nitrogen 5. Increase in the reduction/oxidation potential of the groundwater that causes an increase in nitrification (ammonia/ammonium oxidation) Calcium (Ca) The primary natural source of calcium in groundwater is dissolution of rock materials. In limestone aquifers, the reaction of recharging water with calcite in the limestone is: H2O + CO2 + CaCO3 Ca+2 + HCO3 -. Deep groundwater flow systems in the Floridan aquifer may skim along the top of the gypsum/anhydrite-rich strata of the Middle Confining Unit of the Floridan. Here, calcium is derived from dissolution of gypsum (CaSO4.2H2O) and/or anhydrite (CaSO4). Near the coasts and where saline water encroachment is a problem, the saline water is a source of Ca2+ as well. 1. The proportion of conduit flow is less and there is more diffuse flow 2. Relative contribution of water held in storage in the aquifer is increasing because of longer residence times and more opportunity to react with the host aquifer 3. A connection with the surface that allowed rapid recharge may be less efficient (a swallet has closed or become blocked) 4. A new, calcium-rich water source has been added to the flow system, either within the springshed or by encroachment of saline water 1. The proportion of conduit flow is increasing and there is less diffuse flow 2. Relative contribution of water held in storage in the aquifer is decreasing because of shorter residence times and less opportunity to react with the host aquifer 3. A connection with the surface that allowed rapid recharge may have developed or become more efficient (a swallet opened up) Chloride (Cl) Chloride is normally present in low concentrations in natural Florida groundwater systems. Th ere are four important sources: (1) low concentrations in rainwater as a result of entrainment of marine aerosols, (2) mixing with se awater near Florida coasts, (3) dissolution of gypsum and/or anhydrite at the base of the upper Floridan aquifer, and (4) connate water trapped within the upper Floridan aquifer. The latter is an important issue within the St. Johns River corridor. 1. Saline water encroachment is occurring, either by lateral movement of sea water or connate water or by up-coning of water from below 2. A new source of chloride has been added to the springshed (landfill, industry, etc.) 1. Saline water intrusion is declining, probably because pumping stresses are reduced or aquifer potentials have risen 2. A source of chloride has been eliminated or reduced in the springshed (landfill, industry, etc.) Discharge or flow Spring discharge is an artifact of the recharge rate of sources water, hydraulic gradient, spring elevation relative to aquifer potentials, and spring vent geometry. 1. Increase in recharge rates (more rainfall and increases in elevation of the potentiometric surface) 2. Reduction of stage in the receiving water (allows for increased drainage of the aquifer) 3. Reduction in pumping stress on aquifer 1. Decrease in recharge rates (less rainfa ll and declines in elevation of the potentiometric surface) 2. Increase of stage in the receiving water (retards flow from the spring) 3. Increase in pumping stress on aquifer

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2 Appendix B2. Origins of Temporal Trends in FloridaÂ’s Groundwater Interpretation When There Is A Pattern of Analyte Origin in Groundwater Increasing Trends Decreasing Trends Dissolved Oxygen (DO) Dissolved oxygen content in spring water is a function of (1) oxygen content of the recharge wa ter, (2) water temp. (the lower the temperature, the higher the oxygen solubility), (3) presence of biota that consume oxygen in the soils and aquifer along the flow path, (4) presence of organic and mineral matter that can be oxidized along the flow path, (5) residence time of the water in the aquifer, and (6) spring vent dynamics and rate of flow. 1. Increase in surfacewater component of spring flow, increase in conduit flow relative to diffuse flow 2. Decrease in ambient water temperature 3. Change in sample location relative to sources of water aeration 1. Decrease in surfacewater component of spring flow, increase in importance of diffuse flow relative to conduit flow 2. Increase in ambient water temperature 3. Change in sample location relative to sources of water aeration Fluoride (F) The primary source of fluoride in Florida spring water is dissolution of carbonate fluorapatite [Ca5(PO4,CO3)3F], the dominant phosphate mineral in the Miocene Hawthorn Group. Minor fluoride concentrations may be associated with saline water encroachment. 1. Increase in flow component derived from contact with the Hawthorn Group 2. Increase in waste sources, in cluding human and animal wastes, especially landfills and septic tanks 3. Increased industrial activity in springshed 1. Decrease in flow component derived from contact with the Hawthorn Group 2. Waste management improvement, including human and animal wastes 3. Decreased industrial activity or better chemical management in springshed Iron (Fe) Iron is a widespread component in Florida rocks, including limestone, dolostone, and siliciclastic strata of the Hawthorn Group. When included within the rock mass, the iron is often present in a reduced form as pyrite [FeS2]. Upon weathering and in a mildly reducing system, the iron remains reduced in the ferrous state (Fe2+) and it can travel with the groundwater. In a chemically oxidizing system, the iron is oxidized to Fe3+ at which time it typically precipitates as ferric hydroxide (Fe(OH)3). In springs, the moderately reducing water results in discharge of ferrous iron. Oxidation and precipitation often occur after the iron has entered the spring run. 1. Changes in water chemistry resulting in increased reduction/oxidation potential in water (dissolution of pyrite and freeing of ferric iron). This is often caused by injection of non-native water into the host aquifer. 2. Increase in sources in springshed, including waste disposal, disposal of waste iron in sinkholes, runoff from metallic sources 3. Increased use of iron-rich ag ricultural and horticultural plant and animal supplements 4. Changes in sample location, sample collection methods, or time of sampling that could change iron because of reduction/oxidation potentials or other physical conditions of sample. 1. Changes in water chemistry resulting in increased reduction/oxidation potential in water (precipitation of ferric hydroxide in water). 2. Decrease in sources in springshed, in cluding waste disposal, disposal of waste iron in sinkholes, runoff from metallic sources 3. Decreased use of iron-rich agricultural and horticultural plant and animal supplements 4. Changes in sample location, sample collection methods, or time of sampling that could change iron availability and oxidation state Magnesium (Mg) In Florida, magnesium is found in dolomite [CaMg(CO3)2] and in several of the important clay minerals of the Hawthorn Group, such as palygorskite [(Mg,Al)5(Si,Al)8O20(OH)2.8H2O] and montmorillonite [(Na,Ca)0.33(Al,Mg)2Si4O10(OH)2.nH2O]. Upon weathering, these and other magnesian clay minerals release magnesium to the groundwater. Saltwater encroachment is another source of magnesium in Florida groundwater. When the magnesium coexists with fluoride derived from weathering of carbonate fluorapatite, it can be assumed that the magnesium is from Hawthorn clays. If chloride is correlated to the magnesium, saline water is a probable source. 1. Up-coning or lateral migration of saline water 2. Increased proportion of flow that is diffuse in dolomitic rocks 3. Increased use of magnesium-rich soil supplements 4. Development of a quarry up-gradient that could increase the availability of highly soluble rock dust 1. Relaxation of up-coning or lateral migration of saline water, usually as a result of reductions in pumping stresses in aquifer or increased potentials 2. Reduced proportion of flow that is diffuse in origin in dolomitic rocks 3. Decreased use of magnesium-rich soil supplements Nitrate plus Nitrite as N (NO3 + NO2 as N) There are no significant natu ral sources of nitrate (NO3) in groundwater in Florida. Small amounts may be derived from naturally occurring organics by nitrification, but most nitrate comes from anthropogenic activities, such as use of fertilizers, waste disposal, and industrial applications. In recent years, nitrate has increased in rainfall as a result of atmospheric emissions and airborne dust related to human activities. 1. Increase use of nitrate-based fertilizers (turf mangmt., row crops, golf courses and other sources have been identified as sources of nitrate increases in Fla. Springs) 2. Increase in the rate of nitrification of reduced forms of nitrogen (e.g. NO2) by lowering of the water table, addition of nutrients that promote growth of nitrification microbes in soil 3. Increased surfacewater runoff to swallets, drainage wells, etc. 1. Decrease in use of nitrate-based fertili zers, especially of rapid-release. 2. Decrease in the rate of nitrificatio n of reduced forms of nitrogen by raising of the water table, reduction of nutrients that promote growth of nitrification microbes in soil 3. Decrease of nitrate-rich surface water runoff to storm-water facilities, swallets, drainage wells, etc. (can result from better storm water management and use of pre-treatment in storm-water infiltration basins) 4. Increase recharge and aquifer flow dynamics result in dilution and dispersion of nitrate in aquifer system

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3 Appendix B2. Origins of Temporal Trends in FloridaÂ’s Groundwater Interpretation When There Is A Pattern of Analyte Origin in Groundwater Increasing Trends Decreasing Trends Nitrogen (total) (N) Total nitrogen is an analyte that reflects ammonium/ ammonia, nitrite, nitrate, and some organic nitrogen compounds. It is sometimes used as a surrogate analyte for some or all of these compounds. See above See above Orthophosphate as P (o-PO4) In Florida groundwater, orthophosphate is derived from several sources, including (1) weathering of phosphatic minerals in the Hawthorn Group, (2) use of fertilizers, (3) waste disposal, including solid and human wastes, and (4), to a minor extent, natural humic substances. Orthophosphate has a very limited solubility in alkaline environments, so carbonate aquifers typically have low concentrations. When springs have relatively high concentrations of orthophosphate, it is typically because the water has had a low residence time in the aquifer and there has not been sufficient time or reaction surface for buffering to occur. In other words, a conduit flow system may be indicated. 1. Increase in acidic, phosphate-rich flow supplied by surfacewater sources, especially storm-water disposal in sinkholes, swallets and siphon s, to conduit flow systems 2. Increase in flow component derived from contact with the Hawthorn Group 3. Increase in phosphatic fertilizer use 4. Increase in animal waste use, including human and animal wastes 5. Increased industrial activity in springshed 1. Increase in low phosphate recharge through surfacewater sources, 2. Decrease of conduit flow component relative to the low-phosphate, diffuse flow component 3. Decrease in the flow component derived from contact with the Hawthorn Group 4. Decrease in, or better management of, phosphatic fertilizer use 5. Decrease in animal waste use or waste management improvement, including human and animal wastes 6. Decreased industrial activity or better phosphate management in springshed pH The analyte pH is a measure of the acid-base balance of water. The pH in limestone aqui fers is buffered by the reaction shown under alkalinity (above), and the groundwater is typically near neutral (6.9-7.3). If pH va lues are low relative to the pH created by chemical equilibration with the minerals in limestone, the water has not had opportunity to equilibrate because of short residence time, insufficient reactio n surface in the karst conduits, or a combination of the two. If the pH is relatively high, reactions other than equilibration with the calcite in the limestone a may be indicated. This includes reactions with the grouting materials in wells and with highly reactive, fine grained calcite. Because of the highly reactive calcite dust produced in limestone quarries, high pH groundwater may result. Some industrial wastes create relatively high pH values. 1. Reduction in the amount of more alkaline, diffuse flow relative to more acidic, conduit flow 2. Increased use of soil amendments to buffer acidic soils 3. Increase in highly soluble, carbonate dust related to the establishment of a quarry up-gradient 4. Change in sampling methods (this usually results in random noise, not a systematic change) 1. Increase in the amount of more alkaline, diffuse flow relative to more acidic, conduit flow in the water discharging from a spring 2. Decreased use of soil amendments to buffer acidic soils 3. Change in sampling methods (this usually results in random noise, not a systematic change) Potassium (K) In Florida, potassium occurs in some clay minerals, such as illite [(K,H3O)(Al,Mg,Fe)2(Si,Al)4O10[(OH)2,(H2O)]], and feldspars, such as orthoclase [KAlSi3O8]. These mineral sources are minor compared to sources associated with saline water intrusion and anthropogenic sources, such as fertilizer and waste disposal. 1. Increased use of potassium-rich fertilizers 2. Saline water intrusion, either as a result of increase pumping stress or reduction in aquifer potentials during droughts 1. Decreased use of potassium-rich fertilizers 2. Decrease in saline water in trusion, either as a result of reduced pumping stress or an increase in aquifer potentials Sodium (Na) The sources of sodium in Flor ida groundwater include saline water (seawater and connate water), animal wastes, and industrial wastes. Rainfall contains small amounts of sodium as a result of marine aerosols and dust. 1. Saline water intrusion, either as a result of increase pumping stress or reduction in aquifer potentials during droughts 2. Increased waste disposal in springshed (landfill leachate, human waste, etc.) 1. Reduction in saline water intrusion, either as a result of decreased pumping stress or increased aquifer potentials during wet periods 2. Decreased waste disposal or better waste management in springshed Specific Conductance (SC) Specific conductance is a measure of the ability of water to conduct an electrical current. The higher the concentrations of dissolved salts in the water, the higher the specific conductance. Bicarbonate, chloride, and sulfate are the constituents that contribute most to the specific conductance of an aqueous solution. 1. Increase in the proportion of diffuse flow relative to conduit flow 2. Saline water encroachment 1. Decrease in the proportion of diffuse flow relative to conduit flow 2. Reduction in saline water encroachment

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4 Appendix B2. Origins of Temporal Trends in Florida’s Groundwater Interpretation When There Is A Pattern of Analyte Origin in Groundwater Increasing Trends Decreasing Trends Strontium (Sr) Strontium is included as a tr ace constituent in aragonite, a calcium carbonate polymorph that commonly occurs in marine shells, corals, and certain algae. Therefore, when newly deposited, the carbonate sediments that become limestone and/or dolostone contain small, but important, concentrations of strontium, primarily in aragonite. As the carbonate sediments are altered to limestone or dolostone, the strontium is released to groundwater. Therefore, strontium is, in part, a good indicator of the chemical maturity of limestone. The strontium in the aragonite is derived from seawater, so seawater and saline waters in general may serve as sources for strontium in groundwater. Ther e are few other natural sources. 1. Saline-water encroachment 2. Increase in the proportion of water from diffuse flow relative to conduit flow 1. Reduction in up-coning of saline-water as a result of reductions in pumping stresses or increases in aquifer potentials 2. Decrease in the proportion of water from diffuse flow relative to conduit flow Sulfate (SO4) The sources of sulfate in Florida water include (1) dissolution of gypsum or anhydrite at the top of the Middle Confining Unit of the Floridan Aquifer System, (2) oxidation of pyrite in the aquifers and confining strata, (3) seawater and connate water, and (4) minor sulfate in marine aerosols in rainfall. Organic-rich sediments, such as peat, can serve as local sources of sulfate, as well. 1. Up-coning of saline water from the bottom of the upper Floridan aquifer or saline or connate water encroachment 2. Increased proportion of diffuse flow component relative to conduit flow 3. Increases in use of gypsum as a soil amendment for alkaline soils 4. Increase waste sources in springshed 5. Increase in industrial sources in springshed 1. Reduction in up-coning of saline water from the bottom of the upper Floridan aquifer or saline or connate water intrusion 2. Decreased proportion of diffuse flow component relative to conduit flow 3. Decreases in use of gypsum as a soil amendment for alkaline soils 4. Decrease waste sources in springshed 5. Decrease in industrial sources in springshed Water Temperature (Temp) In spring systems, the water temperature generally reflects mean annual air temperature in the springshed. Low or high temperatures typically reflec t conduit flow systems where seasonal variations in temperat ure create temperature variations that are not ameliorated by diffusion or mixing in the aquifer. 1. Climate cycles resulting in increased annual mean temperatures 2. Changes in the proportion of conduit and diffuse flow 3. Decreased influx of season ally cool water through swallets, siphons, drainage wells, storm-water basins 1. Climate cycles resulting in decreased annual mean temperatures 2. Changes in the proportion of conduit and diffuse flow 3. Increased influx of seasonally cool water through swallets, siphons, drainage wells, storm-water basins Total Dissolved Solids (TDS) Total dissolved solids is a measure of the total mass of constituents dissolved in groundwater. 1. Major causes of increased total dissolved solids relate to saline water encroachment 2. Introduction of new water sources to aquifer through waste disposal or construction 1. Major causes of decreased total dissolved solids relate to reductions in saline water encroachment Total Kjeldahl Nitrogen (TKN) Total Kjeldahl nitrogen TKN) refers to concentrations of organic nitrogen plus ammonia/ammonium in a water sample. The organic nitrogen concentration in the water can be obtained by subtracting ammonium/ammonia concentration from TKN concentration. The presence of TKN in groundwater indicates a nearby source of organic or am monia/ammonium nitrogen, such as a swamp or wetland or organic wastes (animal, human). The Avon Park Formation, which is part of the upper Floridan aquifer, contains peat beds that locally contribute TKN to groundwater. 1. Influx of organic materials to aquifer via swallets, siphons, injection wells, drainage wells, sinkholes in storm-water basins, etc. 2. Increase of surfacewater component in aquifer relative to groundwater with long residence time and filtration 1. Reduction in influx of organic materials to aquifer via swallets, siphons, injection wells, drainage wells, sinkholes in storm-water basins, etc. 2. Decrease of surfacewater component in aquifer relative to groundwater with long residence time and filtration Total Organic Carbon (TOC) Total organic carbon (TOC) is an analyte that is similar to TKN (above). It’s sources include organic-rich sediments and animal and plant wastes. Small amounts may be disseminated in sediments, such as clays and silts of the Hawthorn Group. See above See above Total Phosphorous (T–P) This includes orthophosphate as well as complex phosphates and other phosphorus, including organic phosphorus, compounds. Sources include naturally occurring org. sediments and wastes. See Total Kjeldahl nitrogen and orthophosphate See Total Kjeldahl nitrogen and orthophosphate

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5 Appendix B2. Origins of Temporal Trends in FloridaÂ’s Groundwater Interpretation When There Is A Pattern of Analyte Origin in Groundwater Increasing Trends Decreasing Trends Total Suspended Solids (TSS) This analyte constitutes the materials entrained in the water that can be recovered by filtering with an 0.45 micropore filter. The analyte, therefore, reflects particulate sediment discharging from the spring, colloidal precipitates forming in the spring, and microbenthic plants and animals living in the spring. 1. Introduction of surface water 2. Increase in turbulent flow in co nduits (often as a result of pumping) 3. Rapid introduction of aquifer or other geologic materials (sinkholes, construction, etc.) 1. Reduction of surface water influx 2. Decrease in turbulent flow in conduits 3. Flushing of particulates (sediments) in conduits Turbidity (Turb) Turbidity is a measure of the ability of light to pass through a water sample. Turbidity is caused by particulate materials suspended in the water and some dissolved or colloidal materials that hinder light penetration. Sources of turbidity in springs include surfacewater that contains high concentrations of humic substances and/or particulate matter, chemical reactions that result on precipitation of colloidal materials, and certain forms of plankton growth. See above See above Water Level/Stage (WL) Water level, or stage, is a meas ure of the hydraulic potential, or elevation of an unconfined wate r level. In a spring, the stage is either controlled by water le vels in the receiving water (the river or stream into which the spring discharges) or by the potentiometric surface of the source aquifer. Unlike rivers and streams, high stage may not reflect high discharge because of backwater effects associated with the receiving water. In fact, at highest stage, many springs (estavelles) flow backwaters from the receiving water into the aquifer. 1. Increase of aquifer potentials as a result of increased recharge 2. Increase in aquifer potentials as a result of reductions in aquifer stress (pumping) 3. Increase in stage of the receiving water (river, spring run) 1. Decrease of aquifer potentials as a result of reduced recharge 2. Decrease in aquifer potentials as a result of increases in aquifer stress (pumping) 3. Decrease in stage of the receiving water (river, spring run)

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APPENDIX D TD = Total Depth Csg = casingDepth LSElev =LandSurface Elevation MP = MeasuringPoint Con/Un = confined orunconfined Florida Geological Survey (FGS) W number Well IDSTATION_NAMETDCsgLSElevMPCon/UnCountyLATITUDE NLONGITUDE W(If applicable) NW 67 Wakulla Spring WellUNWakulla301407841809 91Donahue805625.6926.33UNLeon301840.901841738.3 129Weller Ave MPZ2322222020.82UNEscambia302228.2872003 131Weller Ave Shallow60502021.05UNEscambia302228.401872003 243Blontstown Floridan30320282.384.75CONCalhoun302700.03850413.2 245Blontstown Surf25582.8284.4UNCalhoun302700.7850412.2 312USGS 422a NR Greenhd15011066.1169.01CONWashington303024.8853503 313USGS 422b NR Greenhd262367.4870.28UNWashington303024.7853503 SR 1943 -1111170073661718UNDixie293137831430 2003-10160100260308988.14UNGilchrist293829.9823948.8 2193-720130016548157158.22CONBradford295236.1821549.7 2259-6140100348185658.72UNSuwannee295950.4825143.9 2353-41734002133113143145CONColumbia300612.5823630 2404-3083300168489091.97CONTaylor301113.7833139.6 2465-2123100180408688.04UNSuwannee301630.9830912 2585-1101100278587880.49CONMadison302451.2831750.6 26752133200410363121123CONHamilton303153.1830229.6 SW 615 ROMP 17 SWNN6706202529CONDesoto271028.2815835.4 707ROMP 23-1 Deep10009046366CONManatee271853.4821039.3 736Crewsville SH-AGW2669092UNHardee272544.6813522.8 737Crewsville UP INT-AG116969092CONHardee272544.6813522.8 775ROMP TR 8-1 INT16010015.219.29CONManatee273459.7823246 996Claywell Elem. SF171051.3453.30UNHillsborough280548.3823122.4 Well Construction and Location Data

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Well IDSTATION_NAMETDCsgLSElevMPCon/UnCountyLATITUDE NLONGITUDE W(If applicable) 997Claywell Elem. FL604052.4453.98CONHillsborough280548.4823122.5W5989 7934ROMP 23 Surf2120606UNManatee271853.4821039.2 7935ROMP 23 PZ225017560CONManatee271853.4821039.2 1087Withla. St. Forest G1759996.9498.54UNSumter282742815855.7 1100RdgeMnrRMP99XSh-A57367576UNHernando283036.7821054.8 SJ 1417 S-0045372717.3218.26UNSeminole284318810857 1420S-00381655519.1421.48CONSeminole284324810928 1762SJ002960335064.7768.29CONSt. Johns300507812726 1763SJ003012010064.8468.29CONSt. Johns300507812726 1764SJ0032604064.7365.64UNSt. Johns300508.8812726.3 1779BA0054700370125.75128.88CONBaker301618821109 1780BA005510080125.72128.77CONBaker301618821109 1781BA00566040 125.17128.71UNBaker301618821109 A L 1674 R22T10Sec20019556102103.19CONAlachua293622.2820815.6 1931R18T11Sec3101755810085.51UNAlachua292850.4823230.2 SF 2793 G-2364808005.92UNBroward260826.3801443.2 2872C-00972442511.1815.28UNCollier260844.9 2873C-009731509011.1814.48CONCollier260844.9813236.7 3108L-0220016312217.420CONLee264331.3813406.1 3109L-0220219717.4320.03UNLee264331.3813406 3398PBS-S4476.661.5911.76UNPalm Beach264901.7800451.4 3433POF-00081941496568.56CONPolk274848.9812619.5 3490KISSPARK73.8356063UNPolk275715812208 649027-3191910.311UNDade252924.4802716.2

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(FILE CONTAINS APPENDIX E1 AND E2) APPENDIX E. STATISTICS APPENDIX E1. STATISTICAL METHODOLOGIES (Xu-Feng Niu, Ph. D. [Department of Statistic s, Florida State University], and R. Copeland) Test for Seasonality Kruskal-Wallis (K-W) test —The K-W test (Hollander and Wolfe, 1973) was designed for comparing multiple populations. For this report , there are considered to be either four (winter, spring, summer, and fall) or 12 monthly seasons. The null hypothesis is: H 0: Measurements of the particular anal yte collected in each season are from the same distribution. The alternative hypothesis is H a: Measurements in the seasons ar e not from the same distribution. The basic assumptions for this test are: i) The measurements from different seas ons are mutually independent, i.e., the four (or 12) groups of observations { Y tniti,,, 1 } are mutually independent. ii) For a given season i, the observations { Y tniti,,, 1 } are a random (independent) sample from population i. iii) The four populations are continuous with distribu tion functions { F x ii(),,,} 14 , and the four (or 12) distribution functions are connected through the relationship F x F x ii()() . The distributions have the same shape and are different only by a mean shift i. Under the null hypothesis, we have F x F x f o r ii()(),,,, 1234 or equivalently 1234 . The test procedure is

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1) Combine the observations in the seasons and order them from the least to the largest 2) Let r it be the rank of Y it in the joint sample. Set RrandRRniit t n iiii 1/, i.e., R i is the rank sum of the observations in season iand Ri is the average rank for these same observations. 3) Let Nni i1 4. The Kruskal-Wallis (K-W) statistic H is then defined as ) 1 ( 3 ) 1 ( 12 2 1 ) 1 ( 124 1 2 2 4 1 N n R N N N R n N N Hi i i i i i, (A1) 4) For testing the null hypothesis at the level of significance, reject H 0 if H ha where the critical value h can be found in Table A.12 of Hollander and Wolfe (1973). 5) Large-Sample Approximation. For comparing four populations ( k=4 ), Table A.12 of Hollander and Wolfe (1973) provides critical values for14 ni. When n f o r ii 51234 ,,,,, the distribution of statistic H can be approximated by a chi-square distributi on with 3 degrees of freedom under the null hypothesis. The test thus can be performed by rejecting H 0 if H 3,; otherwise do not reject H 0. Mann-Whitney (M-W) test (o r Wilcoxon Rank Sum test) —For testing seasonality of a water quality analyte, one can first perform the Kruskal-Wallis (K-W) test. If the null hypothesis { F x F x f o r ii()(),,,, 1234} is not rejected, we may conclude that there is no seasonality in the data. If the null hypothesis is rejected, we need to figure out measurements in which two seasons have di fferent distributions (different means). For comparing any two populations, the Mann-Whitney (M-W) test can be employed. For example, suppose that we want to compare measurements of a water quality analyte from two different seasons, { Y tniti,,, 1 } and { Y tnjtj,,, 1}. The null hypothesis in this comparison is H F x F x ij 0:()() and the alternat ive hypothesis is H F x F x aij:()() or equivalently Y Y itjt where is the location shift or the difference between the two season.

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The Mann-Whitney (M-W) test procedur e can be performed as follows: 1) Combine the observations in the two seasons and order them from the least to the largest 2) Let r it be the rank of Y it in the joint sample. Set Wriit t ni 1, i.e., W i is the rank sum of the observations in season i. 3) One-Sided Upper-Tail Test. To test H 00 : versus H a: 0 at the significance level , reject H 0 if W wi where the critical value w can be found in Table A.6 of Hollander and Wolfe (1999). 4) One-Sided Lower-Tail Test. To test H 00 : versus H a: 0 at the significance level , reject H 0 if W nnnwiiij () 1 . 5) Two-Sided Test. To test H 00 : versus H a: 0 at the significance level , reject H 0 if W wi/2 or W nnnwiiij ()/12 . 6) Large-Sample Approximation. When nandnij 1010, define W W nnn nnnni iiij ijij * /[()] [()] 1 112. (A2) The distribution of the statistic Wi * can be approximated by the standard normal distribution N(0, 1). For the one-sided upper-tail test at th e significance level , reject H 0 if Wi* z. For the one-sided lower-tail te st at the significance level , reject H 0 if Wi* z. For the two-sided test, reject H 0 if |Wi* | z/2. Both M-W test and K-W test are nonpara metric tests (also ca lled distribution-free tests) that are applicable to different familie s of distributions such as normal, log-normal, and other continuous dist ributions. It should be pointed out that nonparametric tests still require independent observations. In other words, for a given season i, the observations { Y tniti,,, 1} need to be independent for the tests to be valid. Test for Trends Mann-Kendall (M-K) Test-For each analyte and each given season, the existence of linear upward or downward trends in the data will be determined by the Mann-Kendall

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(M-K) test (Gilbert, 1987; Ho llander and Wolfe, 1973) or th e Seasonal-Kendall (S-K) test if seasonality is present. Regarding th e M-K test, consider observations in the ith season { Y tnit,,, 1}. The M-K test can be performed in the following steps: 1) Calculate the differences { Y Y Y Y Y Y Y Y Y Y Y Y iiiiiniiiiniinin213113221 ,,,,,,,,,}. 2) Let sign( Y Y isit ) be the indicator function that takes the values 1, 0, and –1 according to the the sign of ( Y Y isit ), i.e., sign( Y Y isit ) = 1 if Y Y isit > 0, sign( Y Y isit ) = 0 if Y Y isit = 0, and sign( Y Y isit ) = -1 if Y Y isit < 0. The Mann-Kendall (M-K) statistic is KsignYYiis s t n t n it ()1 1 1. (A3) 3) Suppose that we want to test the null hypothesis of no trend in the data against the alternative hypothesis of an upward linear trend at the significance level . We reject the null hypothesis if K k i where the critical value k can be found in Table A.21 of Hollander and Wo lfe (1973). The one-sided lower-tail test and the two-sided test can be performed similarly. 3) Large sample approximation. When the sample size of the particular analyte for a given season is greater than 40 (n>40), normal approximation can be used for the trend testing. Specifi cally, we have (Gilbert, 1987, Chapter 16) ) 5 2 )( 1 ( ) 5 2 )( 1 ( 18 1 ) (1 j j q j j im m m n n n K Var, (A4) where q is the number of tied groups and mj is the number of observations in the j th group. Define ZKVarKifKiiii ()/[()],/1012; Z if K ii 00 ,; and ZKVarKifKiiii ()/[()],/1012 . If the H0 is true, the statistic Z i has a standard normal distribution.

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Sen Slope (S-S) SenÂ’s nonparametric estimator of slope is based on the Mann-Kendall approach and is intended to identify the sl ope of data regardless of seasonal influences. The first step is to calculate the number of slope estimates (N) for the time series, where N = [(n)(n-1)/2], and n = the number of observati ons in the series. Each slope estimate is determined by: , i j x x = Qi j (A5) where xj and xi are the values of data collected at times i and j, and j > i. In other words, the difference in the numerator of equation A5 reflects the change in condition of a sample collected at time j as comp ared to an earlier sample colle cted at time i. If the time intervals are equal, then the denominator of equation A5 becomes a constant and equation A5 results in the differences calculated for the Mann-Kendall test. The median of the ranked series is determined as follows: Sen s estimator = median slope, = Q(N + 1)/2 if N is odd, = (QN/2 + Q(N + 2)/2) if N is even. A two-sided test for confidence on the slope is determined using the table of the cumulative normal distribution. At an = 0.10, the Z1/2 is 1.64. This value from the table is compared to , ] [VAR(S) Z = C0.5 /2 1 where . 5)] + t 1)(2 t ( t 5) + 1)(2n [n(n 18 1 = VAR(S)p p p q =1, p (A6) The value of n is the number of samples in the time series, q is the number of ties, and tp is the number data in the pth group (the number of multiple samples in group p). For the example, n = 5 samples, q, the number of tied groups = 0, and tp, the number of ties in the pth group = 0.

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Time Series Models and Estimation of Trends Recall assumptions i, ii, and iii. If one of the three assumptions fails, results from the test methods may not be valid. The observations of a particular wa ter quality analyte are collecte d in a time order and hence likely to be temporally correlated. Thus for trend analyses, one or more of the assumptions may not be valid. With this consideration in mind, the test methods described so far should only be used for initial data analysis. For a formal trend analysis, time series models should be considered. Time series models are widely applied to data analyses in many fields of economical, biological, physical , and social sciences (Box and Jenkins, 1976; Brockwell and Davis, 1991; Pankratz , 1991; Tsay, 2002). Let { I ti(), i 1234 ,,,} be the four indicator variables for the four s easons, respectively. For example, I tift11 (), is a spring quarter and I tift10 (), is one of the other three quarters. Let { Y tnt,,, 1} be the quarterly measurements of a water quality analyte at a given sample well. We may consider the following regression and tim e series model for the observations: YIttItti i ii i it1 4 1 4()(), (A7) where { ii,,,, 1234} are the intercepts for the four (or 12) seasons, { ii,,,, 1234} are the slopes (linear trends) for the four seasons, and { ttn ,,, 1 } are random noises that may follow an autoregressive and movi ng-average (ARMA) mode l. A special class of ARMA models is the autoregressive type of models that have the form: tj j p tjt 1, (A8) where p is the order of the autoregression, { j j p ,,, 1} are unknown coefficients, and the tÂ’s are assumed to be uncorrelated and with identical normal distribution N(0, 2). The models in (A7) and (A8) can be fitted simultaneously by the SAS or the Splus statistical packages. The coefficients in the models can be estimated by the maximum likelihood methods. Different hypothese s on the coefficients can be tested by model comparison. For example, we test the null hypothesis H 01234: , (A9) which is equivalent to comparing model (A?) with the model

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YtItti i it1 4(). (A10) Similarly, we may test diffe rent hypotheses on the slopes { ii,,,, 1234}. Transformations Notice that in model (A8), the random errors tÂ’s are assumed to be uncorrelated, normally distributed, and with constant variance, which implies that the observations { Y tnt,,,1} are 1) normally distributed a nd 2) with constant variance 2. If one of the two assump tions is invalid, transforma tions should be performed on Y t to improve normality or to stabilize the variance. When { Y tnt,,,1} are positive numbers, the most popular transformation family is the Box-Cox power transformation family {Yt , 33} where 0 corresponding to the logarithm transformation. In practice, an appropriate transformation for Y t is usually chosen from the class { 21510500510152 ,.,,.,,.,.,.,}. The logarithm and the square-root transformatio ns are the most popular transformations chosen in data analysis. Missing data and censored data --Missing data will cause some problems in time series analysis. Here are two ad hoc ways to impute missing data in a time series: 1) Suppose that Y t is missing, we may impute Y t by Y Y Y t tt * 112 . 2) Another way is to impute Y t by the sample mean of the same season. For example, if the time t is a spring quarter, Y t can be imputed by the sample mean of the spring quarter observations in the series. The same way can be applied to monthly data. In water quality data analysis, censored data are usually caused by the minimum detection limit (MDL) of analytical laborat ories. A popular way is to impute censored data by MDL/2 or to simply use MDL.

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APPENDIX E2. MACRO CODES FOR MANN-KEDALL AND SEN SLOPE Macro Codes for Mann-Kendall Analysis macro mk x mcolumn x diffs y freqs wp S VarS Z p temp mconstant i j k m nx nx1 ny y1 y2 xname lab1 lab2 mreset notitle brief 0 noecho kkname xname x kkset lab1 " Ho: No trend in " kkcat lab1 xname lab2 let nx = n(x) if nx lt 10 brief 2 Note note *** Error *** The number of observations in the data set must note be greater than or equal to 10 for the Normal note Approximation method to produce valid results. note note *** Macro Exiting *** note note goto 100 endif let nx1 = nx-1 let m = 1 do i = 1:nx1 let k = i + 1 do j = k:nx let diffs(m) = x(j)-x(i) let m = m+1 enddo enddo tally x ; store y wp. sign diffs y tally y; store y freqs. let ny = n(y) if ny = 1 if y = -1 let S = -1*freqs elseif y = 0

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let S = 0 elseif y = 1 let S = Freqs endif elseif ny = 2 let y1 = y(1) let y2 = y(2) if y1 = -1 and y2 = 1 let S = freqs(2) freqs(1) elseif y1 = -1 and y2 = 0 let S = -1*freqs(1) elseif y1 = 0 and y2 = 1 let S = freqs(2) endif elseif ny = 3 let S = freqs(3) freqs(1) endif let VarS =((nx*nx1*(2*nx+5)) sum(wp*(wp-1)*(2*wp+5)))/18 if S > 0 let Z = (S-1)/sqrt(VarS) elseif S = 0 let Z = 0 elseif S < 0 let Z = (S+1)/sqrt(varS) endif cdf Z p let p = 1-p ### p-value for upward trend. title mtitle "Mann-Kendall Trend Test using the Normal Approximation" mtitle lab2 notitle note brief 2 print Z ; format('The calculated Z = ', f9.4). print p; format('For Ha: Upperward trend, the p-value = ', f8.5). cdf Z p ### p-value for downward trend print p; format('For Ha: Downward tre nd, the p-value = ', f8.5). Note The Normal approximation is valid only for data sets where n >= 10 copy nx temp print temp; Format(' For the given data set, n = ', I5). mlabel 100 endmacro

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Macro Codes for Sen Slope macro sens X; season sn. mcolumn X slope medslope mconstant i j k m nX nX1 xname ss ttl1 ttl2 ttl3 ttl4 sn mreset notitle if season = 0 let nX = n(X) let nX1 = n(X) 1 let k = 1 do i = 1:nX1 let m = i + 1 do j = m:nX let slope(k) = (X(i)-X(j))/(i-j) let k = k + 1 enddo enddo let medslope = median(slope) text medslope medslope; maxwidth 20. let ss = medslope(1) kkname xname x kkset ttl1 "Sen's Slope for " kkset ttl2 " = " kkcat ttl1 xname ttl3 kkcat ttl3 ttl2 ttl4 kkcat ttl4 ss ttl3 let medslope(1) = ttl3 mtitle "Sen's Slope" write medslope else endif endmacro

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The table below lists the method in whic h the data are displayed. Corresponding spring and well data are stored on the CD in three geographical regions. Northwest Florida contains information for the NW FWMD and the SRWMD. Central Florida contains data and information for the SJRWMD and the SWFWMD. Finally, South Florida contains well data and informati on for the SFWMD. Read more below table. Table A1. Diagram for Finding Corresponding Spring and Well Data. SJRWMD SWFWMD Northwest Florida NWFWMD SRWMD SFWMD Central Florida South Florida Data Individual Spring and Well Data ( 1991-2003 ) Northwest Fl o ri d a NWFWMD SRWMD SJRWMD SWFWMD SFWMD Central Fl o ri d a South Florida Complete Statistical Anal y sis Plus/minus Charts Plus/minus Charts Plus/minus Charts Individual Spring andWell Individual Spring andWell Individual Spring andWell

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Spring data files are listed by spring name . For example, Catfish Spring in the SWFWMD is found under Central Florida, SW springs, Catfish Spring.xls. Well data files are labeled by well number and are fo llowed by a letter. The number corresponds to the well number. The letter corresponds to th e time sequence (i.e. A, B, or C). For example, for the NWFWMD well 91, the data file is found Northwest, NW wells, 91A.xls.

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SpringDateMonth(nu)SeasonSeason_N o TempSCfpHT-AlkD-NO3NO2T-CaT-Mg Alexander S p 1/9/91 1Winter4 23.511667.89830.055** Alexander S p 7/8/91 7Summer2241402 7.72860.038** Alexander S p 9/25/91 9Fall323****** Alexander S p 1/7/92 1Winter4 23.311867.75**** Alexander S p 5/20/92 5Spring123****** Alexander S p 7/6/92 7Summer224.8 11637.43810.048*20 Alexander S p 9/21/92 9Fall323****** Alexander S p 1/18/93 1Winter4 23.311637.8830.0434520.5 Alexander S p 5/21/93 5Spring123****** Alexander S p 7/14/93 7Summer224*7.75 *0.044121.4 Alexander S p 9/24/93 9Fall323****** Alexander S p 1/20/94 1Winter4 22.711667.22810.0544422 Alexander S p 5/25/94 5Spring123****** Alexander S p 7/5/94 7Summer223.5 11807.75810.0394821.5 Alexander S p 9/22/94 9Fall323****** Alexander S p 1/10/95 1Winter4 22.110237.84810.0964319 Alexander S p 3/23/95 3Spring12411528.13810.0574419.6 Alexander S p 7/18/95 7Summer223.9 1084*800.065*22.7 Alexander S p 11/22/95 11Fall323.210597.7279*4419.2 Alexander S p 1/22/96 1Winter4 23.210257.47780.074620.2 Alexander S p 3/28/96 3Spring123.510777.35770.0644619.8 Alexander S p 7/9/96 7Summer224.2 11637.32780.0544520.1 Alexander S p 9/30/96 9Fall3241110***** Alexander S p 11/19/96 11Fall323.26*7.87780.0364619 Alexander S p 3/11/97 3Spring123.311107.85790.0554221.8 Alexander S p 5/21/97 5Spring123.51100***** Alexander S p 7/21/97 7Summer224.8* 7.7580.8310.0554121.3 Alexander S p 9/23/97 9Fall323.51170***** Alexander S p 11/5/97 11Fall323.36*7.5382.42180.0446.6220.97 Alexander S p 1/22/98 1Winter4 23.2*7.79 82.41380.03647.1920.77 Alexander S p 3/18/98 3Spring1**7.781.62260.03644.620.93 Alexander S p 5/22/98 5Spring12410207.8**** Alexander S p 7/17/98 7Summer223.45 969*78.84550.084*19.83 Alexander S p 11/11/98 11Fall323.3211387.5481.11780.06646.9319.83 Alexander S p 1/12/99 1Winter4 22.7910087.18 77.93430.0743.120.13 Alexander S p 3/18/99 3Spring123.329407.9278.13220.06343.619.08

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SpringDateMonth(nu)SeasonSeason_N o TempSCfpHT-AlkD-NO3NO2T-CaT-Mg Alexander S p 7/13/99 7Summer223.4 11327.8179.64920.04647.5320.31 Alexander S p 11/16/99 11Fall322.9611987.8380.3260.03948.7821.53 Alexander S p 3/20/00 3Spring123.411407.7480.0370.04747.1321.93 1/17/01 1Winter4 23.712007.9482.5410.02746.70321.251 Alexander S 3/1/01 3Spring1 2411927.7982.3460.03646.95321.464 7/3/01 7Summer2 23.7993884.1120.04248.58321.654 11/1/01 11Fall3 23.89047.7378.9730.04741.94818.644 1/22/02 1Winter4 23.76958.0982.2550.0545.9920.041 3/22/02 3Spring1 24.710217.6681.994*48.3321.242 7/12/02 7Summer2 *7798.4780.6780.0346.71420.868 11/15/02 11Fall3 19.17668.34820.054820 1/23/03 1Winter4 24.48047.88800.054721 6/27/03 6Summer2 23.911027.71820.054520

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DateT-NaT-KT-SO4T-FT-Sr TDST-PO4TClDischDate FLOW-CFS 1/9/91 **700.126644574*178.001/9/9198.17 7/8/91 **710.12765623*265.007/8/91105.07 9/25/91 ******** 9/25/91100 1/7/92 ******** 1/7/92101.64 5/20/92 ******** 5/20/9289 7/6/92 1374.2680.11483590*249.007/6/92101.01 9/21/92 ******** 9/21/9282 1/18/93 1383.9700.11733566*270.001/18/9384.28 5/21/93 ******** 5/21/9386 7/14/93 1494.1*0.12700**252.007/14/9389.82 9/24/93 ******** 9/24/9383 1/20/94 1374.1750.12769630*255.001/24/9495.1 5/25/94 ******** 5/25/94112 7/5/94 1253.9710.25894623*245.007/5/9485.7 9/22/94 ******** 9/22/9491.1 1/10/95 1283.5570.17395580.051224.001/10/9592.2 3/23/95 1244.2610.097295900.046239.003/23/9593.2 7/18/95 **690.12*6390.048307.007/18/9586.8 11/22/95 1263.8630.12408578*240.0011/22/9594.3 1/22/96 1313.2600.147085770.053234.001/22/96111 3/28/96 1384.2660.127636060.059254.003/28/96108 7/9/96 1384.3680.137406040.056265.007/9/96113.9 9/30/96 ******** 9/30/9698.4 11/19/96 1303.8630.157235780.076246.00** 3/11/97 1344660.127525860.047256.003/11/97132 5/21/97 ******** 5/21/97105 7/21/97 1313.765.7970.116825780.054251.40** 9/23/97 ******** 9/23/97106 11/5/97 140.34.64181.9130.127756340.046271.7011/12/9791.91 1/22/98 136.14.53274.620.137736840.046278.50** 3/18/98 133.94.29369.3360.127876190.053265.503/20/98111 5/22/98 ******** 5/22/98120 7/17/98 114.73.54357.1870.137175320.05216.207/17/9879.72 11/11/98 136.43.7264.4580.12837135560.049244.5011/11/98111.79 1/12/99 125.73.25860.1580.12876825500.053228.101/12/99112.58 3/18/99 124.23.59362.3890.13177525840.043238.003/18/99105.6

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DateT-NaT-KT-SO4T-FT-Sr TDST-PO4TClDischDate FLOW-CFS 7/13/99 1413.93568.20.12457846280.047261.007/13/99100.36 11/16/99 153.44.04972.0330.1357835*0.045278.4011/16/99110.06 3/20/00 146.34.2869.3410.12727906140.05263.003/20/0091.8 1/17/01143.544.31571.6610.12058146240.036262.20 1/17/0189.4 3/1/01144.754.39871.40.1286804.666370.019272.20 3/1/0180 7/3/01150.853.58560.0530.1356823.49*0.037271.00 7/5/0191.5 11/1/01120.513.93963.0370.1336701.054960.042227.70 1/22/02131.534.16864.5750.1396730.46*0.038238.30 3/22/02139.134.22467.2810.123780.336100.034250.20 7/12/02139.973.9690.1439782.095810.049258.90 11/15/021403.9680.17706310.04260.00 1/23/031403.9670.17706300.03260.00 6/27/031303.7680.17506460.05250.00

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SpringDateSeason_N o TempDsnTempSClpHT-AlkDsnT-AlkD-NO3NO2 Apopka (Gourd Neck) Spring nr Oakland 2/8/95 424.526.43522378.197373.47834.88 Apopka (Gourd Neck) Spring nr Oakland 8/28/95 22524.02022468.087271.0243* Apopka (Gourd Neck) Spring nr Oakland 11/21/95 32222.51592768.127372.28824.79 Apopka (Gourd Neck) Spring nr Oakland 2/21/96 42122.9352292*7070.47834.88 Apopka (Gourd Neck) Spring nr Oakland 5/28/96 12726.41792327.957070.99185.08 Apopka (Gourd Neck) Spring nr Oakland 8/21/96 224.723.72022558.037271.02434.84 Apopka (Gourd Neck) Spring nr Oakland 11/19/96 323.724.21592478.057170.28825.1 Apopka (Gourd Neck) Spring nr Oakland 3/4/97 126.9926.40792478.067272.99185.08 Apopka (Gourd Neck) Spring nr Oakland 5/13/97 124.423.81792408.337272.99185.131 Apopka (Gourd Neck) Spring nr Oakland 8/19/97 226.125.12022567.8272.42871.4523* Apopka (Gourd Neck) Spring nr Oakland 11/13/97 323.4323.94592407.8273.336872.6254.649 Apopka (Gourd Neck) Spring nr Oakland 2/18/98 421.623.53522478.6371.485271.96354.765 Apopka (Gourd Neck) Spring nr Oakland 5/13/98 124.624.01792378.0761.17462.16584.935 Apopka (Gourd Neck) Spring nr Oakland 8/18/98 22625.02022478.3772.696871.72114.827 Apopka (Gourd Neck) Spring nr Oakland 11/18/98 324.3524.86592578.0175.800275.08844.896 Apopka (Gourd Neck) Spring nr Oakland 2/17/99 423.4125.3452*8.4571.8604372.33885.095 Apopka (Gourd Neck) Spring nr Oakland 5/12/99 124.824.21792508.2271.232872.22465.394 Apopka (Gourd Neck) Spring nr Oakland 8/11/99 225.324.32022498.2272.639971.66425.184 Apopka (Gourd Neck) Spring nr Oakland 11/18/99 323.824.31592508.572.5471.82825.031 Apopka (Gourd Neck) Spring nr Oakland 3/8/00 124.123.51792478.0171.69872.68985.498 Apopka (Gourd Neck) Spring nr Oakland 5/17/00 124.724.11792628.6274.51775.50885.21 Apopka (Gourd Neck) Spring nr Oakland 3/21/01 1 22.68 22.0979 2517.372.569 73.5608 4.883 Apopka (Gourd Neck) Spring nr Oakland 6/19/01 2 25.1 24.1202 2477.9873.5 72.5243 4.581 Apopka (Gourd Neck) Spring nr Oakland 9/18/01 3 25.3 25.8159 2548.1972.981 72.2692 4.479 Apopka (Gourd Neck) Spring nr Oakland 12/20/01 4 21.7 23.6352 2378.1674.25 74.7283 4.523 Apopka (Gourd Neck) Spring nr Oakland 3/20/02 1 24.905 24.3229 2528.3474.659 75.6508 4.162 Apopka (Gourd Neck) Spring nr Oakland 6/20/02 2 24.55 23.5702 2548.1175.481 74.5053 4.364 Apopka (Gourd Neck) Spring nr Oakland 9/18/02 3 25.1 25.6159 2568.374.362 73.6502 * Apopka (Gourd Neck) Spring nr Oakland 1/2/03 4 23 24.9352 2537.8571.995 72.4733 4.408 Apopka (Gourd Neck) Spring nr Oakland 3/19/03 1 25.4 24.8179 2568.3676 76.9918 4.614 Apopka (Gourd Neck) Spring nr Oakland 7/29/03 2 26.6 25.6202 2707.9277.674 76.6983 4.227 Apopka

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DateDsnT-NO3NO2T-PDsnT-PTOCDsnTOCD-CaD-MgDsnMgT-NaDsnNaT-KDsnT-K 2/8/95 4.961****267.57.6895754.952111.41.23693 8/28/95 *0.0450.15828**287.77.5572454.9354411.02043 11/21/95 4.805330.0250.146483.12.792287.97.9335755.17227** 2/21/96 4.961****298.28.3895754.95211** 5/28/96 4.92080.036-0.02409**297.87.7733954.96302** 8/21/96 5.0090.0570.17028**287.87.657244.94.83544** 11/19/96 5.11533**2.11.792287.47.4335755.1722711.03343 3/4/97 4.92080.034-0.02609**277.27.1733954.963021.11.1296 5/13/97 4.97180.051-0.009092.042.29228.738.598.563395.065.02302** 8/19/97 *0.0290.14228 ********* 11/13/97 4.664330.0250.14648**30.48.28.233574.84.97227** 2/18/98 4.8460.029-0.212471.811.99229.636.957.139575.115.06211** 5/13/98 4.77580.033-0.02709**28.067.877.843394.834.79302** 8/18/98 4.9960.0160.12928**29.568.388.237245.255.18544** 11/18/98 4.911330.0270.14848**29.767.847.873574.7374.90927** 2/17/99 5.1761.4011.15953**28.827.868.049575.215.16211** 5/12/99 5.23480.0640.00391**30.758.048.013395.155.113021.0261.0556 8/11/99 5.3530.0690.18228**32.078.147.997245.275.205441.0981.11843 11/18/99 5.04633****30.487.787.813574.6624.83427** 3/8/00 5.33881.7391.67891**32.88.268.233395.365.323021.1281.1576 5/17/00 5.05080.0650.00491**27.87.937.903394.954.91302** 3/21/01 4.7238 0.031 -0.02909 * * 29.4848.041 8.01439 5.07 5.03302 1.028 1.0576 6/19/01 4.75 0.041 0.15428 * * 30.2218.262 8.11924 5.2 5.13544 1.036 1.05643 9/18/01 4.49433 0.033 0.15448 * * ** * * * * * 12/20/01 4.604 0.098 -0.14347 * * 28.8858.125 8.31457 5.18 5.13211 1.046 0.88293 3/20/02 4.0028 0.14 0.07991 * * 30.5858.344 8.31739 5.06 5.02302 * * 6/20/02 4.533 0.03 0.14328 * * 30.0458.074 7.93124 5.08 5.01544 1.024 1.04443 9/18/02 * 0.044 0.16548 * * 29.9828.178 8.21157 5.08 5.25227 1.053 1.08643 1/2/03 4.489 0.047 -0.19447 2.41 2.592 ** * * * * * 3/19/03 4.4548 0.123 0.06291 * * 307.8 7.77339 5.3 5.26302 1 1.0296 7/29/03 4.396 0.034 0.14728** ** * * * * *

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DateTKNT-SO4DsnT-SO4T-FSi(SIO3 as S D-SrTDSDsnTDST-PO4 ClFlowDateFlow-cfs 2/8/95 1287.82680.07548164168.4230.031*2/8/9231 8/28/95 12109.9403*458153150.683*12.007/18/9723.8 11/21/95 1187.9793*459187185.2660.03512.009/17/9730.85 2/21/96 11109.8268*460140144.4230.03111.0011/13/9730.08 5/28/96 1188.1512*460131131.410.03212.0012/17/9727.98 8/21/96 1287.9403*458136133.6830.03411.001/6/9830.74 11/19/96 1287.9793*458124122.2660.0312.002/18/9834.55 3/4/97 121010.1512*585144144.410.03112.003/20/9836.49 5/13/97 1199.1512*4.7563155155.410.02912.004/29/9834.68 8/19/97 12.0859.1469.0863*4.89*154151.6830.02611.007/21/9830.65 11/13/97 11.4449.0479.0263*4.9659.7155153.2660.02612.097/23/9826.27 2/18/98 11.339.7699.5958*4.9160.6**0.02811.448/24/9831 5/13/98 127.437.5812*5.0359.7151151.410.02811.331/25/9929.76 8/18/98 10.9029.6599.5993*4.7762.2**0.02712.005/4/9926.28 11/18/98 10.80110.81910.7983*5.2661.6140138.2660.02910.906/16/9927.4 2/17/99 11.4929.5219.3478*4.8260.3146150.4230.03210.8010/9/9922.44 5/12/99 12.89.910.0512*5.1262.5133133.410.02811.49 8/11/99 11.0679.0769.0163*4.9463.5128125.6830.025* 11/18/99 11.2959.3629.3413**59.8**0.02911.07 3/8/00 10.8629.1639.3142*4.8776144144.410.03211.30 5/17/00 11.2979.5749.7252*4.7963.9171171.410.03910.86 3/21/01 * 9.53 9.6812 0.0744.81861.58137 137.41 0.0211.3 6/19/01 * 9.571 9.5113 0.07454.84165.19155 152.683 0.01911.65 9/18/01 * 9.86 9.8393 *5.235*134 132.266 0.02612.4 12/20/01 * 9.72 9.5468 0.0812*60.91167 171.423 0.022511.5 3/20/02 * 9.322 9.4732 0.07325.37562.63150 150.41 0.0210.88 6/20/02 * 9.54 9.4803 0.07125.084561.15155 152.683 0.025511.21 9/18/02 * 10.082 10.0613 0.07184.95164.41144.5 142.766 *11.71 1/2/03 * 9.765 9.5918 *4.897*89.3 93.723 0.03311.41 3/19/03 * 10 10.1512 *5.01162140 140.41 0.0212 7/29/03 * 9.8 9.7403 *4.593*155 152.683 0.02512

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SpringDateSeason_N o TempSClSCfpHT-Alk D-NO3NO2T-Ca T-MgT-Na Fern Hammock Springs 5/23/91 122*137****** Fern Hammock Springs 7/10/91 222.7*2445.14830.079*** Fern Hammock Springs 1/6/92 421.3*1388.36520.089*** Fern Hammock Springs 1/18/93 421.31221228.14460.071114.42 Fern Hammock Springs 7/14/93 221.81201208.13*0.05313.34.572.86 Fern Hammock Springs 1/11/94 420.411211217.38440.0831342 Fern Hammock Springs 7/6/94 222.11161168.31470.058155.73 Fern Hammock Springs 11/14/94 321.89116*7.84450.098124.72 Fern Hammock Springs 1/9/95 4211141148.12460.122124.22 Fern Hammock Springs 3/21/95 122.11431438.32450.082145.13 Fern Hammock Springs 7/12/95 222.31191198.01440.075114.22 Fern Hammock Springs 11/16/95 321.3117*8.17440.127124.74 Fern Hammock Springs 1/16/96 421.41151157.64420.009124.73 Fern Hammock Springs 3/20/96 121.071161167.69440.086134.63 Fern Hammock Springs 7/10/96 222.61231237.66420.105124.53 Fern Hammock Springs 11/18/96 321.73***440.081124.23 Fern Hammock Springs 1/14/97 421.11181188440.069124.33 Fern Hammock Springs 3/10/97 121.81111118.15440.07114.43 Fern Hammock Springs 7/21/97 222.2111*844.18010.079114.42 Fern Hammock Springs 11/4/97 321.37112*7.1644.48490.08411.724.2783.029 Fern Hammock Springs 1/20/98 421.4**8.3644.43760.08812.934.3623.603 Fern Hammock Springs 3/10/98 121.07**7.5643.93710.0912.524.5122.909 Fern Hammock Springs 5/18/98 1**1287.08* **** Fern Hammock Springs 7/21/98 221.91112*8.0244.63560.08913.84.8932.234 Fern Hammock Springs 1/11/99 420.85114*7.3643.65010.08112.884.9432.678 Fern Hammock Springs 3/11/99 121.4106*8.542.9590.07612.94.6722.507 Fern Hammock Springs 5/19/99 121.6*117** **** Fern Hammock Springs 7/12/99 222.13115*8.1345.47860.06515.856.472.766 Fern Hammock Springs 11/15/99 321.68111*8.3643.0340.08313.364.832.191 Fern Hammock Springs 3/21/00 121.95114*8.3142.9060.0812.234.742.576 Fern Hammock Springs1/16/01 4 21.35 * 1218.1645.5530.08915.8245.0942.8 Fern Hammock Springs3/5/01 1 21.5 * 114.38.4844.6970.07312.2714.5952.543 Fern Hammock Springs7/3/01 2 22 * 1158.145.8760.08813.0684.6752.533 Fern Hammock Springs11/1/01 3 21.9 * 1158.5343.7730.0912.6264.6472.661 Fern Hammock Springs1/22/02 4 21.7 * 1118.3545.2660.08512.7644.7652.69 Fern Hammock Springs3/22/02 1 21.6 * 1268.5144.6990.0814.135.3772.734 Fern Hammock Springs7/12/02 2 22.1 * 1228.4745.273*13.0194.872.725 Fern Hammock Springs11/15/02 3 * * 1258.43470.08145.22.4 Fern Hammock Springs1/24/03 4 20.5 * 1268.76460.09145.12.5 Fern Hammock Springs3/21/03 1 22.1 * 1238.42470.24144.92.6 Fern Hammock Springs6/26/03 2 22.5 * 1238.36470.08155.42.6 Fern Hammock Springs8/7/03 2 22 * 1248.17470.1145.22.6

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DateTKNT-SO4F(TorF)Si(SIO3 as T-Sr TDST-PO4T-ClSTAGE FEETDateFlow FLOW-CFS 5/23/91 ******* 3.001.8405/23/199110.6 7/10/91 3200.124*152**07/10/199110.2 1/6/92 550.064*64*3.0001/06/199212.02 1/18/93 780.0645369*4.0001/18/199311.93 7/14/93 4*0.068*86.8**4.0007/14/199310.3 1/11/94 460.07464**6.0001/11/199410.8 7/6/94 6200.08418692*5.0007/06/199410.5 11/14/94 550.06470610.0243.00 1/9/95 360.06474640.0249.0011/17/199413.82 3/21/95 9100.064146750.025*01/09/199513.3 7/12/95 *50.07470730.0245.0003/21/199513.1 11/16/95 530.07484770.0253.0023.2305/26/199511.9 1/16/96 350.07479670.1094.0007/12/199512.5 3/20/96 460.07481680.0245.0023.4809/25/199514.3 7/10/96 560.07483610.0214.0011/16/199513 11/18/96 470.07479560.0224.0001/16/199612.6 1/14/97 480.07479490.0254.0003/20/199613.3 3/10/97 470.07464660.02311.6723.404/29/199616.8 7/21/97 11.6658.3820.073.9354850.0215.4507/10/199613.36 11/4/97 5.4486.2110.074.0684.3690.0224.5923.3709/27/199613.2 1/20/98 4.5878.4270.073.8782.8760.0234.8511/18/199614.8 3/10/98 4.8536.7670.064.2488.2550.027*01/14/199713 5/18/98 ******* 4.3703/10/199712.8 7/21/98 4.3665.8570.074.0489.1630.0264.6204/30/199712.5 1/11/99 4.6176.2090.07384.0576.2660.0195.4823.2105/24/199712.84 3/11/99 5.4756.550.07534.1486.5750.022*07/15/199711.8 5/19/99 ******* 4.8009/25/199711.4 7/12/99 4.87.10.07924.44210.8860.0224.7123.211/04/199711.51 11/15/99 4.7066.580.0763.9791.3*0.0194.4101/20/199812.2 3/21/00 4.4075.2240.07054.174.9580.023 4.54 03/10/199811.98 1/16/01 * 8.0190.0725 * 112.857640.0174.539 05/18/199813.4 3/5/01 * 5.4230.0702 * 78.179420.0184.514 23.2707/21/199811.9 7/3/01 * 5.830.0757 * 81.402*0.0254.564 09/24/199815 11/1/01 * 5.3360.0768 * 77.855670.0214.414 23.411/10/199812.91 1/22/02 * 5.5750.0791 * 81.241*0.0224.607 01/11/199911.81 3/22/02 * 8.3520.0732 * 116.651880.0243.978 03/11/199911.46 7/12/02 * 8.5320.0819 * 103.155770.0226.827 05/19/199912.1 11/15/02 * 9.50.1 * 120760.024.4 23.2707/12/199912.81 1/24/03 * 8.90.1 * 120720.024.5 09/24/199912.6 3/21/03 * 8.5 ** 110720.024.5 11/15/199911.67 6/26/03 * 9.9 ** 140740.024.4 01/08/200011.8 8/7/03 * 9.5 ** 120770.024.4 01/18/200011.8 03/21/200010.68 05/22/20009.27 23.0406/13/200010.5 09/19/200011

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SpringSampDateYearDayDateMonth(txt)Month(nu)SeasonSeason_N o SourceTempSClSCfpHT-AlkD-NO3 Juniper Springs 19910108199108 1/8/91 11Winter4SJR21.3116*8.6846* Juniper Springs19910523199123 5/23/91 55Spring1USGS22*122*** Juniper Springs19910710199110 7/10/91 77Summer2SJR22.2*1166.444* Juniper Springs19910729199129 7/29/91 77Summer2SJR***8.53** Juniper Springs19920706199206 7/6/92 77Summer2SJR**117*48* Juniper Springs19930118199318 1/18/93 11Winter4SJR21.51171178.552* Juniper Springs19930712199312 7/12/93 77Summer2SJR22.31391398.0746* Juniper Springs19940111199411 1/11/94 11Winter4SJR20.71181187.8144* Juniper Springs19940706199406 7/6/94 77Summer2SJR221141148.4845* Juniper Springs19941114199414 11/14/94 1111Fall3SJR21.98117*8.344* Juniper Springs19950109199509 1/9/95 11Winter4SJR21.41231238.2645* Juniper Springs19950321199521 3/21/95 33Spring1SJR21.41441448.444* Juniper Springs19950712199512 7/12/95 77Summer2SJR22.21171178.3444* Juniper Springs19951116199516 11/16/95 1111Fall3SJR21.3110*8.2644* Juniper Springs19960116199616 1/16/96 11Winter4SJR21.6113113*42* Juniper Springs19960320199620 3/20/96 33Spring1SJR21.5119*7.6543* Juniper Springs19960328199628 3/28/96 33Spring1SJR21.5*1197.65** Juniper Springs19960429199629 4/29/96 44Spring1SJR ****42* Juniper Springs19960503199603 5/3/96 55Spring1SJR22.05108*8.32** Juniper Springs19960710199610 7/10/96 77Summer2SJR22.11181187.9242* Juniper Springs19961118199618 11/18/96 1111Fall3SJR21.79***44* Juniper Springs19970114199714 1/14/97 11Winter4SJR21.41191198.2744* Juniper Springs19970115199715 1/15/97 11Winter4USGS21.6*1067.8** Juniper Springs19970310199710 3/10/97 33Spring1SJR21.71281287.7744* Juniper Springs19970721199721 7/21/97 77Summer2SJR22.2110*8.5543.8247* Juniper Springs19971103199703 11/3/97 1111Fall3SJR21.78***44.1878* Juniper Springs19980114199814 1/14/98 11Winter4SJR21.31**7.4146.4* Juniper Springs19980310199810 3/10/98 33Spring1SJR21.45**8.2443.597* Juniper Springs19980518199818 5/18/98 55Spring1USGS22*1165.87** Juniper Springs19980721199821 7/21/98 77Summer2SJR22.05113*8.1144.2045* Juniper Springs19981111199811 11/11/98 1111Fall3SJR22.07121*8.2245.663* Juniper Springs19990111199911 1/11/99 11Winter4SJR21.38117*7.8443.3149* Juniper Springs19990311199911 3/11/99 33Spring1SJR21.38105*8.8342.8315* Juniper Springs19990519199919 5/19/99 55Spring1USGS22.2*115*** Juniper Springs19990712199912 7/12/99 77Summer2SJR21.87177*8.6144.0692* Juniper Springs19991115199915 11/15/99 1111Fall3SJR21.59112*8.5542.498* Juniper Springs20000321200021 3/21/00 33Spring1SJR21.62112*8.2543.177* Juniper Springs *** 1/19/01 *1Winter4* 21.6 * 11468.5745.25 * Juniper Springs *** 2/27/01 *2Winter4* 21.92 * 1197.2344.347 * Juniper Springs *** 3/5/01 *3Spring1* 21.3 * 113.78.744.804 * Juniper Springs *** 7/3/01 *7Summer2* 21.9 * 114.48.644.696 * Juniper Springs *** 11/1/01 *11Fall3* 22.1 * 1098.5643.069 * Juniper Springs *** 1/22/02 *1Winter4* 21.8 * 1108.4444.513 * Juniper Springs *** 3/22/02 *3Spring1* 21.7 * 1148.6744.489 * Juniper Springs *** 7/12/02 *7Summer2* 22.5 * 1158.744.792 * Juniper Springs *** 10/15/02 *10Fall3* * * 1148.6447 * Juniper Springs *** 1/24/03 *1Winter4* 21.2 * 1168.9245 * Juniper Springs *** 3/21/03 *3Spring1* 22.2 * 1148.7846 * Juniper Springs *** 6/26/03 *6Summer2* 22.9 * 1148.7546 * Juniper Springs *** 8/7/03 *8Summer2* 22.2 * 1158.4646 * Juniper Springs *** 11/21/03 *11Fall3* 21.5 * 1158.4744.9 *

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DateT-NO3D-NO3NO2T-NO3NO2T-NO3andD-NO3NO2NitrateT-PD-PTOCCaT-CaMgT-MgT-NaNa 1/8/91 *0.082*Nitrate is a combination0.082***9*5.7**2 5/23/91 ***For Juniper Spring* ********* 7/10/91 *0.074*Labeled as Nitrate0.074***10*4.3**9 7/29/91 ************** 7/6/92 *0.071**0.071***11114.44.833 1/18/93 *0.083**0.083***20124.44.235 7/12/93 *0.084**0.084***13134.44.433 1/11/94 *0.08**0.08**1.711133.93.823 7/6/94 *0.066**0.066***12134.54.633 11/14/94 *0.08**0.08***12124.54.522 1/9/95 *0.112**0.112***1212 4432 3/21/95 *0.079**0.079***12843.933 7/12/95 *0.074**0.074 ****12*4.33* 11/16/95 *0.118**0.118 ****12*4.54* 1/16/96 *********13*4.84* 3/20/96 *0.08**0.08 ****14*4.73* 3/28/96 ************** 4/29/96 *0.0770.076*0.0770.0290.028*13*4.5**3 5/3/96 ************** 7/10/96 *0.097**0.097 ****12*4.44* 11/18/96 *0.08**0.08 ****12*4.23* 1/14/97 *0.067**0.067 ****12*4.23* 1/15/97 ********13*4.4**2.5 3/10/97 *0.073**0.073 ****11*4.13* 7/21/97 *0.072**0.072 ****11*42* 11/3/97 *0.081**0.081 **** 11.57*4.0353.2* 1/14/98 *0.074**0.074 **** 11.37*4.4283.548* 3/10/98 *0.081**0.081 **** 12.62*4.1992.916* 5/18/98 ************** 7/21/98 *0.082**0.082 **** 14.26*4.7912.312* 11/11/98 *0.102**0.102 **** 13.46*4.4372.6* 1/11/99 *0.076**0.076 **** 13.23*5.093.257* 3/11/99 *0.079**0.079 **** 13.06*4.4842.571* 5/19/99 ************** 7/12/99 *0.069**0.069 **** 12.71*4.5052.526* 11/15/99 *0.08**0.08 **** 12.97*4.5952.1* 3/21/00 *0.081**0.081 **** 12.34*4.5742.566* 1/19/010.08 *** 0.08* *** 12.959 * 4.6612.8 * 2/27/01* *** *0.030.025 ** 12.294 * 4.3482.53 * 3/5/010.077 *** 0.077* *** 12.422 * 4.4412.52 * 7/3/010.1 *** 0.1* *** 12.794 * 4.3692.46 * 11/1/010.078 *** 0.078* *** 13.076 * 4.4682.66 * 1/22/020.077 *** 0.077* *** 13.284 * 4.5562.64 * 3/22/020.075 *** 0.075* *** 13.55 * 4.742.66 * 7/12/02* *** ** *** 13.358 * 4.4922.59 * 10/15/020.08 *** 0.08* *** 13 * 4.52.5 * 1/24/030.08 *** 0.08* *** 13 * 4.52.4 * 3/21/030.09 *** 0.09* *** 13 * 4.42.6 * 6/26/030.08 *** 0.08* *** 13 * 4.42.5 * 8/7/030.12 *** 0.12* *** 13 * 4.42.5 * 11/21/030.0877 *** 0.08770.047 *** 12.95 * 4.4212.67 *

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DateKT-KTKNT-SO4FT-FD-F and T-FFluorideSiSi(SIO3 as T-FeD-FeD-SrT-SrTDS 1/8/91 0.3*440.07*Fluoride is a combinationn0.07*4 ***** 5/23/91 ******of D-F and T-F ******** 7/10/91 **460.07**0.07*4**35*84 7/29/91 *************** 7/6/92 **460.06**0.06*4***4670 1/18/93 **1350.06**0.06*4**484594 7/12/93 ***70.062**0.062*477 **** 1/11/94 **460.070.07*0.07*4***54* 7/6/94 0.40.856*0.07*0.07*441*4910781 11/14/94 **54*0.07*0.07*4**676558 1/9/95 **56*0.06*0.06*4**686972 3/21/95 **86*0.06*0.06*4**657264 7/12/95 ***6*0.06*0.06*452**7780 11/16/95 ***** 0.07*0.07*4***7875 1/16/96 **45*0.08*0.08*4***8164 3/20/96 **56*0.13*0.13*4680**9467 3/28/96 *************** 4/29/96 **48*0.07*0.075***80*65 5/3/96 *************** 7/10/96 **55*0.07*0.07*4***8160 11/18/96 **5**0.07*0.07*4***7957 1/14/97 **49*0.07*0.07*4***7950 1/15/97 0.2*4.36.30.1**0.18.8***80*80 3/10/97 **47*0.06*0.06*4***6170 7/21/97 **4.7395.794*0.06*0.06*4.05***5533 11/3/97 **5.396.42*0.06*0.06*4.32***75.576 1/14/98 **12.5817.992*0.06*0.06*3.89***79.874 3/10/98 **4.7426.082*0.06*0.06*4.31***80.157 5/18/98 *************** 7/21/98 **4.3865.69*0.07*0.07*4.13***8965 11/11/98 **4.86.132*0.0713*0.0713*4.53***78.461 1/11/99 **6.867.083*0.0712*0.0712*4.11***7768 3/11/99 **8.6146.691*0.0716*0.0716*4.22***83.882 5/19/99 *************** 7/12/99 **4.85.9*0.0684*0.0684*4.42***82.475 11/15/99 **4.8885.863*0.0733*0.0733*4.17***82.2* 3/21/00 **4.4826.11*0.0688*0.0688*4.24***75.875 1/19/01 * * * 5.6730.0673 ** 0.0673 * 4.415 *** 80.3159 2/27/01 * * * 5.7080.0689 ** 0.06898.703* ** 76.80776.1773 3/5/01 * * * 5.7860.0682 ** 0.0682 * 4.064 *** 76.7854 7/3/01 * * * 7.9440.0728 ** 0.0728 * 4.073 *** 77.2* 11/1/01 * * * 5.6380.0768 ** 0.0768 * 4.55 *** 82.4566 1/22/02 * * * 5.4870.0783 ** 0.0783 * 4.69 *** 81.12* 3/22/02 * * * 5.4760.0667 ** 0.0667 * 4.502 *** 83.2873 7/12/02 * * * 5.3680.0768 ** 0.0768 * 4.434 *** 85.0481 10/15/02 * 0.3 * 5.50.1 ** 0.1 * * *** 8063 1/24/03 * 0.3 * 5.50.1 ** 0.1 * * *** 7966 3/21/03 * 0.3 * 5.4* **** * *** 8168 6/26/03 * 0.3 * 5.6* **** * *** 8168 8/7/03 * 0.3 * 5.6* **** * *** 7875 11/21/03 * * * 4.98* **** * *** *63

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DateT-PO4T-Cl*DateFlowT-Cl*DateFlow 1/8/91 ***Flow Data01/08/19917.55 5/23/91 ***03/07/19916.83 7/10/91 ***04/29/19917.59 7/29/91 *4.00*05/23/19915.6 7/6/92 ***07/10/19918.33 1/18/93 *4.00*** 7/12/93 ***09/04/19919.42 1/11/94 ***09/27/19918.2 7/6/94 ***11/04/19918.15 11/14/94 0.031**03/02/19928.73 1/9/95 0.027**05/11/19928.79 3/21/95 0.025**05/22/19927.8 7/12/95 0.02613.00*07/06/19929.37 continued: 11/16/95 0.025**09/08/19929.1212.58*11/03/19979.53 1/16/96 ***09/24/199284.74*01/14/199810.18 3/20/96 0.082**11/04/19929.6**03/10/199810.23 3/28/96 ***01/18/199310.314.39*05/18/199810.9 4/29/96 0.03**03/01/19939.294.80*07/21/199810.9 5/3/96 ***05/20/19937.5**09/24/199810.9 7/10/96 0.024**05/20/19938.66**11/10/199812.38 11/18/96 0.0254.00*07/12/19939.036.86*** 1/14/97 0.023**09/07/19937.988.61*01/11/199910.29 1/15/97 ***09/23/19938.3**03/11/199910.98 3/10/97 0.0265.00*01/11/19948.014.80*05/19/199911.2 7/21/97 0.025**03/10/19948.444.89*07/12/199910.88 11/3/97 0.024**05/03/19947.86**09/24/19998.27 1/14/98 0.027**05/26/199484.48*11/15/199910.28 3/10/98 0.0275.00*07/06/19948.86**01/18/20009.56 5/18/98 ***09/20/199410.5 4.83 *03/21/20009.53 7/21/98 0.032**09/23/199410 * *05/22/20007.54 11/11/98 0.0265.00*11/14/199410.79 * *06/13/20008.59 1/11/99 0.0218.00*01/09/199511.8 * *09/19/20008.2 3/11/99 0.023**03/21/199512.5 5/19/99 ***05/26/199510.3 7/12/99 0.02**07/12/199510.8 11/15/99 0.025**09/25/199512.5 3/21/00 0.0224.00*11/16/199512.72 1/19/010.013 5.00*01/16/199612.3 2/27/01* **** 3/5/010.019 4.00*03/28/199611.8 7/3/01* **04/29/199612.4 11/1/010.039 5.00*** 1/22/020.032 5.00*07/10/199611.38 3/22/020.019 **09/27/199612.2 7/12/020.034 **11/11/199613.46 10/15/020.02 4.00*11/18/199613.46 1/24/030.02 4.30*01/14/199711.4 3/21/030.02 4.00*** 6/26/030.03 4.74*03/10/199710.7 8/7/030.02 **04/30/199711.3 11/21/030.0236 **05/24/199710.5 5.39*** **09/25/19979.83

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SpringSampDateYearDayDateMonth(txt)Month(nu)SeasonSeason_N o SourceTempSClSCfpHT-Alk Miami Springs 19930517199317 5/17/93 55Spring1USGS25.2*2608.2* Miami Springs19930930199330 9/30/93 99Fall3SJR24.12692697.42106 Miami Springs19950526199526 5/26/95 55Spring1USGS24.4*263** Miami Springs19950620199520 6/20/95 66Summer2SJR23.5261*7.55108 Miami Springs19950907199507 9/7/95 99Fall3SJR24.092672677.08109 Miami Springs19951102199502 11/2/95 1111Fall3USGS24.5*271** Miami Springs19960521199621 5/21/96 55Spring1SJR24.08264*7.25110 Miami Springs19960917199617 9/17/96 99Fall3SJR25.072562567.52112 Miami Springs19970421199721 4/21/97 44Spring1USGS25.1*265** Miami Springs19970514199714 5/14/97 55Spring1SJR24.11269*7.24111 Miami Springs19970910199710 9/10/97 99Fall3SJR24.1254*6.99110.4462 Miami Springs19980519199819 5/19/98 55Spring1USGS24*2737.56* Miami Springs19980520199820 5/20/98 55Spring1SJR24.13260*7.55109.7779 Miami Springs19980909199809 9/9/98 99Fall3SJR24.1269*7.25112.2451 Miami Springs19990518199918 5/18/99 55Spring1SJR24.04275**108.7445 Miami Springs19990519199919 5/19/99 55Spring1USGS24.9*275** Miami Springs19990908199908 9/8/99 99Fall3SJR24.15272*7.04111.3038 Miami Springs20000517200017 5/17/00 55Spring1SJR24.13282*7.51113.77 Miami Springs1/17/01 11Winter4 24.19 * 2767.7116.756 Miami Springs1/18/01 11Winter4 24.12 * 2807.11115.314 Miami Springs3/6/01 33Spring1 24.04 * 2777.72113.446 Miami Springs5/15/01 55Spring1 24.16 * 2767.48113.57 Miami Springs7/10/01 77Summer2 24.14 * 2707.54114.675 Miami Springs9/17/01 99Fall3 24.23 * 280*110.929 Miami Springs11/13/01 1111Fall3 24.1 * 2587.59113.873 Miami Springs1/29/02 11Winter4 24.4 * 2727.6115.637 Miami Springs3/19/02 33Spring1 24.4 * 2757.56115.342 Miami Springs7/16/02 77Summer2 25.2 * 2837.58114.127 Miami Springs11/14/02 1111Fall3 * * 2827.66117 Miami Springs1/23/03 11Winter4 23 * 2427.81113 Miami Springs3/27/03 33Spring1 24 * 2768.3114 Miami Springs6/25/03 66Summer2 24.1 * 2757.33115 Miami Springs8/12/03 88Summer2 24.3 * 2677.57114 Miami Springs11/18/03 1111Fall3 24.4 * 2467.79112

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DateD-NO3T-NO3D-NO3NO2DNO3NO2 or TNO3T-NO3NO 2 T-PD-PTOCCaT-CaMgT-MgT-Na 5/17/93 ********33*8.4** 9/30/93 **0.0780.078 ****33288.78.67 5/26/95 ********32*8** 6/20/95 **0.0390.039 *****33*8.76 9/7/95 **0.3650.365 ****343298.56 11/2/95 ************* 5/21/96 **0.2390.239 *****34*95 9/17/96 **0.1540.154 *****33*8.86 4/21/97 ************* 5/14/97 **0.0140.014 ***** 33.21*8.546.07 9/10/97 **0.1570.157 ***** 31.6*8.455.71 5/19/98 ************* 5/20/98 **0.190.19 ***** 34.5*9.835.67 9/9/98 **0.1340.134 ***** 35.4*9.335.51 5/18/99 **0.0620.062 ***** 37.05*9.225.93 5/19/99 ************* 9/8/99 **0.1860.186 ***** 35.7*9.696.43 5/17/00 **0.070.07 ***** 36.44*9.786.38 1/17/01 * 0.049 * 0.049 * * *** 36.852 * 9.6556.04 1/18/010.0420.042 * 0.042 * 0.0990.097 ** 36.33 * 9.7215.92 3/6/01 * 0.009 * 0.009 * * *** 35.176 * 9.4076.06 5/15/01 * * * * * * *** 34.929 * 9.3865.83 7/10/01 * 0.043 * 0.043 * * *** 35.803 * 9.1765.93 9/17/01 * 0.176 * 0.176 * * *** 34.109 * 9.6216.21 11/13/01 * 0.259 * 0.259 * * *** 36.865 * 9.9996 1/29/02 * 0.066 * 0.066 * * *** 35.514 * 9.7836.09 3/19/02 * 0.043 * 0.043 * * *** 37.143 * 10.0785.97 7/16/02 * 0.264 * 0.264 * * *** 35.304 * 9.6245.98 11/14/02 * 0.21 * 0.21 * * *** 37 * 9.75.7 1/23/03 * 0.4 * 0.4 * * *** 37 * 9.95.9 3/27/03 * 0.31 * 0.31 * * *** 37 * 9.56.3 6/25/03 * 0.49 * 0.49 * * *** 37 * 106.7 8/12/03 * 0.54 * 0.54 * * *** 35 * 106.3 11/18/03 * 0.194 * 0.194 * 0.13 *** 35.65 * 9.4486.26

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DateNaKT-KTKNT-SO4FT-FFluoride (DF or TF)SiSi(SIO3 asT-FeD-FeD-SrT-Sr 5/17/93 5.40.72*107.70.2*0.28.5***190* 9/30/93 6*19100.150.150.15*4**186218 5/26/95 6.20.8*118.50.2*0.28**3240* 6/20/95 **1.4109*0.160.16*493**180 9/7/95 6**113*0.150.15*457*171160 11/2/95 ************** 5/21/96 **11117*0.160.16*880**175 9/17/96 **11012*0.180.18*4***177 4/21/97 ***109.5********* 5/14/97 ***108*0.150.15*4.24***186.7 9/10/97 **1.16710.1859.08*0.160.16*4.18***174.8 5/19/98 ************** 5/20/98 ***10.59.048*0.16290.1629*4.22***181.8 9/9/98 ***10.1399.146*0.16490.1649*4.15***176.9 5/18/99 ****9.576*0.15460.1546*4.34***195.1 5/19/99 ************** 9/8/99 **1.12810.279.738*0.15820.1582*4.32***188.7 5/17/00 **1.15810.73610.536*0.15930.1593*4.08***185.8 1/17/01 ** * * 10.5790.1541 * 0.1541 * 4.225 *** 189.76 1/18/01 ** *0.08710.2670.1541 * 0.15419.155* ** 188.268191.03 3/6/01 ** * * 10.160.1711 * 0.1711 * 4.077 *** 215.41 5/15/01 ** * * 10.3240.1654 * 0.1654 * 4.135 *** 190.54 7/10/01 ** * * 10.5050.1619 * 0.1619 * 4.195 *** 188.75 9/17/01 ** * * 11.10.1938 * 0.1938 * 4.449 *** 231.38 11/13/01 ** * * 10.6180.1694 * 0.1694 * 4.141 *** 191.3 1/29/02 ** * * 10.8260.1709 * 0.1709 * 4.82 *** 187.98 3/19/02 ** * * 10.6270.1557 * 0.1557 * 4.749 *** 199.77 7/16/02 ** 1.122 * 12.0720.1865 * 0.1865 * 4.311 *** 193.2 11/14/02 ** 0.9 * 110.2 * 0.2 * * *** 180 1/23/03 ** 1 * 110.2 * 0.2 * * *** 180 3/27/03 ** 1 * 120.2 * 0.2 * * *** 180 6/25/03 ** 1.3 * 130.2 * 0.2 * * *** 170 8/12/03 ** 1.1 * 120.2 * 0.2 * * *** 170 11/18/03 ** 1.094 * 12.1* * * * * *** *

PAGE 263

DateTDSDesnTDST-PO4 T-ClFlowDateFLOW-CFS 5/17/93 148145.246**05/21/19915.4 9/30/93 ***9.0009/26/19915.2 5/26/95 136133.246*11.0005/21/19925 6/20/95 **0.10510.0009/23/19925.6 9/7/95 132141.8940.13511.0005/17/19934.9 11/2/95 ****06/17/19934.19 5/21/96 141138.2460.11911.0009/23/19934.9 9/17/96 144153.8940.12910.0009/30/19934.71 4/21/97 ***10.0005/26/19943.16 5/14/97 146143.2460.110.0009/22/19945.8 9/10/97 141150.8940.11710.1905/26/19955.5 5/19/98 ****05/26/19955.52 5/20/98 152149.2460.1410.5009/22/19956.2 9/9/98 130139.8940.12510.1409/26/19956.22 5/18/99 154151.2460.092*11/02/19956.8 5/19/99 ****04/15/19966.93 9/8/99 147156.8940.10610.2705/01/19966.4 5/17/00 168165.2460.11710.7406/11/19965.59 1/17/01154154.0190.07710.67 07/26/19965.7 1/18/01149149.0190.0710.39 07/26/19965.9 3/6/01194191.2460.0810.54 08/13/19966.63 5/15/01150147.246*10.64 09/04/19966.45 7/10/01158145.7690.07810.43 10/16/19966.34 9/17/01140149.8940.10712.50 11/19/19966.19 11/13/01**0.111.13 01/02/19975.77 1/29/02140140.0190.06710.55 01/15/19975.71 3/19/02150147.2460.07310.42 02/25/19975.75 7/16/02182169.7690.12611.42 03/27/19975.39 11/14/02156165.8940.1112.00 04/21/19975.1 1/23/03163163.0190.1212.00 05/22/19975.17 3/27/03158155.2460.1212.00 06/24/19976.09 6/25/03163150.7690.2312.00 07/15/19974.71 8/12/03152139.7690.1513.00 08/13/19975.56 11/18/03143152.8940.1311.80 09/23/19975.12 10/22/19974.8 11/21/19975.69 05/19/19984.8 09/23/19985.33 05/19/19994.73 09/28/19996.17 05/22/20004.33 09/25/20005

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SpringSampDateYearDayDateMonth(txt)Month(nu)SeasonSeason_N o SourceTempSCl Palm Springs 19930525199325 5/25/93 55Spring1USGS24.1* Palm Springs19930929199329 9/29/93 99Fall3SJR24.3333 Palm Springs19950525199525 5/25/95 55Spring1USGS24.5* Palm Springs19950620199520 6/20/95 66Summer2SJR23.7326 Palm Springs19950906199506 9/6/95 99Fall3SJR24.55354 Palm Springs19960517199617 5/17/96 55Spring1SJR24.27331 Palm Springs19960917199617 9/17/96 99Fall3SJR24.38313 Palm Springs19970417199717 4/17/97 44Spring1USGS24.5* Palm Springs19970514199714 5/14/97 55Spring1SJR24.16321 Palm Springs19970521199721 5/21/97 55Spring1USGS24.5* Palm Springs, Seminole State Forest19970611199711 6/11/97 66Summer2USGS27.4* Palm Springs19970910199710 9/10/97 99Fall3SJR24.1317 Palm Springs19980519199819 5/19/98 55Spring1USGS24.5* Palm Springs19980520199820 5/20/98 55Spring1SJR24.26339 Palm Springs19980909199809 9/9/98 99Fall3SJR24.2334 Palm Springs19990518199918 5/18/99 55Spring1SJR24.19342 Palm Springs19990908199908 9/8/99 99Fall3SJR24.29337 Palm Springs20000517200017 5/17/00 55Spring1SJR24.23343 Palm Springs Seminole1/16/01 1Winter4 24.14 * Palm Springs Seminole2/26/01 2Winter4 24.24 * Palm Springs Seminole3/6/01 3Spring1 24.24 * Palm Springs Seminole5/15/01 5Spring1 24.35 * Palm Springs Seminole7/9/01 7Summer2 24.32 * Palm Springs Seminole9/17/01 9Fall3 24.6 * Palm Springs Seminole11/13/01 11Fall3 24.2 * Palm Springs Seminole1/29/02 1Winter4 24.9 * Palm Springs Seminole3/19/02 3Spring1 24.8 * Palm Springs Seminole7/16/02 7Summer2 24.9 * Palm Springs Seminole11/14/02 11Fall3 * * Palm Springs Seminole1/23/03 1Winter4 24.4 * Palm Springs Seminole3/27/03 3Spring1 24.5 * Palm Springs Seminole6/25/03 6Summer2 25 * Palm Springs Seminole8/12/03 8Summer2 23.6 * Palm Springs Seminole11/18/03 11Fall3 24.5 *

PAGE 265

DateSCfpHT-AlkD-NO3T-NO3D-NO3NO2T-NO3NO2DNO3NO2 or TNO3 N T-PD-PTOCCa 5/25/93 3287.6*********40 9/29/93 3337.28116**0.651*0.651***39 5/25/95 325**********38 6/20/95 3267.33116**0.586*0.586 **** 9/6/95 3547.25119*****0.1330.145*40 5/17/96 *7.08118**0.883*0.883 **** 9/17/96 3137.08121**0.647*0.647 **** 4/17/97 335*********** 5/14/97 *6.9121**0.488*0.488 **** 5/21/97 331*********** 6/11/97 17907.99 *********130 9/10/97 *6.82120.5833**0.537*0.537 **** 5/19/98 3447.09 ********** 5/20/98 *7.06118.2877**0.922*0.922 **** 9/9/98 *7.05121.0912**0.611*0.611 **** 5/18/99 **118.3156**0.534*0.534 **** 9/8/99 *7.27120.5455**0.672*0.672 **** 5/17/00 *7.15121.223**0.691*0.691 **** 1/16/013377.4125.973 *** 0.6110.611* *** 2/26/013496.36123.563 *** **0.1230.122 ** 3/6/013377.45124.046 *** 0.5380.538* *** 5/15/013357.2121.098 *** *** *** 7/9/013367.37123.643 *** 0.5680.568* *** 9/17/01306*114.23 *** 0.5420.542* *** 11/13/013317.48120.014 *** 0.8350.835* *** 1/29/023337.45121.718 *** 0.6470.647* *** 3/19/023597.59122.871 *** 0.5980.598* *** 7/16/023417.46122.659 *** 0.5110.511* *** 11/14/023407.63123 *** 0.790.79* *** 1/23/033527.72120 *** 0.780.78* *** 3/27/033287.67121 *** 0.640.64* *** 6/25/033467.44122 *** 0.650.65* *** 8/12/033057.16123 *** 0.930.93* *** 11/18/033527.48118 *** 0.8390.8390.129 ***

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DateT-CaMgT-MgT-NaNaKT-KTKNT-SO4FT-FFluoride = (D or T)Si 5/25/93 *12**8.31*14210.2*0.29 9/29/93 3411.111.5 98111322 0.160.160.16* 5/25/95 *10**8.61*15230.2*0.217 6/20/95 38*10.98**1.61825*0.170.17* 9/6/95 *11.9**81.2*1519*0.160.168 5/17/96 40*11.89**1.11526*0.170.17* 9/17/96 38*11.39**11524*0.170.17* 4/17/97 ************* 5/14/97 39.66*118.84***1522*0.160.16* 5/21/97 ************* 6/11/97 *40**1806.5*3203200.2**12 9/10/97 35.59*10.988.72**1.24514.49922.373*0.160.16* 5/19/98 ************* 5/20/98 39.98*13.059.38**1.22215.47323.431*0.17650.1765* 9/9/98 40.59*12.138.68***14.91723.681*0.17850.1785* 5/18/99 43.43*11.649.15**1.063*22.74*0.17410.1741* 9/8/99 42.16*12.259.58**1.03614.70123.184*0.17280.1728* 5/17/00 42.12*12.6311.71**1.75515.53424.061*0.17420.1742* 1/16/0142.25 * 12.6389.4 ** 1.129 * 22.6010.1692 * 0.1692 * 2/26/0139.947 * 11.9558.91 ** 1.066 * 22.6170.1694 * 0.16949.119 3/6/0140.76 * 11.9759.29 ** 1.124 * 22.8340.1779 * 0.1779 * 5/15/0130.147 * 8.6586.9 ** * * 22.4880.1832 * 0.1832 * 7/9/0140.9 * 11.4558.89 ** 1.087 * 21.9090.176 * 0.176 * 9/17/0138.014 * 10.6439.26 ** 1.539 * 19.20.1763 * 0.1763 * 11/13/0140.953 * 12.4469.48 ** 1.081 * 23.4650.1768 * 0.1768 * 1/29/0240.698 * 12.3349.69 ** 1.096 * 24.9060.1887 * 0.1887 * 3/19/0242.056 * 12.3659.3 ** * * 23.8680.1748 * 0.1748 * 7/16/0240.626 * 11.8038.87 ** 1.051 * 23.9860.1922 * 0.1922 * 11/14/0241 * 129.1 ** 1 * 240.2 * 0.2 * 1/23/0342 * 129.1 ** 1 * 240.2 * 0.2 * 3/27/0342 * 129.6 ** 1.1 * 250.2 * 0.2 * 6/25/0341 * 129.8 ** 1.1 * 270.2 * 0.2 * 8/12/0340 * 1310 ** 1.1 * 270.2 * 0.2 * 11/18/0340.62 * 12.099.96 ** 1.158 * 25.4* * * *

PAGE 267

DateSi(SIO3 as T-FeD-FeD-SrT-SrTDST-PO4T-ClDateFLOW-CFS 5/25/93 ***280*211**05/21/19915.78 9/29/93 4**301302**13.0009/25/19917.4 5/25/95 **3360*184*15.0005/21/19925.4 6/20/95 453**328*0.18318.0009/24/19926.2 9/6/95 ***343*1680.1315.0005/25/19935.4 5/17/96 8***3541770.14615.0006/02/19935.82 9/17/96 4***3381790.1315.0009/24/19935.02 4/17/97 ******** 09/29/19935.35 5/14/97 4.51***340.91880.11815.0005/25/19943.23 5/21/97 ******** 05/25/19955.32 6/11/97 ***2600*1130**05/25/19955.32 9/10/97 4.43***328.71750.12914.5009/06/19956.74 5/19/98 ******** 09/06/19956.74 5/20/98 4.45***362.81910.15215.4703/13/19964.37 9/9/98 4.3753.4**355.61740.13114.9204/15/19966.11 5/18/99 4.54***369.22020.111*05/03/19965.32 9/8/99 4.49***373.52130.09514.7006/11/19964.17 5/17/00 4.3***3662100.13615.5307/29/19963.86 1/16/014.481 *** 351.711860.09314.93 08/13/19965.51 2/26/01* ** 351.401350.44198*14.93 09/03/19964.54 3/6/014.27 *** 351.961750.10315.34 10/16/19964.54 5/15/014.771 *** 245.28284*14.77 11/20/19965.47 7/9/014.238 *** 344.731970.09714.50 12/10/19965.54 9/17/013.981 *** 254.681590.09516.50 01/13/19974.77 11/13/014.323 *** 358.16*0.10815.59 02/26/19974.24 1/29/024.927 *** 368.831900.08416.15 03/19/19975.81 3/19/024.948 *** 377.741800.08815.06 04/17/19976.14 7/16/024.536 *** 369.892220.10314.57 05/21/19976.28 11/14/02* *** 3601890.1117.00 06/24/19974.58 1/23/03* *** 3601960.1117.00 07/16/19973.74 3/27/03* *** 3701890.1117.00 08/13/19973.89 6/25/03* *** 3801950.1117.00 09/30/19974.57 8/12/03* *** 3601930.1217.00 10/22/19976.13 11/18/03* *** *1910.12317.50 11/22/19974.96 09/23/19984.08 05/18/19995.31 09/29/19995.8 05/22/20005.02 09/25/20014.8

PAGE 268

SpringSampDat e YearDayDateMonth(txt ) Month(nu ) SeasonSeason_ N SourceTempSCl Ponce DeLeon Sprin g 2E+07199102 1/2/91 11Winter4SJR22.2573 Ponce DeLeon Spring s 2E+07199108 7/8/91 77Summer2SJR22.8842 Ponce DeLeon Spring s 2E+07199206 1/6/92 11Winter4SJR22.7885 Ponce DeLeon Spring s 2E+07199206 7/6/92 77Summer2SJR23.6867 Ponce DeLeon Spring s 2E+07199318 1/18/93 11Winter4SJR22.7887 Ponce DeLeon Spring s 2E+07199314 7/14/93 77Summer2SJR22.8* Ponce DeLeon Spring s 2E+07199410 1/10/94 11Winter4SJR21.44* Ponce DeLeon Spring s 2E+07199407 7/7/94 77Summer2SJR22.9766 Ponce DeLeon Spring s 2E+07199510 1/10/95 11Winter4SJR22.61062 Ponce DeLeon Spring s 2E+07199522 3/22/95 33Spring1SJR22.5856 Ponce DeLeon Spring s 2E+07199531 5/31/95 55Spring1SJR23.18662 Ponce DeLeon Spring s 2E+07199511 7/11/95 77Summer2SJR22.7747 Ponce DeLeon Spring s 2E+07199522 11/22/95 1111Fall3SJR22.3967 Ponce DeLeon Spring s 2E+07199622 1/22/96 11Winter4SJR22.6826 Ponce DeLeon Spring s 2E+07199628 3/28/96 33Spring1SJR22.3864 Ponce DeLeon Spring s 2E+07199608 7/8/96 77Summer2SJR** Ponce DeLeon Spring s 2E+07199713 1/13/97 11Winter4SJR22.4802 Ponce DeLeon Spring s 2E+07199707 4/7/97 44Spring1SJR21.5* Ponce DeLeon Spring s 2E+07199705 11/5/97 1111Fall3SJR22.86793 Ponce DeLeon Spring s 2E+07199822 1/22/98 11Winter4SJR22.5* Ponce DeLeon Spring s 2E+07199818 3/18/98 33Spring1SJR22.58* Ponce DeLeon Spring s 2E+07199814 7/14/98 77Summer2SJR22.86689 Ponce DeLeon Spring s 2E+07199812 11/12/98 1111Fall3SJR22.6902 Ponce DeLeon Spring s 2E+07199913 1/13/99 11Winter4SJR22.33777 Ponce DeLeon Spring s 2E+07199915 3/15/99 33Spring1SJR22.64755 Ponce DeLeon Spring s 2E+07199914 7/14/99 77Summer2SJR23.2710 Ponce DeLeon Spring s 2E+07199923 11/23/99 1111Fall3SJR22.61862 Ponce DeLeon Spring s 2E+07200021 3/21/00 33Spring1SJR22.36* Ponce de Leon 1/18/0111Winter422.8* Ponce de Leon 2/28/0122Winter423.65* Ponce de Leon 3/1/0133Spring122.5* Ponce de Leon 7/18/0177Summer222.8* Ponce de Leon 11/20/011111Fall322.4* Ponce de Leon 1/25/0211Winter422.8* Ponce de Leon 3/22/0233Spring122* Ponce de Leon 7/16/0277Summer223.6* Ponce de Leon 11/14/021111Fall3** Ponce de Leon 1/23/0311Winter422.1* Ponce de Leon 3/27/0333Spring122.4* Ponce de Leon 6/26/0366Summer223.3* Ponce de Leon 8/7/0388Summer222.9* Ponce de Leon 11/18/031111Fall322.6*

PAGE 269

DateSCfpHT-AlkD-NO3T-NO3D-NO3N O T-NO3NO 2 DNO3NO2orTNO3T-PD-PTOCCa 1/2/91 5737.64121**0.572*0.572**1.3545 7/8/91 8427.51120**1.05*1.05***51 1/6/92 8857.62118**1.02*1.02**250 7/6/92 *7.67120**0.884*0.884**1.548 1/18/93 8877.54119**0.775*0.775**0.748 7/14/93 *7.35119**0.843*0.843**0.748 1/10/94 7256.86118**0.753*0.753***46 7/7/94 *7.47120**0.571*0.571***48 1/10/95 10627.46120**0.977*0.977***57 3/22/95 *7.68119**1.03*1.03***52 5/31/95 6627.46117**0.948*0.9480.0490.017*49 7/11/95 7477.59120**0.743*0.743 **** 11/22/95 9677.32120 ********* 1/22/96 8267.26112**1.18*1.18 **** 3/28/96 8647.14116**1.28*1.28 **** 7/8/96 813*114**1.03*1.03 **** 1/13/97 8026.91118**0.872*0.872 **** 4/7/97 **120**0.869*0.869 **** 11/5/97 *7.12120.543**0.862*0.862 **** 1/22/98 *7.72122.081**0.911*0.911 **** 3/18/98 **119.918**1.163*1.163 **** 7/14/98 *6.91114.045**1.037*1.037 **** 11/12/98 *7.07118.881**1.062*1.062 **** 1/13/99 *6.92113.902**1.091*1.091 **** 3/15/99 *7.72115.618**0.91*0.91 **** 7/14/99 *7.56119.717**0.785*0.785 **** 11/23/99 *7.35118.446**0.781*0.781 **** 3/21/00 **116.565**1.014*1.014 **** 1/18/015647.78114.329*1.355**1.355**** 2/28/016297.78118.9461.1431.152**1.1520.0560.061.5* 3/1/016227.74119.379*1.134**1.134**** 7/18/017967.9122.932*0.762**0.762**** 11/20/019987.59117.949*1.191**1.191**** 1/25/027417.6116.495*1.183**1.183**** 3/22/027947.75118.684*1.087**1.087**** 7/16/028617.63121.729*0.758**0.758**** 11/14/0210377.67121*0.99**0.99**** 1/23/039937.78118*1.1**1.1**** 3/27/0310747.74120*1.1**1.1**** 6/26/039117.65120*1**1**** 8/7/039527.58121*0.94**0.94**** 11/18/039627.66120*0.902**0.9020.056***

PAGE 270

DateT-CaMgT-MgT-NaNaKT-KTKNT-SO4FT-FFluroide = (D or T Si 1/2/91 *8.6**533.1*9920**** 7/8/91 *13.2**833.8*15425**** 1/6/92 *14.3**925*17527**** 7/6/92 *1312.880814.54.214927**** 1/18/93 4814.813.788934.44.117631**** 7/14/93 4412.11568683.84.613022**** 1/10/94 461112.274733.83.6132230.10.10.1* 7/7/94 4512.612.174804.34.613724*0.090.09* 1/10/95 5418.117.31191255.75.522234*0.090.09* 3/22/95 5213.412.990934.84.615729*0.070.07* 5/31/95 4812.211.471744.44.313225*0.090.09* 7/11/95 46*11.771**4.214922*0.090.09* 11/22/95 52*15.4106**4.920037*0.10.1* 1/22/96 54*14.293**3.917026*0.090.09* 3/28/96 53*14.898**518031*0.10.1* 7/8/96 51*13.991**4.517531*0.10.1* 1/13/97 49*12.580**4.115427*0.110.11* 4/7/97 51*19135**5.727243*0.10.1* 11/5/97 48.71*13.0781.9**4.542165.08728.657*0.090.09* 1/22/98 52.6*16.38114.2**5.47226.7338.492*0.10.1* 3/18/98 52.4*17.44116.9**5.71225.66335.461*0.090.09* 7/14/98 51.1*1268.7***132.76923.905*0.09650.0965* 11/12/98 51.1*13.8394.3**4.389185.49631.242*0.09850.0985* 1/13/99 48.58*13.2581.8**3.861148.41828.531*0.0980.098* 3/15/99 50.2*12.4174.9**3.93515226.5*0.10150.1015* 7/14/99 51*12.6775.5**3.96414726.4*0.09950.0995* 11/23/99 **18.4765.1**1.689181.18930.059*0.10290.1029* 3/21/00 47.65*11.1360.4**3.476112.96821.633*0.10.1* 1/18/0147.473*9.44846.81**3.267*20.3350.0933*0.0933* 2/28/0148.027*10.45654.03**3.5550.16421.210.1009*0.10096.881 3/1/0148.504*10.45954.53**3.628*21.1230.1034*0.1034* 7/18/0150.976*12.29279.44**4.416*26.8750.1107*0.1107* 11/20/0153.367*16.953120.28**5.632*38.6060.1054*0.1054* 1/25/0252.684*14.09191.49**4.754*30.3220.1075*0.1075* 3/22/0253.807*14.03988.74**4.656*28.2560.092*0.092* 7/16/0252.155*14.3895.83**4.822*31.580.1149*0.1149* 11/14/0253*17120**5.3*370.1*0.1* 1/23/0354*16110**5*350.1*0.1* 3/27/0354*17130**5.7*380.1*0.1* 6/26/0350*15100**4.9*33**** 8/7/0353*17120**5.5*37**** 11/18/0353.77*16.2111.8**5.166*34.7****

PAGE 271

DateSi(SIO3 a s T-FeD-FeD-SrT-SrTDST-PO4T-ClFlowDateFLOW-CFSFlowDateFLOW-CFS1/2/91 3*50246*313*1541/2/9119.497/14/9813.87/8/91 3.3*50331*424*1753/11/9120.419/24/9823.71/6/92 3*50291*438*1495/2/9116.6711/12/9819.337/6/92 35350304142439*1767/8/9125.711/13/9920.71/18/93 35050291360435*1309/4/9125.453/15/9926.587/14/93 321*318281388*13211/4/9128.115/20/9922.11/10/94 3**321330**1371/6/9222.347/16/9923.537/7/94 31632357484423*2223/3/9231.189/28/9922.11/10/95 3**4604365690.0591575/12/9218.7411/23/9923.223/22/95 3**3843744690.0521325/20/92251/19/0023.045/31/95 3**3042903850.0531497/6/9230.15/25/0012.77/11/95 338**3264430.0562009/8/9225.039/19/002011/22/95 3****498*170 9/25/9226 1/22/96 3***3844610.05318011/4/9226.64 3/28/96 3***3944810.0571751/18/9325.68 7/8/96 3***3674400.0571543/2/9326.46 1/13/97 3***3254050.0492725/17/9324.76 4/7/97 4***4396120.049165.097/14/9322.2 11/5/97 3.36***355.54540.055226.739/8/9324.3 1/22/98 3.43***420.75580.058225.6611/1/9324.7 3/18/98 3.9***450.35790.06132.771/10/9422.34 7/14/98 3.34***333.83790.06185.53/8/9421.26 11/12/98 3.64***357.64900.041148.425/16/9421.4 1/13/99 3.34***328.54160.0521525/26/9423 3/15/99 3.39***355.34060.0521477/7/9421.1 7/14/99 3.43***348.13840.061181.199/22/9423 11/23/99 **** 382.3*0.049112.9710/3/9427.48 3/21/00 3.5***3013400.0691.751/10/9527.9 1/18/013.385***3072930.036102.23/22/9522.8 2/28/01***307.507303.133300.037101.725/31/9521.1 3/1/013.297***304.13230.032153.437/11/9520.1 7/18/013.549***350.55*0.041225.311/22/9619.9 11/20/013.534***436.65*0.049166.83/28/9621.4 1/25/023.672***382.634600.03160.597/8/9622.6 3/22/023.618***384.474100.037186.8711/12/9626.6 7/16/023.631***378.674820.0492201/13/9722.6 11/14/02****4305500.052004/7/9736.4 1/23/03****4205380.052306/2/9731.2 3/27/03****4405790.041906/5/9724 6/26/03****3905200.062109/23/9719.4 8/7/03****4105540.0420011/12/9712.2 11/18/03*****5140.05521/22/9819.87 3/18/9827.045/18/9826.8

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SpringSampDateYearDayDateMonth(txt)Month(nu)SeasonSeason_NoSourceTempSClSCfpHT-AlkD-NO3 Rock Springs19910103199103 1/3/91 11Winter4SJR23.5263*7.3889* Rock Springs19910710199110 7/10/91 77Summer2SJR23.8*3567.5789* Rock Springs19920107199207 1/7/92 11Winter4SJR23.72552558.1290* Rock Springs19920707199207 7/7/92 77Summer2SJR23.72612617.5989* Rock Springs19930119199319 1/19/93 11Winter4SJR23.72642647.7391* Rock Springs19930520199320 5/20/93 55Spring1USGS23.8*2527.83** Rock Springs19930720199320 7/20/93 77Summer2SJR23.82592597.7789* Rock Springs19940112199412 1/12/94 11Winter4SJR23.82802807.5489* Rock Springs19940713199413 7/13/94 77Summer2SJR23.73003007.7189* Rock Springs19941122199422 11/22/94 1111Fall3SJR23.82622627.5890* Rock Springs19950109199509 1/9/95 11Winter4SJR23.52602607.4** Rock Springs19950322199522 3/22/95 33Spring1SJR23.62572577.489* Rock Springs19950525199525 5/25/95 55Spring1USGS24*250*** Rock Springs19950606199506 6/6/95 66Summer2SJR24.1*2387.16** Rock Springs19950712199512 7/12/95 77Summer2SJR23.62562567.6889* Rock Springs19951102199502 11/2/95 1111Fall3USGS24*251*** Rock Springs19951115199515 11/15/95 1111Fall3SJR23.6*2487.4586* Rock Springs19960117199617 1/17/96 11Winter4SJR23.62452457.3387* Rock Springs19960321199621 3/21/96 33Spring1SJR23.62592597.2886* Rock Springs19960611199611 6/11/96 66Summer2USGS24*250*** Rock Springs19960710199610 7/10/96 77Summer2SJR23.8251*7.6584* Rock Springs19960711199611 7/11/96 77Summer2SJR23.8*2517.65** Rock Springs19961113199613 11/13/96 1111Fall3SJR23.6269*7.5788* Rock Springs19970115199715 1/15/97 11Winter4SJR23.42422427.6288* Rock Springs19970312199712 3/12/97 33Spring1SJR24.12482487.6789* Rock Springs19970421199721 4/21/97 44Spring1USGS23.5*254*** Rock Springs19970722199722 7/22/97 77Summer2SJR23.7257*7.6390.955* Rock Springs19971111199711 11/11/97 1111Fall3SJR23.7253*7.4993.0509* Rock Springs19980121199821 1/21/98 11Winter4SJR23.59**7.5193.8819* Rock Springs19980327199827 3/27/98 33Spring1SJR23.61**7.26117.2972* Rock Springs19980715199815 7/15/98 77Summer2SJR23.73**7.0286.1681* Rock Springs19981116199816 11/16/98 1111Fall3SJR23.73245*7.3689.0963* Rock Springs19990114199914 1/14/99 11Winter4SJR23.59248*7.0787.8134* Rock Springs19990317199917 3/17/99 33Spring1SJR23.73224*7.7987.8916* Rock Springs19990519199919 5/19/99 55Spring1USGS23.9*256*** Rock Springs19990714199914 7/14/99 77Summer2SJR23.65258*7.6590.1079* Rock Springs19990816199916 8/16/99 88Summer2USGS23.7*2578.1** Rock Springs19991116199916 11/16/99 1111Fall3SJR23.7255*7.8589.479* Rock Springs20000315200015 3/15/00 33Spring1SJR23.74250*7.6288.034* Rock Springs ***1/17/01 *********** ****2/27/01 *********** ****3/6/01 *********** ****5/15/01 *********** ****7/10/01 *********** ****9/17/01 *********** ****11/13/01 *********** ****7/16/02 *********** ****1/23/03 *********** ****3/27/03 *********** ****6/25/03 *********** ****8/12/03 *********** ****11/18/03 ***********

PAGE 273

DateT-NO3D-NO3NO2T-NO3NO2T-PD-PTOCCaT-CaMgT-MgT-NaNaKT-KTKNT-SO4 1/3/91 *1.45***0.529*9.3**51.2*919 7/10/91 *1.47 ****27*8.5**31.1*721 1/7/92 *1.8****29*8.7**51.2*915 7/7/92 *1.55 ****30289.49551.21.2820 1/19/93 *1.49***1.630289.19.7551.11.11121 5/20/93 ******30*8.9**4.91.1*8.319 7/20/93 *1.81 ****29 31.98.658.897.814.711.11.82420 1/12/94 *1.57 ****27268.28.3551.11.2815 7/13/94 *1.46 ****29308.89.3551.41.3820 11/22/94 *1.42 ****32309.89.4551.61.51320 1/9/95 *1.49 ****32309.28.9551.31.4520 3/22/95 ******31308.18451.71.6719 5/25/95 ******32*8**5.11.2*8.220 6/6/95 **************** 7/12/95 *1.55 *****27*8.55**1.8719 11/2/95 **************** 11/15/95 *1.46 *****29*96**1.2922 1/17/96 *1.55 *****30*8.86**1.4820 3/21/96 *1.62 *****30*9.25**1.6818 6/11/96 **************** 7/10/96 *1.57 *****29*8.55**1.3922 7/11/96 **************** 11/13/96 *1.58 *****29*8.65**1.4821 1/15/97 *1.51 *****29*8.65**1.3824 3/12/97 *1.446 *****28*9.25**1.3820 4/21/97 **************7.918 7/22/97 *1.347 *****28*9.65**1.3 8.73719.008 11/11/97 *1.413 ***** 28.97*8.815.42**1.5558.49319.063 1/21/98 *1.222 ***** 29.17*8.955.38**1.44510.48722.353 3/27/98 ******* 37.42*11.039.08**1.85313.82918.003 7/15/98 *1.581 ***** 31.04*9.334.473**1.2098.94617.284 11/16/98 *1.561 ***** 30.24*9.084.948**1.2937.64917.87 1/14/99 *1.536 ***** 30.61*9.755.53***8.83218.853 3/17/99 *1.461 ***** 30.64*9.264.975**1.0988.56317.798 5/19/99 **************** 7/14/99 *1.382 ***** 31.33*9.485.03**1.1558.219.5 8/16/99 **1.40.080.08 *********** 11/16/99 *1.443 ***** 31.92*9.514.733**1.05411.22418.793 3/15/00 *1.51 ***** 31.23*9.685.43**1.4437.76217.155 1/17/01 **************** 2/27/01 **************** 3/6/01 **************** 5/15/01 **************** 7/10/01 **************** 9/17/01 **************** 11/13/01 **************** 7/16/02 **************** 1/23/03 **************** 3/27/03 **************** 6/25/03 **************** 8/12/03 **************** 11/18/03 ****************

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DateFT-FSiSi(SIO3 as S T-FeD-FeD-SrT-SrTDST-PO4 T-ClFlowDate FLOW-CFS FlowDate FLOW-CFS 1/3/91 0.15**5**120*156**01/03/199144.6710/16/199661.6 7/10/91 0.14**5**46*168*703/06/199143.0211/13/199655.6 1/7/92 0.13**5**129*144*904/29/199152.3211/19/199666.9 7/7/92 0.13**5**35152148*805/22/19914812/12/199660.7 1/19/93 0.13**5**168*147*1107/10/199162.301/15/199754.6 5/20/93 0.1*9.3***160*145*8.309/03/199163.2201/16/199759.1 7/20/93 0.15**5213*167122**2409/25/19916302/25/199758.9 1/12/94 0.150.15*4**193133130*811/11/199158.4903/12/199756.3 7/13/94 *0.14*46*162154148*801/07/199263.9403/21/199760.2 11/22/94 *0.13*5**1771701470.0831303/05/199261.5604/21/199755.6 1/9/95 *0.14*5**1811721340.085505/14/199260.2505/02/199752 3/22/95 *0.12*4**192185139*705/19/19925605/20/199753.6 5/25/95 0.1*9.4**3170*132*8.207/07/199254.8706/24/199755.6 6/6/95 *********** 09/09/199258.6507/15/199751.9 7/12/95 *0.13*4***1621900.085709/24/19925307/15/199753.2 11/2/95 *********** 11/03/199258.8608/14/199758.8 11/15/95 *0.14*4***1721480.094901/19/199368.6409/23/199754.3 1/17/96 *0.15*4***1641350.093803/02/199362.3910/22/199752.8 3/21/96 *0.13*4100**1711290.085805/18/199357.5211/11/199754.2 6/11/96 *********** 05/20/199357.311/20/199756.8 7/10/96 *0.15*4***1591360.09907/20/199351.503/25/199865.4 7/11/96 *********** 09/08/199356.503/25/199865.4 11/13/96 *0.14*4***1671430.084809/23/199353.805/08/199857.7 1/15/97 *0.15*4***1701360.082811/08/199358.1106/29/199859.5 3/12/97 *0.14*5***1731420.084801/12/199454.307/15/199834.14 4/21/97 **********7.9 03/23/199453.108/20/199854.9 7/22/97 *0.14*4.54***1291380.068.7405/04/199455.7909/23/199854.5 11/11/97 *0.14*4.95***174.61380.0718.4905/25/199451.610/14/199860.9 1/21/98 *0.15*4.61***180.61520.08110.4907/13/199457.111/16/199855.14 3/27/98 ***4.55***137.3174*13.8309/21/199465.1712/11/199854.7 7/15/98 *0.1536*4.43***167.92890.0798.9509/23/199457.601/14/199965.7 11/16/98 *0.1551*4.94***167.71480.0837.6511/22/199468.802/02/199950.6 1/14/99 *0.1569*4.77***153.71400.098.8301/09/199568.903/17/199956.7 3/17/99 *0.1564*4.85***175.71500.0848.5603/22/199561.303/31/199952.3 5/19/99 *********** 05/25/199558.105/19/199951.4 7/14/99 *0.1505*4.76***175.61440.0818.206/06/19955706/01/199947.5 8/16/99 *********** 06/06/199557.406/29/199946.5 11/16/99 *0.154*5.16***174.9*0.0811.2207/12/199560.107/14/199956.8 3/15/00 *0.1497*4.79***169.51730.0787.7609/22/199561.507/21/199947.1 1/17/01 ********** 10.0511/02/199563.409/24/199957.7 2/27/01 ********** 8.4311/15/19956711/16/199954.7 3/6/01 ********** 8.2201/17/199664.111/16/199963.83 5/15/01 ********** 8.1203/14/19966301/19/200057 7/10/01 ********** 7.8603/21/199661.503/15/200045.76 9/17/01 ********** 8.4304/16/199662.906/15/200048.73 11/13/01 ********** 8.0305/02/199680.107/26/200051.1 7/16/02 **********8.1 06/11/199660.601/17/200150.7 1/23/03 **********8.6 07/08/199662.9 3/27/03 **********8.7** 6/25/03 **********8.6 07/11/199659.8 8/12/03 **********8.7 08/14/199665 11/18/03 ********** 8.7209/04/199660.8

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SpringDateMonth(nu ) SeasonSeason_N o SourceTempSCfpHT-AlkT-NO3NO2T-CaT-MgT-NaT-K Salt Springs 1/8/91 1Winter4SJR23* 7.64680.114 **** Salt Springs 5/23/91 5Spring1USGS23.54430.00** ***** Salt Springs 7/9/91 7Summer2SJR24.3412.007.95640.086 **** Salt Springs 7/29/91 7Summer2SJR**7.73* ***** Salt Springs 1/8/92 1Winter4SJR 22.8*7.65710.107 **** Salt Springs 7/8/92 7Summer2SJR23.64920.007.39640.11112883.471020.9 Salt Springs 1/18/93 1Winter4SJR 23.65190.007.72650.09212778.674920.1 Salt Springs 7/15/93 7Summer2SJR23.74730.007.58*0.0791378681028.3 Salt Springs 1/20/94 1Winter4SJR 23.55490.006.95630.113144*81624.4 Salt Springs 7/6/94 7Summer2SJR23.55620.007.6640.09114794.382424.7 Salt Springs 1/9/95 1Winter4SJR 23.65870.007.81660.13115195.194429 Salt Springs 3/20/95 3Spring1SJR23.76920.007.38660.10615485.686629 Salt Springs 7/11/95 7Summer2SJR23.45670.007.58650.10414087.681627 Salt Springs 11/14/95 11Fall3SJR22.96*7.47*0.098165110101032.2 Salt Springs 1/18/96 1Winter4SJR 23.86320.007.47640.10816010792331.2 Salt Springs 3/19/96 3Spring1SJR23.56360.007.13630.216610486330.7 Salt Springs 5/6/96 5Spring1SJR23.65*7.18640.112 **** Salt Springs 7/10/96 7Summer2SJR23.77160.007.16650.116182115112034.7 Salt Springs 11/18/96 11Fall3SJR***650.09415896.592428.5 Salt Springs 1/13/97 1Winter4SJR 23.46640.007.13650.096168105101032.1 Salt Springs 3/11/97 3Spring1SJR23.77000.007.55660.105176113104032.3 Salt Springs 7/21/97 7Summer2SJR23.7*7.4565.42930.09716710697129.1 Salt Springs 11/5/97 11Fall3SJR23.56*7.2166.59450.1154.499.9906* Salt Springs 1/6/98 1Winter4 USGS23.76180.007.4276 ***** Salt Springs 1/14/98 1Winter4SJR 23.38*7.5667.23960.095170.3106.197234.26 Salt Springs 3/11/98 3Spring1SJR***68.31070.1183.1115.71085* Salt Springs 5/20/98 5Spring1USGS247300.006.11* ***** Salt Springs 7/17/98 7Summer2SJR23.746910.00*67.58770.112193122.9114135.86 Salt Springs 11/11/98 11Fall3SJR23.837090.007.1366.20290.125151.3101.1104230.04 Salt Springs 1/12/99 1Winter4SJR 23.516480.006.7978.62790.102165.9112107233.55 Salt Springs 3/16/99 3Spring1SJR23.45474.007.8364.5450.086156.198.794228.21 Salt Springs 5/19/99 5Spring1USGS23.84940.00** ***** Salt Springs 7/12/99 7Summer2SJR23.8*7.2664.6750.064148.497.891228.23 Salt Springs 11/29/99 11Fall3SJR23.475169.007.5561.7620.085121.671.162720.61 Salt Springs 3/22/00 3Spring1SJR23.625318.007.5563.6260.1138.584.5799.624.34 Salt Springs 5/19/00 5Spring1USGS ********* Salt Springs1/17/01 1Winter4 23.55160.007.7664.7160.089138.43582.822773.4525.714 Salt Springs2/27/012 Winter4 23.565170.007.0464.1270.082137.3483.921786.0724.855 Salt Springs3/7/013Spring123.64970.00 *63.5620.083130.26878.408725.3422.965 Salt Springs7/3/017Summer223.74465.00 7.763.7730.088126.56173.56367721.492 Salt Springs11/1/0111Fall 323.65360.007.665.5130.099156.96598.096945.8430.448 Salt Springs1/22/021 Winter4 21.85550.007.7767.0050.098168.01107.977100935.856 Salt Springs3/18/023Spring123.85330.00 7.3766.460.102154.16194.758936.532.29 Salt Springs7/12/027Summer225.44643.00 7.7662.726*132.03778.633713.623.507 Salt Springs10/24/02 10Fall323.16710.007.76670.1180114103030 Salt Springs11/15/02 11Fall3*6270.007.73680.09169106100031 Salt Springs3/21/033Spring123.95720.00 7.53650.081559391028 Salt Springs6/27/036Summer2245050.00 7.62660.1116710497029

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DateTKNT-SO4T-FT-SrTDST-PO4DtoH2OCFS(atwq)FlowDateCFSFlowDateCFS 1/8/91 1120336**2597*15.873.91/8/9173.911/11/9889.98 5/23/91 ****** 15.1773/13/9165.621/12/9998.55 7/9/91 1290***2570*13.3564.264/30/9176.993/16/9997.71 7/29/91 ******* 61.225/23/91775/19/9988 1/8/92 1360332**2690*13.1287.817/9/9164.267/12/9984.06 7/8/92 1410350*26302740*13.5171.459/5/9161.229/28/9961.4 1/18/93 1360340*26702560**71.369/27/917311/29/9966.9 7/15/93 1860**2790**13.5370.3111/21/9196.591/19/0085.5 1/20/94 14623770.0929703200*13.374.81/7/9287.813/22/0068.2 7/6/94 14603580.083560*0.01412.58833/3/9280.335/19/0082.7 1/9/95 1610356*337033600.016*69.95/11/9283.896/13/0079.53 3/20/95 17503940.08299034600.016*69.45/22/92687/18/0070.61 7/11/95 17503830.09303036100.014*78.17/8/9271.459/25/0073 11/14/95 18903860.0936203820***9/17/9270.511/13/0070.3 1/18/96 20903380.09333037100.012*86.211/3/9267.691/17/0175.3 3/19/96 17003990.1344034300.021*79.41/18/9371.363/7/0162.9 5/6/96 21305110.09*41700.014**3/9/9383.87 7/10/96 20704620.138304160**86.295/20/9385.87 11/18/96 18263980.132803580*10.7592.147/15/9370.31 1/13/97 18604330.1325037800.012*869/7/9378.41 3/11/97 19604320.0937603900**94.99/24/9377 7/21/97 2381.07413.1280.0933003400***11/2/9361.2 11/5/97 1813403.2180.0934923290**82.651/24/9474.8 1/6/98 1800410**3770***3/7/9482.4 1/14/98 2090.544320.1360234200.013*77.585/2/9481.7 3/11/98 2428.97464.8920.09372539600.013*76.55/27/9481 5/20/98 ******* 96.67/6/9483 7/17/98 2279457.4030.143034020**78.389/20/9465.9 11/11/98 1979.31418.0560.105133723420**89.981/11/9569.9 1/12/99 *454.4250.1077341638400.012*98.553/20/9569.4 3/16/99 1916.76407.8820.107135343520**97.715/23/9575 5/19/99 *******88 7/11/9578.1 7/12/99 17504160.1005348037100.019*84.069/22/9570 11/29/99 1220.5312.4080.09692870*0.01212.7266.91/18/9686.2 3/22/00 1532.4392.8380.101531802950*17.3268.23/19/9679.4 5/19/00 1200320**2570*14.982.74/30/9683 1/17/01 * 388.9520.13203.98429400.034 15.862.97/10/9686.29 2/27/01*386.580.10543226.43929200.013 16.1*9/30/9692 3/7/01*345.0240.1053045.8572650* 16.2*11/13/9692.14 7/3/01*345.910.10452883.102*0.017 15.1*1/13/9786 11/1/01*447.9030.11483614.80833100.012 12.7*3/11/9794.9 1/22/02*460.2970.10843722.582*0.016 13.3*5/21/9781 3/18/02*4480.10493704.54732000.013 18.26*9/23/9771 7/12/02*338.2620.10832966.96627200.079 12.22*11/5/9782.65 10/24/02*4500.1384039500.01 11.95*1/14/9877.58 11/15/02*4100.1359038500.01 11.2*3/11/9876.5 3/21/03*400*329032200.01 10.4*5/20/9896.6 6/27/03*420*362041400.01 10.8*7/17/9878.38

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SpringSampDateYearDayDateMonth(txt)Month(nu)SeasonSeason_NoSourceTemp Sanlando Springs 19930524199324 5/24/93 055Spring1USGS24 Sanlando Springs19930929199329 9/29/93 099Fall3SJR24.4 Sanlando Springs19950525199525 5/25/95 055Spring1USGS24.5 Sanlando Springs19950620199520 6/20/95 066Summer2SJR23.7 Sanlando Springs19950906199506 9/6/95 099Fall3SJR24.26 Sanlando Springs19960517199617 5/17/96 055Spring1SJR24.2 Sanlando Springs19960612199612 6/12/96 066Summer2USGS24 Sanlando Springs19960917199617 9/17/96 099Fall3SJR24.93 Sanlando Springs19970417199717 4/17/97 044Spring1USGS24.5 Sanlando Springs19970514199714 5/14/97 055Spring1SJR24.62 Sanlando Springs19970910199710 9/10/97 099Fall3SJR24.2 Sanlando Springs19980520199820 5/20/98 055Spring1SJR24.13 Sanlando Springs19980909199809 9/9/98 099Fall3SJR24 Sanlando Springs19990518199918 5/18/99 055Spring1SJR24.22 Sanlando Springs19990908199908 9/8/99 099Fall3SJR24.31 Sanlando Springs20000517200017 5/17/00 055Spring1SJR24.08 Sanlando Springs1/16/01 11Winter4 24.18 Sanlando Springs2/26/01 22Winter4 21.45 Sanlando Springs3/6/01 33Spring1 23.62 Sanlando Springs5/15/01 55Spring1 24.27 Sanlando Springs7/10/01 77Summer2 24.21 Sanlando Springs9/17/01 99Fall3 24.38 Sanlando Springs11/13/01 1111Fall3 24 Sanlando Springs1/29/02 11Winter4 24.2 Sanlando Springs3/19/02 33Spring1 24.6 Sanlando Springs7/16/02 77Summer2 25.8 Sanlando Springs11/14/02 1111Fall3 * Sanlando Springs1/23/03 11Winter4 23.3 Sanlando Springs3/27/03 33Spring1 24.6 Sanlando Springs6/25/03 66Summer2 25.6 Sanlando Springs8/12/03 88Summer2 24.9 Sanlando Springs11/18/03 1111Fall3 24.3

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DateSClSCfpHT-AlkD-NO3T-NO3D-NO3NO2T-NO3NO2DNO3NO2orTNO3T-PD-PTOC 5/24/93 *3367.2********* 9/29/93 3433437.18130**0.647*0.647*** 5/25/95 *336********** 6/20/95 3343347.07133**0.589*0.589*** 9/6/95 3663637.02131*****0.2120.203* 5/17/96 339*6.87127**1.08*1.08*** 6/12/96 ************ 9/17/96 3033037.17***0.509*0.509*** 4/17/97 *352********** 5/14/97 345*6.75136**0.402*0.402*** 9/10/97 331*6.65137.9926**0.51*0.51*** 5/20/98 347*7.01129.5161**1.199*1.199*** 9/9/98 350*6.83138.3624**0.436*0.436*** 5/18/99 362**136.6778**0.293*0.293*** 9/8/99 357*7.09138.3617**0.564*0.564*** 5/17/00 378*7.06140.124**0.571*0.571*** 1/16/01*3627.27145.265*0.282**0.282*** 2/26/01*3746.23144.2*****0.1890.184* 3/6/01*3617.36145.028*0.225**0.225*** 5/15/01*3607.19143.422**** **** 7/10/01*3557.25144.509*0.481**0.481*** 9/17/01*356*143.763*0.518**0.518*** 11/13/01*3367.19139.081*0.869**0.869*** 1/29/02*3537.24143.678*0.466**0.466*** 3/19/02*3647.39143.566*0.364**0.364*** 7/16/02*3627.32146.185*0.259**0.259*** 11/14/02*3617.37142*0.66**0.66*** 1/23/03*3667.74140*0.69**0.69*** 3/27/03*3547.6140*0.49**0.49*** 6/25/03*3557.38142*0.38**0.38*** 8/12/03*3277.25141*0.8**0.8*** 11/18/03*3637.38126*0.896**0.8960.198**

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DateCaT-CaMgT-MgT-NaNaKT-KTKNT-SO4FT-F 5/24/93 40*12**8.81.5*15120.2* 9/29/93 413711.311991.61.615140.150.15 5/25/95 43*12**9.51.6*17120.2* 6/20/95 *40*10.99**2.11815*0.16 9/6/95 41*11.7**101.8*1711*0.16 5/17/96 *41*11.911**1.61819*0.16 6/12/96 ************ 9/17/96 *41*11.110**1.81615*0.19 4/17/97 ********1712** 5/14/97 *41.36*11.1810.32**1.6761712*0.16 9/10/97 *39.06*10.99.88**1.81315.5311.453*0.16 5/20/98 *39.98*12.7811**1.64519.07913.057*0.1704 9/9/98 *43.42*12.0110.2**1.50217.09512.313*0.1767 5/18/99 *45.29*11.7410.76**1.616*12.073*0.1682 9/8/99 *43.95*12.3611.5**1.54917.58111.935*0.1661 5/17/00 *44.24*12.7612.53**1.94419.02913.498*0.1716 1/16/01*44.907*12.43211.14**1.71*12.5010.1659* 2/26/01*43.632*12.18810.98**1.6090.25212.130.1686* 3/6/01*44.534*12.22611.19**1.637*12.2120.1728* 5/15/01*43.685*11.98511.3**1.621*11.8270.1795* 7/10/01*44.214*11.62811.03**1.682*11.680.1701* 9/17/01*44.099*12.55710.94**1.739*11.50.1771* 11/13/01*44.329*12.87111.91**1.59*12.2650.176* 1/29/02*43.588*12.43911.67**1.616*12.8950.1803* 3/19/02*46.061*12.72111.45**1.563*11.9170.1674* 7/16/02*44.369*11.92110.74**1.648*11.7460.1837* 11/14/02*44*1211**1.5*120.2* 1/23/03*43*1211**1.5*120.2* 3/27/03*43*1212**1.6*120.2* 6/25/03*43*1212**1.6*130.2* 8/12/03*41*1212**1.7*130.2* 11/18/03*43.41*12.3612.78**1.608*13.3**

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DateFluoride(DF orTF)SiSi(SIO3 as Si)T-FeD-FeD-SrT-SrTDST-PO4T-Cl 5/24/93 0.28.4***63*192** 9/29/93 0.15*4**5460**15.00 5/25/95 0.28.6**480*198*17.00 6/20/95 0.16*463**76*0.10518.00 9/6/95 0.168***86*1790.18217.00 5/17/96 0.16*7***861800.21918.00 6/12/96 ********** 9/17/96 0.19*4***831810.19116.00 4/17/97 ********* 17.00 5/14/97 0.16*4.11***80.51920.17817.00 9/10/97 0.16*4.16***831880.18215.53 5/20/98 0.1704*4.2***82.31970.22819.08 9/9/98 0.1767*4.06***86.71730.18517.10 5/18/99 0.1682*4.18***852040.169* 9/8/99 0.1661*4.14***83.71980.16117.58 5/17/00 0.1716*4.06***86.62060.19619.03 1/16/010.1659*4.156***86.761940.14618.55 2/26/010.16868.923***87.49387.71229*18.20 3/6/010.1728*3.956***88.691790.15818.21 5/15/010.1795*4.404***86.77190*18.71 7/10/010.1701*4.077***88.112090.14917.87 9/17/010.1771*4.135***93.171940.14418.70 11/13/010.176*4.057***90.67*0.16719.52 1/29/020.1803*4.568***89.872300.13919.27 3/19/020.1674*4.584***92.912000.13617.97 7/16/020.1837*4.076***93.671990.14518.18 11/14/020.2* ****92203 0.1721.00 1/23/030.2* ****93204 0.1620.00 3/27/030.2* ****93214 0.1621.00 6/25/030.2* ****93199 0.1620.00 8/12/030.2* ****94198 0.1621.00 11/18/03** *****189 0.191 *

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FlowDateFLOW-CFS 05/21/199116 09/25/199123 05/22/199220 09/23/199224 05/24/199317 09/06/199527.2 09/06/199527.2 09/27/199521.8 11/03/199524.8 03/13/199622.2 04/15/199625.6 05/03/199630.3 06/12/199619.6 07/29/199630.9 08/16/199625.07 09/04/199620.2 10/16/199628.8 11/19/199636 12/10/199627.9 01/13/199720.4 02/26/199717.8 03/19/199716.5 04/17/199716.2 05/21/199717 07/15/199725.7 08/13/199719 09/25/199716.3 10/22/199714.9 11/21/199718.4 05/19/199822.4 09/23/199821.6 05/18/199914.4 09/29/199925.6 05/22/200014.14 09/21/200016

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SpringSampDateYearDayDateSourceTempSClSCfpHT-AlkD-NO3T-NO3D-NO3NO 2 Silver Glen Springs 199101211991211/21/91SJR22.8203420347.9867**0.063 Silver Glen Springs199107181991187/18/91SJR23.5**7.7970**0.034 Silver Glen Springs19920108199281/8/92SJR23.3*21408 **** Silver Glen Springs19920708199287/8/92SJR23.3204020407.7470**0.055 Silver Glen Springs199301201993201/20/93SJR23.1205020507.7568**0.043 Silver Glen Springs199307191993197/19/93SJR23.6**7.94 **** Silver Glen Springs1994011819941811/18/93SJR22.97205020507.2168**0.053 Silver Glen Springs19940705199457/5/94SJR23.5215021508.5171**0.039 Silver Glen Springs199501111995111/11/95SJR22.9200020007.968**0.058 Silver Glen Springs199501241995241/24/95SJR23*19307.56 **** Silver Glen Springs199503201995203/20/95SJR23.1199019907.6568**0.047 Silver Glen Springs199507131995137/13/95SJR23.3*21507.94 **** Silver Glen Springs1995112019952011/20/95SJR22.8210021007.6980**0.044 Silver Glen Springs199601241996241/24/96SJR23*19307.5668**0.046 Silver Glen Springs199603191996193/19/96SJR23.2208020807.4666**0.047 Silver Glen Springs199604291996294/29/96SJR ****67** 0.041 Silver Glen Springs19960503199635/3/96SJR23.341830*7.53 **** Silver Glen Springs199607111996117/11/96SJR23.4196019607.6668**0.048 Silver Glen Springs1996111419961411/14/96SJR23.05**7.5370**0.04 Silver Glen Springs199701161997161/16/97SJR23.8195019507.5267**0.017 Silver Glen Springs19970204199742/4/97USGS23.2*19607.59 **** Silver Glen Springs199703111997113/11/97SJR23.3193819387.966**0.03 Silver Glen Springs199707211997217/21/97SJR23.61890*7.6270.4326**0.041 Silver Glen Springs199711051997511/5/97SJR23.371910*7.5968.4401**0.041 Silver Glen Springs199801131998131/13/98SJR23.371974*7.7468.5091**0.043 Silver Glen Springs199803191998193/19/98SJR22.98**7.5968.2443**0.047 Silver Glen Springs*1998107/10/98SJR23.23**7.3167.3323**0.041 Silver Glen Springs1999011319981311/13/98SJR23.04**7.367.0575**0.049 Silver Glen Springs199903161999131/13/99SJR23.072010*7.1465.9803**0.047 Silver Glen Springs199905201999163/16/99SJR22.851652*8.1665.9768**0.039 Silver Glen Springs199907131999205/20/99USGS23*1930 ***** Silver Glen Springs*1999137/13/99SJR23.21792*7.9365.8072**0.041 Silver Glen Springs*19992911/29/99SJR23.131956*7.9166.347**0.044 Silver Glen Springs2000223/22/00SJR23.031970*7.9565.966**0.047 Silver Glen Springs1/18/0123.1*20467.3167.545*0.042* Silver Glen Springs3/1/0123.4*19307.9468.8530.0270.028* Silver Glen Springs7/3/0123.4*20487.8967.857*0.043* Silver Glen Springs11/1/0124.1*18017.9565.725*0.044* Silver Glen Springs1/22/0223.1*16127.9467.381*0.041* Silver Glen Springs3/22/0224.7*17938.4166.286*0.021* Silver Glen Springs7/12/0223.7*18918.2467.878*** Silver Glen Springs11/15/02**18848.5768*0.03* Silver Glen Springs1/24/0321.9*19138.2767*0.04* Silver Glen Springs3/21/0323.3*18857.9468*0.06* Silver Glen Springs6/27/0324.1*9567.9470*0.04* Silver Glen Springs8/7/0323.6*15187.8768*0.07* Silver Glen Springs11/21/0322.9*18588.0768.4*0.0429*

PAGE 283

DateT-NO3NO 2 T-PD-PTOCCaT-CaMgT-MgT-NaNaKT-KTKNT-SO4 1/21/91***0.6183*35.5**2559.2*462195 7/18/91 ****64* 33.6**4128.3*500191 1/8/92 ************** 7/8/92 ****7272 36.534.82542689.59.2394179 1/20/93 ****7369 36.734.32562709.38.1471214 7/19/93 **** 68.867.533.931.924927012.412.3498* 11/18/93 ****6869 37.236272280*8.7489210 7/5/94 ****7775 38.4372612439.48.4428189 1/11/95 ****7373 35.234.22462478.88.6435171 1/24/95 ************** 3/20/95 ****7270 31.330.324624599471172 7/13/95 ************** 11/20/95 *****72* 36.8257**8.8475187 1/24/96 *****75* 36.4264**8.5432172 3/19/96 *****77*38287**9.9500207 4/29/960.0450.016**75*36.8**2969.3*472194 5/3/96 ************** 7/11/96 *****71* 34.5253**8.7473196 11/14/96 *****70* 32.9243**8.4** 1/16/97 *****72* 33.3253**8.7454194 2/4/97 ****74*37**2508.2*470180 3/11/97 *****68* 33.9239**8.3451182 7/21/97 *****71* 36.5253**8.8454.409178.943 11/5/97 ***** 69.9*35.19250.3**9.74476.859184.542 1/13/98 ***** 75.2*35.38249.9**9.48471.617182.279 3/19/98 ***** 67.6*33.99227.3**8.62438.477179.584 7/10/98 ***** 75.3*35.64238.8**8.37452.893176.324 11/13/98 ***** 77.6*35.82271.2**9.3497.954190.624 1/13/99 ***** 72.2*37.37270.1**8.71473.73183.333 3/16/99 ***** 70.9*33.45247.5**8.18441.785177.311 5/20/99 ************** 7/13/99 ***** 71.5*34.09253.8**8.56456178 11/29/99 ***** 74.5*36.45266.3**9.05470.629184.175 3/22/00 ***** 71.1*35.53255.7**8.76464.701184.506 1/18/01 ***** 72.454*36.142255.77**9.171*179.41 3/1/01*0.0310.025**72.057*35.53258.41**9.0970.205179.322 7/3/01 ***** 75.405*37.092280.54**9.618*186.232 11/1/01 ***** 71.528*35.251257.58**8.964*177.532 1/22/02 ***** 71.111*35.041248.28**9.171*175.902 3/22/02 ***** 76.066*36.868259.95**9.515*181.088 7/12/02 ***** 71.915*34.726246.29**9.006*177.04 11/15/02 *****70*35240**8*160 1/24/03 *****72*35240**7.9*160 3/21/03 *****70*34250**8.8*160 6/27/03 *****67*34240**8.4*170 8/7/03 *****71*36240**8.6*170 11/21/03*0.029***71.37*34.82257.6**8.095*154

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DateFT-FSiSi(SIO3 as T-FeD-Fe D-SrT-SrTDST-PO4 T-ClFlowDate FLOW-CFS 1/21/910.14**5**1484*1023*4621/21/9159.08 7/18/910.034**5**1240*1200*5003/12/9177.32 1/8/92 *********** 5/2/9192.81 7/8/920.11**4**138013101140*3945/22/9188 1/20/930.11**9**138014301120*4717/18/91103.16 7/19/930.12 ***** 14801470**4987/18/91113.17 11/18/930.110.11*4**139014601140*4899/4/9187.28 7/5/94*0.12*418*1610171011500.0214289/27/91110 1/11/95*0.09*471261590158011200.02743511/7/9182.1 1/24/95 *********** 1/8/9288.2 3/20/95*0.1*4**1380133010700.0264713/4/9287.66 7/13/95 *********** 5/13/9287.62 11/20/95*0.12*4***152011300.0274755/21/9298 1/24/96*0.12*4***156011100.0284327/8/9298.19 3/19/96*0.12*4***158011500.0395009/21/9283.09 4/29/96*0.116***1560**0.0244729/23/9291 5/3/96 *********** 11/3/9298.71 7/11/96*0.13*4***149011100.0254731/20/9387.86 11/14/96*0.12*4***144010700.028*3/23/9392.46 1/16/97*0.13*4***149010700.0224545/19/9397.05 2/4/970.1*8.4***1400*1170*4705/20/9382 3/11/97*0.12*4***150010400.0254517/19/9387.06 7/21/97*0.12*4.21***146010600.036454.419/23/9391.5 11/5/97*0.12*4.25***156210500.025476.869/23/93101 1/13/98*0.12*4.66***155211000.026471.6211/18/9393.6 3/19/98*0.12*5***148210800.028438.481/25/94106.7 7/10/98*0.1316*4.42***1487*0.021452.893/10/9493.2 11/13/98*0.1356*4.7***150111400.02497.955/3/9497.5 1/13/99*0.1353*4.27***154911400.025473.735/25/9499 3/16/99*0.137*4.31***153810600.025441.797/7/9493.4 5/20/99 *********** 9/20/94100.15 7/13/99*0.129*4.61***153910400.0234569/22/94168 11/29/99*0.1331 ***** 1632*0.023470.6311/30/94138 3/22/00*0.1343*4.43***152210600.022464.71/11/95121 1/18/010.1278**4.395***1659.510400.021457.631/24/95120 3/1/010.1292*9.7564.608**1640.4416209930.013450.763/20/9586.9 7/3/010.1363**4.292***1702.1*0.021491.785/24/9584 11/1/010.1395**4.707***1594.3410100.023457.137/13/9589.7 1/22/020.1427**4.9***1559.11*0.023435.099/21/95160 3/22/020.1291**4.709***1632.631100*448.9310/30/95114 7/12/020.1446**4.587***1553.5612300.023450.6311/20/95101 11/15/020.1 ****** 148010900.024501/24/96120 1/24/030.1 ****** 149010700.024403/18/96104 3/21/030.1 ****** 150010300.024504/29/96137 6/27/030.1 ****** 149011300.024507/11/96112 8/7/030.1 ****** 143010800.024409/30/96110 11/21/03 ******** 12500.026843411/14/96113.6

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FlowDate FLOW-CF S 1/16/9790.05 3/17/9799 5/23/97100 6/25/97106 7/15/9787.2 9/26/9797.3 11/10/9787.82 1/13/98114.09 3/19/9887.8 5/20/98102 7/10/98108.3 9/25/98103 11/13/9896.69 1/13/99108.81 3/16/9993.62 5/20/9987.3 7/13/9995.5 9/28/99123 11/29/99129.05 1/19/0080.6 3/22/00119.6 5/22/0093 6/13/0079.09 6/19/0085.4 7/18/0090.6 9/19/0090 11/13/00115 1/18/0192.6 3/7/0197.8 5/24/01115 7/10/0188.7

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SpringSampDateYearDayDateMonth(txt)Month(nu)SeasonSeason_N o SourceTempSCl Starbuck Springs 19930525199325 5/25/93 55Spring1USGS24.2* Starbuck Springs19930930199330 9/30/93 99Fall3SJR24.1356 Starbuck Springs19950506199506 5/6/95 55Spring1SJR24.6* Starbuck Springs19950525199525 5/25/95 55Spring1USGS24.2* Starbuck Springs19950620199520 6/20/95 66Summer2SJR23.5350 Starbuck Springs19950906199506 9/6/95 99Fall3SJR24.64376 Starbuck Springs19960517199617 5/17/96 55Spring1SJR24.07346 Starbuck Springs19960911199611 9/11/96 99Fall3SJR24.31333 Starbuck Springs19970417199717 4/17/97 44Spring1USGS24.1* Starbuck Springs19970514199714 5/14/97 55Spring1SJR24.02358 Starbuck Springs19970910199710 9/10/97 99Fall3SJR24336 Starbuck Springs19980520199820 5/20/98 55Spring1SJR24.26354 Starbuck Springs19980909199809 9/9/98 99Fall3SJR24358 Starbuck Springs19990518199918 5/18/99 55Spring1SJR24.11362 Starbuck Springs19990908199908 9/8/99 99Fall3SJR24.12357 Starbuck Springs20000517200017 5/17/00 55Spring1SJR24.28380 Starbuck Spring1/18/01 11Winter4 24.23 * Starbuck Spring3/1/01 33Spring1 24.08 * Starbuck Spring3/6/01 33Spring1 24.15 * Starbuck Spring5/15/01 55Spring1 24.27 * Starbuck Spring7/9/01 77Summer2 24.21 * Starbuck Spring9/17/01 99Fall3 24.29 * Starbuck Spring11/13/01 1111Fall3 24 * Starbuck Spring1/29/02 11Winter4 24.4 * Starbuck Spring3/19/02 33Spring1 24.5 * Starbuck Spring7/16/02 77Summer2 24.4 * Starbuck Spring11/14/02 1111Fall3 * * Starbuck Spring1/23/03 11Winter4 23 * Starbuck Spring3/27/03 33Spring1 24.1 * Starbuck Spring6/25/03 66Summer2 25.2 * Starbuck Spring8/12/03 88Summer2 24.8 * Starbuck Spring11/18/03 1111Fall3 24.2 *

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DateSCfpHT-AlkD-NO3T-NO3D-NO3NO 2 T-NO3NO 2 DNO3NO2orTNO3T-PD-PTOCCa 5/25/93 3487.6*********41 9/30/93 3567.3119**0.592*0.592***40 5/6/95 3767.3********** 5/25/95 350**********44 6/20/95 3507.31120**0.52*0.52 **** 9/6/95 *7.3118**0.4470.4610.4470.1680.159*41 5/17/96 *7.14116**0.643*0.643 **** 9/11/96 *7.21120**0.313*0.313 **** 4/17/97 360*********** 5/14/97 *7.06123**0.307*0.307 **** 9/10/97 *6.88122.7148**0.317*0.317 **** 5/20/98 *7.44118.0753**0.652*0.652 **** 9/9/98 *7.04123.6884**0.397*0.397 **** 5/18/99 **121.7528**0.304*0.304 **** 9/8/99 *7.19123.735**0.39*0.39 **** 5/17/00 *7.32125.046**0.507*0.507 **** 1/18/013597.47128.58 * 0.295 ** 0.295* *** 3/1/013747.37125.4410.2230.215 ** 0.2150.1620.151 ** 3/6/013597.52126.717 * 0.21 ** 0.21* *** 5/15/013587.4126.619 * * ** ** *** 7/9/013617.49126.837 * 0.269 ** 0.269* *** 9/17/01361*124.94 * 0.353 ** 0.353* *** 11/13/013307.43119.977 * 0.535 ** 0.535* *** 1/29/023537.42* * * ** ** *** 3/19/023657.37126.446 * 0.342 ** 0.342* *** 7/16/023637.53126.591 * 0.129 ** 0.129* *** 11/14/023677.49126 * 0.44 ** 0.44* *** 1/23/033687.87119 * 0.49 ** 0.49* *** 3/27/033557.58121 * 0.35 ** 0.35* *** 6/25/033647.49124 * 0.32 ** 0.32* *** 8/12/033227.74120 * 0.46 ** 0.46* *** 11/18/033577.57122 * 0.41 ** 0.410.184 ***

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DateT-CaMgT-MgT-NaNaKT-KTKNT-SO4FT-FFluoride = (D or T) 5/25/93 *12**111.3*19220.2*0.2 9/30/93 3511.411.612111.31.320250.180.180.18 5/6/95 ************ 5/25/95 *11**111.4*21240.2*0.2 6/20/95 40*11.111**1.92026*0.180.18 9/6/95 *11.4**121.5*2119*0.180.18 5/17/96 40*11.512**1.42128*0.170.17 9/11/96 38*10.713**1.42122*0.190.19 4/17/97 *******2023*** 5/14/97 40.47*10.9612**1.181922*0.180.18 9/10/97 38.39*10.7711.57**1.58718.11223.481*0.190.19 5/20/98 40.36*12.6112.47**1.49720.40524.043*0.19410.1941 9/9/98 42.95*1212.04**1.29720.523.806*0.2020.202 5/18/99 43.93*11.8612.31**1.301*21.682*0.1980.198 9/8/99 43.33*12.3412.5**1.33618.3623.713*0.19520.1952 5/17/00 42.45*12.4412.99**1.58919.17125.511*0.20.2 1/18/0143.553 * 12.69612.54 ** 1.389 * 24.5920.1981 * 0.1981 3/1/0141.63 * 12.07611.99 ** 1.3290.12125.5680.1898 * 0.1898 3/6/0141.647 * 11.78712.35 ** 1.292 * 24.8220.2058 * 0.2058 5/15/0141.96 * 11.89612.19 ** 1.297 * 24.4970.2098 * 0.2098 7/9/0142.109 * 11.27712.01 ** 1.311 * 23.9620.202 * 0.202 9/17/0142.267 * 12.23612.97 ** 1.379 * 280.2114 * 0.2114 11/13/0140.906 * 12.19913.16 ** 1.431 * 25.3030.2 * 0.2 1/29/0242.719 * 12.27913.35 ** 1.41 * 25.6620.2124 * 0.2124 3/19/0244.632 * 12.64112.93 ** 1.309 * 25.1390.1962 * 0.1962 7/16/0242.578 * 11.86312.36 ** 1.368 * 26.1380.2205 * 0.2205 11/14/0243 * 1213 ** 1.4 * 270.2 * 0.2 1/23/0342 * 1213 ** 1.3 * 260.2 * 0.2 3/27/0342 * 1113 ** 1.4 * 260.2 * 0.2 6/25/0342 * 1213 ** 1.5 * 270.2 * 0.2 8/12/0339 * 1213 ** 1.4 * 270.2 * 0.2 11/18/0341.15 * 11.513.56 ** 1.601 * 24.8* * *

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DateSiSi(SIO3 as T-FeD-FeD-SrT-SrTDST-PO4T-ClFlowDateFLOW-CFS 5/25/93 8.7***220*192*1905/22/199112 9/30/93 *4**233233**2009/25/199117 5/6/95 ********* 05/22/199213 5/25/95 8.9**3300*208*2109/24/199216 6/20/95 *456**277*0.1632005/25/199313.3 9/6/95 8***303*1790.1512106/17/199312.4 5/17/96 *8***3101910.1682109/24/199311.9 9/11/96 *4***2921980.1542109/30/199312.7 4/17/97 ********20 05/25/199412.6 5/14/97 *4.62***293.91980.1581905/06/199516.3 9/10/97 *4.46***303.11900.16118.11205/25/199513.5 5/20/98 *4.33***305.31990.19120.40505/25/199513.5 9/9/98 *4.41***307.71790.16920.509/06/199516.3 5/18/99 *4.59***307.12120.155*03/15/199617 9/8/99 *4.52***335.52130.15118.3604/17/199617.9 5/17/00 *4.32***328.52070.1719.17105/02/199618.7 1/18/01 * 4.701 *** 341.752020.12819.421 06/18/199615.3 3/1/0110.206* ** 325.009328.971840.1220.88 07/10/199616.9 3/6/01 * 4.445 *** 332.111900.13622.539 08/15/199613.8 5/15/01 * 4.419 *** 335.83190*19.125 09/04/199615.1 7/9/01 * 4.468 *** 330.562030.12618.754 10/16/199618.7 9/17/01 * 4.635 *** 351.372030.13423.8 11/20/199614.5 11/13/01 * 4.392 *** 335.89*0.13621.659 12/10/199615 1/29/02 * 5.198 *** 334.172500.1320.826 01/13/199716.6 3/19/02 * 5.043 *** 342.482100.12919.364 02/26/199715.4 7/16/02 * 4.61 *** 341.572100.13119.932 03/19/199715.3 11/14/02 * * *** 3502110.1423 04/17/199712.7 1/23/03 * * *** 3502050.1322 05/21/199713.4 3/27/03 * * *** 3502130.1323 06/23/199713.9 6/25/03 * * *** 3602110.1423 07/17/199712.9 8/12/03 * * *** 3501880.1423 09/25/199711.8 11/18/03 * * *** *1980.14622.6 10/22/199711.6 05/20/199813.5 09/23/199816.11 05/18/199911.2 09/28/199915.1 05/22/20008.28 09/25/200012

PAGE 290

SpringDateMonth(nu)SeasonSeason_NoTempDesnTempSClSCfpHT-AlkD-NO3T-NO3D-NO3NO 2 Sweetwater Springs 1/10/91 1Winter422.822.9624419741977.7175**0.054 Sweetwater Springs 7/10/91 7Summer223.523.375**6.7676**0.014 Sweetwater Springs 7/29/91 7Summer2 **** 7.68 **** Sweetwater Springs 1/9/92 1Winter423.223.3624*42907.48 **** Sweetwater Springs 7/8/92 7Summer223.323.175417041707.5174**0.114 Sweetwater Springs 1/19/93 1Winter423.223.3624426042607.6674**0.042 Sweetwater Springs 7/14/93 7Summer223.523.375**7.67***0.03 Sweetwater Springs 1/18/94 1Winter42222.1624431043107.0673**0.041 Sweetwater Springs 7/7/94 7Summer223.323.175408040807.5873**0.045 Sweetwater Springs 11/15/94 11Fall323.223.27663940*7.474**0.041 Sweetwater Springs 1/9/95 1Winter423.223.36243870*7.6572**0.051 Sweetwater Springs 1/10/95 1Winter423.223.3624*38707.65 **** Sweetwater Springs 3/22/95 3Spring123.523.4115355035507.8272**0.037 Sweetwater Springs 7/12/95 7Summer223.323.175**7.5572**0.042 Sweetwater Springs 7/13/95 7Summer223.323.175*40307.55 **** Sweetwater Springs 11/20/95 11Fall323.123.1766386038607.6670**0.039 Sweetwater Springs 1/18/96 1Winter423.123.2624376037607.5175**0.042 Sweetwater Springs 3/19/96 3Spring123.223.1115393037307.3871**0.143 Sweetwater Springs 5/3/96 5Spring123.123.01153640*7.3767**0.036 Sweetwater Springs 7/9/96 7Summer223.223.075382038207.3269**0.039 Sweetwater Springs 11/18/96 11Fall323.1923.2666***71**0.039 Sweetwater Springs 1/14/97 1Winter42323.1624372037207.4371**0.041 Sweetwater Springs 3/10/97 3Spring123.723.6115369036907.7471**0.04 Sweetwater Springs 7/21/97 7Summer223.223.0753710*7.4972.4124**0.036 Sweetwater Springs 11/4/97 11Fall323.123.17663530*7.2573.4392**0.04 Sweetwater Springs 1/20/98 1Winter422.7622.92243800*7.6473.0674**0.046 Sweetwater Springs 3/20/98 3Spring123.223.11153789*7.7272.9619*** Sweetwater Springs 5/22/98 5Spring12322.9115*35207.7 **** Sweetwater Springs 7/10/98 7Summer223.3423.215**6.971.5024**0.035 Sweetwater Springs 11/13/98 11Fall323.0223.0966**7.2171.9611**0.035 Sweetwater Springs 1/8/99 1Winter423.2423.40243650*7.7870.5456**0.036 Sweetwater Springs 3/12/99 3Spring123.2323.14153306*7.8470.2337**0.033 Sweetwater Springs 5/21/99 5Spring123.223.1115*3860 ***** Sweetwater Springs 7/9/99 7Summer223.122.9753580*7.6670.5419**0.035 Sweetwater Springs 11/12/99 11Fall32323.07663781*8.0870.989**0.038 Sweetwater Springs 3/17/00 3Spring1 ***** 72.066*** Sweetwater Springs1/19/01 1Winter4 23.223.3624 * 37607.7473.189 * 0.034 * Sweetwater Springs3/2/01 3Spring1 23.323.2115 * 37257.8571.271 * 0.02 * Sweetwater Springs7/13/01 7Summer2 23.223.075 * **72.386 * 0.033 * Sweetwater Springs11/1/01 11Fall3 23.123.1766 * 29187.870.005 * 0.038 * Sweetwater Springs1/25/02 1Winter4 23.323.4624 * 29297.5471.162 * 0.039 * Sweetwater Springs3/22/02 3Spring1 23.223.1115 * 33977.9671.629 * 0.035 * Sweetwater Springs7/12/02 7Summer2 23.423.275 * 31697.7571.408 * * * Sweetwater Springs11/15/02 11Fall3 ** * 32907.9772 * 0.03 * Sweetwater Springs1/24/03 1Winter4 2323.1624 * 37198.0869 * 0.04 * Sweetwater Springs3/21/03 3Spring1 23.323.2115 * 35807.8573 * 0.19 * Sweetwater Springs6/27/03 6Summer2 23.423.275 * 22527.7672 * 0.06 * Sweetwater Springs8/15/03 8Summer2 23.223.075 * 28407.771 * 0.03 * Sweetwater Springs11/21/03 11Fall3 23.123.1766 * 34717.7370.9 * 0.0366 *

PAGE 291

DateT-NO3NO2DNO3NO2orTN O T-PD-PTOCCaT-CaMgT-MgT-NaNaKT-KTKN 1/10/91 *0.054**0.7130*69.9**61818.5*1120 7/10/91 *0.014***105 ***** 18.5*1160 7/29/91 ************** 1/9/92 ************** 7/8/92 *0.114***11511069.567.161562019.518.61150 1/19/93 *0.042***11110766.464.462261318.917.41120 7/14/93 *0.03***10511366.261.760262018.816.52160 1/18/94 *0.041***10410562.861.661661618.917.51061 7/7/94 *0.045***10810264.662.157370521.822.21080 11/15/94 *0.041***11811671.2**58317.717.9978 1/9/95 *0.051***10910362.760.160062319.418.61020 1/10/95 ************** 3/22/95 *0.037***10910656.354.552952418.818.41080 7/12/95 *0.042 ****102* 59.8570**19.3846 7/13/95 ************** 11/20/95 *0.039 ****99* 58.6522**16.6* 1/18/96 *0.042 ****104* 60.2520**18.11140 3/19/96 *0.143 ****112* 63.8530**19.41030 5/3/96 0.0370.0360.0190.019*102*57.5**55817.2*966 7/9/96 *0.039 ****104* 58.1558**17.61010 11/18/96 *0.039 ****99* 54.8530**16.7966 1/14/97 *0.041 ****101* 57.2507**17.41010 3/10/97 *0.04 ****100* 60.2543**17.41005 7/21/97 *0.036 ****108* 62.6562**181104.98 11/4/97 *0.04 **** 100.8*58.7534**20.181057 1/20/98 *0.046 **** 103.3*61.9564**22.871103.37 3/20/98 ****** 114.3*59.4519**18.091047.18 5/22/98 ************** 7/10/98 *0.035 **** 103.5*58.3504**16.431051.71 11/13/98 *0.035 **** 105.6 ****** 1068.34 1/8/99 *0.036 **** 106.8*64.4567**19.01* 3/12/99 *0.033 **** 100.4*58558**17.371044.8 5/21/99 ************** 7/9/99 *0.035 ****100* 57.7556**12.931031.04 11/12/99 *0.038 **** 102.5*61.9561**17.541068.96 3/17/00 ****** 106.3*63.2562**18.511058.56 1/19/01 * 0.034* *** 102.653 * 58.342549.22 ** 18.801 * 3/2/01 * 0.02* *** 99.931 * 58.32556.81 ** 17.939 * 7/13/01 * 0.033* *** 101.693 * 55.059532.79 ** 18.295 * 11/1/01 * 0.038* *** 100.474 * 57.84543.46 ** 18.081 * 1/25/02 * 0.039* *** 109.484 * 62.105560.57 ** 20.693 * 3/22/02 * 0.035* *** 107.677 * 61.767543.12 ** 20.357 * 7/12/02 * ** *** 102.03 * 58.009546.32 ** 18.584 * 11/15/02 * 0.03* *** 98 * 56500 ** 16 * 1/24/03 * 0.04* *** 92 * 52450 ** 14 * 3/21/03 * 0.19* *** 98 * 55520 ** 17 * 6/27/03 * 0.06* *** 95 * 55500 ** 16 * 8/15/03 * 0.03* *** 98 * 61540 ** 17 * 11/21/03 * 0.03660.027 *** 92.32 * 53.065112 ** 15.52 *

PAGE 292

DateT-SO4FT-FFluoride = (D orT)SiSi(SIO3 as T-FeD-FeD-SrT-SrTDST-PO4T-Cl 1/10/91 2890.127*0.127*4**2210*2230*1120 7/10/91 2960.12*0.12*4 **** 2360*1160 7/29/91 ************* 1/9/92 ************* 7/8/92 2590.11*0.11*4**240022802360*1150 1/19/93 2940.11*0.11*4**216022502200*1120 7/14/93 *0.12*0.12 **** 22502430**2160 1/18/94 2460.110.110.11*4***22302260*1061 7/7/94 251*0.110.11*4*3224802344**1080 11/15/94 249*0.110.11*458*4730494022100.026978 1/9/95 244****4**2400230021400.0261020 1/10/95 ************* 3/22/95 246*0.090.09*4**2210217021300.0281080 7/12/95 277*0.110.11*452**223022000.023846 7/13/95 ************* 11/20/95 252*0.120.12*4***213020200.026* 1/18/96 224*0.110.11*4***210021500.0241140 3/19/96 262*0.120.12*458**233021900.0351030 5/3/96 273*0.110.118***2130*20000.025966 7/9/96 293*0.130.13*4***214020700.0261010 11/18/96 250*0.130.13*4***208020500.028966 1/14/97 273*0.120.12*4***207020500.0231010 3/10/97 268*0.120.12*5***225020700.0211005 7/21/97 261.674*0.120.12*4.12***220022500.0211104.98 11/4/97 263.777*0.120.12*4.19***233121400.0221057 1/20/98 277.706*0.120.12*4.02***2394*0.0261103.37 3/20/98 260.317*0.110.11*4.35***22522070*1047.18 5/22/98 ************* 7/10/98 237.51*0.12580.1258*4.37***232820300.0191051.71 11/13/98 263.013*0.13420.1342*4.59116.2**171421000.0171068.34 1/8/99 260.642*0.1380.138*4.22***244820400.021* 3/12/99 262.339*0.13370.1337*4.21***2192*0.0251044.8 5/21/99 ************* 7/9/99 256.198*0.12750.1275*4.47***234620100.0211031.04 11/12/99 254.843*0.13710.1371*4.06***2350*0.0191068.96 3/17/00 252.235*0.13170.1317*4.37***22762050*1058.56 1/19/01256.1080.1272 * 0.1272 * 4.387 *** 2288.9520100.031017.9 3/2/01261.9270.1262 * 0.1262 * 4.093 *** 2292.8719500.0121035.23 7/13/01255.8490.1324 * 0.1324 * 4.361 *** 2266.1321900.0211025.28 11/1/01*0.1388 * 0.1388 * 4.499 *** 2222.6519500.02* 1/25/02250.3220.1434 * 0.1434 * 4.55 *** 2299.7318000.012977.564 3/22/02265.0820.126 * 0.126 * 4.584 *** 2235.7820000.0161039.18 7/12/02251.5810.1418 * 0.1418 * 4.369 *** 2274.0616200.031012.04 11/15/022200.1 * 0.1 * * *** 210020100.02920 1/24/032000.1 * 0.1 * * *** 194017900.02840 3/21/032400.1 * 0.1 * * *** 209018800.01940 6/27/032200.1 * 0.1 * * *** 206020800.02930 8/15/032400.1 * 0.1 * * *** 211020400.01960 11/21/03212* * * * * *** *18400.0227889

PAGE 293

DateFlowFLOW-CFSDateFlowFLOW-CFS 01/10/199112.6911/04/199711.31 03/14/199112.3101/20/199813.51 05/23/19911203/20/199813.99 05/28/199113.7703/20/199814 07/10/199112.9105/22/199816.2 09/05/199113.8207/10/199815.1 09/27/19911409/25/199813.3 11/07/199115.1211/13/199812.27 01/09/199213.6301/08/199911.51 03/11/199213.5203/12/199913.85 05/14/199213.0205/21/199913.2 05/22/19921207/09/199911.38 07/08/199211.0909/24/199913 09/21/199213.0311/12/199912.89 09/25/19921301/14/200012.44 11/04/199213.8603/17/200010.61 01/19/199310.9905/19/200010.9 03/04/19939.8606/16/200011.64 05/18/199312.7509/22/200012 05/21/199312 07/14/199311.7 09/07/199312.1 09/24/199313 11/01/199312 01/18/199411.4 03/07/199411.9 05/03/199411 05/27/199412 07/07/199410.8 09/23/199413 09/29/199415.21 11/15/199412.91 01/10/199513.4 03/22/199512.8 05/26/19958.5 07/13/199512.9 09/22/199512.5 11/20/199513.8 01/18/199613.9 03/19/199613.5 05/03/199613.8 07/09/199613.52 09/27/199616.1 11/18/199615.51 01/14/199712.3 03/10/199712.6 04/30/199711.6 05/24/199712 07/15/199712.2

PAGE 294

SpringDate Month(txt) Month(nu)Season_N o Source TempDesnTem p SClSCf pH T-Alk Blue Springs nr Orange City 01/22/1991 114SJR22.722.8076228122817.47133 Blue Springs nr Orange City 02/11/1991 224USGS23.223.3076*2440** *04/02/1991*41 ******* Blue Springs nr Orange City 04/08/1991 441USGS2323.0181*2610** Blue Springs nr Orange City 05/23/1991 551USGS2323.0181*2610** *06/12/1991*62 ******* * 08/09/1991 *82******* Blue Springs nr Orange City 08/19/1991 882SJR2322.8398217021707.37141 *08/26/1991*103 ******* *10/01/1991*103 ******* Blue Springs nr Orange City 10/09/1991 10124USGS23.123.1648*1930** Blue Springs nr Orange City 12/10/1991 12124USGS2323.1076*1530** *12/16/1991*14 ******* Blue Springs nr Orange City 01/24/1992 124USGS22.822.9076*1630** Blue Springs nr Orange City 02/20/1992 231SJR22.923.0076*17357.35129 Blue Springs nr Orange City 03/17/1992 341USGS2323.0181*1800** *04/09/1992*51 ******* Blue Springs nr Orange City 05/07/1992 562USGS22.722.7181*1860** *06/08/1992*72 ******* Blue Springs nr Orange City 07/02/1992 782USGS23.223.0398*1870** Blue Springs nr Orange City 08/19/1992 882SJR2322.8398220022007.22145 *08/27/1992*103 ******* Blue Springs nr Orange City 10/21/1992 10124USGS2323.0648*2220** Blue Springs nr Orange City 12/14/1992 1224USGS22.923.0076*1790** Blue Springs nr Orange City 02/03/1993 224SJR22.923.0076181518157.36137 Blue Springs nr Orange City 02/08/1993 241USGS22.822.9076*1860** Blue Springs nr Orange City 04/09/1993 441USGS22.822.8181*1860** *04/21/1993*62 ******* Blue Springs nr Orange City 06/02/1993 662USGS2322.8398*1590** *06/08/1993*72 ******* Blue Springs nr Orange City 07/23/1993 782USGS22.922.7398*1620** Blue Springs nr Orange City 08/03/1993 893SJR2322.8398171217127.27130 Blue Springs nr Orange City 09/17/1993 9103USGS2323.0648*1750** *10/14/1993*113 ******* Blue Springs nr Orange City 11/23/1993 11124USGS22.822.8648*1990** *12/16/1993*14 ******* Blue Springs nr Orange City 01/19/1994 124USGS22.822.9076*2180** *02/16/1994*31 ******* Blue Springs nr Orange City 02/17/1994 241SJR22.923.0076232023207.35* Blue Springs nr Orange City 03/04/1994 351USGS2323.0181*2300** *04/12/1994*62 ******* Blue Springs nr Orange City 05/06/1994 562USGS2424.0181*2110**

PAGE 295

DateD-NO3T-NO3D-NO3NO2DNO3NO2+TNO3T-NO3NO 2 T-PD-PTOCCaT-CaMgT-Mg 01/22/1991 **0.1690.169***1.3687*38.7* 02/11/1991 ************ 04/02/1991**** ******** 04/08/1991 ************ 05/23/1991 ************ 06/12/1991**** ******** 08/09/1991 ************ 08/19/1991 **0.260.26 ****72* 34.8* 08/26/1991**** ******** 10/01/1991**** ******** 10/09/1991 ************ 12/10/1991 ************ 12/16/1991**** ******** 01/24/1992 ************ 02/20/1992 **0.3940.394 ****6341 27.826.8 03/17/1992 ************ 04/09/1992**** ******** 05/07/1992 ************ 06/08/1992**** ******** 07/02/1992 ************ 08/19/1992 **0.1740.174 ****7068 37.634.1 08/27/1992**** ******** 10/21/1992 ************ 12/14/1992 ************ 02/03/1993 **0.2970.297 ****6066 28.530.2 02/08/1993 ************ 04/09/1993 ************ 04/21/1993**** ******** 06/02/1993 ************ 06/08/1993**** ******** 07/23/1993 ************ 08/03/1993 ********6762 27.426.9 09/17/1993 ************ 10/14/1993**** ******** 11/23/1993 ************ 12/16/1993**** ******** 01/19/1994 ************ 02/16/1994**** ******** 02/17/1994 **0.1510.151 ****6965 36.834.7 03/04/1994 ************ 04/12/1994**** ******** 05/06/1994 ************

PAGE 296

DateT-NaNaKT-KTKNT-SO4FT-FSiSi(SIO3 asT-FeD-Fe 01/22/1991 *32411.7*150920.1**5** 02/11/1991 ****580******* 04/02/1991 ************ 04/08/1991 ****670******* 05/23/1991 ****700******* 06/12/1991 ************ 08/09/1991 ************ 08/19/1991 *7010.2*508770.09**4** 08/26/1991 ************ 10/01/1991 ************ 10/09/1991 ****490******* 12/10/1991 ****360******* 12/16/1991 ************ 01/24/1992 ****380******* 02/20/1992 2182188.99404650.08**4** 03/17/1992 ****420******* 04/09/1992 ************ 05/07/1992 ****470******* 06/08/1992 ************ 07/02/1992 ****560******* 08/19/1992 29228510.410542800.09**4** 08/27/1992 ************ 10/21/1992 ****580******* 12/14/1992 ****420******* 02/03/1993 2322318.47.8443670.07**4** 02/08/1993 ****450******* 04/09/1993 ****473******* 04/21/1993 ************ 06/02/1993 ************ 06/08/1993 ************ 07/23/1993 ****395******* 08/03/1993 2142198.37.8416630.08**4** 09/17/1993 ****424******* 10/14/1993 ************ 11/23/1993 ****505******* 12/16/1993 ************ 01/19/1994 ****555******* 02/16/1994 ************ 02/17/1994 31031611.410.253194***4** 03/04/1994 ****610******* 04/12/1994 ************ 05/06/1994 ****530*******

PAGE 297

DateD-SrT-SrTDS T-PO4D-ClFlowDate FLOW-CFS DeSnFlowSTAGE FEETSource 01/22/1991 1222*1113*15001/22/1991114.69103.38*SJR 02/11/1991 ****580 02/11/1991126114.691.77USGS 04/02/1991 ***** 04/02/1991130.83129.3*SJR 04/08/1991 ****670 04/08/1991112110.471.49USGS 05/23/1991 ****700 05/23/1991133131.472.03USGS 06/12/1991 ***** 06/12/1991104.03111.821*SJR 08/09/1991 ****520 08/09/1991152159.7913.72USGS 08/19/1991 1010*1060*508 ***** 08/26/1991 ***** 08/26/1991122.68130.471*SJR 10/01/1991 ***** 10/01/1991155.44161.407*SJR 10/09/1991 ****490 10/09/1991125130.9674.21USGS 12/10/1991 ****360 12/10/1991160148.692.18USGS 12/16/1991 ***** 12/16/1991162.14150.83*SJR 01/24/1992 ****380 01/24/1992157145.691.74USGS 02/20/1992 868845897*40402/20/1992156.67145.36*SJR 03/17/1992 ****420 03/17/1992146144.471.2USGS 04/09/1992 ***** 04/09/1992160.37158.84*SJR 05/07/1992 ****470 05/07/1992135133.471.66USGS 06/08/1992 ***** 06/08/1992138.34146.131*SJR 07/02/1992 ****560 07/02/1992103110.7911.88USGS 08/19/1992 122010501160*54208/19/1992144.37152.161*SJR 08/27/1992 ****580 08/27/1992120127.7912.96USGS 10/21/1992 ****580 10/21/1992126.905132.8724.58USGS 12/14/1992 ****420 12/14/1992150.845139.5352.63USGS 02/03/1993 8039981050*44302/03/1993137.34126.03*SJR 02/08/1993 ****450 02/08/1993150138.692.87USGS 04/09/1993 ****473 04/09/1993150148.472.42USGS 04/21/1993 ***** 04/21/1993157.63156.1*SJR 06/02/1993 ***** 06/02/1993144151.7911.76USGS 06/08/1993 ***** 06/08/1993136.5144.291*SJR 07/23/1993 ****395 07/23/1993142149.7911.4USGS 08/03/1993 926881**41608/03/1993129.6137.391*SJR 09/17/1993 ****424 09/17/1993136141.9672.05USGS 10/14/1993 ***** 10/14/1993139144.967*SJR 11/23/1993 ****505 11/23/1993139144.9672.27USGS 12/16/1993 ***** 12/16/1993139.5128.19*SJR 01/19/1994 ****555 01/19/1994138126.691.63USGS 02/16/1994 ***** 02/16/1994134.6123.29*SJR 02/17/1994 120011601200*531 ***** 03/04/1994 ****610 03/04/1994133131.472.02USGS 04/12/1994 ***** 04/12/1994140.6139.07*SJR 05/06/1994 ****530 05/06/1994134.05132.521.39USGS

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SpringDate Month(txt) Month(nu)Season_N o Source TempDesnTem p SClSCf pH T-Alk *06/14/1994*82 ******* Blue Springs nr Orange City 06/24/1994 682USGS2423.8398*2170** *08/17/1994*93 ******* Blue Springs nr Orange City 08/18/1994 8103SJR23.122.9398*23967.32* *09/30/1994*124 ******* *10/31/1994*24 ******* *12/06/1994*41 ******* *02/01/1995*62 ******* *04/12/1995*82 ******* *06/13/1995*103 ******* *08/04/1995*103 ******* *10/02/1995*103 ******* *10/13/1995*124 ******* *10/31/1995*124 ******* *12/01/1995*24 ******* *12/08/1995*24 ******* *02/09/1996*41 ******* *02/28/1996*41 ******* *04/22/1996*51 ******* *04/24/1996*62 ******* Blue Springs nr Orange City 05/02/1996 582SJR22.7622.77811162*7.12127 *06/14/1996*103 ******* *08/13/1996*124 ******* *10/04/1996*14 ******* *12/03/1996*41 ******* *01/27/1997*51 ******* *04/22/1997*93 ******* *05/23/1997*103 ******* *09/08/1997*14 ******* *10/31/1997*31 ******* *01/12/1998*41 ******* *03/03/1998*62 ******* Blue Springs nr Orange City 04/23/1998*82 ******* Blue Springs nr Orange City 06/16/1998 693USGS23.122.9398*14806.87* Blue Springs nr Orange City 08/07/1998 8124USGS2322.8398*10207.6* Blue Springs nr Orange City 09/28/1998 914USGS2323.0648*14386.78* Blue Springs nr Orange City 12/04/1998 1231USGS2323.1076*14837.4* Blue Springs nr Orange City 01/22/1999 151USGS2323.1076*16107.53* Blue Springs nr Orange City 03/18/1999 372USGS23.323.3181*16607.27* Blue Springs nr Orange City 05/18/1999 593USGS22.822.8181*10507.5* *07/07/1999*113 ******* Blue Springs nr Orange City 09/01/1999 941USGS2323.0648*17606.96*

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DateD-NO3T-NO3D-NO3NO2DNO3NO2+TNO3T-NO3NO 2 T-PD-PTOCCaT-CaMgT-Mg 06/14/1994**** ******** 06/24/1994 ************ 08/17/1994**** ******** 08/18/1994 ************ 09/30/1994**** ******** 10/31/1994**** ******** 12/06/1994**** ******** 02/01/1995**** ******** 04/12/1995**** ******** 06/13/1995**** ******** 08/04/1995**** ******** 10/02/1995**** ******** 10/13/1995**** ******** 10/31/1995**** ******** 12/01/1995**** ******** 12/08/1995**** ******** 02/09/1996**** ******** 02/28/1996**** ******** 04/22/1996**** ******** 04/24/1996**** ******** 05/02/1996 **0.6170.6170.6150.0920.074*61*19.9* 06/14/1996**** ******** 08/13/1996**** ******** 10/04/1996**** ******** 12/03/1996**** ******** 01/27/1997**** ******** 04/22/1997**** ******** 05/23/1997**** ******** 09/08/1997**** ******** 10/31/1997**** ******** 01/12/1998**** ******** 03/03/1998**** ******** 04/23/1998**** ******** 06/16/1998 **0.490.49*0.07**61*21* 08/07/1998 **0.570.57*0.04**57*16* 09/28/1998 **0.40.4*0.07**60*21* 12/04/1998 *0.340.350.35*0.07**63*25* 01/22/1999 **0.40.4*0.07**63*23* 03/18/1999 **0.380.38*0.09**63*25* 05/18/1999 ****0.02*0.02*42*17* 07/07/1999**** ******** 09/01/1999 **0.30.3*0.06**65*27*

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DateT-NaNaKT-KTKNT-SO4FT-FSiSi(SIO3 asT-FeD-Fe 06/14/1994 ************ 06/24/1994 ****580******* 08/17/1994 ************ 08/18/1994 ************ 09/30/1994 ************ 10/31/1994 ************ 12/06/1994 ************ 02/01/1995 ************ 04/12/1995 ************ 06/13/1995 ************ 08/04/1995 ************ 10/02/1995 ************ 10/13/1995 ************ 10/31/1995 ************ 12/01/1995 ************ 12/08/1995 ************ 02/09/1996 ************ 02/28/1996 ************ 04/22/1996 ************ 04/24/1996 ************ 05/02/1996 *1675.9*27848*0.07 **** 06/14/1996 ************ 08/13/1996 ************ 10/04/1996 ************ 12/03/1996 ************ 01/27/1997 ************ 04/22/1997 ************ 05/23/1997 ************ 09/08/1997 ************ 10/31/1997 ************ 01/12/1998 ************ 03/03/1998 ************ 04/23/1998 ************ 06/16/1998 *1806.5*320510.1*8.6*** 08/07/1998 *1204.5*210330.1*8.4*** 09/28/1998 *1906.4*320510.1*8.7*** 12/04/1998 *2008*380580.1*8.4*** 01/22/1999 *1907.1*360570.1*8.4*** 03/18/1999 *2106.8*400600.1*8.4*** 05/18/1999 *1303.6*240530.1*9.6**1 07/07/1999 ************ 09/01/1999 *2308.1*420640.1*8.4***

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DateD-SrT-SrTDS T-PO4D-ClFlowDate FLOW-CFS DeSnFlowSTAGE FEETSource 06/14/1994 ***** 06/14/1994121.4129.191*SJR 06/24/1994 ****580 06/24/1994140147.7912.76USGS 08/17/1994 ****590 08/17/1994134141.7913.36USGS 08/18/1994 ***** 08/18/1994120127.791*SJR 09/30/1994 ***** 09/30/1994151156.967*USGS 10/31/1994 ***** 10/31/1994143148.967*SJR 12/06/1994 ***** 12/06/1994212200.695.75USGS 02/01/1995 ***** 02/01/1995174162.693.2USGS 04/12/1995 ***** 04/12/1995153151.474.38USGS 06/13/1995 ***** 06/13/1995157164.7915.18USGS 08/04/1995 ***** 08/04/1995116123.7914.09USGS 10/02/1995 ***** 10/02/1995131136.9675.06USGS 10/13/1995 ***** 10/13/1995136141.9675.22USGS 10/31/1995 ***** 10/31/1995159164.9675.55USGS 12/01/1995 ***** 12/01/1995155143.69*SJR 12/08/1995 ***** 12/08/1995166154.694.03USGS 02/09/1996 ***** 02/09/1996161.4150.09*SJR 02/28/1996 ***** 02/28/1996176164.691.79USGS 04/22/1996 ***** 04/22/1996144142.473.55USGS 04/24/1996 ***** 04/24/1996160158.473.35USGS 05/02/1996 737*6670.06327805/02/1996160158.472.82USGS 06/14/1996 ***** 06/14/1996167174.7911.88USGS 08/13/1996 ***** 08/13/1996152159.7911.78USGS 10/04/1996 ***** 10/04/1996151156.9672.73USGS 12/03/1996 ***** 12/03/1996171159.692.51USGS 01/27/1997 ***** 01/27/1997173161.691.86USGS 04/22/1997 ***** 04/22/1997151149.471.99USGS 05/23/1997 ***** 05/23/1997162160.471.55USGS 09/08/1997 ***** 09/08/1997153158.9673.4USGS 10/31/1997 ***** 10/31/1997152157.9672.46USGS 01/12/1998 ***** 01/12/1998145133.691.88USGS 03/03/1998 ***** 03/03/1998165163.475.5USGS 04/23/1998 ***** 04/23/1998183181.473.38USGS 06/16/1998 790*7730.0632006/16/1998182189.7911.03USGS 08/07/1998 640*5760.0721008/07/1998163170.7911.78USGS 09/28/1998 800*7420.0732009/28/1998146151.9673.08USGS 12/04/1998 850*8800.0738012/04/1998164152.691.8USGS 01/22/1999 850*8550.0736001/22/1999166154.691.51USGS 03/18/1999 870*9060.0740003/18/1999163161.471.58USGS 05/18/1999 **578*24005/18/1999132130.471.78USGS 07/07/1999 ***** 07/07/1999139146.7911.65USGS 09/01/1999 930*9860.0842009/01/1999120125.9672.09USGS

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SpringDate Month(txt) Month(nu)Season_N o Source TempDesnTem p SClSCf pH T-Alk *11/15/1999*62 ******* Blue Springs nr Orange City 01/11/2000 182USGS23.123.2076*16707.25* Blue Springs nr Orange City 04/18/2000 493USGS2323.0181*15507.4* Blue Springs nr Orange City 06/08/2000 6113USGS23.623.4398*14607.38* *08/15/2000*14 ******* *09/28/2000*31 ******* *11/16/2000*51 ******* *01/24/2001*72 ******* Blue Spring Volusia02/28/2001 **4* 23.0523.1576 * 19206.62142.759 * 03/19/2001 **** ** * *** * 05/17/2001 **** ** * *** * 07/17/2001 **** ** * *** Blue Spring Volusia11/20/2001 **3* 22.922.9648 * 12967.74137.543 Blue Spring Volusia07/16/2002 **2* 23.723.5398 * 14527.35141.407 Blue Spring Volusia03/27/2003 **1* 22.922.9181 * 11737.36136 Blue Spring Volusia06/26/2003 **2* 2322.8398 * 9507.43134 Blue Spring Volusia08/12/2003 **2* 23.223.0398 * 11387.42137 Blue Spring Volusia11/18/2003 **3* 2323.0648 * 13527.57134 * *********** * *********** * *********** * ***********

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DateD-NO3T-NO3D-NO3NO2DNO3NO2+TNO3T-NO3NO 2 T-PD-PTOCCaT-CaMgT-Mg 11/15/1999**** ******** 01/11/2000 **0.420.42*0.04**65*26* 04/18/2000 **0.390.39*0.06**66*24* 06/08/2000 **0.360.36*0.06**64*22* 08/15/2000**** ******** 09/28/2000**** ******** 11/16/2000**** ******** 01/24/2001**** ******** 02/28/20010.2390.238 *** 0.0820.0822.14 * 70.641 * 31.467 03/19/2001 ************ 05/17/2001 ************ 07/17/2001 ************ 11/20/2001 * 0.638 * 0.638 * * *** 64.722 * 21.691 07/16/2002 * 0.291 * 0.291 * * *** 66.968 * 23.285 03/27/2003 * 0.65 * 0.65 * * *** 61 * 18 06/26/2003 * 0.68 * 0.68 * * *** 57 * 16 08/12/2003 * 0.59 * 0.59 * * *** 62 * 21 11/18/2003 * 0.613 * 0.613 * 0.077 *** 62.78 * 21.5 ***** * * * * * * * ***** * * * * * * * ***** * * * * * * * ***** * * * * * * *

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DateT-NaNaKT-KTKNT-SO4FT-FSiSi(SIO3 asT-FeD-Fe 11/15/1999 ************ 01/11/2000 *2107.7*400610.1*8.3*** 04/18/2000 *1907.2*360550.1*8.3*** 06/08/2000 *1806.5*340520.1*8.4*** 08/15/2000 ************ 09/28/2000 ************ 11/16/2000 ************ 01/24/2001 ************ 02/28/2001260.27 ** 9.5070.23271.6770.0925 * 8.882* ** 03/19/2001 ************ 05/17/2001 ************ 07/17/2001 ************ 11/20/2001170.24 ** 6.613 * 49.4920.0901 ** 4.274 ** 07/16/2002186.8 ** 7.244 * 53.6190.0995 ** 4.327 ** 03/27/2003140 ** 5.5 * 40* ** * ** 06/26/2003120 ** 4.6 * 36* ** * ** 08/12/2003160 ** 6 * 44* ** * ** 11/18/2003168.3 ** 6.38 * 47.1* ** * ** * * * * * ******* * * * * * ******* * * * * * ******* * * * * * *******

PAGE 305

DateD-SrT-SrTDS T-PO4D-ClFlowDate FLOW-CFS DeSnFlowSTAGE FEETSource 11/15/1999 ***** 11/15/1999146151.9674.94USGS 01/11/2000 930*8940.07400 ***** 04/18/2000 860*8370.0736004/18/2000149147.471.37USGS 06/08/2000 860*7830.0834006/08/2000117124.7911.46USGS 08/15/2000 ***** 08/15/2000127134.7910.88USGS 09/28/2000 ***** 09/28/200097.3103.267*USGS 11/16/2000 ***** 11/16/2000115120.967*USGS 01/24/2001 ***** 01/24/2001136124.69*USGS 02/28/20011146.1131198.0310300.063464.12 ***** 03/19/2001 ***** 03/19/2001113111.47*USGS 05/17/2001 ***** 05/17/2001124122.47*USGS 07/17/2001 ***** 07/17/2001132139.791*USGS 11/20/2001 * 833.35*0.082302.526 ** *** 07/16/2002 * 882.318270.065344.237 ***** 03/27/2003 * 7006590.05260 ***** 06/26/2003 * 6306250.06220 ***** 08/12/2003 * 7506460.06280 ***** 11/18/2003 * *7800.07293 ***** ********** ********** ********** **********

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SpringDateMonth(nu)SeasonSeason_No.TempDeSnTempSCfpH T-AlkD-NO3NO2T-CaMgT-MgT-NaT-K Wekiva Springs 1/3/91 1Winter4 23.223.36733087.491101.543210.8*71.4 Wekiva Springs 7/9/91 7Summer224 23.84233237.351101.493610*61.4 Wekiva Springs 1/7/92 1Winter4 23.423.56733068.221061.753510.5*71.4 Wekiva Springs 7/7/92 7Summer223.7 23.54233117.451091.473310.310.281.3 Wekiva Springs 1/19/93 1Winter4 23.623.76733167.371131.473310.210.881.3 Wekiva Springs 5/19/93 5Spring123.723.72533017.57**3710*7.91.3 Wekiva Springs 7/20/93 7Summer224 23.84233197.751131.9125.69.97.654.671.3 Wekiva Springs 1/12/94 1Winter4 23.623.76733417.071131.45329.61081.3 Wekiva Springs 7/13/94 7Summer224.5 24.34233157.451131.49371010.681.9 Wekiva Springs 11/22/94 11Fall323.723.6837 3117.221101.813610.910.481.7 Wekiva Springs 1/9/95 1Winter4 23.323.46733217.73*23710.810.481.5 Wekiva Springs 3/22/95 3Spring123.523.52533247.34113*379.89.481.8 Wekiva Springs 4/19/95 4Spring123.723.72533347.291121.924010.9*81.7 Wekiva Springs 5/25/95 5Spring123.823.8253319***4010*8.71.5 Wekiva Springs 7/12/95 7Summer223.5 23.34233267.371141.6734*10.282 Wekiva Springs 9/22/95 9Fall324 23.9837309** ****** Wekiva Springs 11/2/95 11Fall323.523.4837327** ****** Wekiva Springs 11/15/95 11Fall323.523.4837 3127.051131.6337*10.691.6 Wekiva Springs 1/17/96 1Winter4 23.523.66733067.021111.737*10.291.7 Wekiva Springs 3/14/96 3Spring124.524.5253*** ****** Wekiva Springs 3/21/96 3Spring123.423.42533276.961101.738*10.891.7 Wekiva Springs 6/11/96 6Summer223.5 23.3423324** ****** Wekiva Springs 7/10/96 7Summer223.7 23.54233096.931101.6838*10.691.6 Wekiva Springs 9/4/96 9Fall32423.9837*** ****** Wekiva Springs 11/13/96 11Fall323.4523.4337 *7.221151.6136*10.591.5 Wekiva Springs 1/15/97 1Winter4 23.423.56733067.151151.4337*10.291.5 Wekiva Springs 3/12/97 3Spring123.723.72533137.211161.37432*1191.5 Wekiva Springs 4/21/97 4Spring123.423.4253319** ****** Wekiva Springs 7/22/97 7Summer223.7 23.54233207.33117.57571.20135*11.381.5 Wekiva Springs 11/11/97 11Fall323.6523.6337 3167.5119.89881.31936*10.298.61.8 Wekiva Springs 1/21/98 1Winter4 23.5823.7473*7.36119.1161.35135.99*10.048.591.736 Wekiva Springs 3/27/98 3Spring123.5623.5853*7.0391.2958*30.33*9.465.611.597 Wekiva Springs 7/15/98 7Summer223.93 23.7723*6.88113.1412*40.22*10.788.551.488 Wekiva Springs 11/16/98 11Fall323.6923.6737 3307.3118.20621.57938.62*11.0491.616 Wekiva Springs 1/14/99 1Winter4 23.6923.85733206.8116.17471.45439.15*11.799.371.298 Wekiva Springs 3/17/99 3Spring123.7123.73532907.52116.61951.33340.01*11.148.991.423 Wekiva Springs 5/19/99 5Spring123.823.8253333** ****** Wekiva Springs 7/14/99 7Summer223.75 23.59233307.33118.26071.26240.03*11.338.881.513 Wekiva Springs 8/10/99 8Summer2 23.623.44233307.6*1.3 ***** Wekiva Springs 11/16/99 11Fall323.6723.6537 3317.53117.0571.58240.4*11.318.971.342 Wekiva Springs 3/15/00 3Spring12323.02533297.48117.361.46139.91*11.8110.061.874 Wekiwa Springs 1/17/01 1Winter4 23.7423.90733267.42123.5860.94240.18513.3311.4189.191.566 Wekiwa Springs 2/26/01 2Winter4 23.6523.81733336.13122.512*38.51513.6811.4728.831.477 Wekiwa Springs 3/6/01 3Spring1 23.723.72533247.52122.8150.90639.89913.511.3279.321.54 Wekiwa Springs 5/15/01 5Spring1 23.8123.83533287.35123.0810.96338.42113.6111.1868.871.498 Wekiwa Springs 7/9/01 7Summer2 23.8923.73233237.58122.2640.80739.39313.2610.6758.651.518 Wekiwa Springs 9/17/01 9Fall3 24.0924.0737316120.3620.98939.22513.911.1758.631.461 Wekiwa Springs 11/13/01 11Fall3 23.623.58372987.56121.9940.96440.78413.3611.829.091.516 Wekiwa Springs 7/16/02 7Summer2 24.123.94233217.7122.0590.87139.81413.0411.0978.641.495 Wekiwa Springs 11/14/02 11Fall3 *3357.421261.34516119.11.5 Wekiwa Springs 1/23/03 1Winter4 23.723.86733417.451221.44116129.21.5 Wekiwa Springs 3/27/03 3Spring1 23.823.82533287.461231.34116119.81.6 Wekiwa Springs 6/25/03 6Summer2 24.123.94233307.771231.44016119.71.7 8/12/03 11/18/03

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DateT-SO4T-FT-SrTDST-PO4T-ClDischDateAllCFSallT-Cl cont. DischDateAllCFSall 1/3/91 170.155*179*12.001/3/9162.72 17.00 1/15/9768.99 7/9/91 180.14*161*10.003/6/9156.82 15.50 1/15/9769 1/7/92 160.13*176*13.004/29/9169.633/12/9765.4 7/7/92 170.14125171*12.005/22/91623/21/9764.3 1/19/93 210.14*166*14.007/9/9173.654/21/9765.1 5/19/93 170.1*182*13.009/3/9167.25/2/9762.1 7/20/93 170.16152**27.009/26/91745/20/9765.1 1/12/94 160.15102166*13.0011/11/9164.256/24/9761.8 7/13/94 160.14107183*12.001/7/9272.697/15/9762.8 11/22/94 180.131121710.11714.003/5/9270.028/14/9766.1 1/9/95 190.151191670.12315.005/14/9260.129/23/9765.2 3/22/95 180.12142169*17.005/19/925610/22/9760.3 4/19/95 190.13*1660.10814.007/7/9263.0411/20/9767.7 5/25/95 180.1*178*14.009/9/9276.933/25/9871.3 7/12/95 190.141241810.11613.009/25/92583/25/9871.3 9/22/95 ****** 11/3/9266.624/22/9872.5 11/2/95 ****** 1/19/9369.085/8/9867.8 11/15/95 140.151261840.12614.003/2/9374.266/29/9868.2 1/17/96 200.151191700.11614.005/18/9362.737/15/9838.6 3/14/96 ****** 5/19/9363.48/20/9871.7 3/21/96 190.141301800.12713.007/20/93669/23/9864.9 6/11/96 ****** 9/8/9367.210/14/9874.6 7/10/96 210.211291700.13714.009/23/9358.911/16/9869.66 9/4/96 ****** 11/8/9362.5312/11/9862.3 11/13/96 210.151291820.11514.001/12/9462.61/14/9975.09 1/15/97 210.161301730.11414.003/23/9459.52/2/9960.7 3/12/97 200.151321760.10714.005/4/9460.443/17/9971.34 4/21/97 18**** 13.005/25/9454.33/31/9956.7 7/22/97 18.1770.15921590.08813.447/13/9463.85/19/9965.1 11/11/97 18.1830.14135.41740.10312.999/21/9469.96/1/9956 1/21/98 19.740.16134.31860.11515.349/22/9467.87/14/9965.39 3/27/98 20.586*188.9136*8.1611/22/9480.77/23/9954.8 7/15/98 17.6840.1566121.2*0.12314.101/9/9587.89/16/9958.3 11/16/98 19.1020.15981331920.11613.223/22/9566.711/16/9966.4 1/14/99 19.6920.16171251820.1213.104/19/9577.411/16/9980.52 3/17/99 19.0620.1619141.31900.11614.085/25/9565.51/6/0064.9 5/19/99 ****** 7/12/9565.91/19/0081.4 7/14/99 19.70.1543140.71820.11213.809/22/9571.42/29/0068.4 8/10/99 ****** 11/2/9576.33/15/0071.8 11/16/99 18.4380.16139.5*0.10714.1211/15/9576.94/26/0054.8 3/15/00 19.0770.1603137.12030.10313.701/17/96826/15/0059.23 1/17/0118.2780.1564144.761840.08213.33 3/21/9680.27/27/0063.3 2/26/0119.1890.16147.3187*13.68 4/16/9688.8 3/6/0118.5590.1614147.991500.09413.50 5/7/9669.5 5/15/0119.270.1671144.481900.05913.61 5/8/9673 7/9/0118.0630.1619146.711970.08713.26 6/11/9670.2 9/17/0118.70.1686143.811770.0913.90 7/8/9668.6 11/13/0118.7790.1686153.87*0.09613.36 7/10/9667.6 7/16/0218.0710.1748145.662170.09813.04 8/14/9669 11/14/02190.21601880.1116.00 10/16/9675.4 1/23/03190.21401960.116.00 11/13/9667.7 3/27/03190.21401900.1116.00 11/20/9668.6 6/25/03200.21401880.1116.00 12/12/9677.6 8/12/03 11/18/03

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FK_STATI O PK_SAMP L COLLECTION_DATECOLLECTIMONTHSEASONSEASON_ N TempFe-DMn-DAlkDOFcolEntero 1417SJRQ91011/22/9115321 Winter4 22.2554033*1.2** 1417SJRQ910 4 4/9/9114344Spring123.26500**0.2** 1417SJRQ910 7 7/22/9113007 Summer222.83800 31.1180*** 1417SJRQ911 0 10/15/91145510Fall3235200*156*** 1417SJRQ92011/14/92830 1Winter4 22.75100*158*** 1417SJRQ920 4 4/7/928304Spring122.33900*161*** 1417SJRQ920 7 7/15/928467 Summer222.44100 *157*** 1417SJRQ921 0 10/13/9283010Fall322.33600*150*** 1417SJRQ93011/13/931223 1Winter4 22.94300*150*** 1417SJRQ930 4 4/14/938384Spring122.24100*150*** 1417SJRQ930 7 7/13/9313447 Summer222.72800 *150*** 1417SJRB9309 9/1/9313459Fall322.8330027150*** 1417SJRQ931 0 10/12/9382710Fall322.43700*150*** 1417SJRQ94011/11/941426 1Winter4 22.64300*180*** 1417SJRQ940 4 4/12/9415374Spring122.74800*170*** 1417SJRQ940 7 7/12/9414327 Summer223.24000 *160*** 1417SJRQ941 0 10/12/94140010Fall322.94000*150*** 1417SJRB9609 9/9/9613489Fall323.34740341700.2** 1417SJRB9909 9/22/9913129Fall323.65260*1780.24** 1417CEDM000 2 2/24/0017322 Winter4 23.06***0.09** 1417CEDM000 3 3/15/0012113Spring123.21***0.21** 1417CEDM000 4 4/25/0014164Spring123.06***0.06** 1417CEDM000 5 5/23/0015015Spring122.95***0.26** 1417CEDM000 6 6/27/0012256 Summer222.65***0.02** 1417CEDM000 7 7/25/0018117 Summer222.56***0.03** 1417CEDM000 8 8/29/0011588 Summer222.89***0.04** 1417CEDM000 9 9/26/0011509Fall323.38***0.34** 1417CEDM001 0 10/20/00101210Fall323.1***0.4** 1417CEDM001 0 10/24/00120010Fall322.87***0.23** 1417SJRM001111/28/0095011Fall322.85***0.41** 1417SJRM001 2 12/19/00103012 Winter4 23.11***0.66** 1417SJRM01011/30/019501 Winter4 23.25***0.34** 1417SJRM010 2 2/28/0114462 Winter4 23.67***0.6** 1417SJRM010 3 3/27/019143Spring123.08***0.72** 1417SJRM010 4 4/26/0110464Spring122.91***0.69** 1417SJRM010 6 5/28/0111075Spring122.71***0.12** 1417SJRM010 5 5/31/019225Spring123.21***0.11** 1417SJRM010 7 7/26/019157 Summer222.73***0.13** 1417SJRM010 8 8/28/0110418 Summer223***0.13** 1417SJRM010 9 9/24/0120299Fall323.08***0.2** 1417SJRM011 0 10/24/0195610Fall323.14***0.18** 1417SJRM011111/26/01181611Fall323.1***0.19** 1417SJRM011 2 12/19/01190412 Winter4 22.9***0.18** 1417SJRM02011/30/0211201 Winter4 23.56***0.54** 1417SJRM020 2 2/18/0218252 Winter4 22.82***0.25** 1417SJRM020 3 3/19/029383Spring123.08***0.28** 1417SJRM020 4 4/24/0216164Spring123.11***0.21** 1417SJRM020 5 5/20/0217405Spring122.98***0.23**

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COLLECTION_DATEpHTSSNH3NO3-DNO3-TNO3NO2Po-PO4TOCTDSTurbColorTurb-FCa 1/22/916.86 **** 0.053*0.3412*120**80.4 4/9/917.03 **** 0.39 *******75 7/22/917.05*0.776**0.02*0.08826255***72 10/15/917.25 **** 0.02 *******65 1/14/927.25 **** 0.02 *******68 4/7/927.24 **** 0.04 *******64 7/15/927.24 **** 0.06 *******63 10/13/927.14 **** 0.02 *******65 1/13/937.27 **** 0.02 *******59 4/14/937.14 **** 0.02 *******61 7/13/937.13 **** 0.04 *******53 9/1/937.24*0.3**0.020.18***81**59 10/12/937.31 **** 0.02 *******60 1/11/947.2 **** 0.02 *******71 4/12/947.06 **** 0.02 *******69 7/12/947.21 **** 0.02 *******64 10/12/947.13 **** 0.02 *******58 9/9/966.52*0.34**0.0190.260.196.5*27**66.1 9/22/997.21*0.37**0.0080.30.276.6*31250*70.1 2/24/007.22 ************* 3/15/007.21 ************* 4/25/007.38 ************* 5/23/007.09 ************* 6/27/006.87 ************* 7/25/007.4 ************* 8/29/006.47 ************* 9/26/005.7 ************* 10/20/007.09 ************* 10/24/007.31 ************* 11/28/007.32 ************* 12/19/007.44 ************* 1/30/017.29 ************* 2/28/017.22 ************* 3/27/017.47 ************* 4/26/017.29 ************* 5/28/017.21 ************* 5/31/017.29 ************* 7/26/017.21 ************* 8/28/016.95 ************* 9/24/017.06 ************* 10/24/017.03 ************* 11/26/017.08 ************* 12/19/017.09 ************* 1/30/027.15 ************* 2/18/027.24 ************* 3/19/027.19 *********** 13.5* 4/24/027.17 *********** 1.44* 5/20/027.2 *********** 0.56*

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COLLECTION_DATEMgNaKSC-FCl SO4FSampDate DtoH2O WL(MSL) MPElev WLWell 1/22/911.49.30.842917150.341/22/9115.82.4618.261417 4/9/911.49.11462145.60.24/9/9115.13.16 7/22/911.38.71.1419142.40.17/22/9111.86.46 10/15/911.18.31388163.40.110/15/9110.617.65 1/14/921.18.71397193.80.11/14/9212.136.13 4/7/921.191392183.70.14/7/9213.125.14 7/15/921.19.11389184.20.17/15/9213.514.75 10/13/9218.81362164.50.110/13/9211.336.93 1/13/930.928.80.72364155.10.11/13/9311.766.5 4/14/9319.30.71370155.20.14/14/9311.267 7/13/930.84100.66363154.80.17/13/9313.534.73 9/1/930.939.50.73378144.30.19/1/9313.694.57 10/12/930.959.20.72358144.20.110/12/9312.865.4 1/11/941.28.80.8403132.90.11/11/9413.34.96 4/12/941.29.20.76403132.90.14/12/9413.724.54 7/12/9418.80.76369154.70.17/12/9412.585.68 10/12/940.9690.68354144.80.110/12/949.818.45 9/9/961.119.020.7383143.20.19/9/9610.757.51 9/22/991.28.50.7318113.10.19/22/9912.725.54 2/24/00***369***2/24/0017.320.94 3/15/00***386***3/15/0013.125.14 4/25/00***376***4/25/0013.934.33 5/23/00***367***5/23/0014.93.36 6/27/00***362***6/27/0015.72.56 7/25/00***359***7/25/0015.32.96 8/29/00***350***8/29/0015.23.06 9/26/00***361***9/26/0014.73.56 10/20/00***404***10/20/00117.26 10/24/00***367***10/24/0014.73.56 11/28/00***368***11/28/0015.32.96 12/19/00***384***12/19/0015.82.46 1/30/01***345***1/30/0115.82.46 2/28/01***334***2/28/0116.12.16 3/27/01***333***3/27/0116.22.06 4/26/01***379***4/26/0116.31.96 5/28/01***382***5/28/0116.22.06 5/31/01***368***5/31/0116.61.66 7/26/01***396***7/26/0115.13.16 8/28/01***395***8/28/0114.24.06 9/24/01***460***9/24/0112.75.56 10/24/01***450***10/24/0112.65.66 11/26/01***380***11/26/0112.75.56 12/19/01***418***12/19/01135.26 1/30/02***384***1/30/0213.34.96 2/18/02***391***2/18/0213.64.66 3/19/02***382***3/19/0218.260 4/24/02***349***4/24/0214.433.83 5/20/02***341***5/20/0215.253.01

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FK_STATI O PK_SAMP L COLLECTION_DATECOLLECTIMONTHSEASONSEASON_ N TempFe-DMn-DAlkDOFcolEntero 1417SJRM020 6 6/25/0220036 Summer223.13***0.14** 1417SJRM020 7 7/23/0214017 Summer223.16***0.44** 1417SJRM020 8 8/19/0216078 Summer223.2***0.39** 1417SJRM020 9 9/23/0216369Fall323.41***0.27** 1417SJRM021 0 10/22/02163510Fall323.61**1390.3211 1417SJRM021111/18/0211Fall322.89**1400.2311 1417SJRM021 2 12/17/0212 Winter4 23.22**1370.3311 1417SJRM03011/28/0320151 Winter4 23.11**1380.2911 1417SJRM030 2 2/17/0317252 Winter4 23.32**1390.2511 1417SJRM030 3 3/26/039203Spring123.77**1351.3911 1417SJRM030 4 4/22/039454Spring123.2**1380.3211 1417SJRM030 5 5/27/0318225Spring123.65**1370.311 1417SJRM030 6 6/24/0310146 Summer223.49** 1370.3611

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COLLECTION_DATEpHTSSNH3NO3-DNO3-TNO3NO2Po-PO4TOCTDSTurbColorTurb-FCa 6/25/027.16 *********** 0.66* 7/23/027.12 ***********1.1* 8/19/027.23 ************* 9/23/027.23 *********** 0.82* 10/22/027.2280.18**0.0040.240.234.7178141000.8953.2 11/18/027.460.17**0.0160.240.234.617415800.9256.3 12/17/027.490.16**0.0110.230.224.420013801.9157.8 1/28/037.3760.18**0.0060.240.224195201003.3455.7 2/17/037.3870.16**0.0160.220.214.7199171001.7455.8 3/26/037.340.16**0.0090.170.184.618816804.7356 4/22/037.0440.17**0.0040.20.194.7193151002.3457.4 5/27/036.9340.16**0.010.210.23.9185151000.756.4 6/24/036.5940.18**0.0180.20.24.4197161000.6655.8

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COLLECTION_DATEMgNaKSC-FCl SO4FSampDate DtoH2O WL(MSL) MPElev WLWell 6/25/02***335***6/25/024.2913.97 7/23/02***322***7/23/0212.226.04 8/19/02***309***8/19/02117.26 9/23/02***302***9/23/0210.258.01 10/22/020.87.60.64324125.70.08410/22/0211.956.31 11/18/020.867.80.64326135.60.07511/18/0211.27.06 12/17/020.878.10.66311145.70.06912/17/0210.47.86 1/28/030.8780.63334145.70.11/28/0310.28.06 2/17/030.867.90.63336155.80.122/17/0310.28.06 3/26/030.857.80.62340155.60.0833/26/039.98.36 4/22/030.97.830.63345165.50.084/22/0310.77.56 5/27/030.867.70.59342165.70.0795/27/0311.486.78 6/24/030.867.680.59336175.70.0826/24/0310.87.46

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FK_STATI O PK_SAMP L COLLECTION_DATECOLLECTIMONTHSEASONSEASON_NO. TempFe-D Mn-DAlkDOFcol 1420SJRQ91011/22/9115001 Winter4 21.699*** 1420SJRQ910 4 4/9/9114004Spring122.650 **** 1420SJRQ910 7 8/5/9110208 Summer223.9 4512.9115** 1420SJRQ911 0 10/15/91141210Fall322.510*119** 1420SJRQ92011/14/92940 1Winter42210*120** 1420SJRQ920 4 4/7/929524Spring122.120*121** 1420SJRQ920 7 7/15/9210277 Summer223.3 5*120** 1420SJRQ921 0 10/13/9294710Fall322.45*121** 1420SJRQ93011/13/931317 1Winter4 22.43*120** 1420SJRQ930 4 4/14/939314Spring122.125*120** 1420SJRQ930 7 7/13/9316457 Summer2233*120** 1420SJRB9309 9/1/9314439Fall324.4511120** 1420SJRQ931 0 10/12/9392810Fall322.413*120** 1420SJRQ94011/11/941515 1Winter4 22.134*120** 1420SJRQ940 4 4/12/9416234Spring122.46*120** 1420SJRQ940 7 7/12/9415207 Summer224.2 3*120** 1420SJRQ941 0 10/12/94144510Fall322.87*121** 1420SJRB9609 9/9/9614469Fall324.48121240.17* 1420SJRB9908 8/3/999568 Summer225.47* 1170.09* 1420CEDM000 2 2/24/0019142 Winter4 22.78***0.04* 1420CEDM000 3 3/15/0011103Spring122.8***0.12* 1420CEDM000 4 4/25/0014574Spring122.88***0* 1420CEDM000 5 5/23/0016375Spring122.99***0* 1420CEDM000 7 7/25/0017337 Summer222.85***0* 1420CEDM001 0 10/20/00110510Fall323***0.08* 1420CEDM001 0 10/24/00111910Fall322.93***0.21* 1420SJRM01011/30/011024 1Winter4 22.26***0.34* 1420SJRM010 4 4/26/0111434Spring122.36***0.43* 1420SJRM010 7 7/26/0110457 Summer222.54 ***0.06* 1420SJRM011 0 10/24/01115110Fall322.52***0.15* 1420SJRM02011/30/021216 1Winter4 22.5***0.42* 1420SJRM020 4 4/24/0217314Spring122.51***0.07* 1420SJRM020 7 7/23/0215377 Summer222.99 ***0.15* 1420SJRM021 0 10/22/02180510Fall322.53**1260.121 1420SJRM03011/28/031910 1Winter4 22.8**1240.191 1420SJRM030 4 4/22/0310504Spring122.46**1250.141

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COLLECTION_DATEEnteropHTSSNH3NO3-DNO3-TNO3NO2Po-PO4TOCTDSDtoH2O 1/22/91*7.39 **** 0.02*0.164*3.47 4/9/91*7.56 **** 0.05 **** 2.73 8/5/91*7.55*0.503**0.02**6.151960* 10/15/91*7.59 **** 0.02 ***** 1/14/92*7.62 **** 0.02 **** 4.22 4/7/92*7.71 **** 0.03 **** 5.02 7/15/92*7.67 **** 0.02 ****5.1 10/13/92*7.55 **** 0.02 **** 2.88 1/13/93*7.69 **** 0.02 **** 2.37 4/14/93*7.52 **** 0.02 **** 2.27 7/13/93*7.51 **** 0.02 **** 4.52 9/1/93*7.59*0.31**0.10.14***4.59 10/12/93*7.68 **** 0.02 **** 3.61 1/11/94*7.6 **** 0.02 **** 3.88 4/12/94*7.56 **** 0.02 ****4.7 7/12/94*7.65 **** 0.04 **** 3.44 10/12/94*7.51 **** 0.02 **** 0.98 9/9/96*7.56*0.29**0.0210.120.122*2.6 8/3/99*7.78*0.25**0.0120.120.123*5.58 2/24/00*7.57 ********* 4.63 3/15/00*7.59 ********* 6.84 4/25/00*7.5 ********* 6.38 5/23/00*7.53 *********8 7/25/00*7.48 ********* 7.13 10/20/00*7.58 ********* 3.09 10/24/00*7.57 ********* 5.94 1/30/01*7.5 ********* 7.29 4/26/01*7.5 ********* 7.71 7/26/01*7.54 ********* 4.76 10/24/01*7.4 ********* 3.54 1/30/02*7.51 ********* 4.45 4/24/02*7.48 ********* 6.05 7/23/02*7.21 ********* 4.02 10/22/0217.4740.3**0.0040.120.142.422303.33 1/28/0317.5340.3**0.0040.120.121.622502.56 4/22/0317.4440.31**0.0040.120.132.521403.05

PAGE 316

COLLECTION_DATEWL(MSL)TurbColorTurb-FCaMg NaKSC-FClSO4F 1/22/9118.010.5**87.173.369621.2413014001600.37 4/9/9118.75***817064021417011005.60.2 8/5/91 ****8062550 21.2367010601600.1 10/15/91 ****867065024 419012001800.2 1/14/9217.26***8974640240420012001800.1 4/7/9216.46***82686502542201400360.2 7/15/9216.38***867265024426012001800.1 10/13/9218.6***927465024409012001800.2 1/13/9319.11***807065022418011501800.2 4/14/9319.21***867265022424011801800.1 7/13/9316.96***867165022413012001800.1 9/1/9316.891.1**827066023426011901900.1 10/12/9317.87***827155022427011601800.2 1/11/9417.6***887164023418011501800.1 4/12/9416.78***907568024428012001800.2 7/12/9418.04***877368023420011901800.2 10/12/9420.5***806865023421012001900.2 9/9/9618.880.2**85.872.365821.7421011001800.18 8/3/9915.9215*88.473.364220.9402812001900.16 2/24/0016.85 ******* 4066*** 3/15/0014.64 ******* 4227*** 4/25/0015.1 ******* 4174*** 5/23/0013.48 ******* 4129*** 7/25/0014.35 ******* 4137*** 10/20/0018.39 ******* 4104*** 10/24/0015.54 ******* 4171*** 1/30/0114.19 ******* 4229*** 4/26/0113.77 ******* 4266*** 7/26/0116.72 ******* 4233*** 10/24/0117.94 ******* 4138*** 1/30/0217.03 ******* 4146*** 4/24/0215.43**0 **** 4157*** 7/23/0217.46 ******* 4094*** 10/22/0218.150.0550.2287.371.665921.2416312001800.18 1/28/0318.920.0550.2488.875.168522418012001800.17 4/22/0318.430.150.4889.175.466321.7405312001700.17

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DateSEASON_ N TempDeSnTempFe-DMn-DAlkDOFcolEnteropHDeSnpHTSSNH3 1/15/91422.722.912551 **** 5.985.87586** 2/20/91422.823.0125 ****** 6.276.16586** 3/18/91122.922.81931 **** 6.196.18657*0.03 4/16/91122.922.81950 ***** 6.186.17657** 5/28/91122.822.719 ****** 5.875.86657** 6/5/91222.822.6912 ****** 5.956.02902** 7/11/91222.922.791210*42***5.885.95902** 8/26/9122322.8912 ****** 6.236.30902** 9/11/9132323.0079 ****** 6.166.1708** 10/28/91322.922.907910*34***6.246.2508** 11/19/91322.922.9079***2.3**6.266.2708** 12/11/91422.923.1125***3.2**6.336.22586** 1/14/92422.823.012510*353**6.46.29586** 1/14/924**10*35 ******* 2/19/92422.923.1125***3.4**6.366.25586** 3/16/9212322.919***3.3**6.236.22657** 4/20/92123.123.01910*342.8**6.226.21657** 5/12/9212322.919***2.6**6.116.10657** 6/9/92223.122.9912***2.9**6.196.26902** 7/13/92223.122.99128*333.2**6.066.13902** 8/20/9222322.8912***2.6**6.196.26902** 9/22/92323.123.1079***2.8**6.16.1108** 10/19/92322.922.907919*332.4**6.086.0908** 11/18/92322.922.9079***2.7**6.16.1108** 12/22/92422.923.1125***2.7**6.266.15586** 1/11/93422.823.0125***2.7**6.566.45586** 1/12/934**18*34 ******* 2/18/93422.823.0125***2.6**6.286.17586** 3/17/93122.822.719***2.8**6.246.23657** 4/13/93122.922.81910*322.8**6.16.09657** 5/24/9312322.919***2.8**6.186.17657** 6/22/9322322.8912***2.8**6.166.23902** 7/27/9322322.89128*332.7**6.086.15902** 8/25/93222.922.7912***2.8**6.126.19902** 9/20/93322.922.9079***2.9**6.216.2208** 10/21/93322.822.807917*322.6**6.156.1608** 11/9/93322.622.6079***2.3**66.0108** 12/15/934** ********** 1/11/944** ********** 2/7/94422.622.8125***2.9**6.196.08586** 3/9/94122.822.719***2.9**5.915.90657** 4/13/94122.822.71914*332.9**5.935.92657** 5/5/94122.822.719***2.8**5.795.78657** 6/16/94222.922.7912***2.9**5.865.93902** 7/14/94222.922.791226*322.6**5.875.94902**

PAGE 318

DateNO3-DNO3-TNO3NO2Po-PO4TOC DeSnTOCTDSDtoH2O WL(MSL) TurbColorTurb-F 1/15/91**0.44*1.912.03077*14.5688.640.34** 2/20/91 ********12.449 0.76*** 3/18/91**0.47**11.98077928.8494.362.2** 4/16/91**0.45 ***** 7.1596.05*** 5/28/91 ******** 9.0494.16*** 6/5/91 ********6.5 96.7*** 7/11/91**0.44 ***** 7.7795.43*** 8/26/91 ******** 4.9598.25*** 9/11/91 ******** 6.5596.65*** 10/28/91**0.43 ***** 8.5894.62*** 11/19/91 ******** 9.5593.65*** 12/11/91 ********10.139 3.07*** 1/14/92**0.42 *****10.959 2.25*** 1/14/92**0.43 ********** 2/19/92 ******** 9.1194.09*** 3/16/92 ******** 7.2595.95*** 4/20/92**0.44 ***** 9.1294.08*** 5/12/92 ********10 93.2*** 6/9/92 ********10.339 2.87*** 7/13/92**0.44 ***** 9.4393.77*** 8/20/92 ******** 9.8593.35*** 9/22/92 ******** 9.3893.82*** 10/19/92**0.47 ***** 7.2595.95*** 11/18/92 ******** 8.9694.24*** 12/22/92 ******** 9.6293.58*** 1/11/93 ********9.4 93.8*** 1/12/93**0.45 ********** 2/18/93 ******** 7.7195.49*** 3/17/93 ******** 5.6297.58*** 4/13/93**0.43 ***** 6.2696.94*** 5/24/93 ******** 9.3493.86*** 6/22/93 ********10.659 2.55*** 7/27/93**0.42 ***** 11.491.8*** 8/25/93 ********12.639 0.57*** 9/20/93 ********12.559 0.65*** 10/21/93**0.41 *****14.068 9.14*** 11/9/93 ********10.089 3.12*** 12/15/93 ********10.939 2.27*** 1/11/94 ********9.1 94.1*** 2/7/94 ******** 5.7897.42*** 3/9/94 ******** 7.0796.13*** 4/13/94**0.8 ***** 8.7794.43*** 5/5/94 ******** 9.6793.53*** 6/16/94 ********10.099 3.11*** 7/14/94**0.52 *****5.6 97.6***

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DateD-CaD-MgD-NaD-KSC-FClDeSnClSO4F 1/15/9112.43.43.10.6101***1.1 2/20/91 ****106**** 3/18/9112.13.43.10.61014.55.1962751.9 4/16/91103.23.4110211.69627110.96 5/28/91 ****97**** 6/5/91 ****102**** 7/11/91123.33.20.81025.45.122460.60.9 8/26/91 ****99**** 9/11/91 ****98**** 10/28/91113.33.10.91025.85.389130.60.9 11/19/91 ****101**** 12/11/91 ****101**** 1/14/92113.23.20.91015.65.414130.60.9 1/14/92113.23.20.9*5.65.414130.60.9 2/19/92 ****102**** 3/16/92 ****100**** 4/20/921343.20.9915.46.096270.61 5/12/92 ****99**** 6/9/92 ****101**** 7/13/92103.530.9885.55.222460.60.9 8/20/92 ****100**** 9/22/92 ****101**** 10/19/929.93.33.40.9955.95.489130.60.9 11/18/92 ****101**** 12/22/92 ****100**** 1/11/93 ****90**** 1/12/939.933.20.58*5.25.014130.61 2/18/93 ****100**** 3/17/93 ****98**** 4/13/939.93.33.20.69655.696270.61 5/24/93 ****100**** 6/22/93 ****99**** 7/27/939.93.33.10.6904.64.322460.61 8/25/93 ****101**** 9/20/93 ****110**** 10/21/93103.43.10.54985.44.989130.60.9 11/9/93 ****92**** 12/15/93 ********* 1/11/94 ********* 2/7/94 ****96**** 3/9/94 ****101**** 4/13/94113.53.10.58995.15.796270.61 5/5/94 ****98**** 6/16/94 ****98**** 7/14/949.93.33.10.59965.45.122460.61

PAGE 320

DateSEASON_ N TempDeSnTempFe-DMn-DAlkDOFcolEnteropHDeSnpHTSSNH3 8/18/94222.822.6912***2.9**5.725.79902** 9/21/94322.422.4079***2.7**5.645.6508** 10/19/94322.722.70798*332.7**5.985.9908** 11/3/94322.922.9079***3**5.985.9908** 1/24/954** ********** 2/14/95422.823.0125***3**6.15.99586** 3/21/95122.922.819***3.2**5.985.97657** 4/11/95122.922.819***3**6.016.00657** 5/9/95122.922.819***3.3**5.965.95657** 6/14/95222.922.7912***3**5.976.04902** 7/11/9522322.8912***3**6.056.12902** 8/14/95223.122.9912***2.8**5.775.84902** 9/26/95322.922.9079***3**6.086.0908** 11/6/95322.722.7079***3**6.096.1008** 1/31/964** ********** 2/19/964** ********** 3/19/961** ********** 4/24/961** ********** 5/20/961** ********** 6/25/9622322.8912***3.3**6.066.13902** 8/19/96221.721.5912***4.6**5.455.52902** 9/26/96322.922.9079***3.2**6.116.1208** 10/14/96322.922.9079***3.3**6.016.0208** 11/4/96322.822.8079***3.2**6.296.3008** 12/12/96422.923.1125***3.2**6.176.06586** 1/16/97422.823.0125***3.2**7.487.37586** 2/12/97422.823.0125***3.3**6.15.99586** 3/10/97122.922.819***3.4**6.26.19657** 4/21/97122.822.7194229.93.4**6.126.11657*0.01 5/13/97122.822.719***3.1**6.096.08657** 6/17/97222.922.7912***3.4**5.95.97902** 7/16/97222.922.7912***3.6**5.755.82902** 8/4/97222.922.7912***3.4**5.795.86902** 9/8/97322.822.8079***3.6**5.395.4008** 10/29/97322.722.7079***3.1**5.695.7008** 11/25/97322.722.7079***2.8**5.945.9508** 12/17/97422.722.9125***3**5.995.88586** 1/28/98422.823.0125***3.5**6.015.90586** 2/18/98422.823.0125***3.1**5.995.88586** 3/23/98122.822.719***3.4**5.945.93657** 5/27/98122.9222.839***3.68**6.276.26657** 6/23/98222.9922.8812***3.67**6.266.33902** 7/28/98222.9222.8112***3.76**6.286.35902** 8/17/98222.9322.8212***3.56**6.246.31902**

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DateNO3-DNO3-TNO3NO2Po-PO4TOC DeSnTOCTDSDtoH2O WL(MSL) TurbColorTurb-F 8/18/94 ******** 5.8597.35*** 9/21/94 ******** 4.4298.78*** 10/19/94**0.72 ***** 5.2897.92*** 11/3/94 ******** 5.8997.31*** 1/24/95 ******** 7.0696.14*** 2/14/95 ******** 7.4195.79*** 3/21/95 ******** 4.9598.25*** 4/11/95 ******** 5.0298.18*** 5/9/95 ******** 7.1196.09*** 6/14/95 ******** 6.0397.17*** 7/11/95 ******** 6.5396.67*** 8/14/95 ******** 6.8296.38*** 9/26/95 ******** 6.9296.28*** 11/6/95 ********7.6 95.6*** 1/31/96 ******** 8.5594.65*** 2/19/96 ******** 9.0794.13*** 3/19/96 ******** 6.1797.03*** 4/24/96 ******** 7.0196.19*** 5/20/96 ******** 8.5994.61*** 6/25/96 ********10.519 2.69*** 8/19/96 ********14.038 9.17*** 9/26/96 ********10.189 3.02*** 10/14/96 ******** 7.3995.81*** 11/4/96 ******** 9.8893.32*** 12/12/96 ******** 8.8494.36*** 1/16/97 ******** 8.5894.62*** 2/12/97 ******** 9.0794.13*** 3/10/97 ******** 9.6493.56*** 4/21/97**0.441.61.611.98077*10.7292.480.06*0.4 5/13/97 ******** 8.8694.34**0.47 6/17/97 ******** 9.9193.29**0.41 7/16/97 ********10.779 2.43**0.16 8/4/97 ********10.919 2.29**0.19 9/8/97 ******** 11.691.6**0.67 10/29/97 ******** 11.791.5**0.43 11/25/97 ******** 7.4995.71**0.76 12/17/97 ******** 4.5598.65**0.51 1/28/98 ******** 4.9898.22**0.45 2/18/98 ******** 2.88100.32**0.52 3/23/98 ********3.4 99.8**0.54 5/27/98 ******** 8.5294.68**0.29 6/23/98 ******** 8.1895.02**0.27 7/28/98 ******** 5.8197.39**1.35 8/17/98 ******** 5.5197.69**0.56

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DateD-CaD-MgD-NaD-KSC-FClDeSnClSO4F 8/18/94 ****98**** 9/21/94 ****76**** 10/19/94103.43.20.57935.44.989130.60.9 11/3/94 ****86**** 1/24/95 ********* 2/14/95 ****98**** 3/21/95 ****93**** 4/11/95 ****95**** 5/9/95 ****94**** 6/14/95 ****94**** 7/11/95 ****96**** 8/14/95 ****93**** 9/26/95 ****97**** 11/6/95 ****96**** 1/31/96 ********* 2/19/96 ********* 3/19/96 ********* 4/24/96 ********* 5/20/96 ********* 6/25/96 ****99**** 8/19/96 ****78**** 9/26/96 ****94**** 10/14/96 ****97**** 11/4/96 ****96**** 12/12/96 ****95**** 1/16/97 ****83**** 2/12/97 ****82**** 3/10/97 ****97**** 4/21/979.933.283.020.51964.85.496270.720.98 5/13/97 ****95**** 6/17/97 ****89**** 7/16/97 ****96**** 8/4/97 ****96**** 9/8/97 ****94**** 10/29/97 ****97**** 11/25/97 ****95**** 12/17/97 ****94**** 1/28/98 ****96**** 2/18/98 ****93**** 3/23/98 ****95**** 5/27/98 ****91**** 6/23/98 ****93**** 7/28/98 ****89**** 8/17/98 ****89****

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DateSEASON_ N TempDeSnTempFe-DMn-DAlkDOFcolEnteropHDeSnpHTSSNH3 9/3/98322.8722.8779***3.31**6.276.2808** 10/20/98322.8622.8679***3.82**6.316.3208** 11/24/98322.7822.7879***3.79**6.286.2908** 12/22/98422.7923.0025***3.86**6.286.17586** 1/20/99422.823.0125***3.63**6.216.10586** 2/23/99422.8323.0425***3.56**6.226.11586** 3/25/99122.8322.749***3.93**6.376.36657** 4/27/99122.9522.869***3.65**6.126.11657** 5/24/99122.9922.909***3.62**6.276.26657** 5/24/99122.9922.909***3.62**6.276.26657** 6/23/99223.0422.9312***3.74**6.136.20902** 7/27/99223.0122.9012***3.68**6.226.29902** 8/23/99222.9922.8812***3.71**6.256.32902** 9/13/99322.9922.9979***3.73**6.156.1608** 10/27/99322.8922.8979**303.44116.156.160840.01 11/23/99322.8822.8879***3.95**6.096.1008** 12/20/99422.825623.0381***3.59**6.146.03586** 1/25/00422.7822.9925**323.73116.36.1958640.01 2/15/00422.8723.0825***3.74**6.266.15586** 3/13/00122.8222.739***3.66**6.276.26657** 4/27/00122.9122.829**303.61116.36.2965740.016 5/30/00122.8222.739***3.59**6.296.28657** 6/26/00222.9722.8612***3.64**6.216.28902** 7/24/00223.0322.9212**273.711206.136.2090240.013 8/31/00222.9122.8012***3.57**6.096.16902** 9/26/00322.9122.9179***3.72**6.096.1008** 10/26/00322.922.9079***3.57**6.246.2508** 11/20/00322.2922.2979***3.61**6.226.2308** 12/21/00418.1518.3625***3.16**6.236.12586** 1/25/01421.9122.1225***3.02**6.236.12586** 4/30/01122.7922.709***3.59**6.096.08657** 7/31/01222.8722.7612***2.67**6.096.16902** 10/26/01322.8322.8379***6.97**6.376.3808** 1/29/02422.6222.8325***3.58**6.236.12586** 4/25/02122.8822.799***3.51**6.036.02657** 7/31/02222.8822.7712***4.02**6.16.17902** 10/31/02322.7422.7479***3.02**6.216.2208** 1/30/03422.4222.6325***3.89**5.255.14586** 2/26/034** ********** 3/27/031** ********** 4/30/03123.0622.979***3.42**6.166.15657**

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DateNO3-DNO3-TNO3NO2Po-PO4TOC DeSnTOCTDSDtoH2O WL(MSL) TurbColorTurb-F 9/3/98 ******** 5.7997.41**0.7 10/20/98 ******** 6.1297.08**0.75 11/24/98 ******** 8.1995.01**0.3 12/22/98 ******** 9.3693.84**0.32 1/20/99 ******** 9.4893.72**0.4 2/23/99 ******** 7.8795.33**0.42 3/25/99 ******** 8.5894.62**1.19 4/27/99 ********10.149 3.06**0.37 5/24/99 ********10.659 2.55**0.42 5/24/99 ********10.659 2.55**0.4 6/23/99 ********10.359 2.85**0.69 7/27/99 ******** 8.8294.38**0.54 8/23/99 ******** 7.6895.52**0.4 9/13/99 ******** 8.6394.57**0.59 10/27/99**0.471.71.51.1-1.16923887.4595.753.2200.24 11/23/99 ********8.9 94.3**0.35 12/20/99 ******** 9.4893.72**1.2 1/25/00**0.41.71.612.030777310.2192.990.1550.26 2/15/00 ********10.029 3.18**0.65 3/13/00 ********10.649 2.56**0.77 4/27/00**0.491.81.611.980778911.8391.371.750.3977 5/30/00 ********12.759 0.45**0.67 6/26/00 ******** 12.191.1*** 7/24/00**0.441.71.712.030775610.1993.011.2200.63 8/31/00 ******** 9.0494.16**0.44 9/26/00 ******** 5.5397.67**0.47 10/26/00 ******** 8.2694.94**0.45 11/20/00 ******** 9.8593.35**0.51 12/21/00 ******** 10.492.8**0.86 1/25/01 ********11 92.2*** 4/30/01 ******** 10.792.5*** 7/31/01 ******** 7.0496.16**2.17 10/26/01 ********10.929 2.28**0.37 1/29/02 ********10.679 2.53**2.3 4/25/02 ********12.539 0.67**3.65 7/31/02 ******** 7.2595.95**1.25 10/31/02 ******** 8.3294.88**0.48 1/30/03 ********7.4 95.8**3.01 2/26/03 ******** 5.7897.42*** 3/27/03 ******** 5.7597.45*** 4/30/03 ******** 7.4495.76**5.31

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DateD-CaD-MgD-NaD-KSC-FClDeSnClSO4F 9/3/98 ****90**** 10/20/98 ****94**** 11/24/98 ****95**** 12/22/98 ****95**** 1/20/99 ****93**** 2/23/99 ****93**** 3/25/99 ****94**** 4/27/99 ****90**** 5/24/99 ****91**** 5/24/99 ****91**** 6/23/99 ****86**** 7/27/99 ********* 8/23/99 ****88**** 9/13/99 ****88**** 10/27/999.83.43.20.56875.34.889130.551.1 11/23/99 ****92**** 12/20/99 ****830**** 1/25/009.933.363.090.573914.94.714130.680.94 2/15/00 ****94**** 3/13/00 ****86**** 4/27/009.53.33.30.59935.35.996270.560.98 5/30/00 ****88**** 6/26/00 ****87**** 7/24/009.43.42.90.55895.65.322460.540.94 8/31/00 ****90**** 9/26/00 ****88**** 10/26/00 ****83**** 11/20/00 ****84**** 12/21/00 ****69**** 1/25/01 ****77**** 4/30/01 ****84**** 7/31/01 ****84**** 10/26/01 ****89**** 1/29/02 ****80**** 4/25/02 ****83**** 7/31/02 ****87**** 10/31/02 ****76**** 1/30/03 ****79**** 2/26/03 ********* 3/27/03 ********* 4/30/03 ****80****

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FK_STATI O PK_SAMP L COLLECTION_DAT E COLLECT I MONTHSEASON SEASON_ N TempFe-DMn-DAlkDOFcolEntero 1762SJRQ91011/14/9116121 Winter4 24.171 **** 1762SJRQ910 4 3/1/9117093Spring1*50 ***** 1762SJRQ910 4 4/1/9117094Spring124.7 ****** 1762SJRQ910 7 7/8/9118147 Summer224.810*133*** 1762SJRQ911 0 10/7/91181010Fall324.410*130*** 1762SJRB9112 12/11/91140012 Winter4 24.910*133*** 1762SJRQ92011/9/9213181 Winter4 24.610*131*** 1762SJRQ920 4 4/15/9212454Spring124.65*133*** 1762SJRQ920 7 7/8/9213557 Summer225.15*134*** 1762SJRQ921 0 10/7/92125510Fall324.75*133*** 1762SJRQ93011/7/9312331 Winter4 24.87*140*** 1762SJRQ930 4 4/6/9312524Spring1243*130*** 1762SJRQ930 7 7/8/9312457 Summer224.93*130*** 1762SJRQ931 0 10/6/93130510Fall324.78*130*** 1762SJRQ94011/4/9413081 Winter4 24.33*130*** 1762SJRQ940 4 4/5/9413524Spring124.54*130*** 1762SJRQ940 7 7/7/9411407 Summer225.13*130*** 1762SJRQ941 0 10/11/94115310Fall324.515*140*** 1762SJRB9506 6/8/9510366 Summer224.851.1132*** 1762SJRM951 2 12/19/95135812 Winter4 25.1***0.15** 1762SJRM96011/9/9612591 Winter4 24.6***0.19** 1762SJRM960 2 2/19/9612142 Winter4 25.2***0.06** 1762SJRM960 3 3/20/9611123Spring124.7***0.2** 1762SJRM960 4 4/2/9611424Spring125***0.08** 1762SJRM960 5 5/14/9612275Spring125.3***0.08** 1762SJRM960 6 6/18/9611446 Summer225.3***0.2** 1762SJRM960 7 7/2/9612107 Summer225.4***0.16** 1762SJRM960 8 8/15/9612038 Summer225.2***0.15** 1762SJRM960 9 9/18/9612059Fall325.4***0.11** 1762SJRM961 0 10/2/96121510Fall325.2***0.08** 1762SJRM961111/14/96114511Fall325.1***0.06** 1762SJRM961 2 12/16/96152112 Winter425*** 0.08** 1762SJRM97011/9/9711371 Winter4 25.1***0.08** 1762SJRM970 2 2/11/9711312 Winter4 24.7***0.07** 1762SJRM970 3 3/12/9712543Spring125.3***0.05** 1762SJRM970 4 4/7/9712194Spring125.3***0.07** 1762SJRM970 5 5/9/9715075Spring125.4***0.07** 1762SJRM970 6 6/6/9715436 Summer225.2***0.03** 1762SJRM970 7 7/3/9715047 Summer225.5***0.15** 1762SJRM970 8 8/13/9711418 Summer225.3***0.09** 1762SJRM970 9 9/2/9715119Fall325.4***0.11** 1762SJRM971 0 10/9/97123510Fall325.4***0.05**

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COLLECTION_DAT E pHTSSNH3NO3-DNO3-TNO3NO2 Po-PO4TOC TDSDtoH2OWL(MSL) 1/14/917.53 **** 0.02*0.111*30.2638.03 3/1/91 ***** 0.05 ****** 4/1/917.47 ********* 30.8637.43 7/8/917.46 **** 0.02 ****** 10/7/917.21 **** 0.02 ****** 12/11/917.47 **** 0.02 **** 28.0740.22 1/9/927.44 **** 0.02 **** 28.140.19 4/15/927.48 **** 0.03 **** 30.6437.65 7/8/927.51 **** 0.02 **** 30.2538.04 10/7/927.54 **** 0.02 **** 27.9440.35 1/7/937.56 **** 0.02 **** 27.4740.82 4/6/937.45 **** 0.02 **** 26.9141.38 7/8/937.52 **** 0.02 **** 31.3236.97 10/6/937.59 **** 0.02 **** 30.5537.74 1/4/947.62 **** 0.02 **** 28.2940 4/5/947.52 **** 0.02 **** 30.5237.77 7/7/947.43 **** 0.02 **** 29.8538.44 10/11/947.37 **** 0.02 **** 27.3740.92 6/8/957.6*0.15**0.020.13***30.3337.96 12/19/957.28 ********* 26.9641.33 1/9/967.31 ********* 27.6240.67 2/19/967.27 ********* 28.5339.76 3/20/967.25 ********* 28.339.99 4/2/967.23 ********* 28.2840.01 5/14/967.24 ********* 31.2837.01 6/18/967.42 ********* 30.4737.82 7/2/967.32 ********* 29.7338.56 8/15/967.3 ********* 30.238.09 9/18/967.41 ********* 29.9438.35 10/2/967.4 ********* 30.0238.27 11/14/967.4 ********* 29.3438.95 12/16/967.4 ********* 28.5839.71 1/9/977.37 ********* 28.4639.83 2/11/977.34 ********* 28.739.59 3/12/977.44 ********* 30.8237.47 4/7/977.45 ********* 31.1837.11 5/9/977.45 ********* 30.7337.56 6/6/977.46 ********* 29.8838.41 7/3/977.43 ********* 29.638.69 8/13/977.37 ********* 29.2139.08 9/2/977.44 ********* 29.3138.98 10/9/977.37 ********* 29.9638.33

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COLLECTION_DATEDeSnWL(MSL)TurbColorTurb-FCaMgNaKSC-FClSO4F 1/14/9136.460.78**80.940.117.43727261901.1 3/1/91****7639194.8*222401 4/1/9137.9067 *******740*** 7/8/91****7737185768142201 10/7/91****7939173.1751192201 12/11/9138.650.24**7738163.4730212300.9 1/9/9238.62***8337163.2756202201 4/15/9238.1267***7436174.2758222301.1 7/8/9239.069***7839163.1767212301.1 10/7/9240.5191***7134163751202301 1/7/9339.25***7940173.4759202201 4/6/9341.8567***7638163.3745202301 7/8/9337.999***7437173758202300.9 10/6/9337.9091***7539162.8764202201 1/4/9438.43***7840173.1741202401 4/5/9438.2467***7939173.4755202201 7/7/9439.469***7338163753202201 10/11/9441.0891***7738132.8751222300.9 6/8/9538.9890.5**7737173757202201 12/19/9539.76 *******758*** 1/9/9639.1 *******762*** 2/19/9638.19 *******759*** 3/20/9640.4667 *******762*** 4/2/9640.4867 *******763*** 5/14/9637.4867 *******757*** 6/18/9638.849 *******758*** 7/2/9639.589 *******755*** 8/15/9639.119 *******759*** 9/18/9638.5191 *******761*** 10/2/9638.4391 *******760*** 11/14/9639.1191 *******760*** 12/16/9638.14 *******761*** 1/9/9738.26 *******753*** 2/11/9738.02 *******750*** 3/12/9737.9467 *******747*** 4/7/9737.5867 *******746*** 5/9/9738.0367 *******752*** 6/6/9739.439 *******752*** 7/3/9739.719 *******740*** 8/13/9740.109 *******718*** 9/2/9739.1491 *******738*** 10/9/9738.4991 *******739***

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FK_STATI O PK_SAMP L COLLECTION_DAT E COLLECT I MONTHSEASON SEASON_ N TempFe-DMn-DAlkDOFcolEntero 1762SJRM971110/31/97141510Fall325.1***0.14** 1762SJRM971 2 12/12/97142512 Winter425*** 0.04** 1762SJRM98011/5/9814261 Winter4 25.2***0.01** 1762SJRB9802 2/5/9812152 Winter4 22.83*1290.87** 1762SJRM980 3 3/18/9810523Spring125.3***0.21** 1762SJRM980 4 4/3/9814144Spring125.6***0.29** 1762SJRM980 5 5/1/9814205Spring125.6***0.68** 1762SJRM980 6 5/29/9813425Spring125.6***1.29** 1762SJRM980 7 7/6/9814087 Summer225.4***0.52** 1762SJRM980 8 8/7/9814108 Summer225.3***0.62** 1762SJRM980 9 9/9/9814039Fall325.2***0.31** 1762NEDM000 3 3/15/0019223Spring125.3***0.13** 1762NEDM000 5 5/23/0011455Spring125.98***0.01** 1762NEDM000 7 7/25/0012407 Summer225.79***0** 1762NEDM001 0 10/23/00171010Fall325.7***0.18** 1762SJRM01011/29/0118221 Winter4 25.8***0.15** 1762SJRM010 4 4/25/0120404Spring125.93***0.44** 1762SJRM010 7 7/24/0112227 Summer225.83***0.05** 1762SJRM011 0 10/24/01214510Fall325.96**1320.05121 1762SJRM02011/23/0217431 Winter4 25.87**1360.211 1762SJRM020 4 4/23/0220454Spring126.09**1300.0311 1762SJRM020 7 7/23/0218057 Summer226.18** 1330.6711 1762SJRM021 0 10/22/02120610Fall326.12***0.14** 1762SJRM03011/30/0312191 Winter4 26.15***0.23** 1762SJRM030 4 4/23/0313534Spring126.17***0.21**

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COLLECTION_DAT E pHTSSNH3NO3-DNO3-TNO3NO2 Po-PO4TOC TDSDtoH2OWL(MSL) 10/31/977.39 ********* 29.1539.14 12/12/977.42 ********* 28.5239.77 1/5/987.4 ********* 27.8840.41 2/5/987.56*0.15**0.0220.0040.011.4*26.6241.67 3/18/987.4 ********* 26.4141.88 4/3/987.42 ********* 27.5940.7 5/1/987.36 ********* 30.3537.94 5/29/987.33 ********* 32.0936.2 7/6/987.35 ********* 33.9234.37 8/7/987.32 ********* 31.9336.36 9/9/987.3 ********* 30.7437.55 3/15/007.38 ********* 32.7135.58 5/23/007.54 ********* 35.233.09 7/25/007.42 ********* 34.733.59 10/23/007.51 ********* 31.836.49 1/29/017.42 ********* 32.935.39 4/25/017.46 ********* 35.133.19 7/24/017.48 *********33 35.29 10/24/017.4640.16**0.0040.0040.0041.548836.331.99 1/23/027.4340.14**0.0040.0040.0061.64923038.29 4/23/027.4840.16**0.0040.0040.0091.848232.9635.33 7/23/027.1940.17**0.0040.0040.0071.649232.835.49 10/22/027.38 ********* 31.336.99 1/30/037.37 ********* 28.3439.95 4/23/037.4 ********* 29.3538.94

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COLLECTION_DATEDeSnWL(MSL)TurbColorTurb-FCaMgNaKSC-FClSO4F 10/31/9739.3091 *******736*** 12/12/9738.2 *******691*** 1/5/9838.84 *******739*** 2/5/9840.10.210*78.139.617.14.54743202201 3/18/9842.3567 *******745*** 4/3/9841.1767 *******741*** 5/1/9838.4167 *******745*** 5/29/9836.6767 *******743*** 7/6/9835.399 *******740*** 8/7/9837.389 *******745*** 9/9/9837.7191 *******747*** 3/15/0036.0567 *******697*** 5/23/0033.5667 *******732*** 7/25/0034.619 *******726*** 10/23/0036.6591 *******717*** 1/29/0133.82 *******730*** 4/25/0133.6667 *******725*** 7/24/0136.319 *******726*** 10/24/0132.15910.555*66.741.217.93.1700172201 1/23/0236.720.35*67.440.517.33708182201 4/23/0235.80670.851.26541.418.23.2712192201.1 7/23/0236.519151.6169.142.418.83.3719182201.2 10/22/0237.1591**1.23 ****724*** 1/30/0338.38**0.6 ****726*** 4/23/0339.4167**4.65 ****682***

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FK_STATI O PK_SAMP L COLLECTION_DA T COLLECTIMONTHSEASONSEASON_ N TempFe-D Mn-DAlkDOFcol 1763SJRQ91011/14/911658 1Winter4 21.76557*** 1763SJRQ910 4 4/1/9115004Spring122.174 **** 1763SJRQ910 7 7/8/9116267 Summer222.2 70*293** 1763SJRQ911 0 10/7/91161810Fall32260*296** 1763SJRB9112 12/11/91111212 Winter4 22.460*291** 1763SJRQ92011/9/921038 1Winter42280*298** 1763SJRQ920 4 4/15/9210204Spring121.940*301** 1763SJRQ920 7 7/8/9211557 Summer222.3 45*297** 1763SJRQ921 0 10/7/92105010Fall32249*301** 1763SJRQ93011/7/931023 1Winter42260*300** 1763SJRQ930 4 4/6/9310544Spring121.545*300** 1763SJRQ930 7 7/8/9310497 Summer222.1 47*300** 1763SJRQ931 0 10/6/93110210Fall321.976*300** 1763SJRQ94011/4/941106 1Winter4 21.757*300** 1763SJRQ940 4 4/5/9411414Spring122.155*300** 1763SJRQ940 7 7/7/9410077 Summer222.1 56*300** 1763SJRQ941 0 10/11/94100810Fall321.961*300** 1763SJRQ95011/3/951427 1Winter4 21.7**287** 1763SJRQ950 4 4/3/9510044Spring121.8**301** 1763SJRQ950 7 7/10/9510147 Summer222.1 **300** 1763SJRQ951 0 10/2/95135310Fall323.4 ***** 1763SJRM951 2 12/19/95122912 Winter4 22.6***0.19* 1763SJRM96011/9/961125 1Winter4 22.1***0.06* 1763SJRM960 2 2/19/9610452 Winter4 23.2***0.08* 1763SJRM960 3 3/20/969453Spring122***0.06* 1763SJRM960 4 4/2/9610154Spring122.6***1.64* 1763SJRM960 5 5/14/9611015Spring122.1***0.13* 1763SJRM960 6 6/18/9610196 Summer223.3 ***0.19* 1763SJRM960 7 7/2/9610437 Summer223.7 ***2.28* 1763SJRM960 8 8/15/9610388 Summer224.2 ***0.18* 1763SJRM960 9 9/18/9610419Fall323.3***0.1* 1763SJRM961 0 10/2/96104810Fall323.2***0.13* 1763SJRM961111/14/96102211Fall322.7***0.09* 1763SJRM961 2 12/16/96135312 Winter4 22.8***0.1* 1763SJRM97011/9/971015 1Winter4 23.1***0.41* 1763SJRM970 2 2/11/9710092 Winter4 22.3***0.07* 1763SJRM970 3 3/12/9711353Spring123.1***0.09* 1763SJRM970 4 4/7/9710594Spring123.1***0.11* 1763SJRM970 5 5/9/9713485Spring123.3***0.07* 1763SJRM970 6 6/6/9714236 Summer222.9 ***0.45* 1763SJRM970 7 7/3/9713407 Summer223.3 ***0.29* 1763SJRM970 8 8/13/9710218 Summer223.4 ***0.34*

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COLLECTION_DATEEnteropHTSSNH3NO3-DNO3-TNO3NO2Po-PO4TOCTDSDtoH2O 1/14/91*6.99 **** 0.02*0.4412*27.86 4/1/91*7 **** 0.05 **** 25.01 7/8/91*6.97 **** 0.02 ***** 10/7/91*6.71 **** 0.02 ***** 12/11/91*6.96 **** 0.02 **** 24.47 1/9/92*7.09 **** 0.02 **** 24.5 4/15/92*7.02 **** 0.02 **** 24.7 7/8/92*6.98 **** 0.02 **** 25.3 10/7/92*7.07 **** 0.03 **** 23.32 1/7/93*7.12 **** 0.02 **** 24.14 4/6/93*6.97 **** 0.02 **** 23.86 7/8/93*7.02 **** 0.02 **** 25.82 10/6/93*7.08 **** 0.02 **** 26.72 1/4/94*7.17 **** 0.02 **** 23.71 4/5/94*7.07 **** 0.02 **** 24.44 7/7/94*7.07 **** 0.02 **** 24.44 10/11/94*6.95 **** 0.02 **** 23.53 1/3/95*7.08*0.29**0.03 **** 23.6 4/3/95*7.02*0.29**0.02 **** 24.15 7/10/95*6.61*0.28**0.02 **** 25.2 10/2/95*6.97 ********* 23.18 12/19/95*6.84 ********* 23.99 1/9/96*6.86 ********* 23.72 2/19/96*6.89 ********* 24.38 3/20/96*6.8 ********* 23.73 4/2/96*6.76 ********* 23.76 5/14/96*6.97 ********* 24.99 6/18/96*6.45 ********* 25.28 7/2/96*6.75 ********* 23.99 8/15/96*6.15 ********* 25.17 9/18/96*6.69 ********* 24.41 10/2/96*6.77 ********* 24.84 11/14/96*6.68 ********* 24.2 12/16/96*6.56 ********* 23.88 1/9/97*6.75 ********* 24.17 2/11/97*7.02 ********* 24.18 3/12/97*6.97 ********* 24.76 4/7/97*6.99 ********* 24.64 5/9/97*7.01 ********* 23.99 6/6/97*7.02 ********* 23.59 7/3/97*6.97 ********* 23.6 8/13/97*6.92 ********* 23.6

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COLLECTION_DATEWL(MSL)TurbColorTurb-FCaMg NaKSC-FClSO4F 1/14/9140.433.9**1163.213.50.8583246.50.27 4/1/9143.28***1103.2141.25832250.2 7/8/91 ****1103.2141.2620210.60.1 10/7/91 ****1203.2131.1623180.20.1 12/11/9143.822**1103121.1574221.20.1 1/9/9243.79***1203.2131.1624200.60.1 4/15/9243.59***1103131.2625220.30.1 7/8/9242.99***1103131.1628200.60.1 10/7/9244.97***1002.7141.2620200.30.1 1/7/9344.15***1203130.91622200.20.1 4/6/9344.43***1203.1130.9622200.30.1 7/8/9342.47***1203.1130.84629190.20.1 10/6/9341.57***1103130.9633200.20.1 1/4/9444.58***1203.1130.87614200.20.1 4/5/9443.85***1203.1130.9626200.30.1 7/7/9443.85***1102.9130.87624210.20.1 10/11/9444.76***1103.1130.95619210.20.1 1/3/9544.69***1102.9120.8605201.8* 4/3/9544.14***1103.1130.8621210.7* 7/10/9543.09***1103.1150.9625200.2* 10/2/9545.11 *******621*** 12/19/9544.3 *******627*** 1/9/9644.57 *******629*** 2/19/9643.91 *******628*** 3/20/9644.56 *******629*** 4/2/9644.53 *******630*** 5/14/9643.3 *******626*** 6/18/9643.01 *******625*** 7/2/9644.3 *******625*** 8/15/9643.12 *******631*** 9/18/9643.88 ******* 632.3*** 10/2/9643.45 *******629*** 11/14/9644.09 *******629*** 12/16/9644.41 *******629*** 1/9/9744.12 *******627*** 2/11/9744.11 *******625*** 3/12/9743.53 *******624*** 4/7/9743.65 *******625*** 5/9/9744.3 *******624*** 6/6/9744.7 *******622*** 7/3/9744.69 *******616*** 8/13/9744.69 *******593***

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FK_STATI O PK_SAMP L COLLECTION_DA T COLLECTIMONTHSEASONSEASON_ N TempFe-D Mn-DAlkDOFcol 1763SJRM970 9 9/2/9713539Fall323.5***0.23* 1763SJRM971 0 10/9/97111110Fall323.4***0.08* 1763SJRM971110/31/97125610Fall322.9***0.19* 1763SJRM971 2 12/12/97130712 Winter4 22.6***0.07* 1763SJRM98011/5/981308 1Winter423 ***0.13* 1763SJRB9802 2/5/9810382 Winter4 20.264*3150.51* 1763SJRM980 3 3/18/989373Spring122.9***0.16* 1763SJRM980 4 4/3/9813054Spring123.1***0.25* 1763SJRM980 5 5/1/9813075Spring122.2***0.44* 1763SJRM980 6 5/29/9812335Spring122.1***0.99* 1763SJRM980 7 7/6/9812527 Summer222.1 ***0.59* 1763SJRM980 8 8/7/9812558 Summer222.2 ***0.76* 1763SJRM980 9 9/9/9812479Fall322.2***0.22* 1763NEDM000 3 3/15/0017173Spring122.27***0.1* 1763NEDM000 5 5/23/0011055Spring122.17***0.14* 1763NEDM000 7 7/25/0012027 Summer222.3***0* 1763NEDM001 0 10/23/00164110Fall322.25***0.18* 1763SJRM01011/29/011735 1Winter4 22.25***0.19* 1763SJRM010 4 4/25/0119504Spring122.21***0.37* 1763SJRM010 7 7/24/0111097 Summer222.29 ***0.07* 1763SJRM011 0 10/24/01190510Fall322.37**3020.121 1763SJRM02011/23/021512 1Winter4 22.3**3040.251 1763SJRM020 4 4/23/0218304Spring122.37**3020.171 1763SJRM020 7 7/23/0216507 Summer222.43** 3020.771 1763SJRM021 0 10/22/02103310Fall322.4***0.25* 1763SJRM03011/30/031057 1Winter4 22.45***0.041* 1763SJRM030 4 4/23/0311284Spring122.29***0.22*

PAGE 336

COLLECTION_DATEEnteropHTSSNH3NO3-DNO3-TNO3NO2Po-PO4TOCTDSDtoH2O 9/2/97*6.99 ********* 24.52 10/9/97*6.91 ********* 24.83 10/31/97*6.94 ********* 24.27 12/12/97*6.96 ********* 23.67 1/5/98*6.95 ********* 23.39 2/5/98*7.16*0.29**0.0040.430.437.7*23.54 3/18/98*6.92 ********* 23.52 4/3/98*6.95 ********* 23.89 5/1/98*6.87 ********* 25.1 5/29/98*6.85 ********* 26.29 7/6/98*6.87 ********* 26.89 8/7/98*6.86 ********* 24.51 9/9/98*6.87 ********* 24.25 3/15/00*6.99 ********* 26.92 5/23/00*6.96 ********* 27.2 7/25/00*6.78 ********* 27.3 10/23/00*7.02 ********* 24.3 1/29/01*6.9 ********* 25.1 4/25/01*6.95 ********* 25.4 7/24/01*6.96 ********* 24.5 10/24/0116.8540.27**0.0040.440.476.138224.7 1/23/0216.940.24**0.0040.440.476.738324.2 4/23/0216.8340.26**0.0040.450.466.638125.85 7/23/0216.6740.26**0.0040.440.446.538425.28 10/22/02*6.85 ********* 24.42 1/30/03*6.91 ********* 24.42 4/23/03*6.93 ********* 24.62

PAGE 337

COLLECTION_DATEWL(MSL)TurbColorTurb-FCaMg NaKSC-FClSO4F 9/2/9743.77 *******607*** 10/9/9743.46 *******613*** 10/31/9744.02 *******610*** 12/12/9744.62 *******570*** 1/5/9844.9 *******611*** 2/5/9844.750.220*1153.1913.10.86617190.380.1 3/18/9844.77 *******622*** 4/3/9844.4 *******615*** 5/1/9843.19 *******615*** 5/29/9842 *******616*** 7/6/9841.4 *******612*** 8/7/9843.78 *******615*** 9/9/9844.04 *******620*** 3/15/0041.37 *******608*** 5/23/0041.09 ******* 61.3*** 7/25/0040.99 *******606*** 10/23/0043.99 *******605*** 1/29/0143.19 *******611*** 4/25/0142.89 *******610*** 7/24/0143.79 *******608*** 10/24/0143.590.255*1113.213.40.8588170.390.094 1/23/0244.090.35*1103.213.10.78606180.20.086 4/23/0242.440.1550.021113.213.40.81603190.20.1 7/23/0243.010.1551.381173.313.90.83605180.20.11 10/22/0243.87**0.43 ****609*** 1/30/0343.87**0.38 **** 6.14*** 4/23/0343.67**0.74 ****581***

PAGE 338

FK_STATI O PK_SAMPLECOLLECTION_DATECOLLECTI O MONTH SEASONSEASON_ N TempFe-DMn-DAlkDO 1764SJRQ9101-41/14/911550 1Winter4 21.929120** 1764SJRQ9104-54/1/9113414Spring122.2290*** 1764SJRQ9107-37/8/9115107Summer222.4310*48* 1764SJRQ9110-310/7/91150210Fall322.2270*38* 1764SJRB9112-1512/11/91910 12Winter4 22.4360*41* 1764SJRQ9201-91/9/92915 1Winter4 22.1430*45* 1764SJRQ9204-224/15/928524Spring121.9410*36* 1764SJRQ9207-97/8/9210107Summer222.5460*52* 1764SJRQ9210-910/7/9291010Fall322.2490*40* 1764SJRQ9301-41/7/93906 1Winter422460*37* 1764SJRQ9304-44/6/939334Spring121.6480*32* 1764SJRQ9307-77/8/939167Summer222560*24* 1764SJRQ9310-810/6/9393410Fall322520*29* 1764SJRQ9401-51/4/94943 1Winter4 21.7480*27* 1764SJRQ9404-54/5/9410094Spring121.8470*26* 1764SJRQ9407-87/7/949007Summer222.1420*21* 1764SJRQ9501-31/3/951325 1Winter4 21.6**29* 1764SJRQ9504-14/3/958424Spring121.7**28* 1764SJRQ9507-27/10/959027Summer222.1**31* 1764SJRQ9510-310/2/95130010Fall322.8 **** 1764SJRM9512-112/19/95 113012 Winter4 22.1***0.14 1764SJRM9601-31/9/96 10291 Winter4 21.6***0.07 1764SJRM9602-42/19/969532 Winter4 22.2***0.07 1764SJRM9603-43/20/968483Spring121.5***0.1 1764SJRM9604-44/2/969024 Spring121.9***0.97 1764SJRM9605-45/14/96 10045Spring122.8***1.8 1764SJRM9606-46/18/969156Summer222.6***0.3 1764SJRM9607-47/2/969397 Summer223***1.49 1764SJRM9608-48/15/969348 Summer222.4***0.24 1764SJRM9609-49/18/969379 Fall322.4***0.23 1764SJRM9610-410/2/9694410 Fall322.3***0.21

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COLLECTION_DATEFcol EnteropHTSSNH3NO3-DNO3-TNO3NO2Po-PO4TOCTDS 1/14/91**5.71 **** 0.02*0.1412* 4/1/91**5.73 **** 0.61 **** 7/8/91**5.55 **** 0.02 **** 10/7/91**5.33 **** 0.02 **** 12/11/91**5.48 **** 0.02 **** 1/9/92**5.83 **** 0.02 **** 4/15/92**5.57 **** 0.02 **** 7/8/92**5.83 **** 0.02 **** 10/7/92**5.67 **** 0.02 **** 1/7/93**5.68 **** 0.02 **** 4/6/93**5.38 **** 0.02 **** 7/8/93**5.4 **** 0.02 **** 10/6/93**5.44 **** 0.04 **** 1/4/94**5.58 **** 0.02 **** 4/5/94**5.47 **** 0.02 **** 7/7/94**5.42 **** 0.02 **** 1/3/95**5.52*0.86**0.03 **** 4/3/95**5.45*0.83**0.02 **** 7/10/95**5.39*0.82**1.2 **** 10/2/95**5.54 ********* 12/19/95**5.16 ********* 1/9/96**5.21 ********* 2/19/96**5.04 ********* 3/20/96**5.29 ********* 4/2/96**5.17 ********* 5/14/96**5.27 ********* 6/18/96**4.82 ********* 7/2/96**4.97 ********* 8/15/96**4.77 ********* 9/18/96**4.8 ********* 10/2/96**4.86 *********

PAGE 340

COLLECTION_DATEDtoH2O WL(MSL)DeSNWL(MSL)Turb ColorTurb-FCaMgNaKSC-F 1/14/9119.9445.745.3485.1**30.52.913.21.3246 4/1/9117.5948.0548.2988***202.5131203 7/8/91******203.1141.6223 10/7/91******172.5131.4197 12/11/9116.9148.7348.37820**173.2151.6206 1/9/9216.8748.7748.418***193.4141.7224 4/15/9217.2448.448.6488***163.1141.7202 7/8/9217.9847.6648.0045***233.8142233 10/7/9215.5250.1249.8304***143.3141.7195 1/7/9316.3849.2648.908***153.2131.4189 4/6/9316.0649.5849.8288***133.2121.3181 7/8/9318.1647.4847.8245***122.7131.2171 10/6/9319.2446.446.1104***102.2121.1165 1/4/9415.9249.7249.368***122.4131.3168 4/5/9416.9648.6848.9288***112.3121.2163 7/7/9416.5849.0649.4045***9.92.1111.2159 1/3/9515.8749.7749.418***122.2121.3162 4/3/9516.2149.4349.6788***142.3131.3178 7/10/9517.5548.0948.4345***142.5151.4179 10/2/9515.2250.4250.1304 *******180 12/19/9516.149.5449.188 *******167 1/9/9616.2649.3849.028 *******152 2/19/9616.8948.7548.398 *******151 3/20/9615.9649.6849.9288 *******157 4/2/9615.9449.749.9488 *******149 5/14/9617.4648.1848.4288 *******144 6/18/9617.5448.148.4445 *******143 7/2/9616.0449.649.9445 *******134 8/15/9617.1848.4648.8045 *******134 9/18/9616.8148.8348.5404 *******138 10/2/9616.9848.6648.3704 *******131

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COLLECTION_DATEClSO4F 1/14/9121240.14 4/1/9119160.2 7/8/9119210.1 10/7/9117160.1 12/11/9120240.1 1/9/9219210.1 4/15/9220210.1 7/8/9219270.1 10/7/9219220.1 1/7/9318190.1 4/6/9319190.1 7/8/9318170.1 10/6/9319210.1 1/4/9419180.1 4/5/9418160.1 7/7/9417130.1 1/3/951616* 4/3/951717* 7/10/951719* 10/2/95*** 12/19/95*** 1/9/96*** 2/19/96*** 3/20/96*** 4/2/96*** 5/14/96*** 6/18/96*** 7/2/96*** 8/15/96*** 9/18/96*** 10/2/96***

PAGE 342

FK_STATI O PK_SAMPLECOLLECTION_DATECOLLECTI O MONTH SEASONSEASON_ N TempFe-DMn-DAlkDO 1764SJRM9611-411/14/9692111 Fall321.9***0.13 1764SJRM9612-412/16/96 130312 Winter4 22.4***0.14 1764SJRM9701-41/9/979181 Winter422 ***0.14 1764SJRM9702-42/11/979282 Winter4 21.7***0.12 1764SJRM9703-43/12/97 10423Spring122.3***0.23 1764SJRM9704-44/7/979574Spring122.6***0.2 1764SJRM9705-45/9/97 12475Spring122.5***0.19 1764SJRM9706-46/6/97 13366Summer222.2***0.27 1764SJRM9707-47/3/97 12507Summer222.6***0.16 1764SJRM9708-48/13/979268 Summer222.6***0.23 1764SJRM9709-49/2/97 13019Fall322.9***0.34 1764SJRM9710-410/9/97102010 Fall322.5***0.12 1764SJRM9711-410/31/97 120910Fall322.3***0.29 1764SJRM9712-412/12/97 122012 Winter4 21.7***0.36 1764SJRM9801-41/5/98 12321 Winter4 22.5***0.13 1764SJRB9802-82/5/98926 2Winter4 19.7272*12.40.55 1764SJRM9803-43/18/988573 Spring122.4***0.24 1764SJRM9804-44/3/98 12294Spring122.6***0.53 1764SJRM9805-45/1/98 12415Spring122.6***0.46 1764SJRM9806-45/29/98 12045Spring123.7***1.16 1764SJRM9807-47/6/98 12277Summer222.9***0.91 1764SJRM9808-48/7/98 12298Summer222.6***1.28 1764SJRM9809-49/9/98 12249Fall322.5***0.36 1764NEDM0003-33/15/00 16123Spring122.4***0.19 1764NEDM0005-35/23/009545 Spring122.32***0.11 1764NEDM0006-16/27/009406 Summer222.38***0.01 1764NEDM0007-37/25/00 11117Summer222.26***0.02 1764NEDM0008-18/28/00 16288Summer222.36***0 1764NEDM0009-19/25/00 16269Fall322.49***0.15 1764NEDM0010-310/23/00 153810Fall322.22***0.31 1764SJRM0011-211/27/00 144611Fall322.16***0.33

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COLLECTION_DATEFcol EnteropHTSSNH3NO3-DNO3-TNO3NO2Po-PO4TOCTDS 11/14/96**4.91 ********* 12/16/96**4.78 ********* 1/9/97**4.94 ********* 2/11/97**5.33 ********* 3/12/97**5.3 ********* 4/7/97**5.38 ********* 5/9/97**5.36 ********* 6/6/97**5.41 ********* 7/3/97**5.35 ********* 8/13/97**5.28 ********* 9/2/97**5.49 ********* 10/9/97**5.39 ********* 10/31/97**5.38 ********* 12/12/97**5.41 ********* 1/5/98**5.38 ********* 2/5/98**5.37*0.72**0.0060.030.02312* 3/18/98**5.28 ********* 4/3/98**5.25 ********* 5/1/98**5.14 ********* 5/29/98**5.24 ********* 7/6/98**5.28 ********* 8/7/98**5.24 ********* 9/9/98**5.23 ********* 3/15/00**5.31 ********* 5/23/00**5.06 ********* 6/27/00**4.81 ********* 7/25/00**4.99 ********* 8/28/00**5.07 ********* 9/25/00**4.95 ********* 10/23/00**5.17 ********* 11/27/00**5.25 *********

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COLLECTION_DATEDtoH2O WL(MSL)DeSNWL(MSL)Turb ColorTurb-FCaMgNaKSC-F 11/14/9616.6149.0348.7404 *******131 12/16/9616.2449.449.048 *******126 1/9/9716.4749.1748.818 *******131 2/11/9716.3249.3248.968 *******124 3/12/9717.0748.5748.8188 *******123 4/7/9717.0548.5948.8388 *******126 5/9/9716.2549.3949.6388 *******126 6/6/9715.5650.0850.4245 *******131 7/3/9715.6749.9750.3145 *******123 8/13/9715.8449.850.1445 *******130 9/2/9716.8448.848.5104 *******137 10/9/9717.148.5448.2504 *******133 10/31/9716.3149.3349.0404 *******133 12/12/9715.7549.8949.538 *******134 1/5/9815.6549.9949.638 *******125 2/5/9815.7649.8849.5281.550*7.121.4811.11.1122 3/18/9815.9349.7149.9588 *******137 4/3/9816.3449.349.5488 *******125 5/1/9817.2348.4148.6588 *******125 5/29/9818.2947.3547.5988 *******154 7/6/9818.9146.7347.0745 *******132 8/7/9816.4949.1549.4945 *******138 9/9/9816.3949.2548.9604 *******140 3/15/0018.247.4447.6888 *******143 5/23/0019.446.2446.4888 *******134 6/27/0020.145.5445.8845 *******135 7/25/0019.246.4446.7845 *******133 8/28/0018.846.8447.1845 *******145 9/25/0015.849.8449.5504 *******144 10/23/0016.149.5449.2504 *******134 11/27/0016.549.1448.8504 *******144

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COLLECTION_DATEClSO4F 11/14/96*** 12/16/96*** 1/9/97*** 2/11/97*** 3/12/97*** 4/7/97*** 5/9/97*** 6/6/97*** 7/3/97*** 8/13/97*** 9/2/97*** 10/9/97*** 10/31/97*** 12/12/97*** 1/5/98*** 2/5/9814120.1 3/18/98*** 4/3/98*** 5/1/98*** 5/29/98*** 7/6/98*** 8/7/98*** 9/9/98*** 3/15/00*** 5/23/00*** 6/27/00*** 7/25/00*** 8/28/00*** 9/25/00*** 10/23/00*** 11/27/00***

PAGE 346

FK_STATI O PK_SAMPLECOLLECTION_DATECOLLECTI O MONTH SEASONSEASON_ N TempFe-DMn-DAlkDO 1764SJRM0012-212/18/00 155012 Winter4 22.23***0.18 1764SJRM0101-61/29/01 16501 Winter4 22.3***0.53 1764SJRM0102-22/26/01 18432 Winter4 22.43***0.4 1764SJRM0103-23/26/01 19333Spring122.26***1.01 1764SJRM0104-24/25/01 19034Spring122.33***0.58 1764SJRM0106-25/28/01 15315Spring122.34***0.11 1764SJRM0105-35/31/01 12405Spring122.56***0.09 1764SJRM0107-57/24/01 10157Summer222.39***0.17 1764SJRM0108-28/27/01 18308Summer222.42***0.09 1764SJRM0109-29/24/01 17359Fall322.34***0.11 1764SJRM0110-310/24/01 170710Fall322.55**140.19 1764SJRM0111-211/26/01 140911Fall322.45**130.32 1764SJRM0112-212/19/01 161412 Winter4 22.22**140.25 1764SJRM0201-11/23/02 13501 Winter4 22.61**130.47 1764SJRM0202-22/19/029082 Winter4 22.27**110.27 1764SJRM0203-23/26/02 10063Spring122.53**120.17 1764SJRM0204-44/23/02 17404Spring122.67***0.06 1764SJRM0205-25/22/029455Spring 122.73**140.21 1764SJRM0206-26/26/029306Summer 222.54**150.28 1764SJRM0207-67/23/02 15507Summer222.64**130.75 1764SJRM0208-28/19/02 12458Summer222.85**120.37 1764SJRM0209-29/23/02 12309Fall322.74**150.26 1764SJRM0210-410/22/0293710 Fall322.42***0.19 1764SJRM0211-311/18/02 11Fall322.32***0.26 1764SJRM0212-212/16/0212 Winter4 22.39***0.26 1764SJRM0301-51/30/03 10131 Winter4 22.52***0.75 1764SJRM0302-22/20/03 14332 Winter4 22.71***0.29 1764SJRM0303-23/24/03 17293Spring122.56***0.16 1764SJRM0304-34/23/03 10014Spring122.3***0.26 1764SJRM0305-25/27/03 14585Spring123.58***0.15 1764SJRM0306-26/23/03 17316Summer222.78***0.33

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COLLECTION_DATEFcol EnteropHTSSNH3NO3-DNO3-TNO3NO2Po-PO4TOCTDS 12/18/00**5.29 ********* 1/29/01**5.1 ********* 2/26/01**5.16 ********* 3/26/01**5.2 ********* 4/25/01**5.16 ********* 5/28/01**5.17 ********* 5/31/01**5.18 ********* 7/24/01**5.19 ********* 8/27/01**5.09 ********* 9/24/01**5.04 ********* 10/24/01 2154 0.82**0.010.0130.0111111 11/26/01 12540.8** 0.0080.0150.01711102 12/19/01115.0840.79**0.0040.0180.02111100 1/23/02115.140.8**0.0040.0190.0212103 2/19/02115.1940.85**0.0040.0180.0151193 3/26/02115.0740.9**0.0040.0190.01610101 4/23/02**5 ********* 5/22/02115.1441**0.0040.0210.01912107 6/26/02 11541.1** 0.0040.0190.0191391 7/23/02124.6740.96**0.0040.0140.01512100 8/19/02114.9841.1**0.0040.0180.01411102 9/23/02115.0241**0.0040.0170.01613111 10/22/02**5.02 ********* 11/18/02**5.23 ********* 12/16/02**5.22 ********* 1/30/03**5.15 ********* 2/20/03**5.1 ********* 3/24/03**5.09 ********* 4/23/03**5.13 ********* 5/27/03**4.97 ********* 6/23/03**4.73 *********

PAGE 348

COLLECTION_DATEDtoH2O WL(MSL)DeSNWL(MSL)Turb ColorTurb-FCaMgNaKSC-F 12/18/0016.948.7448.388 *******150 1/29/0117.248.4448.088 *******151 2/26/0117.348.3447.988 *******151 3/26/0116.349.3449.5888 *******149 4/25/0117.448.2448.4888 *******155 5/28/0117.747.9448.1888 *******157 5/31/0117.947.7447.9888 *******153 7/24/0116.249.4449.7845 *******153 8/27/011748.6448.9845 *******152 9/24/0115.650.0449.7504 *******164 10/24/0116.848.8448.55041.515*6.93.812.41.2152 11/26/0116.349.3449.05042.215*6.53.812.21.2156 12/19/0116.249.4449.0880.8515*6.63.512.61.3156 1/23/0216.249.4449.0881.75*6.13.912.21.2158 2/19/0216.848.8448.4881.15*5.83.912.41.2158 3/26/021748.6448.88881.750.1263.812.21.2146 4/23/021847.6447.8888**0.34 ****156 5/22/0218.946.7446.98882.8300.147.23.812.51.5159 6/26/0216.9548.6949.03452.8400.438.23.612.91.6163 7/23/0216.948.7449.08455301.217.23.812.61.4160 8/19/0216.549.1449.48455.230*6.73.912.91.4156 9/23/0216.149.5449.25043.8202.237.83.912.91.5162 10/22/0216.5949.0548.7604**0.79 ****160 11/18/0218.6247.0246.7304**0.27 ****157 12/16/0216.149.5449.188**1.2 ****152 1/30/0316.6149.0348.678**0.78 ****157 2/20/0316.349.3448.988**0.56 ****160 3/24/0316.0349.6149.8588**0.98 ****170 4/23/0316.748.9449.1888**0.95 ****159 5/27/0317.6747.9748.2188**0.4 ****178 6/23/0316.848.8449.1845**0.74 ****190

PAGE 349

COLLECTION_DATEClSO4F 12/18/00*** 1/29/01*** 2/26/01*** 3/26/01*** 4/25/01*** 5/28/01*** 5/31/01*** 7/24/01*** 8/27/01*** 9/24/01*** 10/24/0113290.032 11/26/0114290.05 12/19/0113280.05 1/23/0213290.05 2/19/0213270.05 3/26/0214290.05 4/23/02*** 5/22/0213300.05 6/26/0213290.05 7/23/0214290.05 8/19/0214280.05 9/23/0215290.05 10/22/02*** 11/18/02*** 12/16/02*** 1/30/03*** 2/20/03*** 3/24/03*** 4/23/03*** 5/27/03*** 6/23/03***

PAGE 350

FK_STATI O PK_SAMP L COLLECTION_DATECOLLECTIMONTHSEASONSEASON_ N TempFe-D Mn-DAlkDOFcol 1779SJRQ91011/15/911634 1Winter4 21.8***1.8* 1779SJRQ910 4 4/2/9116254Spring121.9***0.9* 1779SJRQ910 7 7/9/9118507 Summer222.6 ***** 1779SJRQ911 0 10/8/91170410Fall322.1 ***** 1779SJRB9203 3/4/9215203Spring122.210*157** 1779SJRB9511 11/7/95114311Fall322.9138160** 1779SJRB9806 6/2/9814046 Summer224.8 25*1640.15* 1779NEDM000 3 3/14/0018103Spring122.02***0.09* 1779NEDM000 5 5/22/0019035Spring122.71***0.1* 1779NEDM000 7 7/24/0016377 Summer222.82***0* 1779NEDM001 0 10/23/00111510Fall322.66***0.26* 1779SJRM01011/29/011445 1Winter4 22.45**1600.181 1779SJCA0101 2/26/0116252 Winter4 22.5**1600.291 1779SJRM010 4 4/25/0115364Spring122.58**1560.41 1779SJRM010 7 7/23/0118107 Summer222.49** 1610.051 1779SJRM011 0 10/25/01131310Fall322.7***0.26* 1779SJRM02011/24/021100 1Winter4 22.73***0.39* 1779SJRM020 4 4/23/0213314Spring122.67***0.11* 1779SJRM020 7 7/23/0211357 Summer222.83 ***0.63* 1779SJRM021 0 10/21/02162610Fall322.69***0.2* 1779SJRM03011/3/031919 1Winter4 22.87***0.14* 1779SJRM030 4 4/23/0319304Spring122.38***0.19*

PAGE 351

COLLECTION_DAT E EnteropHTSSNH3NO3-DNO3-TNO3NO2Po-PO4TOCTDSDtoH2O 1/15/91*7.61 ********* 79.34 4/2/91*7.75 ********* 75.56 7/9/91*7.63 ********** 10/8/91*7.39 ********** 3/4/92*7.86 **** 0.020.02***75.36 11/7/95*7.62*0.1**0.020.02***75.38 6/2/98*7.82*0.075**0.0270.0050.0041*72.27 3/14/00*7.77 ********* 78.35 5/22/00*7.49 ********* 79.7 7/24/00*7.42 ********* 81.2 10/23/00*7.68 ********* 80.2 1/29/0117.6640.084**0.0040.0040.0041.118179.9 2/26/0117.6540.091**0.0040.0040.004116679.73 4/25/0117.5940.094**0.0040.0040.004121679.6 7/23/0117.6440.1**0.0040.0080.006117980.6 10/25/01*7.52 ********* 79.8 1/24/02*7.62 ********* 79.7 4/23/02*7.69 ********* 79.4 7/23/02*7.52 ********* 81.77 10/21/02*7.46 ********* 80.87 1/3/03*7.62 ********* 78.1 4/23/03*7.61 ********* 73.91

PAGE 352

COLLECTION_DATE WL(MSL)Turb ColorTurb-FCaMgNaKSC-FClSO4F 1/15/9149.56 *******313*** 4/2/9153.34 *******317*** 7/9/91 ********327*** 10/8/91 ********329*** 3/4/9253.542.2**351681.8320620.5 11/7/9553.521.7**34158.21.53266.51.90.5 6/2/9856.630.955*3214.28.32.883246.52.30.31 3/14/0050.55 *******319*** 5/22/0049.2 ******* 31.9*** 7/24/0047.7 *******321*** 10/23/0048.7 *******313*** 1/29/01490.855*39.617.29.11.432362.10.4 2/26/0149.170.85*35.215.87.91.232051.90.5 4/25/0149.30.55*3515.28.31.23185.82.10.5 7/23/0148.30.055*34.915.18.31.33195.61.80.5 10/25/0149.1 *******306*** 1/24/0249.2 *******317*** 4/23/0249.5**0.47 ****317*** 7/23/0247.13**2.57 ****312*** 10/21/0248.03**4.22 ****324*** 1/3/0350.8**0.72 ****321*** 4/23/0354.99**1.62 ****314***

PAGE 353

FK_STATI O PK_SAMP L COLLECTION_DATECOLLECTIMONTHSEASONSEASON_ N TempFe-DMn-DAlkDOFcol 1780SJRQ91011/15/9115121Winter420.7***0.7* 1780SJRQ91044/2/9115344Spring120.6***0.8* 1780SJRQ910 7 7/9/9116447Summer221.9 ***** 1780SJRQ911 0 10/8/91144810Fall321 ***** 1780SJRB9203 3/4/9212003Spring120.5130*135** 1780SJRB9511 11/7/9593111Fall321.126037136** 1780SJRB9806 6/2/9812256Summer222.729*360.16* 1780NEDM000 3 3/14/0019153Spring121.25***0.07* 1780NEDM000 5 5/22/0019295Spring121.19***0.09* 1780NEDM000 7 7/24/0016297Summer221.39***0* 1780NEDM001 0 10/23/00115510Fall321.18***0.26* 1780SJRM01011/29/0113301Winter421.42**1300.191 1780SJCA0101 2/26/0114502Winter421.28**1300.311 1780SJRM010 4 4/25/0114004Spring121.34**1320.431 1780SJRM010 7 7/23/0116357Summer221.27**1360.051 1780SJRM011 0 10/25/01121110Fall321.25***0.11* 1780SJRM02011/24/0210061Winter421.22***2.42* 1780SJRM020 4 4/23/0212124Spring121.43***0.12* 1780SJRM020 7 7/23/0210277Summer221.3***0.48* 1780SJRM021 0 10/21/02145710Fall321.45***0.22* 1780SJRM03011/30/0317151Winter421.36***0.3* 1780SJRM030 4 4/23/0318044Spring120.95***0.24*

PAGE 354

COLLECTION_DATEEnteropHTSSNH3NO3-DNO3-TNO3NO2Po-PO4TOCTDSDtoH2O 1/15/91*7.51 ********* 13.17 4/2/91*7.32 ********* 8.22 7/9/91*8.02 ********** 10/8/91*7.36 ********** 3/4/92*7.66 **** 0.020.38***8.75 11/7/95*7.45*0.01**0.020.32***6.35 6/2/98*9.75*0.01**0.0560.0430.021*10.12 3/14/00*7.49 ********* 12.2 5/22/00*7.39 ********* 13.7 7/24/00*7.14 ********* 14.1 10/23/00*7.5 ********* 12.6 1/29/0117.4940.015**0.0060.470.32117614.5 2/26/0117.4640.01**0.0040.410.3116014.7 4/25/0117.4340.014**0.0040.380.3121514.7 7/23/0117.4740.01**0.0040.390.31116512.8 10/25/01*7.3 ********* 11.8 1/24/02*7.46 ********* 12.7 4/23/02*7.47 ********* 11.33 7/23/02*7.4 ********* 12.44 10/21/02*7.28 ********* 9.51 1/30/03*7.32 *********9.1 4/23/03*7.12 ********* 8.91

PAGE 355

COLLECTION_DATEWL(MSL)TurbColorTurb-FCaMgNaKSC-FClSO4F 1/15/91115.63 *******293*** 4/2/91120.58 *******288*** 7/9/91 ********291*** 10/8/91 ********301*** 3/4/92120.051.3**301482298102.70.2 11/7/95122.450.8**29147.71.6301102.90.2 6/2/98118.683.55*8.871.347.62.44138133.50.14 3/14/00116.6 *******291*** 5/22/00115.1 *******293*** 7/24/00114.7 *******294*** 10/23/00116.2 *******286*** 1/29/01114.31.410*32.816.581.72929.82.90.16 2/26/01114.11.35*29.415.17.81.52939.22.60.24 4/25/01114.11.45*28.814.57.61.42909.83.30.23 7/23/011161.55*30.215.27.81.52889.42.50.23 10/25/01117 *******277*** 1/24/02116.1 *******286*** 4/23/02117.47**0 ****284*** 7/23/02116.36**0.99 ****287*** 10/21/02119.29**0.99 ****294*** 1/30/03119.7**0.26 ****292*** 4/23/03119.89**0.83 ****287***

PAGE 356

FK_STATI O PK_SAMPLECOLLECTION_DATECOLLECTIMONTH SEASONSEASON_ N TempFe-DMn-DAlkDOFcolEntero 1781SJRQ9101-121/15/911642 1Winter4 20.7***1.15** 1781SJRQ9104-114/2/9114304Spring120.6***1.7** 1781SJRQ9107-97/9/9115307Summer222.9 ****** 1781SJRQ9110-910/8/91141910Fall320.6 ****** 1781SJRB9203-53/4/9210153Spring122.610*68*** 1781SJRB9511-1211/7/9583411Fall320.4251075*** 1781SJRB9806-86/2/9811496Summer223.425*855.19** 1781NEDM0003-63/14/00 20103Spring121.03***0.57** 1781NEDM0005-65/22/00 18235Spring121.18***0.8** 1781NEDM0006-26/26/00 14486Summer221.31***0.21** 1781NEDM0007-67/24/00 15347Summer221.38***0.55** 1781NEDM0008-28/28/00 13188Summer221.4***0.6** 1781NEDM0009-29/25/00 13429Fall321.43***0.75** 1781NEDM0010-710/23/00 101010Fall321.14***0.86** 1781SJRM0011-311/27/00 124811Fall321.09**348.411 1781SJRM0012-312/18/00 135512 Winter4 20.98**350.6611 1781SJRM0101-11/29/01 12251 Winter4 21.25**340.9311 1781SJRM0102-12/26/01 13402 Winter4 21.29**340.8311 1781SJRM0103-13/26/01 15293Spring121.13**330.9811 1781SJRM0104-64/25/01 12204Spring120.98**290.9211 1781SJUA0104-295/21/0116055Spring121.57**320.4611 1781SJRM0106-46/27/01 19106Summer221.31**330.511 1781SJRM0107-17/23/01 14507Summer221.39**290.511 1781SJRM0108-18/27/01 14508Summer221.33**320.5511 1781SJRM0109-19/24/01 13009Fall321.25**310.6411 1781SJRM0110-910/25/01 111910Fall321.23***0.71** 1781SJRM0111-111/26/01 115011Fall321.19***0.68** 1781SJRM0112-112/19/01 133512 Winter4 21.02***0.71** 1781SJRM0201-41/24/026001 Winter4 21.09***0.86** 1781SJRM0202-32/19/02 11542 Winter4 21.08***0.78** 1781SJRM0203-33/26/02 12533Spring121.3***0.74** 1781SJRM0204-14/23/02 11054Spring121.24***0.71** 1781SJRM0205-35/22/02 12255Spring121.3***0.73** 1781SJRM0206-36/26/02 12156Summer221.47***0.84** 1781SJRM0207-17/23/029247Summer 221.27***1.04** 1781SJRM0208-18/19/02 10318Summer221.42***0.76** 1781SJRM0209-19/23/029119Fall 321.28***0.78** 1781SJRM0210-110/21/02 135610Fall321.27***0.87** 1781SJRM0211-111/18/0211 Fall321.02***0.75** 1781SJRM0212-112/16/0212 Winter421 ***0.74** 1781SJRM0301-81/30/03 16141 Winter4 21.27***1.03** 1781SJRM0302-32/20/03 16542 Winter4 21.29***0.84** 1781SJRM0303-13/24/03 13263Spring121.26***0.98** 1781SJRM0304-64/23/03 17204Spring121.35***1.36** 1781SJRM0305-15/27/03 11325Spring121.37***0.84** 1781SJRM0306-16/23/03 15046Summer221.46***0.94**

PAGE 357

COLLECTION_DATpHTSSNH3NO3-DNO3-TNO3NO2P o-PO4TOCTDSDtoH2O WL(MSL)Turb Color 1/15/919.71 ********* 12.2116.51** 4/2/919.29 *********7.8 120.91** 7/9/918.47 ************* 10/8/916.29 ************* 3/4/926.98 **** 0.020.07***8.38120.330.68* 11/7/957.04*0.01**0.070.08***6.04122.672.1* 6/2/987.24*0.01**0.0130.0790.0791*9.67119.041.75 3/14/006.84 ********* 11.83116.88** 5/22/006.15 ********* 13.5115.21** 6/26/006.18 ********* 10.87117.84** 7/24/005.79 ********* 13.8114.91** 8/28/006.13 ********* 13.2115.51** 9/25/006.08 ********* 11.2117.51** 10/23/006.12 ********* 12.2116.51** 11/27/006.2340.01**0.0090.0490.04507613.3115.410.055 12/18/006.1440.021**0.010.0510.06118013.7115.010.055 1/29/016.0840.01**0.0110.0460.0519014.1114.610.655 2/26/015.9840.01**0.0090.0470.04117514.4114.310.15 3/26/016.0540.01**0.0090.0530.04517813.9114.810.15 4/25/015.9840.017**0.0090.0380.037112014114.710.055 5/21/015.9140.01**0.0060.0360.03217714.7114.010.155 6/27/015.9940.01**0.010.0360.03619613.8114.910.15 7/23/015.9240.01**0.010.0590.03418012.2116.510.35 8/27/015.9640.018**0.010.0390.03919112116.710.255 9/24/015.7540.01**0.010.0440.03617610.3118.410.15 10/25/015.76 ********* 11.3117.41** 11/26/015.88 ********* 12.1116.61** 12/19/015.86 ********* 12.5116.21** 1/24/025.95 ********* 12.1116.61** 2/19/026.07 ********* 11.6117.11** 3/26/025.98 ********* 10.63118.08** 4/23/025.89 ********* 10.75117.96** 5/22/025.92 ********* 12.58116.13** 6/26/025.69 ********* 13.58115.13** 7/23/025.71 ********* 11.8116.91** 8/19/025.82 ********* 9.85118.86** 9/23/025.87 ********* 9.57119.14** 10/21/025.78 ********* 8.76119.95** 11/18/025.88 ********* 8.43120.28** 12/16/025.56 *********7.6 121.11** 1/30/035.77 ********* 8.66120.05** 2/20/035.82 ********* 7.99120.72** 3/24/035.8 ********* 6.99121.72** 4/23/035.73 ********* 8.34120.37** 5/27/035.56 ********* 9.82118.89** 6/23/035.34 *********8 120.71**

PAGE 358

COLLECTION_DAT E Turb-FCaMgNaKSC-FClSO4F 1/15/91 *****168*** 4/2/91 *****172*** 7/9/91 *****190*** 10/8/91 *****161*** 3/4/92*211.79.73.1168112.30.1 11/7/95*262.18.51.9191102.80.2 6/2/98*28.82.047.81.82213113.50.1 3/14/00 *****191*** 5/22/00 *****131*** 6/26/00 *****131*** 7/24/00 *****129*** 8/28/00 *****122*** 9/25/00 *****117*** 10/23/00 *****109*** 11/27/00*11.81.37.61.4120111.90.1 12/18/00*10.91.27.31.3111111.90.05 1/29/01*12.21.47.91.5119101.80.036 2/26/01*10.11.27.61.31079.61.60.069 3/26/01*10.11.27.31.3109101.70.065 4/25/01*91.17.41.3106101.70.068 5/21/01*10.81.17.61.3106101.70.046 6/27/01*9.91.17.21.3105111.60.066 7/23/01*91.17.41.3100101.60.059 8/27/01*9.91.17.51.3112101.80.072 9/24/01*9.41.17.51.399111.80.063 10/25/01 *****98*** 11/26/01 *****107*** 12/19/01 *****93*** 1/24/02 *****104*** 2/19/02 *****116*** 3/26/020.16 ****104*** 4/23/020.44 ****106*** 5/22/020.02 ****110*** 6/26/020.62 ****103*** 7/23/020.64 ****99*** 8/19/02 *****98*** 9/23/020.54 ****107*** 10/21/020.24 ****102*** 11/18/020.6 ****95*** 12/16/020.43 **** 0.089*** 1/30/030.4 ****103*** 2/20/030.28 ****95*** 3/24/030.85 ****110*** 4/23/031.6 ****106*** 5/27/030.25 ****120*** 6/23/030.43 ****118***

PAGE 359

FK_STATI O DateSEASON_ N TempDeSnTempFe-DMn-DAlkDOFcolEnteropHTSS 19311/14/9142222.2979 ****** 7.74* 19312/18/9142222.2979 ****** 7.92* 19313/11/9112221.8549 ****** 7.91* 19314/17/91122.121.9549 ****** 7.79* 19315/23/91122.121.9549 ****** 7.68* 19316/3/91222.121.9133 ******7.6* 19317/9/91222.121.9133 ****** 7.44* 19318/20/91222.121.9133 ****** 7.83* 19319/9/91322.222.2374 ****** 7.86* 193110/14/91322.122.1374 ****** 7.85* 193111/18/91322.122.1374***6.8**7.88* 193112/9/91422.122.3979***7.1**7.96* 19311/16/9242222.2979***6.8**8.09* 19312/17/92422.122.3979***7.6**7.91* 19313/18/92122.121.9549***8*