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The Relationship Between Specific Conductivity and Flow Paths in a Karst Aquifer, North-Central Florida

Permanent Link: http://ufdc.ufl.edu/UFE0025041/00001

Material Information

Title: The Relationship Between Specific Conductivity and Flow Paths in a Karst Aquifer, North-Central Florida
Physical Description: 1 online resource (95 p.)
Language: english
Creator: Langston, Abigail
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: carbonate, dissolution, florida, hydrology, karst, river, springs
Geological Sciences -- Dissertations, Academic -- UF
Genre: Geology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: The Floridan aquifer system is the primary source of drinking water in north-central Florida and provides a source of recreation where it discharges at Florida s springs. At O Leno State Park, the Santa Fe River flows into the Floridan Aquifer system via a 36-meter-deep sinkhole, flows through a conduit system, and re-emerges 5 km from its sink at a first magnitude spring. Research conducted at O Leno State Park investigated the response of the unconfined upper Floridan aquifer to two flood events on the Santa Fe River, one in March 2008 and one from Tropical Storm Fay in August 2008. The March 2008 event was largely a result of local diffuse recharge, in contrast to a large flood pulse from upstream during Tropical Storm Fay. The aquifer matrix surrounding the conduit system was monitored by 4 nested well pairs equipped with data loggers that recorded water level, temperature, and specific conductivity. Both diffuse recharge and conduit-influenced responses were detected at water table wells, but no recharge response was detected in wells screened at the level of the conduit. This result contrasted with expectations that conduit water would invade the matrix uniformly around the conduit passages. Slug tests conducted as part of this study indicate that the matrix at the water table has hydraulic conductivity up to one order of magnitude higher than deeper in the aquifer. A two-dimensional groundwater model was constructed to determine the conditions necessary to 11 observe conduit water flowing in significant quantities to the water table, as indicated by the monitoring results. The model was constructed using input parameters based on published total porosities, hydraulic conductivities calculated for this study, and gradients from collected water level data. The major parameter adjusted in the modeling was effective porosity. Reducing the effective porosity mimics a small conduit or preferential flow path, and allows water to move faster along the water table. The results of this study alter conceptual models about how allogenic recharge flows through a karst aquifer and the role of the water table as a dynamic area of water flow. This study also emphasizes the contamination risk to karst aquifers. Contaminants have ample access to the unconfined Floridan Aquifer through diffuse recharge as well as point source contamination. If the higher hydraulic conductivity and lower effective porosity along the water table is a common feature, it would provide transport paths for the rapid flow of contaminants.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Abigail Langston.
Thesis: Thesis (M.S.)--University of Florida, 2009.
Local: Adviser: Screaton, Elizabeth J.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2010-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0025041:00001

Permanent Link: http://ufdc.ufl.edu/UFE0025041/00001

Material Information

Title: The Relationship Between Specific Conductivity and Flow Paths in a Karst Aquifer, North-Central Florida
Physical Description: 1 online resource (95 p.)
Language: english
Creator: Langston, Abigail
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: carbonate, dissolution, florida, hydrology, karst, river, springs
Geological Sciences -- Dissertations, Academic -- UF
Genre: Geology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: The Floridan aquifer system is the primary source of drinking water in north-central Florida and provides a source of recreation where it discharges at Florida s springs. At O Leno State Park, the Santa Fe River flows into the Floridan Aquifer system via a 36-meter-deep sinkhole, flows through a conduit system, and re-emerges 5 km from its sink at a first magnitude spring. Research conducted at O Leno State Park investigated the response of the unconfined upper Floridan aquifer to two flood events on the Santa Fe River, one in March 2008 and one from Tropical Storm Fay in August 2008. The March 2008 event was largely a result of local diffuse recharge, in contrast to a large flood pulse from upstream during Tropical Storm Fay. The aquifer matrix surrounding the conduit system was monitored by 4 nested well pairs equipped with data loggers that recorded water level, temperature, and specific conductivity. Both diffuse recharge and conduit-influenced responses were detected at water table wells, but no recharge response was detected in wells screened at the level of the conduit. This result contrasted with expectations that conduit water would invade the matrix uniformly around the conduit passages. Slug tests conducted as part of this study indicate that the matrix at the water table has hydraulic conductivity up to one order of magnitude higher than deeper in the aquifer. A two-dimensional groundwater model was constructed to determine the conditions necessary to 11 observe conduit water flowing in significant quantities to the water table, as indicated by the monitoring results. The model was constructed using input parameters based on published total porosities, hydraulic conductivities calculated for this study, and gradients from collected water level data. The major parameter adjusted in the modeling was effective porosity. Reducing the effective porosity mimics a small conduit or preferential flow path, and allows water to move faster along the water table. The results of this study alter conceptual models about how allogenic recharge flows through a karst aquifer and the role of the water table as a dynamic area of water flow. This study also emphasizes the contamination risk to karst aquifers. Contaminants have ample access to the unconfined Floridan Aquifer through diffuse recharge as well as point source contamination. If the higher hydraulic conductivity and lower effective porosity along the water table is a common feature, it would provide transport paths for the rapid flow of contaminants.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Abigail Langston.
Thesis: Thesis (M.S.)--University of Florida, 2009.
Local: Adviser: Screaton, Elizabeth J.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2010-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0025041:00001


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THE RELATIONSHIP BETWEEN SPECIFIC CONDUCTIVITY AND FLOW PATHS IN A
KARST AQUIFER, NORTH-CENTRAL FLORIDA





















By

ABIGAIL L. LANGSTON


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2009


































2009 Abigail L. Langston




































To my father, Marcus C. Langston









ACKNOWLEDGMENTS

I want to thank my advisor, Dr. Elizabeth Screaton, for lending her knowledge and

expertise to this project. I thank the many field assistants who assisted in data collection at

O'Leno State Park. I am grateful to my mom, Crystal Langston, for her unending support and

belief in me. Finally, I thank Ethan and Zoe, two rays of sunshine that light my life.










TABLE OF CONTENTS

page

A C K N O W L E D G M E N T S ..............................................................................................................4

LIST OF TABLES ................... ............................ ........7

LIST OF FIGURES ....................................................... ........8

ABSTRAC T ......... .................. ................. ... .. .. ............... 10

CHAPTER

1 INTRODUCTION ............... ........................ ........................ ...... ..........12

2 BACKGROUND ............... ....................... ...................... .......... ..............15

Conceptual M odels of Karst and Dissolution..................................... ................... 15
D dissolution in C onduits .............. .......................................................................... ......... 16
Dissolution from Diffuse Recharge........................................................... .... ........... 17
Study A rea ...................................... ............................................ 18
G eologic Background ................. ....................... ...................... ...... .. ..............19
Previous Research in the Study Area................................ ...............21

3 METHODS ......................................................... ................. ........25

Data Collection....................................................... ........25
Precipitation...................................... ................... ............ ........25
Recharge......................................................... ................ .........25
Sink and Rise Discharge...................................... ......................................27
W ell and Surface Site M onitoring...................................... ....................... ...........28
Pumping during Drought and Storm Events.................................. .................30
Hvorslev Method ................... ........................... ........31
Bouwer-Rice method.......................... ............ ..................32
Adjustment for Wells Screened through Sand Pack.......................................33

4 RESULTS ........... .............................................36

Precipitation and Recharge ............. .... .. ............. ......... .... ........36
Water Level, Specific Conductivity, and Temperature Monitoring ............... ............37
Nested Well Pairs Water Level, Specific Conductivity, Temperature ................................37
Discharge at the River Sink and River Rise ............... ..... ............. ...............39
Well Response to Recharge and Pumping during Drought and Minor Rain Events ............40
Well Response to Recharge and Pumping during a Flood Event................. .............40
Well and Surface Water Response during Tropical Storm Fay................ ..............42
Shallow well specific conductivity response during Tropical Storm Fay .............................43
Slug Tests Shallow and Deep Wells..................... ......................43










5 DISCUSSION .......................... .... ... ............... .63

Slug Tests and Applicability to Matrix Hydraulic Conductivity.................. ... ...........63
Specific conductivity response in shallow wells: evidence for reactive water....................64
Initial well Response: Tropical Storm Fay ............. ........... ................... 64
Shallow Well Response to Peak Flood Level.......... ........... ... ................. 65
Specific Conductivity Signal During March 2008 Event......................... .............67
Interpretation of Specific Conductivity Response using Groundwater Modeling...............70
2-D Modeling of Conduit-matrix interactions during Tropical Storm Fay .....................71
M odeled Concentrations of conduit water .......................................... 73
M odeled concentrations of diffuse recharge ........................................ ............... 75
Model applied to the March 2008 Flood event and pumping .......................................76
Implications .................................................78

L IST O F R E F E R E N C E S ............. ................. .............................................................92

BIOGRAPHICAL SKETCH ............... ......... ................ 95









LIST OF TABLES


Table page

3-1 Summary of well depths, screened intervals, depth to bedrock and ground surface
elevation of all wells at O'Leno State Park used in this study and previous studies.........34

4-1 Summary of precipitation, recharge, and water levels during the 2008 floods. ................44

4-2 Shortest distances from nested wells to known conduits.......... ......... ..................45

4-3 Summary of the limestone and water levels during high and low water levels................45









LIST OF FIGURES


Figure page

2-1 Location of study area in north-central Florida ..........................................24

3-1 Rating curve developed by the SRWMD for the Santa Fe River Sink.............................34

3-2 Rating curve for Santa Fe River Rise from Screaton et al. (2004) .................................35

3-3 Head ratio vs. time plot used to determine variables in Hvorslev and Bouwer-Rice
slug test calculations. ....................... .............. ...............35

4-1 Total precipitation and recharge at O'Leno State Park during the study period, 2006-
2008................................................................ ...... 46

4-2 Precipitation from the O'Leno State Park rain gauge.............................. ...........47

4-3 Water level from the River Rise for the study period 2006-2008................48

4-4 Water levels at the River Sink, River Rise, and shallow wells during the March 2008
flood event. ................................................ ........49

4-5 Water levels at the River Sink, River Rise, and shallow wells during Tropical Storm
Fay flood event. .......................................................50

4-6 Head difference between wells 5 and 5A .............................. ............... 51

4-7 Temperature and specific conductivity changes over 18 months in a shallow well and
deep well in the study area................................. ..................................... 52

4-8 Discharge from the River Sink and the River Rise for 2008 .................................53

4-9 Specific conductivity responses and recovery at the shallow wells during low flow........53

4-10 a,b. Water level and specific conductivity response to a diffuse recharge event............54

4-11 Values recorded during pumping at the shallow wells during March 2008. ..................55

4-12 Specific conductivity measurements from both loggers and pumping during the
M arch 2008 flood................... .................................................. .. ...............56

4-13 Specific conductivity in well 7 showing both pumping and logger values ....................57

4-14 Specific conductivity values from both pumping and loggers in well 6A during the
M arch 2008 flood event. .............................................................58

4-15 Specific conductivity response at the River Sink and the River Rise during Tropical
Storm Fay......................................................... 59









4-16 Specific conductivity response at the deep wells during Tropical Storm Fay.................60

4-17 Specific conductivity response in the shallow wells during Tropical Storm Fay..........61

4-18 Results of hydraulic conductivity calculations from slug tests........................................62

5-1 Water levels at the River Sink, River Rise, and Well 4A with specific conductivity
from well 4A during Tropical Storm Fay. ............................ ............... 81

5-2 Close up view of precipitation and calculated precipitation at O'Leno State Park
during Tropical Storm Fay .........................................................82

5-3 Water levels at the River Sink, River Rise, and Well 5A with specific conductivity
from well 5A during Tropical Storm Fay. ............................ ............... 83

5-4 Water Level at the River Sink, River Rise, and well 6A with specific conductivity
from well 6A. ..............................................................84

5-5 Close up view of precipitation and recharge during the March 2008 flood ......................85

5-6 Water level from the River Sink, River Rise, and well 4A with specific conductivity
from well 4A .............................................................. 86

5-7 Cross sections of groundwater model during Tropical Storm Fay ..............................87

5-8 Cross sections of groundwater model during Tropical Storm Fay ..............................88

5-9 Figure showing percent conduit water. .................................... ..................... 89

5-10 Cross sections of groundwater model during Tropical Storm Fay ..............................90

5-11 Cross sections of groundwater model during March 2008 .............................................91

5-12 Cross sections of groundwater model during March 2008 .............................................91









Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

THE RELATIONSHIP BETWEEN SPECIFIC CONDUCTIVITY AND FLOW PATHS IN A
KARST AQUIFER, NORTH-CENTRAL FLORIDA

By

Abigail L. Langston

August 2009

Chair: Elizabeth Screaton
Major: Geology

The Floridan aquifer system is the primary source of drinking water in north-central

Florida and provides a source of recreation where it discharges at Florida's springs. At O'Leno

State Park, the Santa Fe River flows into the Floridan Aquifer system via a 36-meter-deep

sinkhole, flows through a conduit system, and re-emerges 5 km from its sink at a first magnitude

spring. Research conducted at O'Leno State Park investigated the response of the unconfined

upper Floridan aquifer to two flood events on the Santa Fe River, one in March 2008 and one

from Tropical Storm Fay in August 2008. The March 2008 event was largely a result of local

diffuse recharge, in contrast to a large flood pulse from upstream during Tropical Storm Fay.

The aquifer matrix surrounding the conduit system was monitored by 4 nested well pairs

equipped with data loggers that recorded water level, temperature, and specific conductivity.

Both diffuse recharge and conduit-influenced responses were detected at water table wells, but

no recharge response was detected in wells screened at the level of the conduit. This result

contrasted with expectations that conduit water would invade the matrix uniformly around the

conduit passages. Slug tests conducted as part of this study indicate that the matrix at the water

table has hydraulic conductivity up to one order of magnitude higher than deeper in the aquifer.

A two-dimensional groundwater model was constructed to determine the conditions necessary to









observe conduit water flowing in significant quantities to the water table, as indicated by the

monitoring results. The model was constructed using input parameters based on published total

porosities, hydraulic conductivities calculated for this study, and gradients from collected water

level data. The major parameter adjusted in the modeling was effective porosity. Reducing the

effective porosity mimics a small conduit or preferential flow path, and allows water to move

faster along the water table. The results of this study alter conceptual models about how

allogenic recharge flows through a karst aquifer and the role of the water table as a dynamic area

of water flow. This study also emphasizes the contamination risk to karst aquifers. Contaminants

have ample access to the unconfined Floridan Aquifer through diffuse recharge as well as point

source contamination. If the higher hydraulic conductivity and lower effective porosity along the

water table is a common feature, it would provide transport paths for the rapid flow of

contaminants.









CHAPTER 1
INTRODUCTION

The importance of groundwater stored in karstic aquifers around the world cannot be

overstated; up to 25% of the global human population depends on these groundwaters (Ford and

Williams 2007). In peninsular Florida, the vast majority of water for drinking and industrial

purposes comes from karst aquifers, either the Floridan Aquifer or the Biscayne Aquifer in south

Florida. The Floridan Aquifer is one of the most productive aquifers in the world, with 4,020

million gallons/day of water withdrawn in 2000 (Marella and Berndt 2005). The Floridan

Aquifer is made of soluble limestone bedrock that is dissolved by acidic rain water. Dissolution

forms conduits in karst aquifers, which quickly allows water transport over great distances with

little filtration. Conduit flow poses the possibility of contaminants rapidly flowing through a

karst aquifer and discharging unfiltered at a well field or spring. Understanding how water flows

through karst aquifers and how flow paths change through time is vital to keeping groundwater

quality high and determining possible transport paths in case of contamination.

Flow through karst aquifers is conceptualized through a triple-porosity model; water flows

through conduits, fractures, and intergranular matrix (White 2002). Conduits range from 1 cm to

many meters in diameter and generally dominate water flow paths where present in karst

aquifers. Onset of non-Darcian turbulent flow can begin in conduits with a diameter greater than

1 cm. Fracture porosity includes fractures, joints, and bedding planes whose width falls between

50-500 am. These fractures are frequently enlarged by dissolution. Intergranular porosity, or

matrix porosity, is extremely low in telogenetic karst aquifers, which have undergone burial and

recrystallization, but plays an important role in young, eogenetic aquifers.

Telogenetic karst has been well studied, beginning with classical Greek scholars (Ford and

Williams 2007). Research on telogenetic karst became so well developed that karstt" became









synonymous with low-permeability matrix, conduit dominated flow regimes (e.g. Palmer 1991;

White 1999; Klimchouk 2004). In contrast, there was significantly less research on younger,

eogenetic carbonate aquifers with higher matrix porosity and both conduit and matrix flow.

Eogenetic karst is found in peninsular Florida, the Yucatan Peninsula, Mexico, the Bahamas and

some Caribbean islands. Research towards understanding the unique functioning of eogenetic

aquifers began in earnest -40 years ago (Back and Hanshaw 1970), and continues to produce

new and important findings (Mylroie and Carew 1995; Martin et al. 2002; Palmer 2002; Vacher

and Mylroie 2002; Florea and Vacher 2005).

Research at O'Leno State Park in north-central Florida has provided further insight into

the interactions of conduit and matrix flow in an eogenetic karst aquifer, and the role of

dissolution in aquifer evolution. O'Leno State Park is situated near the Cody Scarp, the boundary

between the confined Floridan Aquifer to the east and the unconfined aquifer to the west. At

O'Leno State Park, the Santa Fe River flows into a 36-meter-deep sinkhole and emerges 5

kilometers downstream at the River Rise. Comparisons of water volume discharging into the

River Sink and volumes discharging from the River Rise indicates that water leaves the conduit

system during high flow into River Sink (Martin and Dean 1999, 2001; Screaton et al., 2004).

Screaton et al. (2004) also address the implications for conduit dissolution when undersaturated

water leaves the conduit and comes into contact with the matrix. Martin et al. (2006) and Ritorto

(2007) used water level data during storm events from wells at variable distances from the

conduit to determine matrix transmissivity and sensitivity to diffuse recharge. Ritorto et al.

(2009) estimated the magnitude of dissolution due to diffuse recharge and due to flow from the

conduit to the matrix during high flow events. This research raised important questions about the









flow paths of allogenic recharge into the matrix and the role of the water table in the local flow

system.

This study uses specific conductivity in nested well pairs to determine how preferential

flow paths affect flow velocities. Well monitoring also allows tracking of inputs from diffuse

recharge and the conduit to better understand dissolution patterns and aquifer evolution. Specific

conductivity responses in the water table wells and conduit level wells were monitored for three

years, from 2006 2008. During this time, low water levels in the aquifer and minimal change in

specific conductivity were followed by two flood events in 2008 that resulted in significant shifts

in specific conductivity that represent both diffuse and conduit inputs. These signals are observed

in water table wells, a result not anticipated by the original conceptual model. A mechanism for

conduit water flowing to the shallow wells is presented in a groundwater model that uses

hydraulic conductivities calculated from slugs tests performed at O'Leno State Park. The

findings of this study suggest a significant feedback between dissolution due to diffuse recharge

and due to conduit influx, and thus improve previous conceptual models of conduit-matrix

interactions in an eogenetic karst aquifer.









CHAPTER 2
BACKGROUND

Conceptual Models of Karst and Dissolution

Karst landscapes can be divided into two distinct groups based on matrix permeability:

telogenetic karst (k= 10 5 10 -20 m2 ) that has been deeply buried, diagenetically altered, and

lost most primary matrix porosity and eogenetic karst (k = 10 -11 10 -14 m2 ) which is younger,

close to the site of deposition, and has high matrix porosity (Vacher and Mylroie 2002). Karst

landscapes, and groundwater flow through these systems, is well studied in Paleozoic

(telogenetic) karst areas in the United States and Europe. Paleozoic karst is characterized by

diagenetically mature rocks with very low intergranular porosity, but extensive conduit systems

that give the aquifers high permeability (Palmer, 2002). Carbonate rocks that are temporally and

spatially close to the site of deposition are termed eogenetic karst and may have both higher

aquifer permeability from large conduits and high primary porosity. Matrix permeability

decreases exponentially with aquifer age, which can be considered a proxy for the likelihood that

carbonate has under gone burial the mesogenetic stage and exhumed back close to the surface

(Vacher and Mylroie 2002; Florea and Vacher 2006). Eogenetic karst is often associated with

small carbonate islands, eg. the Bahamas, Bermuda, the Florida Keys, but this is not always the

case (Vacher and Mylroie 2002). The Biscayne aquifer in south Florida and the upper Floridan

aquifer are also areas of eogenetic karst (Vacher and Mylroie 2002; Moore 2009). The idea that

older karst has lower permeability holds up through the course of the geologic time scale, but

perhaps not on shorter time scales; on shorter time scales the permeability of karst aquifers will

increase over time due to dissolution (Vacher and Mylroie 2002). Large scale horizontal

hydraulic conductivity increases over the evolution of a small-scale eogenetic karst landscapes

(Vacher and Mylroie 2002). Often principles and concepts developed in telogenetic karst cannot









be applied to eogenetic karst systems where intergranular matrix porosity is a large factor in

groundwater flow and storage, unlike telogenetic karst where storage and transport is largely

through fractures and conduits (Palmer 2002).

The permeability of both telogenetic karst and eogenetic karst is increased by dissolution

of the limestone aquifer. The acidity of the water, and therefore the potential to dissolve

limestone, is primarily dictated by the amount of CO 2 dissolved into water. CO 2 dissolves into

water exposed to atmospheric conditions until equilibrium is reached (Drever 1997) and carbonic

acid is formed:

CO2 +H2O <--H2CO3

The carbonic acid (H2 CO3) dissociates to provide the H+ ion needed to dissolve

carbonates:

H2 CO 3 -- H + HCO 3

With higher amounts of P C2, more carbonic acid is produced and results in more acidic

water with more potential to aggressively dissolve limestone.

Dissolution in Conduits

Where surficial lithology changes from insoluble bedrock to limestone (or from a

confined to unconfined limestone aquifer), allogenic or point recharge can occur (Mylroie and

Carew 2003). Dissolution in karst systems is generally greatest at the inflow point of

undersaturated water into a system. When flow paths are established, higher flow rates through

the system can occur, leading to more rapid dissolution (Singurindy and Berkowitz 2003). As

discharge through preferential pathways increases, wall retreat rates of conduits increase to 0.01

- 0.1 cm/yr (Palmer 1991). These ranges for wall retreat apply to telogenetic carbonates with

little intergranular porosity. Maximum wall retreat is determined by chemical kinetics when









sufficient discharge is provided; kinetics is the limiting factor at this point. The timing required

to reach maximum dissolution rate (wall retreat) varies with flow distance and temperature and

varies inversely with initial fracture width, discharge, gradient, and P C02 (Palmer 1991). The

saturation concentration of calcite is an important parameter for determining ability of waters to

dissolve carbonate rocks. Temperature and P C02 are the most important factors in determining

the saturation concentration. As initial P C02 increases, calcite solubility increases and pH

decreases; dissolution rates depend on the under-saturation of the water, but less so on the flow

velocity (Palmer 1991).

Dissolution from Diffuse Recharge

Diffuse recharge and bursts of overland flow on a young carbonate platform form a

rugged, pitted surface, called epikarst. Diffuse recharge over a scale of hundreds of meters is

evenly distributed over the exposed carbonate rocks. This epikarst surface generally extends

through the upper few meters of soluble rock (Mylroie and Carew 2003). This weathered zone

topping the bed rock also termed the subcutaneous zone is particularly important in karst

hydrogeology because of this highly developed secondary porosity (Williams 1983). The water

table is also an important area of dissolution (Mylroie and Carew 2003; Moore 2009). The

dissolution effects of the epikarst and water table are enhanced when the two occur in the same

location, as in the study area. Epikarst development is linked with soil development and the

biogenic processes that occur in the overlying soil, due to the addition of CO 2 to meteoric water

from these biogenic processes. Water stored in the vadose zone and in the soil is close to

biogenic sources of CO 2 (Ford and Williams 2007), and can more aggressively dissolve calcite.

The dissolution can be indicated by increased specific conductivity. The CO 2 present in soil is

one of the most important drivers of carbonate dissolution (Ford and Williams 2007). High soil









porosity (-20% in the field area) allows gases to accumulate and mix. Respiring plants release

-40% of CO 2 absorbed from the atmosphere into soil pore spaces below ground (Ford and

Williams, 2007). More productive sources of CO 2 are respiring micro-flora and micro-fauna:

bacteria, actinomycetes (primary bacterial sources of decomposition in soil), and fungi. Bacteria

in the soil are sensitive to temperature and water content; most bacteria thrive in warm, wet

conditions and increase CO 2 in the soil during these times (Ford and Williams 2007).

Study Area

The Santa Fe River basin, in north-central Florida, encompasses 3,585 km2 of forests,

agricultural land, and small towns (Hunn and Slack 1983). The Santa Fe River can be divided

into two distinct stretches along its path: the 60 km stretch from the river's source at Santa Fe

Lake to the River Sink, where the River flows over the Hawthorn group, and the 45 km stretch

from the River Rise to the Suwannee River where the Santa Fe River flows over the unconfined

Floridan Aquifer. The Cody Scarp marks the boundary between the confined highlands to the

east and the unconfined lowlands to the west. The Central Highlands, to the east of the study

area, are underlain by the Hawthorn Group which elevates this area up to 75 meters above sea

level (masl). The eastern part of the Santa Fe River Basin is characterized by gently sloping

plateaus, rolling hills, and plentiful surface streams and lakes; the surface streams tend to flow

into sink holes as they near the Cody Scarp (Grubbs 1998). The unconfined lowlands in the

western part of the Santa Fe River Basin slope gently to the Gulf of Mexico to the west. Some

outcroppings of Ocala Limestone are found in the western Santa Fe River Basin, but limestone is

generally mantled by unconsolidated sand (Grubbs 1998).

North-central Florida has a transitional temperate-humid subtropical climate. This climate

is characterized by short, mild winters with temperatures ranging from 4-100C, and long humid









summers with temperatures that range from 25-350C (Grubbs 1998). Average yearly

precipitation in the Santa Fe River Basin is 140 cm, though this number can vary significantly

with location, especially in the summer months. Precipitation is carried to the basin in three

ways: through passing fronts, which typically occur in the winter, through convective, localized

thunderstorms which produce intense, but generally brief afternoon showers in the summer, and

through seasonal tropical storms (Grubbs 1998). Precipitation values vary throughout the Santa

Fe River Basin due to localized afternoon thunderstorms in the summer months and the transient

nature of tropical storms that move through the area. Recharge to the aquifer from precipitation

events varies due to seasonal changes in temperature, wind speeds, solar radiation, and canopy

cover (Ritorto et al. 2009), and the spatial variability in the Hawthorn Group, which acts as a

confining unit in the eastern Santa Fe Basin (Grubbs 1998).

Geologic Background

Peninsular Florida is underlain by a thick sequence of carbonate rocks. In the Santa Fe

River Basin, the upper 250-100 meters of limestone is saturated with freshwater (Hunn and Slack

1983). Because topographic relief on the Floridan Peninsula is so low, there is little exposure of

the underlying strata that make up the Floridan Aquifer. Descriptions of hydrographic and

stratigraphic units are based on description of cores, examination of quarries, and investigating

the few available outcrops. Absolute dating of the Floridan Aquifer units is unavailable, so the

units are relatively dated using microfossils (Miller 1986).

The Paleocene-aged Cedar Keys Formation, the lowest stratigraphic unit included in the

Floridan Aquifer, is a permeable carbonate-evaporite deposit that underlies the Floridan

peninsula. The Cedar Keys Formation is made up of fine to coarsely crystalline dolomite, with

gypsum or anhydrite filling most pore spaces; thick, impermeable anhydrite beds are present

locally. The Oldsmar Formation overlies the Cedar Keys Formation and is early Eocene in age.









Oldsmar Formation is a mictitic to finely pelloidal limestone with interbedded fine to medium

crystalline, often vuggy, dolomite. The middle-Eocene aged Avon Park Limestone, the oldest

stratigraphic unit exposes at the surface in Florida, is a mostly pelloidal, locally micritic, well-

indurated limestone with some dolomitization. The Ocala Limestone is late Eocene in age and is

the primary water-bearer for the Floridan aquifer. The Ocala Limestone is buried under up to 365

meters of overburden in southern part of peninsular Florida; but in north-central Florida, the

Ocala Limestone is much more accessible and often crops out at the surface in the western part

of the study area. The Ocala Limestone in divided into upper and lower sections: the upper Ocala

is white, softly indurated, porous coquina with a micritic matrix and the lower Ocala is semi-

indurated micritic limestone that may be dolomitized in some areas. Horizontal zones of

enhanced permeability in the Floridan aquifer are frequent and often correspond with bedding

planes enhanced by dissolution or fracturing (Miller 1986). The Hawthorn Group is a middle-

Miocene aged unit and is made up of interbedded clay, silt, and sand and ranges from gray to

green to cream in color. The abundant clay and silt in the Hawthorn Group cause this unit to act

as a confining layer when present overlying the Floridan aquifer. Quaternary silica sands with

trace amounts of mica and carbonate material overly the Hawthorn Group and the Ocala

Limestone in the study area with variable thicknesses (Miller 1986).

Grubbs (1998) determined that recharge rates to the confined Floridan aquifer were less

than 30 centimeters per year while recharge to the unconfined Floridan aquifer was between 40-

80 centimeters per year. The poorly confined regions of the Floridan aquifer are characterized by

a leaky confining unit (Grubbs 1998). Recharge in the poorly confined area can equal the

recharge in unconfined areas if surface water in the area is absent; when surface streams are not

present, precipitation will recharge to the surficial aquifer and ultimately the Floridan aquifer.









Surface streams are present over the poorly confined aquifer in some areas, thus a range of

recharge rates in poorly confined areas is necessary (Grubbs 1998).

Previous Research in the Study Area

Hisert (1994) conducted some of the first research on the Santa Fe Sink Rise system

specifically aimed at groundwater flow paths in the O'Leno State Park (Figure 2-1). Using SF as

a tracer, Hisert (1994) established a connection between the River Sink, 7 karst windows, and

Sweetwater Lake and Sweetwater Lake. The conduit system in and around O'Leno State Park

has been partially mapped by cave divers since 1995 (Old Bellamy Cave System, 2009). Cave

divers later connected Sweetwater Lake with the River Rise through a single conduit and mapped

a conduit system upstream of Sweetwater Lake that connects to the River Sink. A separate

conduit system connects from the east to the O'Leno conduit system north of Sweetwater Lake;

this conduit system is not sourced from a direct allogenic point (Old Bellamy Cave System,

2009).

Martin and Dean (1999) used temperature as a natural tracer through the Sink-Rise System

to determine residence times of allogenically recharged water in the conduits. Using these

estimated travel times (1.3-9 km/day) allowed sampling and analyzing a package of water

entering the River Sink and leaving the River Rise. Martin and Dean (2001) also used chemical

analyses of surface and ground waters to trace the flow of water within the conduits in O'Leno

State Park and the matrix. Three surface sites, the River Sink, Sweetwater Lake, and the River

Rise were sampled as well as two water supply wells: one -500 m upstream from the Sink and

one 2 km downstream from the Rise. During low flow on the Santa Fe River (-10.5 masl in

1998) chemical analyses suggests that water discharging at Sweetwater Lake and the River Rise

is not directly related to water at the River Sink. During high water conditions (11.90 13.43









masl), chemical compositions for the three surface sites was similar and composition of well

samples suggested conduit water reached a well in the aquifer matrix.

Screaton et al. (2004) used temperature signals at the River Sink, Sweetwater, and the

River Rise to determine conduit residence times and flow velocities, and to estimate conduit

dimensions. The average calculated diameter of a single conduit at O'Leno is 22 m, which is

consistent with reports from cave divers. Discharge into the River Sink exceeds discharge out of

the River Rise for short times during high flow periods, confirming flow from the conduit to the

matrix. Martin et al. (2006) used water level data from monitoring wells and the conduits at

O'Leno State Park to determine matrix response to conduit flooding. Passive monitoring at wells

situated at variable distances from the conduit allowed quantification of matrix transmissivity;

calculated transmissivity values ranged from 950 160,000 m2 /d. Martin inferred that with

increasing distance from the conduit, preferential flow paths become more important. Martin

(2003) also used a one dimensional groundwater model to calculate velocities for water particles

leaving the conduit during a storm event using calculated hydraulic conductivities, well

gradients, and porosity, 0.2 from Palmer (2002). The particle tracing suggested that water

particles flowing to two wells traveled between 0.45 and 8.5 meters into the matrix before

returning to the conduit. These simple models assumed a homogeneous matrix and no

preferential flow paths.

Precipitation and recharge values in north-central Florida vary tremendously due to high

evapotranspiration and a soil moisture component that must be satisfied before recharge can

occur (Ritorto et al. 2009). Three methods for determining recharge to the Floridan aquifer in the

study area were used: a basin-wide water budget method, chloride concentration method, and a

water budget method using a modified Penmen-Monteith method. Ritorto (2007) found the









modified Penmen-Monteith most useful as it estimated daily recharge with inputs of daily

precipitation and various other daily data which are easily accessible for some areas in Florida.

Ritorto et al. (2009) used the calculated daily recharge and geochemical modeling (PHREEQC)

to assess the amount of calcite being dissolved from diffuse recharge. PCO2 values for

groundwater were estimated from alkalinity measurements of the water, and precipitation was

assumed to be in equilibrium with atmospheric P C02 10 35 Recharge in eogenetic aquifers

occurs through allogenic recharge to conduits and diffuse recharge from the surface (Ritorto et

al. 2009); the areas of contact between limestone and undersaturated water are thus the areas that

undergo dissolution (Moore 2009).

Moore (2009) used the variable geochemistry of the surface waters and ground waters

during low flow and high flow on the Santa Fe River to evaluate sources of water and mixing of

these waters in the aquifer and to examine the physical and chemical properties responsible for

dissolution in an eogenetic karst conduit. Moore (2009) found that water in the Floridan aquifer

within the Santa Fe River basin can be characterized by mixing of three end-member types of

water: shallow matrix water, deep aquifer water, and surface water. Mixing of these three

compositionally distinct waters causes spring chemistry to vary with time and supports the idea

that flow through the matrix is an important aspect of the groundwater system at O'Leno State

Park (Moore 2009). Moore (2009) also asserted that dissolution in the conduit during low flow in

the river is inhibited by flow of calcium rich water from the matrix to the conduit, potentially

creating a barrier between undersaturated surface water and the conduit walls. Consequently,

dissolution in the conduit system would occur primarily during high flow events when conduit-

matrix gradients reverse and undersaturated water is pushed out of the conduit (Moore, 2009).











































'- Boundary between poorly confined and confined
Boundvrybwtwn, unconild arid pou4yy connedir
5 grangih bounarlW (Grutinbl 99M
S prin.iahd boundary VpurchurWt al 12M1





Figure 2-1. Location of study area in north-central Florida and two interpretations for boundary
of the River Rise spring shed. Detailed map showing location of the River Sink,
Sweetwater Lake, the River Rise, mapped conduits, and wells monitored during this
study From Ritorto et al. (2009).


ARA CAMNADA

A

JAA
ATLANTIC
M100 km OCEAN

"M E Florida
____ ja___c_









CHAPTER 3
METHODS

Data Collection

Precipitation

Precipitation data was collected by the Suwannee River Water Management District

(SRWMD). Precipitation at five stations in the Santa Fe River basin was recorded daily by the

Suwannee River Water Management District using a tipping bucket precipitation collector. The

precipitation recorded at the O'Leno station during each month is collected every thirty days. An

additional daily precipitation record is kept by O'Leno Park staff. This precipitation data is

largely a safeguard against missing data and check for spatial variations in precipitation data

provided by the Suwannee River Water Management District.

Recharge

The recharge for the study area was calculated using a modified Penman-Monteith

method to calculate evapotranspiration and subtracting this value and the amount added to soil

moisture storage from precipitation.


A-R +p -c -C -e (1- )
ET a Ca aC a )
p, 2, [A + y (1 + Ca, /Can)]


A = slope of relation between saturation vapor pressure and temperature

Rn = net radiation input

pa = density of air

ca = heat capacity of air

Cat = atmospheric conductance

ea* = saturation vapor pressure in air









Wa = relative humidity

pw = density of water

Xv = latent heat of vaporization

Ccan = canopy conductance

y = psychrometric constant

Air temperature, soil temperature, humidity, wind speed, and average solar radiation were

daily inputs to the evapotranspiration equation; these data were retrieved from Florida

Automated Weather Network, FAWN (http://fawn.ifas.ufl.edu/). The Alachua station, 15 miles

south of O'Leno State Park, was used.

Ritorto et al. (2009) estimated the maximum soil moisture storage for the soil overlying the

Floridan aquifer at O'Leno State Park by first determining the field capacity of the soil, 0. The

field capacity of soil is an index of the water content that can be held against the force of gravity

(Dingman 2002). This dimensionless number is calculated in the laboratory by determining the

volume of water in the soil/the volume of the soil. For sands, this number can be as low at 0.1

and as high at 0.3 for clays (Dingman 2002). A field capacity of 0.1 was chosen for the soil at

O'Leno State Park as it is made up almost entirely of siliciclastic sands (Miller 1986). Ritorto et

al. (2009) assumed a root zone of 100 cm in the study area. This designation was based on

studies that show that tree roots in a variety of forest settings are most abundant in the upper foot

of soil and are not common below four feet of soil.

Stewart (1988) applied the Penmen-Monteith method to determine evapotranspiration in

forest in Norfolk, England. According to this application, the tree roots did not significantly

exceed one meter of soil depth. Ritorto et al. (2009) adopted a root depth of one meter for the

mixed pine and oak forest of O'Leno State Park. A notable section of the study area is vegetated









with palmetto scrub, which would have a shallower root depth, and thus 1 m may be an

overestimate of root depth. The maximum soil moisture storage capacity is determined by

multiplying the field capacity of the soil (0.1) by the depth of the root zone (100 cm). Ten

centimeters of precipitation would be needed to fill this soil zone before recharge to the water

table can occur. If less than 10 cm of rain fall on completely unsaturated soil, the precipitation

will remain in the root zone and be transpired, evaporated, or stored. Precipitation may remain

stored in the root zone of the soil and be pushed out to the water table with the following episode

of precipitation; thus it is generally not necessary to have more than 10 cm of precipitation per

event to have recharge to the aquifer.

Sink and Rise Discharge

Discharge into the River Sink and out of the River Rise are based on rating curves that

convert water level (m) to discharge (m3 /s). The rating curve for the River Sink was created by

the Suwannee River Water Management District based on data collected on the Santa Fe River at

O'Leno State Park (Figure 3-1). This rating curve is used when river stage measurements from a

gauge at the O'Leno State Park Bridge ~ 1 km upstream from the Sink are available. The

rating curve used for the River Rise was developed from unpublished data collected by the

Suwannee River Water Management District (Screaton et al. 2004; Figure 3-2). Most of the

water level values used in constructing the rating curve ranged between 9.5 and 11 meter above

sea level, the typical range for base flow at the Santa Fe River Rise, which makes this part of the

rating curve most accurate. Values are absent for river stage levels over 12.5 meters, making

discharges over this level uncertain (Figure 3-2). It should also be noted that the rating curves for

the River Sink and the River Rise are > 5 years old. River bed morphology affects discharge









measurements with relation to cross-sectional area. Scouring and reshaping of the river bed could

result in skewed discharge measurements if cross sectional area has been significantly changed.

Well and Surface Site Monitoring

Data downloaded on a monthly basis throughout this study (2006 2008) included

groundwater levels, water temperature, and specific conductivity in the wells and surface sites,

and stage at the River Sink and the River Rise. Gaps in well and sink data are largely due to

logger failure and loggers were replaced in the wells as available.

Eight monitoring wells were to a depth of 30 meters at variable distances from the

conduit system. The lower 6 meters is surrounded by 5 cm of sand pack and screened to allow

water flow. In January 2006, four wells were drilled and screened at the water table to form

nested pairs with wells screened at 30 meters. The drilling reached limestone bedrock between

2.4 meters and 5.2 meters below the surface. The overburden was largely unconsolidated sands,

but some clay was present around wells 4A and 5A. The four wells were screened over a 3.3

meter (10 foot) interval spanning the water table (Table 3-1).

Water levels in twelve wells and several surface water sites at O'Leno have been

monitored as far back as 2001 (Martin et al. 2006; Ritorto et al. 2009). Monitoring in the shallow

wells began in February 2006. The wells sites in this study were monitored by Van Essen CTD

loggers and In-Situ Mini Troll loggers which were suspended at the screened interval by a plastic

coated cablel. Seven CTD loggers were deployed in the nested well pairs (wells 4, 4A, 5, 5A, 6,

6A, 7, 7A) and the River Sink and the River Rise to monitor water level, specific conductivity,

and temperature. Loggers were generally set to log measurements every 10 minutes, but during

some periods, loggers recorded data every five minutes. Two types of CTD loggers were

deployed in the monitoring wells and surface water sites: loggers designed for depths up to 10

meters were deployed in the shallow wells and surface water sites while loggers designed for









depths up to 30 meters were deployed in the deep wells. The CTD loggers measure water levels

with an accuracy of + 0.1 meter (30 meter loggers) or + 0.03 meters (10 meter loggers). The

CTD divers also log conductivity and temperature. Due to limited supply of CTD loggers, wells

1, 2, 8, and 4A were equipped with mini-Troll loggers which only record water level. The mini-

Troll loggers measured water level with an accuracy of + 0.02 meters.

Conductivity, measured in mS/cm, is the ability of a medium to conduct electrical current

and is used as a proxy for ion concentration in the water. The sensors recorded conductivity with

a 30 mS/cm range. Some loggers were initially set in with an 80 mS/cm range. Conductivity is

highly dependent on temperature, so a correction for temperature was made to calculate specific

conductivity:

Specific Conductance (250C) = Conductivity

1+TC*(T-25)

Where a temperature coefficient (TC) of 0.0191 is used (Section 5.1 Conductivity).

Because the pressure gauges are unvented, water pressure in the monitoring wells and the

surface site was corrected using either a barometric pressure logger in either well 3 (Mini-troll)

or in well 8 (CTD). The corrected pressures were then referenced to a manual water level taken

at each site. Manual water levels in the wells were measured by an electronic tape. The water

level data at the River Sink was collected by measuring distance to the water with the electronic

water level tape from a benchmark above the water. The water level at Sweetwater Lake was

generally taken by surveying from a previously established benchmark to the water level. When

the water level was sufficiently elevated, the water level tape was used to measure the distance

from a marked survey point above the water's surface. The surface water measurement for the

River Rise was made by reading a gauge -10 m from the limestone rim surrounding the spring.









Differences between manually measured water level and logger measured water level were

generally less than 0.7 cm, and shifts greater than this are generally attributed to loggers

physically drifting in the casing or errors in barometric pressure measurements.

Pumping during Drought and Storm Events

As part of a related study, the wells and surface sites monitored during this study were

pumped and sampled every three months throughout the monitoring period and more frequently

during the March 2008 storm event. Although the sampling results are not part of this study, the

pumping perturbed the specific conductivity signals, and thus is described here. The well

samples were obtained using a Grundfos II submersible pump that pumps at a rate of two

gallons/minute. The volume of water pumped from each well varied with the time it took the

water chemistry to stabilize for sampling, which ranged from 7 minutes total pumping time to

over 30 minutes total pumping time. Water was pumped until pH, dissolved oxygen, temperature

and specific conductivity reading stabilized, and samples could be collected. Specific

conductivity fluctuated by up to 0.40 mS/cm in 6 minutes in the wells during pumping

(unpublished field data), while the specific conductivity stabilized quickly in the surface sites

(River Sink, Rise, and Sweetwater).

During pumping, it was often necessary to remove loggers from the wells to accommodate

the pump. When the logger was removed from the well, it was placed in a bucket filling with

well water from the pump while the chemistry stabilized. During the high resolution pumping

during the March 2008 storm event, the loggers were not downloaded, but during some routine

pumping expeditions, the data from the loggers were downloaded and the loggers re-launched.

Slug Tests
Slug tests were performed on eight monitoring wells at O'Leno State Park in order to

determine the variability in hydraulic conductivity at the site. Eight deep wells and 4 shallow









wells were tested using a "slug-out" withdrawal method. Deep wells 1, 2, 7, and 8 and shallow

wells 4A, 5A, 6A, and 7Awere tested in this study and wells 3, 4, 5, 6, 7 were previously tested

by Hamilton (2003 unpublished data). The head recovery in the well was recorded using a logger

placed below the slug, and the recorded data were analyzed using two different methods to

determine hydraulic conductivity of the formation surrounding the well.

The slug tests were conducted by first lowering a pressure transducer into the well and then

lowering in the slug, with a diameter of 3.35 cm, length of 152.5 cm, and a volume of 1303.67

cm3. After several minutes, when the head in the well returned to pre-perturbation level, the slug

was withdrawn as rapidly as possible while recording of the pressure transducer readings below

it was simultaneously started. The pressure transducer recorded water level three times per

second for the first six seconds and recorded at gradually longer intervals following. After the

water level approached pretest values, the pressure transducer was stopped and the test repeated

two more times for each well.

Two different methods were used for analyzing slug test data gathered in the field: the

Hvorslev method, the Bouwer-Rice method.

Hvorslev Method

The Hvorslev method was the first slug test method developed that evaluates the recovery

time in a perturbed piezometer (monitoring well) in relation to the hydraulic conductivity of the

surrounding formation. Hvorslev (1951) found that well recovery was exponential and related to

hydraulic conductivity, the radius of the well, and length of the well screen. Hvorslev's equation

takes different forms depending on the parameters and geometry of the well being tested. In

wells where the length of the piezometer is more than 8 times the radius of the well screen, as in

this case, the following equation is used:










K r ln(L, IR)
2L e
2Let37

Where

K = hydraulic conductivity

r = radius of the well casing

R = radius of the well screen

L, = length of well screen

t37 = time for head to rise 37% of initial change

All of the variables in this equation are measurements taken from the geometry of the well,

except t37 This value is found by plotting the head in the well for a value of time (h), divided by

the maximum head difference in the well (hO) on a logarithmic y axis versus time in the x axis

(Figure 3.3).

Bouwer-Rice method

The Bouwer-Rice method was developed specifically for slug tests in unconfined aquifers,

but can also be used in confined aquifers. The parameters used in this method are similar to those

in the Hvorslev method with the addition of a value representing the radius of well influence.


rc2 In(R / R)1 h
2Le t h,

K = hydraulic conductivity

rc = radius of well casing

R = radius of sand pack

Re = effective radial distance over which head is dissipated

Le = length of the screen









ho = drawdown at t=0

ht = drawdown at t=t

t = time since h = ho

Re is effectively the distance surrounding the well where hydraulic conductivity is being

measured. Bower and Rice (1976) developed a method to determine the relationship In(Re/R)

when the well being tested is not fully penetrating.


In 1.1 A + Bln[(h- L)/R]] 1
R In(L / R) L, IR

L, = distance from water table to bottom of screen

A, B = dimensionless parameters plotted as a function of Le/R (Bouwer, 1989)

The values ht as a function of t were then plotted on a semi-logarithmic plot (Figure 3.3)

and two points representing hi, tl, h2, and t2 were chosen for each slug out test and entered in to

the above formula.

Adjustment for Wells Screened through Sand Pack

Four of the eight wells in the study were shallow wells, drilled to depths of 18-32 feet. In

each of these wells, the water table crossed the well screen and the L, value was adjusted to

reflect the portion of the screen submerged on the day of the slug tests. The radius of well casing,

R, was also adjusted where the water table crossed the screen to include the sand pack in the

radius of the well casing. The adjustment took both the thickness and porosity of the sand pack

into account in the following equation (Bouwer, 1989):


rA = [(1- n)r +nR2 ]


Where r, = adjusted radius










n, = porosity of sand pack


Table 3-1. Summary of well depths, screened intervals, depth to bedrock and ground surface
elevation of all wells at O'Leno State Park used in this study and previous studies.
Ground surface
Completed Depth Screened Interval Depth to bedrock elevation
(m bgs) (m bgs) (m) (masl)
Well 1 23 23-17 17 14.45
Well 2 30 30-24 6 15.96
Well 3 28 28-22 3 17.87
Well 4 29 29-23 5 17.89
Well 4a 10 10-7 5 17.96
Well 5 30 30-24 5 16.22
Well 5a 8 8-5 3 16.2
Well 6 31 31-25 5 13.51
Well 6a 5 5-2 4 13.55
Well 7 30 30-24 5 15.22
Well 7a 8 8-5 2 15.19
Well 8 100 30-24 3 13.32



140 I

Sink Discharge from SRWN1D curve (m3Is) A
120
to Measured Sink Discharge (m3/s)
E 100

o Au




c 40

20
Data and curve from SRWMD

10 10.5 11 11.5 12 12.5 13 13.5 14
Sink Stage (masl)


Figure 3-1. Rating curve developed by the SRWMD for the Santa Fe River Sink. Note: at water
levels below 10.25 there is no discharge at the Sink.













100


9 9.5


Figure 3-2. Rating curve











0.1 ---------- ---


10 10.5 11 11.5 12 12.5
Rise elevation (masi)
for Santa Fe River Rise from Screaton et al. (2004)


Well 4A head ratio vs. time


0.01 ----------------------------------






0.001 II
-10 0 10 20 30 40 50

Time (s)


Figure 3-3. Head ratio vs. time plot used to determine variables in Hvorslev and Bouwer-Rice
slug test calculations.









CHAPTER 4
RESULTS

Precipitation and Recharge

Historically, the average precipitation in the Santa Fe River basin is 137 cm/yr (Hunn and

Slack 1983). During 2006 and 2007, north-central Florida experienced drier than normal

conditions with average rain fall of 88 cm/yr and 103 cm/yr, respectively (Figure 4-1). Despite

two flood events during 2008, precipitation for this year was below average with 101cm.

Precipitation amounts during Tropical Storm Fay illustrate the variability of rainfall over

the Santa Fe River basin, even in a widespread tropical system. Gauging stations in the eastern

reaches of the Santa Fe Basin received up to 9.6 cm of precipitation during Tropical Storm Fay

while the O'Leno gauging station received 4.7 cm of precipitation (Figure 4-2 b). The gauging

stations recorded between 6.5-8.5 cm of precipitation during the March 2008 storm event (Figure

4-2 a); this precipitation during this storm event is more evenly distributed with a smaller flood

pulse than precipitation during Tropical Storm Fay (Figure 4-2).

During 2006 to 2008, recharge to the unconfined Santa Fe River basin was largely due to

small recharge events under 4 cm (Figure 4-1). There were only three events during the study

with daily recharge greater than 4 cm. These three larger recharge events occurred in January

2006, July 2007, and March 2008, and did not show any seasonality in their timing. Significant

recharge occurred during Tropical Storm Fay, but was spread out over four days (Table 4.1). The

smaller recharge events were seen both during winter months when low evapotranspiration

allowed more precipitation to reach the aquifer and during the rainy summer season, despite

higher evapotranspiration. There was significantly less recharge during 2006 and 2007 compared

to average yearly recharge for the region, 45-60 cm/yr (Grubbs 1998); 14 cm of recharge was

estimated to have entered the Floridan Aquifer in the Santa Fe River Basin in 2006 and 27 cm of









recharge during 2007. During 2008, 58 cm of recharge reached the aquifer, the upper part of the

range for the yearly average.

Water Level, Specific Conductivity, and Temperature Monitoring

The water level at the River Rise and throughout O'Leno State Park fell during the spring

of 2006 from 10.7 masl to a baseline level of -9.7 masl (Figure 4-3). Water levels remained low

from August 2006 to March 2008, when a major recharge event and flooding from the River

Sink brought water levels up 10.4 masl at the River Rise and -10.3 masl in the well locations in

the park (Figure 4-4). By June 2008, water levels returned to baseline levels and remained low

until August 2008 when recharge and a river flood pulse from Tropical Storm Fay caused water

levels in the wells to rise to -11.3 masl (Figure 4-5).

Nested Well Pairs Water Level, Specific Conductivity, Temperature

The nested shallow and deep well pairs allow differences in hydraulic head to be

observed. Water levels in the shallow wells and deep wells were nearly identical during much of

the study period when north-central Florida was experiencing drought conditions. The calculated

vertical gradient between the shallow and deep wells was less than the typical water level

monitoring error, indicating that the vertical gradient is too small to be detected by our

equipment.

Significant vertical gradients were present in the nested wells during the Tropical Storm

Fay flood event at O'Leno. Water levels in both the shallow and deep wells began to rise on the

same day at the beginning of the rising limb of the well hydrograph, but the deep well water

level rise outpaces the shallow water level, causing a maximum upward gradient of 0.007. The

gradient is most pronounced in wells 5 and 5A (Figure 4-6). Wells 4 and 4A and 5 and 5A are an

estimated 115 and 125 m from the conduit, respectively (Table 4-2).









The specific conductivity values in the deep wells showed generally stable values

throughout the study with occasional slow, steady climbs in specific conductivity that do not

correlate to any flood event or change in seasonality. Specific conductivity values are

occasionally perturbed by data downloads. Following a data download, measured specific

conductivity value may be slightly higher or lower than the value recorded before the data

download by -0.020 mS/cm. These changes in specific conductivity seen at data collection times

should not necessarily be interpreted as changes in water chemistry or flow patterns unless the

changes in specific conductivity are part of a temporally larger pattern.

During the spring 2007, we noted that the specific conductivities in two of the deep wells

were experiencing significant drift. Some loggers drifted to extremely high values over 0.700

mS/cm in a single month long monitoring period. With each data down load during this time, the

specific conductivity would be reset and rise again to extreme levels during the sampling period

(Figure 4-7 a). This problem was resolved in the spring of 2007 by rinsing the loggers

periodically with acetic acid.

Specific conductivity changes in the shallow wells were more frequent and variable than

the deep wells. Well 6A was the only well in the study to show regular response to diffuse

recharge events. At well 6A, the water table was close to the limestone-sand boundary, so the

screened interval covered both the sand and the limestone (Table 4-3). Some of the drops in

specific conductivity seen at well 6A were not related to recharge, but to data downloads.

Temperatures at the shallow wells, in contrast with the deep wells, showed significant

seasonal variation (Figure 4-7 b). The peak temperature for the shallow wells was reached in

late fall to early winter and annual lows were reached in early to late spring. The magnitude and

timing of the temperature fluctuation at the water table is directly related to the depth of the









water table below the ground surface, with wells screened closer to the surface responding more

quickly than deeper wells. The wells screened at 30 meters in this study showed no temperature

variation. This delayed seasonal variation is seen in other shallow monitoring wells in other field

areas; temperature responds more dramatically with increasing proximity to the surface (Thiros

2003).

Discharge at the River Sink and River Rise

Under typical low flow conditions, the discharge into the River Sink is lower than the

discharge out of the River Rise. When this occurs, the discharge from the River Rise is made up

in part by groundwater from the matrix flowing into the conduit. During a major storm event,

discharge into the Sink can exceed discharge out of the Rise, meaning that some river water is

leaving the conduit and entering the matrix (Martin et al. 2006). The two flood events in 2008

showed greater discharge at the River Sink than at the River Rise (Figure 4-8).

The storm event in March 2008 caused discharge to increase at the River Sink and the

River Rise to 22 m3/s and 19 m3/s, respectively (Figure 4-8). The flow of water from the

conduit into the surrounding matrix occurred over a period of 7 days at the flood peak, based on

higher discharge at the River Sink. The discharge into the River Sink fell from its peak of 22 m3

/s to 2 m3/s, 19 days after the flood peak. The River Rise discharge also began to decline after

cresting the same day at the Sink; the River Rise fell from peak discharge of 19 m3/s to 6 m3/s

19 days later (Figure 4-8).

The discharge during Tropical Storm Fay rose sharply at both the Sink and Rise, despite

only 11 cm of precipitation and 8.6 cm of recharge to the water table distributed over four days

(Figure 4-1). The discharge at the River Sink increased from 0 m3/s to 148 m3/s into the conduit

over six days, and peaked on August 27. Discharge at the River Rise increased from 5 m3 /s, base









flow for the River Rise, to 99 m3/s over the same six days that the Sink discharge increased, with

no observed lag in the discharge curves (Figure 4-8). Sink discharge remained higher than Rise

discharge for 10 days in late August and early September 2008. This reversal indicates that water

from the Santa Fe River was entering the Floridan Aquifer as it left the conduit between the

River Sink and the River Rise. This finding agrees with observed reversals in head gradients

between the conduit and the matrix wells during these two storm events.

Well Response to Recharge and Pumping during Drought and Minor Rain Events

Routine well sampling took place during June 2006, when north-central Florida was in a

drought and a period of declining regional water levels. Well sampling on June 15, 2006 caused

no perturbation to the specific conductivities in the shallow wells the specific conductivity of the

sampled water match values recorded by loggers. Minor perturbations on July 12 were caused

either from removing loggers during data download or due to pumping, which occurred on the

same day. Specific conductivity returns to previous levels within a few days (Figure 4-9).

Recharge events occurred throughout the drought in 2006 and 2007; most events resulted

in minor increases in water level and no appreciable change in specific conductivity at the wells.

There is one notable exception, which occurs at well 6A. On August 2, 2007, an estimated 6.9

cm of recharge reached the water table. Water levels in the shallow wells increased by as much

as 0.22 meters (Figure 4-10 a), but the specific conductivity in wells 5A and 7A remains

stagnant, while well 6A experiences drop in specific conductivity, from 0.423 mS/cm to 0.390

mS/cm over 4 days (Figure 4-10 b).

Well Response to Recharge and Pumping during a Flood Event

Following the March 2008 recharge event, wells 4, 4a, 5, 5a, 6, 6a, 7, 7a, and 2 and three

surface sites, River Sink, Sweetwater, and River Rise were pumped to obtain samples for

chemical analysis. The wells were pumped 7 times, 2-3 days apart, during the rising limb, peak









water levels, and the first part of the recession limb in the well hydrographs. The wells with

functioning loggers during pumping 4A, 5A, 6A, 7A, and 7 -showed a distinct specific

conductivity response to pumping. The specific conductivity values recorded during pumping

showed increases until the fourth or fifth day of sampling, when each well showed a drop in the

specific conductivity (Figure 4-11). The specific conductivity values measured during pumping

varied from the recorded specific conductivity values from the loggers (Figure 4-12); however,

since the pumping values were recorded while pumping was still occurring, both values may

accurately reflect the specific conductivity of the water measured.

The specific conductivity signal measured by the loggers in wells 7A, 5A, and 4A

showed a distinct specific conductivity pattern following pumping; specific conductivity values

measured by the loggers rose by 0.030 and 0.080 mS/cm by the second or third pumping day, but

sharply decreased during pumping of the well (Figure 4-13). The specific conductivity measured

manually during pumping generally corresponded to lower specific conductivity values than

recorded by the loggers immediately after pumping. Well 7 was the only deep well that recorded

specific conductivity values during this event (Figure 4-13); the other wells either were not either

equipped with a logger at this time or the specific conductivity capability was failing, resulting in

erroneous data. The lone deep well showed a rise in specific conductivity from a low value of 0.4

mS/cm on March 7 to 0.49 mS/cm at the peak logger reading, April 1. The variation in specific

conductivity for manual measurements taken during sampling was similar, with readings ranging

from 0.36 to 0.48 mS/cm.

The specific conductivity signal at well 6A shows the opposite pattern from the rest of the

wells. After pumping, the logger records a spike of 0.050 mS/cm in specific conductivity that

decays over two to three days and rises again by the same magnitude with the next sampling









event. The logger in well 6A was installed March 14, so there was no previous baseline specific

conductivity for comparison; however, specific conductivity levels for well 6A tend to fall in the

range of 0.3 0.35 mS/cm (Figure 4-14). During the March 2008 event, pumping during the

flood produced complex specific conductivity signals in the shallow wells and one deep well.

Well and Surface Water Response during Tropical Storm Fay

Following the passage of Tropical Storm Fay on August 21 and 22, water levels in both

surface sites and the wells began to rise on August 23, two days after the main precipitation

event. Surface water levels increased much more rapidly than the well sites; the River Sink

crested on August 27, the River Rise crested on August 28, and most of the wells peaked on

August 30, with the exception of well 6A which peaked on September 2 (Figure 4-5). The

maximum water level of the River Sink was 13.9 meters, and the maximum water level at the

River Rise was 12.4 meters. The specific conductivity at the Sink fell from 0.220 mS/cm to

0.050 mS/cm on August 25, three days after the initial precipitation from Tropical Storm Fay.

Subsequently, specific conductivity gradually increased to 0.123 mS/cm by September 16

(Figure 4-15). Specific conductivity at the River Rise during Tropical Storm Fay was artificially

high due to algae covering the PVC housing the logger. Despite this problem, specific

conductivity showed a significant drop of 0.1 mS/cm during the flood, reflecting an influx of

River water flowing from the conduit. An increase in specific conductivity of 0.04 mS/cm is seen

directly before the drop in specific conductivity begins, possibly reflecting the flushing of higher

specific conductivity water through the system (eg. Grasso and Jeannin 2002).

Despite the flow from the conduit to the matrix and evidence of conduit influence on well

water level, no evidence shows that conduit water reached the deep wells. The specific

conductivity at the deep wells screened at the conduit showed only minor changes throughout the

event, even with significant increases in water level (Figure 4-16).









Shallow well specific conductivity response during Tropical Storm Fay

The shallow wells showed a range of responses to the recharge associated with Tropical

Storm Fay. Two days after the initial recharge associated with Fay, the specific conductivity in

well 6A increased by 0.054 mS/cm over one day, then dropped by 0.100 mS/cm within hours

(Figure 4-17). The specific conductivity remained low for two days, and again rose by 0.1

mS/cm within hours. From August 25-26, well 7A showed an undulatory pattern in specific

conductivity that varied by 0.07 mS/cm (Fig 4-17). During this short time period, wells 4A and

5A showed no significant response to the recharge event.

Water levels continued to rise in the wells until a peak around August 31 (Figure 4-5). As

water level in the conduit reached its maximum on August 28, specific conductivity in well 4A

fell within 30 minutes by 0.260 mS/cm (Figure 4-17). This large drop in specific conductivity,

the largest recorded in a well in this study area, was followed by a rapid rise in specific

conductivity. The increasing specific conductivity at well 4A progressed through two stages: the

first stage lasted for four days with a gradual increase, followed by the second stage lasting

another four days with a much faster increase in specific conductivity. During the same time

period, specific conductivity at well 5A experienced gradual increases over 4 days. Following

this gradual rise, specific conductivity began to increase rapidly in well 5A beginning on

September 2, reaching specific conductivity values of 0.128 mS/cm over baseline value (Figure

4-17). Starting on September 3, specific conductivity in well 6a increased by 0.118 mS/cm over

two days. Following four days of relatively steady specific conductivity in well 6A, values fell

by 0.154 mS/cm over four days, leveling off near values seen before the storm event.

Slug Tests Shallow and Deep Wells

The slug tests were analyzed using two methods, the Hvorslev method and the Bouwer-

Rice method. There was generally good agreement between the two methods for each individual









test run. We saw two ranges of hydraulic conductivity in the study area for the shallow wells and

the deep wells (Figure 4-18).

The Hvorslev method showed higher calculated hydraulic conductivities than the

Bouwer-Rice method in the deep wells, while the Bouwer-Rice method generally showed higher

calculated hydraulic conductivities in the shallow wells. The greatest difference between

methods results in the deep wells was found at well 1 with the Hvorslev method giving 5.47

meters/day (6.34 x 10 5 m/s) and the Bouwer-Rice method giving 3.56 m/d (4.13 x 10 5 m/s).

The largest difference between methods in the shallow wells was in well 4a and the only test run

for the shallow wells where the Hvorslev method showed a higher result than the Bouwer-Rice

method: the Hvorslev method calculated 96.77 m/d (1.1 x 10 -3 m/s) and the Bouwer-Rice

method calculated 56.76 m/d (6.5 x 10 -4 m/s). The hydraulic conductivity calculations for both

tests were very similar in the remaining shallow wells.

Average hydraulic conductivity for the shallow wells was calculated to be more than an

order of magnitude greater than the deep wells (Figure 4-18). The hydraulic conductivity for the

shallow wells averaged 90 m/d, excluding well 6A. Due to its unique well construction, the slug

tests for well 6A measured some of the sand that mantles the limestone, and is not considered an

accurate representation of limestone matrix hydraulic conductivity. Hydraulic conductivity range

for the deep wells averaged ~4 m/d.

Table 4-1. Summary of precipitation, recharge, and water levels during the 2008 floods.
Mar-08 Fay Aug 2008
Precip (cm) 7.2 11
Recharge (cm) 6.9 9
Sink (masl) 10.7 13.9
Rise (masl) 10.45 12.4
Wells (masl 10.36 11.3









Table 4-2. Shortest distances from nested wells to known conduits.
Well Distance from
Number Conduit (m)
4, 4A 115
5, 5A 125
6, 6A 140
7, 7A 1025


Table 4-3 Summary the top of the limestone and water levels during high and low water levels.
Land Top of Water Table Water Table Water Water Table
Surface Limestone Feb 2008 Peak March Table July Peak Fay
Well # (masl) (masl) (masl) 2008 2008 2008
4, 4A 17.89 13.32 9.8 10.32 9.6 11.25
5, 5A 16.2 13.15 9.79 10.32 9.6 11.27
6, 6A 13.51 9.55 9.79 10.32 9.6 11.07
7, 7A 15.22 9.73 9.74 10.21 9.6 10.8

















precip
- recharge


Precipitation and Recharge 2006-2008


0
Jan/1/2006


Jan/1/2007 Jan/1/2008


Jan/1/2009


Figure 4-1. Total precipitation and recharge at O'Leno State Park during the study period, 2006-
2008. The two flood events discussed, March Flood and Tropical Storm Fay, are
noted.



















5
4
3
2

0 L" "






10
1U ~ ~~ 4" --------------------------------------------------------

9 ----------------------------------
1 0 1--------------------------------
71 -------- --------------------------------


I I It~I~7~1~hz7iJ1


* O'Leno
* Union Tower
* New River
* Santa Fe Lake
I Louis Hill


O'Leno
Union
New River
U V Santa Fe Lake
I Ell Louis Hill


\VO rS' c c 4 c c V 4' ( Q $4\' 4 \V \x
.^~ b^~ ^ ^^c^, <


Figure 4-2. Precipitation from the O'Leno State Park rain gauge and other stations in the Santa
Fe River Basin during the two flood events, March 2008 and Tropical Storm Fay.









River Rise Water Level 2006-2008


Tropicdi Storm Fa






---------- ------------ --------------- ------------ --- -------

Marth 2008 Fldod
. . .
- - - - -- - - -

-- ---------
. . .
--- ----------- --- --- ---- --


Lpgger Malifnction
I I


Jan/1/2007


Jan/1/2008


p.


Jan/1/2009


Figure 4-3. Water level from the River Rise for the study period 2006-2008. The flood events
studied are marked and times of logger malfunction are noted.


10.5


10


9.5


9 1
Jan/1/2006


-- - -












--- River Sink
*-*- River Rise
-0- Well 4A
--X--Well 5A
--+--Well6A


Water Levels March 2008


Cn




10.5 ------------------- A---------- ----------- -------- ---------- ---------- -------- -








0 -------- ---------- --- ---------- --------- -------------- ------
9 .5 IIII










Febl29/2008 Mar/8/2008 Mar/1 6/2008 Mar/24/2008 Apr/1/2008

Figure 4-4. Water levels at the River Sink, River Rise, and shallow wells during the March 2008
flood event.
95 1 __ _J____ ___ I ____ I ____
Fe/2/20 Ma//20 Ma/ 6/00 Ma/420 Ap/ /20
Figure 4-4 Wae level at th Rie ikRvrRs n hlo eluingteMrh20
flo event.rC I I










Water Level Tropical Storm Fay


-B- Sink
-0- Rise
-o- Well 4A
--X--Well 5A


9 1 I I I I I I1
Aug/17/2008 Aug/27/2008 Sep/6/2008 Sep/16/2008
Figure 4-5. Water levels at the River Sink, River Rise, and shallow wells during Tropical Storm
Fay flood event.










Water Levels Wells 5&5A


11.5





11



-j

10.5





10


9.5 I I I I
Aug/17/2008 Aug/27/2008 Sep/6/2008


Sep/16/2008


Figure 4-6. Head difference between wells 5 and 5A showing vertical gradients during the flood
pulse of Tropical Storm Fay.










SWell 6A
-- Well 6
21.5

21

20.5


1


Feb/1/2006


Temperature -Well 6&6A


Aug/1/2006


Feb/1/2007


-- Well 6a
-a- Well 6


Conductivity, Well 6&6A


0.4 ---


0.3--------\I ----------------- I----------- -------- -- I-------- --- ---------
0.3 -


0.2
Dec/31/2005 Jul/1/2006 Dec/31/2006 Jul/1/2007 Dec/31/2007
Figure 4-7. Temperature and specific conductivity changes over 18 months in a shallow well and
deep well in the study area.


- -----------+-------------+------ -- ---------f-+------------t-+---------

-- - - ----I 16 -- - - -I- - -




- ----------- -------- ----- --------- ------ ------ ----------- ---------




------ -- ----I --------------


Aug/1/2007


1 8










160
140
120 Si-ik is didil(uIII )
100
80 Rise Discharge (cms)
60
40
20
0K







Figure 4-8. Discharge from the River Sink and the River Rise for 2008.


Pumping effects on specific conductivity
during low flow
0.6



0.55---- ---------------------- --------



S--0.5



0.45


e 5A
S 0.4 6A -----------


0.35


0.3 L'
May/11/2006


Jun/22/2006 Aug/3/2006


Figure 4-9. Specific conductivity responses and recovery at the shallow wells during low flow.
Specific conductivity values measured during pumping are plotted and pumping
periods are marked.
















Recharge Event-August 2007


JuV19/2007 Jul/29/2007


Aug/8/2007 Aug/18/2007


Specific Conductivity-August 2007 Event


Jul/21/2007 Jul/31/2007 Aug/1i 0/2007


Figure 4-10 a,b. Water level and specific conductivity response to a diffuse recharge event. Well
6A shows the only discernable specific conductivity response to the diffuse recharge.


- 5a
-- 6a
-- 7a

9.9 i


9.4 1-
Jul/9/2007


0.25 -
Jul/11/2007




















A

A


- - -- -- -- -- - -~-- -- -- -- t--- -- - -- - -- -
A

-- -- ---------------- - ^- - -










- -- - ---
*

**


A *






---------------- ----------------- ------- - - - -


----------------------------------------


Mar/20/2008


Mar/30/2008


Figure 4-11. Values recorded during pumping at the shallow wells during March 2008.


* 4A
A 5A
* 6A
* 7A


0.55



0.5



0.45



0.4



0.35


0.3 -



0.25
Mar/10/


2008












Logger and Pumping
Specific Conductivity Values


- Well 4A Logger
- Well 5A Logger
- Well 7A Logger
Well 4A Pumping


0.2 -
Feb/24/2008


Mar/30/2008 May/4/2008 Jun/8/2008


Figure 4-12. Specific conductivity measurements from both loggers and pumping during the
March 2008 flood.


Jul/1i 3/2008











e Well 7 sp.cond

07


0.5




0.45 ----





0.4 A





0.35 -




0.3 -
Mar/5/2008


Well 7 Pumping and Loggers


Apr/2/2008


Apr/30/2008


Figure 4-13. Specific conductivity in well 7 showing both pumping and logger values. Well 7
was the only deep well with a functioning logger during the March 2008 event.











Well 6A Logger
a Well 6A Pumping


Well 6A Pumping and Loggers


0.55




0.5




0.45




0.4




0.35




0.3


0.25
Mar/10/2008


---------- :- ------













--- --- -- ---- -- ----
- - - - -



-- - - -


Mar/20/2008


*


Mar/30/2008


Apr/9/2008


Apr/1 9/2008


Figure 4-14. Specific conductivity values from both pumping and loggers in well 6A during the
March 2008 flood event.










0.5

S-Sink

;-- Rise
0.4 -----1










0 .3 \-- ------ - - -
0.3



0.2




0.1






Aug/1 7 Aug/22 Aug/27 Sep/1 Sep/6 Sep/11 Sep/1 6
Figure 4-15. Specific conductivity response at the River Sink and the River Rise during Tropical
Storm Fay. Note that the River Rise was likely reading artificially high specific
conductivities due to algae growth on the logger housing.











0.55 I I 1

Well 4
-WWell 5
Well 7
0.5 -



03
E
0.45



0
C
4-r
0.4 ---------------------------------





0.35





0.3
Aug/17/2008 Aug/25/2008 Sep/2/2008 Sep/10/2008

Figure 4-16. Specific conductivity response at the deep wells during Tropical Storm Fay.
Specific conductivity fluctuations, if any appear to be minor.














A -
--6A



0.7 -






0.6 -
E

E


t5 0.5





O 0.4
Co



'0
(,
Q- 0.4






0.3


Specific Conductivity-Shallow Wells


Aug/17/2008 Aug/27/2008 Sep/6/2008 Sep/16/2008

Figure 4-17. Specific conductivity response in the shallow wells during Tropical Storm Fay







1000


-A.. ... ..IL.


Figure 4-18. Results of hydraulic conductivity calculations from slug tests. Note y axis is in log
scale.


* Hvorslev (m/day)
* Bouwer-Rice (m/day)


1









CHAPTER 5
DISCUSSION

Integration of the slug test results and the specific conductivity observations provides

insight into the feedback effects between permeability enhancement and dissolution in the

unconfined upper Floridan aquifer. In this section, the timing of specific conductivity variations

is used to identify arrival of diffuse and conduit recharge at the wells. Then, a 2-D groundwater

model is used to understand whether the known variations in hydraulic conductivity could be

responsible for the inferred patterns of diffuse and conduit water migration.

Slug Tests and Applicability to Matrix Hydraulic Conductivity

Calculations using both the Hvorslev Method and the Bouwer-Rice method to interpret

slug tests conducted at O'Leno State Park show that matrix hydraulic conductivity is higher at

the water table than deeper in the aquifer (Figure 4-19). This result affirms previous findings that

hydraulic conductivity at the top of the limestone often has higher hydraulic conductivity than

the rest of the aquifer (Williams 1983; Mylroie and Carew 2003). A likely cause of dissolution at

the water table is diffuse recharge from precipitation, which is undersaturated with respect to

carbonate minerals. Dissolution at the top of the limestone forms a higher permeability zone,

called epikarst (Williams 1983). The dissolution can be especially vigorous when diffuse

recharge passes through a soil zone that has higher CO 2 (Mylroie and Carew 2003). Epikarst

development will be further advanced by the presence of the water table near the top of the

limestone (Mylroie and Carew 1995).

Lower hydraulic conductivity at well 6A, relative to the other shallow wells, may be

related to lithology (Table 4-3). Because well 6A is screened in the sands above the water table,

the calculated hydraulic conductivity value may partially reflect the value of the sands rather

than the underlying limestone. Typical hydraulic conductivity values for sand are 0.01-10 m/d or









1. 1x10 -1.1x10-4 m/s (Schwartz and Zhang 2003), lower than the hydraulic conductivity

calculated at well 6A (3.3x10 4). Alternatively, the limestone near well 6A may have less

primary porosity, a depositional artifact, or this area could have fewer dissolution produced

preferential flow paths.

Well 2 showed an oscillatory response to the slug tests, indicating very high hydraulic

conductivity (Weight and Sondregger 2000). Well 2 has chemistry that is characteristic of water

upwelling from deep in the aquifer (Moore 2009). Higher hydraulic conductivity and upwelling

water may be related in this case, but it's unclear if upwelling causes dissolution that creates

higher hydraulic conductivity or if the upwelling preferentially flows into higher hydraulic

conductivity areas. The calculated hydraulic conductivity in well 7 is higher than the other deep

wells that were analyzed (Figure 4-19). Well 7 is the furthest well from the conduit and may sit

near the shifting spring shed boundary for the River Rise (Figure 2-1, Table 4-2). Well 7 is

characterized by the smell of sulfur during pumping and has a unique chemistry compared to

other wells in the study area (Moore 2009). Moore (2009) suggests that upwelling water from

deep in the Floridan aquifer influences the chemistry of well 7.Upwelling water and higher

hydraulic conductivity may be related in this location.

Specific conductivity response in shallow wells: evidence for reactive water

Initial well Response: Tropical Storm Fay

The rapid rise and subsequent fall of specific conductivity in wells 6A and 7A on August

23 and 24 is interpreted as a piston flow response from diffuse recharge in which high specific

conductivity water stored in the soil zone being pushed out of storage (Figure 4-18). The soil

zone above the aquifer is rich in CO2 from biogenic production of CO 2 in the soil. CO 2

produced in the soil by micro- and macro-soil flora and fauna tends to circulate in the sandy soil









and acidify the water stored in the soil. During a diffuse recharge event, the first water to reach

the water table is the more acidic water stored in the soil zone. This acidic water is pushed out of

the soil zone when precipitation fills the soil to its field capacity, 10 cm in O'Leno State Park

(Ritorto et al. 2009). When the water from the soil zone reaches the water table it will begin to

dissolving the surrounding limestone, increasing specific conductivity. The arrival of lower

specific conductivity water suggest that after the soil zone is flushed of stored water, dilute

meteoric water can reach the water table and mix with the matrix water (Figure 4-18). This

effect should be widespread across the water table. The timing of the specific conductivity

response in well 7A lagged one day behind the response in well 6A, which may be because the

water table is farther from the surface at well 7A (Table 4.3).

Shallow Well Response to Peak Flood Level

The possible sources of dilute water to well 4A are diffuse recharge from precipitation,

recharge from overland flow, or influx of conduit water. The timing of the dilute water suggests

that it is not from diffuse recharge (Figure 5-1). The specific conductivity response in well 4A on

August 29 occurs five days after the specific conductivity drops seen in wells 6A and 7A which

are attributed to diffuse meteoric recharge. No precipitation or diffuse recharge occurs after

August 25, except 0.4 cm of precipitation that contributed no calculated recharge (Figure 5-2).

Overland flow between the River Sink and River Rise has occurred during major floods,

notably the flood event during March 2003 when the stage at the River Sink reached 14.4 masl

(Martin et al., 2006). Martin and Dean (2001) state that overland flow can occur when the Santa

Fe River reaches 14.20 meters above sea level. The maximum height for the River Sink from

2006-2008 was 13.9 masl in response to Tropical Storm Fay. Field observations support some

overland flooding at O'Leno State Park during Tropical Storm Fay, especially near the River

Sink. Well 4A is closer to the River Rise and this area is locally at higher elevation (17.89 masl;









Table 4-3) than surrounding areas (13-15 masl; Table 4-3), and patchy overland flow from the

River Sink would be unlikely to flow over this minor topographic high; any overland flow would

have flowed in low-lying swamps or ditches leading to the River Rise.

Because the diffuse recharge and overland flow seem unlikely explanations, the lowered

specific conductivity response at well 4A is attributed to migration of conduit water. Allogenic

recharge from the conduit into the matrix began on August 25 and continued to -September 7

(Figure 4-5, Figure 4-8). The matrix area surrounding well 4A appears to have a direct

hydrologic connection to the conduit through preferential flow paths or smaller, centimeter scale

conduits, allowing dilute conduit water to reach the well quickly without equilibrating with the

surrounding matrix.

Well 5A shows specific conductivity that increases from baseline levels on September 1,

three days following the drop in specific conductivity in well 4A, while water levels in the wells

were still near peak levels (Figure 5-3). Well 6A shows similar increased specific conductivity

two days after well 5A (Figure 5-4). Both well 5A and 6A show a gradual, but significant rise in

specific conductivity. Similar to well 4A, these specific conductivity responses in wells 5A and

6A may reflect conduit water reaching the water table wells. Conduit water apparently reacts

with the formation prior to arriving at wells 5A and 6A, increasing the specific conductivity.

This contrasts with well 4A, where a low specific conductivity signal was observed prior to the

elevated specific conductivity (Figure 4-18). The elevated specific conductivity signal suggests

that conduit water arriving at wells 5A and 6A has already begun significant dissolution in the

matrix as the water flowed through the matrix, rather than moving through preferential flow

paths, as inferred for conduit water migration to well 4A. The large pulse of conduit water would

likely have higher P C02 than the water in the matrix and therefore greater potential to dissolve









the limestone. Water originating from the surface is assumed to equilibrate with atmospheric

levels of CO 2 giving surface water higher P CO2 than groundwater. In contrast, water in the

matrix is not in connection with the atmosphere and has no biogenic sources of CO 2, resulting in

a comparatively lower P CO2 in the matrix water (Ford and Williams 2007). The higher P CO2 of

the conduit water allows greater dissolution than baseline levels in the wells.

Specific Conductivity Signal During the March 2008 Event

Sources of water, flow paths, and resulting specific conductivity signals are complex

during the March 2008 flood event. The most significant cause of the difficulty interpreting the

results is the seven pumping periods in the wells during the rising limb, flood crest, and recession

curve.

An immediate response to the 7 cm of diffuse recharge on March 7 to the aquifer was seen

at one shallow well. At well 7A, the slight increase and subsequent drop in specific conductivity

on March 7-8 is interpreted as diffuse recharge reaching the water table (Figure 4-13). The initial

rise in specific conductivity from a diffuse recharge event seen at wells 6A and 7A during

Tropical Storm Fay is not clearly present in this storm event. This may be due to seasonality in

presence of CO 2 in the soil zone (Ford and Williams 2007) that causes lower P C2 in water

stored in the soil zone during cooler months. In addition, residence time of water stored in the

soil zone could be a factor in specific conductivity of water reaching the water table. The soil

zone was flushed with 3 cm of recharge two weeks before the March event and flushed with 5

cm of recharge five weeks before the Fay event (Figure 5-5).

Pumping at the wells in O'Leno State Park began on March 11, 3 days before the flood

peak in the river and conduit system. On March 16, two days after a round of pumping, specific

conductivity fell significantly at well 4A, from 0.514 mS/cm 0.382 mS/cm (Figure 5-6). As









discussed earlier, a similar specific conductivity drop though of a greater magnitude was seen

at well 4A during flooding from Tropical Storm Fay. As with the response to Fay, the lower

specific conductivity response was likely sourced from the conduit. This water was pushed from

the conduit near maximum gradient between the conduit and the matrix, on March 14 (Figure 5-

6). There was no precipitation or recharge in the O'Leno area other than the 7 centimeters of rain

that initiated the high water levels in March 2008 (Figure 5-5), minimizing the possibility of

diffuse recharge as a source of undersaturated water. The peak water level in the River Sink was

10.6 meters, well below the threshold for overland flow established by Martin and Dean (2001).

There was no overland flow between the River Sink and the River Rise observed during field

work during the flood event. Thus, conduit water appears the most likely source.

Pumping in karst aquifers can preferentially draw water from conduits or high permeability

zones (Marechal et al., 2008), which do not necessarily have the same chemical composition as

water stored in the matrix. Specific conductivity monitoring at O'Leno State Park provides

insight into aquifer chemical heterogeneity and flow paths. During periods of low flow and low

diffuse recharge, specific conductivity measurements taken during pumping were very close to

values read by the loggers (Figure 4-9) and the loggers did not record significant perturbations

due to the pumping. The matching specific conductivities suggest that during low flow the water

stored in the matrix is similar to that of the conduit. In contrast, significant specific conductivity

fluctuations were observed during and following pumping during the March 2008 flood event,

suggesting compositional differences between conduit and matrix water.

Beginning on March 17, pumping in the wells began to perturb the recorded specific

conductivity signal (Figures 4-13). This water may come from the conduit, which began to flow

into the matrix on March 12. The conduit water is the only source of water that is undersaturated









with respect to calcite and has higher P CO2 following the diffuse recharge event. The rise in

specific conductivity following pumping periods suggests dissolution due to the circulation of

the undersaturated conduit water.

Following the pumping period on March 17, specific conductivity in well 4A rose by 0.200

mS/cm in four days. The increase in specific conductivity began immediately after pumping

ended, suggesting that the pumping drew in water that began aggressive dissolution at well 4A.

A pattern of rising specific conductivity between pumping periods, followed by lowered specific

conductivities during pumping, was also seen at well 5A and well 7A, although there was no

drop in specific conductivity from conduit sourced water in well 5A or 7A as seen on March 16th

in well 4A. Specific conductivities measured during pumping confirm the record from the

loggers; the specific conductivity measured during pumping at both 4A and 5A is well below

logger measurements (Figure 4-13) indicating pumping draws in dilute water. This may have

driven dissolution around the well. Following the last pumping period in wells 4A, 5A, and 7A

on April 1, specific conductivity returned to pre-pumping levels (Figure 4-13), indicating that the

specific conductivity fluctuations were due to conduit influenced flow brought to the wells by

pumping during the flood on the Santa Fe River.

While wells 4A, 5A, and 7A showed decreasing specific conductivity responses to

pumping followed by increasing specific conductivity, well 6A showed the opposite response.

Rising specific conductivity in well 6A during pumping shows that water pulled in from

pumping did not come from the same dilute source as seen in other shallow wells pumped in this

study. This result emphasized the chemical heterogeneity in karst aquifers and the various

sources of water that may be tapped during pumping.









Interpretation of Specific Conductivity Response using Groundwater Modeling

Prior to this study, the conceptual model for this system was that when water flowed from

the conduit into the matrix, it would flow into the matrix surrounding the conduit and along

preferential flow paths at the level of the conduit. Seeing a significant specific conductivity

response at the water table but not at the deeper wells days after an allogenic recharge event

requires that the conceptual model be modified.

A two-dimensional model was constructed in MODFLOW (McDonald and Harbaugh

1984) using known aquifer parameter values to visualize the possible flow paths from the

conduit into the matrix. Additionally, modular three-dimensional transport (MT3D) simulations

were run to show transport paths of recharged water from both allogenic recharge and diffuse

recharge. The MT3D program uses results of the MODFLOW simulation to model the transport

vectors and velocities into and out of cells. MT3D is generally used to model contaminant

transport, but in this case a concentration of 100 is assigned to the conduit water to allow

concentrations to be interpreted as percentages of recharged water, rather than concentrations.

No reactions between river water and matrix water or diffusion or dispersion within the matrix

were considered in this simulation.

A grid of 50 columns and 10 layers was constructed with the conduit represented at the

west end of the model, and the eastern edge representing a no-flow boundary. Each column is 25

meters wide at near the conduit, grading to 100 meters in width at the distal end of the model.

The thickness of the model is set at 100 meters-equal to the estimated thickness of active flow in

the upper Floridan aquifer in the Santa Fe River Basin-and divided into 10 layers to which

variable hydraulic conductivities and recharge amounts can be applied. Hydraulic conductivities

were assigned based on actual values measured by slug tests. The hydraulic conductivity for the

top two layers, which includes the water table, was set at 120 meters per day (the maximum









value of the hydraulic conductivity calculated from slug tests at the shallow wells; Figure 4-19)

and the remaining eight layers were assigned a hydraulic conductivity of 4 m/d (the average

value of the hydraulic conductivity calculated from slug tests at the deep wells; Figure 4-19).

Porosity for the model was set at 0.3 and specific yield the water drained from a porous

medium by gravity is 0.2 (Palmer 2002). Effective porosity was adjusted during the simulation,

because this value is difficult to assess in karst aquifers (Renken et al. 2005).

The conduit was placed in layer five of the model, corresponding to a depth of 40 meters

below the water table. The conduit was simulated by placing a single cell constant head

boundary in layer five, using water level values from the River Rise to approximate head in the

conduit. Daily recharge values calculated for this study (Figure 4-1) were applied to the top layer

of the model. Initial head values for the matrix were set at 9.8 meters, the average water level in

the monitoring wells on June 1, and then allowed to fluctuate in response to recharge and

changing head in the conduit.

Two separate models were run to simulate the flood events for March 2008 and Tropical

Storm Fay. The initial rain event that induced flooding on the Santa Fe River in March 2008,

occurred on March 7, but model simulation began on January 1, 2008 in order to establish a

typical, low-flow matrix-to-conduit flow regime in the model before perturbing the system. The

model simulation for Tropical Storm Fay began on June 1 to establish antecedent conditions

during the low-flow months during the summer leading up to the Fay flood event.

2-D Modeling of Conduit-matrix interactions during Tropical Storm Fay

During Tropical Storm Fay, elevated specific conductivity values were seen at the shallow

water table wells, but not at the wells screened on the level of the conduit. An explanation for

this effect is demonstrated by 2-D modeling in a cross-sectional groundwater model of the

Floridan aquifer at O'Leno State Park.









Flow vectors in the model for August 17 show water moving from the matrix into the

conduit, as the head in the matrix is higher than the head in the conduit at this point (Figure 5-7

a.). Relative flow velocities are indicated by the size of the arrows; faster flow velocities have

larger arrows. Velocities can be compared in the each model diagram, but not between model

diagrams, as the vectors are scaled differently for each time step. The fastest flow velocities are

in the top two layers of the model, which have a higher hydraulic conductivity (120 m/d) than the

rest of the layers.

On August 22, the first day of recharge occurred at O'Leno State Park. The recharge

added to the aquifer caused the head contours (shown in blue) to become slightly more

horizontal in the lower part of the model (Figure 5.7 b.). The shift in head contours means that

recharge has shifted gradients to direct water down in the lower part of the model, but head

contours remain vertical in the upper layer of the model. This means that even with recharge,

horizontal flow paths towards the conduit still dominate in the upper part of the model.

On August 28, peak water levels were reached in the River Sink and the River Rise and

maximum gradients occurred between the conduit and the matrix (Figure 5-7 c). Numerous head

contours surrounding the conduit show the large gradient between the conduit and the matrix on

this day. Flow vectors are directed up toward the high hydraulic conductivity layers throughout

the model, but velocities in the lower layers remain very small compared to velocities in the

upper layers. These lower velocities indicate that though water is moving through the lower area

of the model, the velocity at depth is much lower than at the water table.

Vertical hydraulic gradients indicate upward flow between the deeper layers and the upper

layers beginning on August 24, the first day conduit water entered the matrix. These upward

vertical gradients, which were also seen in actual water levels in the shallow and deep wells at









O'Leno, are indicated by head contours reaching farther into the deeper layers than in the

shallow layers. A vertical gradient, with hydraulic head higher in the deeper part of the aquifer,

will move water up from depth. The vertical gradient assists in moving water to the water table,

but flow velocities in the matrix are very small, which can explain why no specific conductivity

response was seen at the deep wells.

On September 5, the gradient reversed and water began to flow from the matrix into the

conduit (5-7 d). The model dates of gradient reversals match well with actual discharge

measurements at the River Sink and River Rise (Figure 4-8) and water levels at the surface water

sites and the monitoring wells (Figure 4-5).

This simulation showing head contours and flow vectors and velocities show possible flow

paths for water sourced from centrally located conduit in an aquifer with a higher hydraulic

conductivity zone near the top. These results support the interpretation that specific conductivity

fluctuations in shallow wells at O'Leno during Tropical Storm Fay could be due to conduit

influence. Flow paths for water in this system have been established, but the next step is

determining if significant quantities of river water could be able to reach shallow wells using

MT3D.

Modeled Concentrations of conduit water

The modeled aquifer has 0% conduit water in it until water flowed from the conduit to the

matrix on August 24. The first conduit water leaves the conduit on all sides, though conduit

water travels further up towards the water table. This initial step shows some conduit water

moving out 25 meters from the conduit (Figure 5-8, a). On August 26, river water reaches the

water table and begins to move along the top layers of the model much more rapidly than river

water in the lower matrix (Figure 5-8, b). On September 4, the last day that water leaves the

conduit, the extent of river water reaches its maximum at the water table (Figure 5-8, c). At its









maximum extent, river water reaches over 300 meters from the conduit into the upper matrix.

The concentrations do not dissipate quickly; rather they tend to linger in the upper part of the

aquifer. The presence of river water in upper layers of the model demonstrates a possible

explanation of why there was a significant change in specific conductivity in the shallow wells.

By the end of the simulation, there are still significant conduit concentrations in the aquifer, but

in the actual aquifer, this conduit-derived water would have induced dissolution and taken on a

higher specific conductivity signal (Figure 5-8, d).

The primary factor controlling the distance conduit water flows through the matrix is the

effective porosity (Figure 5-9). For river water to reach the wells, an effective porosity used in

this model is 0.01, meaning that the majority of the flow moves through 1 percent of the total

volume of rock. A block of rock with equal volume can have similar permeability and total

porosity, but can have very different effective porosities depending on the interconnections

between small conduits or preferential flow paths. Decreasing the effective porosity in the model

decreases the available space for the water to flow through. When no other factor is changed (eg.

discharge from the conduit), water is forced to flow through the available pore spaces at a greater

velocity and can flow further into the aquifer. Lowering the effective porosity to 0.01 is

comparable to simulating a conduit with a 10 cm diameter in a zone 10 meters thick, the same

thickness of the higher hydraulic conductivity area of the model. Changing hydraulic

conductivity in the model did not elevate conduit water concentrations beyond what is thought to

be necessary to produce specific conductivity responses seen at the shallow wells (> 10% conduit

water). Hydraulic conductivity appears to influence head contours, while effective porosity has

no effect observable effect on head contours in the model.









The approach of lowering effective porosity well below total porosity has been used to

explain observed tracer velocities in the karstic Biscayne aquifer in south Florida. Renken et al.

(2005) found that effective porosity in the Biscayne aquifer was an order of magnitude lower

than previously assumed. Renken et al. (2005) used effective porosity to describe the velocity of

a conservative tracer introduced at an injection well in the Biscayne aquifer. The velocity of the

tracer was one two orders of magnitude greater than previously measured. To reproduce field

observations, Renken et al. (2005) modified a mass balance equation for a radially converging

flow regime to calculate effective porosity at 2-4% of total porosity.

Modeled concentrations of diffuse recharge

A model simulation was run to show the movement and percentages of recharge at the

water table during the Tropical Storm Fay model simulation. To examine only the movement of

diffuse recharge, the conduit water concentration was assigned a value of 0, and a concentration

of 100 was assigned to the incoming diffuse recharge. Because no reactions were modeled in this

simulation, recharge in the model does not equilibrate with the surrounding matrix water; it only

mixes with the matrix water. When water enters the top of the aquifer as diffuse recharge, it

flows with the local gradient along the water table from the matrix to the conduit (Figure 5.10,

a). The diffuse recharge makes its way into the lower layers of the aquifer over tens of meters

near the conduit forming a wedge of down welling water from the water table. On August 29, the

gradient in the conduit had reversed and water was flowing into the matrix (Figure 5.10, b). The

river water flowing out of the conduit pushes the diffuse recharge away from the conduit as

conduit water (here in blue) floods the water table. This supports the previous conclusion that a

drop in specific conductivity at well 4A during Fay is not likely to be due to diffuse recharge or

overland flow. The model shows that these sources of water were being pushed away from the

wells, rather than flowing towards them. On the last day of the modeling simulation, October 14,









water is flowing from the matrix into the conduit and the diffuse recharge is flowing into the

conduit (Figure 5.10, c). The last diffuse recharge into the aquifer at this point was one month

previously. The diffuse recharge appears to be long lasting at the water table and shows very

little mixing with the lower layers. This could explain the differences in specific conductivity we

see consistently between the shallow and deep wells (Figure 4-17; Figure 4-18). The higher

hydraulic conductivity in the upper layers moves water horizontally to the conduit, overpowering

any vertical gradient that is present between the shallow and deep wells.

Model applied to the March 2008 Flood event and pumping

A model with the same dimensions and aquifer parameters as the model used to simulate

the Fay storm event was used to visualize flow paths and conduit water penetration into the

conduit. The March 2008 flood event showed flow paths and flow vectors similar to the flow

paths seen in the Tropical Storm Fay event, but the movement of river water through the matrix

was much more limited.

The March 2008 event begins with water flowing from the matrix into the conduit, a

typical occurrence during low-flow times. On March 7, the single largest day of recharge in 2008

is shown in the model (Figure 5-11, a). The recharge creates strong vertical gradients that cause

recharged water to flow down in the lower layers. Flow vectors in the upper part of the model are

angled slightly downward, but velocities are comparatively large. This suggests that the primary

direction for water flow, even with significant recharge, is horizontal. Peak water level in the

conduit was reached on March 14 (Figure 5-11, b). Head contours do not show the large gradient

present during Fay, but flow vectors show water moving from the conduit towards the water

table. Following the peak flow of water from the conduit to the matrix, the gradient reverses

quickly; water begins flowing back into the conduit from the matrix on March 17 (Figure

5-11, c).









The flood event was largely influenced by diffuse recharge, rather than overwhelmed by a

large pulse of flood water from the Santa Fe River. Precipitation in Santa Fe River Basin was

evenly distributed on March 7 and runoff from upstream did not produce a large flood pulse on

the River. Water level in the aquifer responded to the diffuse recharge and rose approximately at

the same rate as the River Sink and the River Rise so hydraulic head in the conduit exceeded

hydraulic head in the matrix for only a few days.

An MT3D simulation was run with the cell-by-cell flow data calculated by MODFLOW

for the March 2008 storm event. The MT3D model uses a concentration of 100 applied to the

conduit water, to estimate percentages of river water that may have reached the monitoring wells.

Simulations show that on March 14, river water left the conduit and flowed into the cells

surrounding the conduit. The cell directly east of the conduit had a maximum of 5% of river

water during the modeling run. Gradients between the conduit and the matrix were fairly small,

so significant amounts conduit water did not reach the shallow well 125 meters away, or even to

the water table directly above the conduit (Figure 5-11). The pumping at representative shallow

and deep wells was modeled, but pumping rates were too small (7.5 liters/min) to affect flow

lines, flow vectors, or concentrations. The model simulations during Tropical Storm Fay showed

good agreement with timing of gradient reversals between the conduit and the matrix. The model

also seems to be capturing the effect of conduit water moving through the aquifer during the

simulation of the Fay flood. This further suggests that the effect of pumping is not being

captured by the model. Pumping of the shallow wells during the March 2008 flood, rather than

the gradient between the conduit and the matrix remains the most likely cause for specific

conductivity changes seen at the shallow wells during pumping in March 2008.









Implications

The chemical state of the matrix waters will be addressed when samples taken during the

March 2008 are analyzed and interpreted. Integration of the sampling results and the results

presented here using specific conductivity and groundwater modeling will further test the

interpretation of conduit water flowing to the shallow wells.

Dissolution at the top of the limestone is often thought to be primarily influenced by

diffuse recharge (Mylroie and Carew 1995); it is frequently thought of as a top-down process.

But these findings suggest that dissolution can occur at the water table from allogenic source

injected deep in the aquifer that flows up to the water table. The higher permeability layers

created by diffuse recharge focus flow along the water table, resulting in a feedback effect

between the dissolution caused by diffuse and allogenic recharge.

Diffuse recharge events are credited with dissolution that occurs uniformly at the water

table in mantled unconfined karst aquifers (Ritorto et al. 2009). If dissolution occurs at the water

table from the influence of conduit water, as the results from this study suggest, the magnitude of

dissolution at the water table would be increased significantly. Though the volume of water

reaching the shallow wells is not known, it is significant enough to cause a persistent specific

conductivity perturbation in the wells, whereas the majority of diffuse recharge events at O'Leno

do not show specific conductivity responses. Yet if dilute precipitation is entering the aquifer, the

water is coming to equilibrium by dissolving carbonate. Ritorto et al. (2009) found that the

magnitude of dissolution of limestone at the water table is similar to the magnitude of dissolution

at the conduit. But with an additional influx of dilute conduit water to the water table, the water

table could be the primary site of denudation in the aquifer.

Groundwater modeling in this study suggests that diffuse recharge to the model does not

readily mix with the lower layers in the conduit, but remains in the upper, higher hydraulic









conductivity layers (Figure 5-10). The diffuse recharge tends to move horizontally along the top

of the water table until it nears the conduit and then flows down toward the conduit, along the

same paths that water leaving the conduit and flowing towards the water table would follow.

This raises the possibility that dissolution-enhanced preferential flow paths could develop in the

area connecting the conduit with the water table, due to two sources of recharge, which are at

times undersaturated with respect to calcite. If these preferential flow paths occur leading to and

from the conduit and water table, it may offer an explanation for why a low specific conductivity

response was seen at well 4A (the closest well to the conduit) and why this signal was not seen at

the wells further from the conduit.

The concept of water flowing primarily through high hydraulic conductivity zones could

be applied to other zones of high hydraulic conductivity at various levels in the aquifer. The

Floridan Aquifer, for example, has several layers of very permeable, vertically limited zones that

are generally associated with dissolution enhanced bedding planes (Miller 1986). That no

significant specific conductivity response was seen at the wells screened at the level of the

conduits could have two possible causes. There may not be a high hydraulic conductivity layer at

the level of the conduit; if there was a high hydraulic conductivity zone, conduit water should

have flowed through this zone and produced a specific conductivity response in the deep wells.

It's also possible that a high hydraulic conductivity layer or proto-conduit exists, but the logger is

too far removed from the specific conductivity to detect it. The deep wells are screened at the

average level of the conduit (24-30 mbgs), but the conduit may be up to 36 m below ground

surface (Old Bellamy Cave System, 2009).

The groundwater model was created to show how water from the conduit can influence

wells at the water table used known parameters about the conditions during the floods and about









the Floridan aquifer: gradient, hydraulic conductivity, total porosity. Effective porosity is not

well known in the Floridan Aquifer and was therefore adjusted during the model simulations. We

found that to bring conduit water to a well 125-150 meters away, water velocities needed to

increase significantly. Lowering the effective porosity to reflect water flowing only through

interconnected preferential flow zones or small conduits produced greater velocities. The role of

effective porosity and water velocity in this study and other studies (Renken et al. 2005), indicate

the vulnerability to rapid transport of contaminants in karst aquifers. This risk of aquifer

contamination is further increased by the inability to map or definitively investigate small

conduits and the many sources for contaminants through both diffuse and allogenic recharge into

the Floridan Aquifer.












- Water Level Sink

Water Level Rise Water Levels Sink, Rise, Well 4A

- Water Level 4A Specific Conductivity Well 4A


14

Sp.Conductivity Well 4A


13 ------------


9 1
Aug/17/2008


Aug/27/2008 Sep/6/2008


0.7




------- 0.6
cn
-o
CD








--- 0.5 3



0.3







-- 0.2
Sep/16/2008


Figure 5-1. Water levels at the River Sink, River Rise, and Well 4A with specific conductivity
from well 4A during Tropical Storm Fay. Diffuse recharge seen at other wells noted.









*


* Precipitation (cm)
* Recharge (cm)


0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
o oooooo oooooooo

Figure 5-2. Close up view of precipitation and calculated precipitation at O'Leno State Park
during Tropical Storm Fay


~lc~t












~-Water Level Sink

Water Level Rise

--Water Level Well 5A

14 1
- Sp Conductivity We


9 1
Aug/17/2008


Water Levels Sink, Rise, Well 5A
Specific Conductivity Well 5A


Aug/27/2008 Sep/6/2008


Figure 5-3. Water levels at the River Sink, River Rise, and Well 5A with specific conductivity
from well 5A during Tropical Storm Fay. Diffuse recharge seen at other wells noted.


0.7




0.65

0
-0
0
0.6 0

C



0.55 -

0.5


0.5


_--- 0.45
Sep/16/2008












-SSinkWL

- Rise WL

-6AWL


Water Levels-Sink, Rise, Well 6A
Specific Conductivity-Well 6A


14

136A


13


12 --------





11





10 --------





9
Aug/1 7/2008


Aug/27/2008


Sep/6/2008


0.7




------- 0.6


0
-o


------- 0.5







0.3


-------- 0.3





-- 0.2
Sep/16/2008


Figure 5-4. Water Level at the River Sink, River Rise, and well 6A with specific conductivity
from well 6A. Response attributed to diffuse recharge also noted.





















* Precipitation (cm)

* Recharge (cm)


00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
000000000000000
000000000000000
r,4 ,4 r,4 ,4 r,4 r4 r,4 r4 ro4 r4 ro4 r4 ro4 ro4 ro




Figure 5-5. Close up view of precipitation and recharge during the March 2008 flood


.. j l~ I II












- Water Level Sink

-- Water Level Rise

-- Water Level Well 4A



SpConductivity Well 4A


10.5 ---- --





U,


1 -
0 10


Feb/27/2008


Sink, Rise, Well 4A Water Level
Well 4A Specific Conductivity


Mar/8/2008 Mar/1i 8/2008


Figure 5-6. Water level from the River Sink, River Rise, and well 4A with specific conductivity
from well 4A. Date of diffuse recharge is noted. Lines coming from the water level in
well 4A indicate when pumping occurred.


0.7



0.65


cn

0.6 C
o
0

0.55
C)


0.5



0.45



0.4


Mar/28/2008












(a) August 17






ft^\ A,,-a Y)


I N 11 1 11|\lI|I


-7144-A M1-1-- I-I II-- I I II

__ E'___ 1 ____ ____ ____


Figure 5-7. Cross sections of groundwater model during Tropical Storm Fay showing the conduit
on the left in blue, the nested wells 125-150 meters from the conduit, head contours,
and water flow vectors. The size of the arrow indicates the magnitude of velocity
within each panel. Velocities should not be compared between time steps as they are
not consistently scaled. Length of the model is 800 m.


1


* I I


II 11 I \ -I


V


--r\,N


f,) An-mct 2R












L) August 24


August 26






geg(c) September 4






I (d) Otobe 16




Figure 5-8. Cross sections of groundwater model during Tropical Storm Fay showing amounts of
conduit water, contours of concentration, flow vectors, and monitoring wells 125-150
meters from the conduit. The lowest values of conduit water are blue and the highest
values are red. Length of the model is 800 m.











hydraulic conductivity vs. effective porosity




--- -S- K= 120 m/d, ne = 0.01 -----------
-- K= 120 m/d; ne = 0.02
-*-- K= 90 m/d; ne = 0.01
-- K = 90 m/d; ne = 0.02 -------------------------















--------------. ---- --------------. ---- --- --.---------- ----
--- ------- ---
p I
____________ ______________________ II __________


Jun/1/2008 Aug/10/2008 Oct/19/2008

Figure 5-9. Figure showing percent conduit water that reached the shallow monitoring well in a
groundwater model of Tropical Storm Fay. Different values of hydraulic conductivity
(K) and effective porosity (ne) were used for four different model runs.












August 23


L C~b Ld4H-kA-1--


Oc) tober 14






Figure 5-10. Cross sections of groundwater model during Tropical Storm Fay showing amounts
of diffuse recharge, contours of concentration, flow vectors, and monitoring wells
125-150 meters from the conduit. The matrix water and conduit water are dark blue
(0 concentration) and diffuse recharge is light blue, green, and red (100
concentration). Length of the model is 1200 m.










(a March 7


Figure 5-11. Cross sections of groundwater model during March 2008 showing the conduit on
the left in blue, the nested wells 125-150 meters from the conduit, head contours, and
water flow vectors. The size of the arrow indicates the magnitude of velocity within
each panel. Velocities should not be compared between time steps as they are not
consistently scaled. Length of model is 600 m.








F~r M-arch 14



Figure 5-12. Cross sections of groundwater model during March 2008 showing amounts of
conduit water, contours of concentration, flow vectors, and monitoring wells 125-150
meters from the conduit. The lowest values of conduit water are dark blue and the
higher values are light blue and green. Length of model is 600 m.









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Moore, P.J., 2009. Controls on the Generation of Secondary Porosity in eogenetic Karst:
examples from San Salvador Island, Bahamas and north-central Florida, USA, University
of Florida, Gainesville, 141 pp.

Mylroie, J.E. and Carew, J.L., 1995. Karst development on carbonate islands, in Budd, D.A.,
Harris, P.M., and Saller, A., eds., Unconformities and Porosity in Carbonate Strata:
American Association of Petroleum Geologists Memoir, 63: 55-76.

Mylroie, J.E. and Carew, J.L., 2003. Karst Development on Carbonate Islands. Speleogenesis
and Evolution ofKarstAquifers, 1 (2): 1-21.

Old Bellamy Cave System, 2009.
http://divefloridacaves.com/Santa%20Fe%20Underground.html, cited April 14, 2009

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Ritorto, M.J., 2007. Impacts of Diffuse Recharge on Transmissivity and Water Budget
Calculations in the Unconfined Karst Aquifer of the Santa Fe River Basin, University of
Florida, Gainesville, 145 pp.

Ritorto, M., Screaton, E.J., Martin, J.B., and Moore, 2009. Magnitudes and chemical effects of
diffuse and focused recharge in an eogenetic karst aquifer: An example from the
unconfined Floridan aquifer: Hydrogeology Journal DOI 10.1007/sl0040-009-0460-0.

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Measurements. Ground Water, 33(5): 769-780.

Schwartz, F.W. and Zhang, H., 2003. Fundamentals of Ground Water. John Wiley and Sons,
Inc., New York, 583 pp.

Screaton, E., Martin, J.B., Ginn, B. and Smith, L., 2004. Conduit Properties and Karstification in
the Unconfined Floridan Aquifer. Ground Water, 42(3): 338-346.

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BIOGRAPHICAL SKETCH

Abigail Langston was born and raised in the heart of the Ozarks, Fayetteville, AR. With

her parents Marc Langston, Crystal Langston, and younger sister Allison, Abby spent her first 18

years exploring the natural beauty of north Arkansas. Abby graduated from Fayetteville High

School in 2000 and began college at Tulane University. At Tulane in an introductory geology

class taught by Dr. Franco Marcantonio, Abby found her professional calling. She graduated

from the University of Maryland in 2006 with a BS in environmental management and began her

master's in geological sciences at the University of Florida. Abby worked with Dr. Liz Screaton

on groundwater flow in the Floridan aquifer. Abby will continue her education and begin

research for her PhD at the University of Colorado, Boulder in the fall of 2009. She looks

forward to continuing to exploring and enjoying life in the Rocky Mountains accompanied as

always by her two children, Ethan and Zoe.





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1 THE RELATIONSHIP BETWEEN SPECIFIC CO NDUCTIVITY AND FLOW PATHS IN A KARST AQUIFER, NORTH-CENTRAL FLORIDA By ABIGAIL L. LANGSTON A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2009

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2 2009 Abigail L. Langston

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3 To my father, Marcus C. Langston

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4 ACKNOWLEDGMENTS I want to thank m y advisor, Dr. Elizab eth Screaton, for lending her knowledge and expertise to this project. I thank the many field assistants who assisted in data collection at OLeno State Park. I am gratef ul to my mom, Crystal Lang ston, for her unending support and belief in me. Finally, I thank Ethan and Zoe, two rays of sunshine that light my life.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ............................................................................................................... 4LIST OF TABLES ...........................................................................................................................7LIST OF FIGURES .........................................................................................................................8ABSTRACT ...................................................................................................................... .............10 CHAP TER 1 INTRODUCTION .................................................................................................................. 122 BACKGROUND ....................................................................................................................15Conceptual Models of Karst and Dissolution ......................................................................... 15Dissolution in Conduits ................................................................................................... 16Dissolution from Diffuse Recharge ................................................................................. 17Study Area ..............................................................................................................................18Geologic Background .............................................................................................................19Previous Research in the Study Area ...................................................................................... 213 METHODS ....................................................................................................................... ......25Data Collection .......................................................................................................................25Precipitation ................................................................................................................. ....25Recharge ...................................................................................................................... ....25Sink and Rise Discharge .................................................................................................. 27Well and Surface Site Monitoring ................................................................................... 28Pumping during Drought and Storm Events ........................................................................... 30Hvorslev Method .............................................................................................................31Bouwer-Rice method ....................................................................................................... 32Adjustment for Wells Screened through Sand Pack ........................................................ 334 RESULTS ....................................................................................................................... ........36Precipitation and Recharge .....................................................................................................36Water Level, Specific Conductivity, and Temperature Monitoring ....................................... 37Nested Well Pairs Water Level, Specific Conductivity, Temperature ................................ 37Discharge at the River Sink and River Rise ........................................................................... 39Well Response to Recharge and Pumping during Drought and Minor Rain Events .............. 40Well Response to Recharge and Pumping during a Flood Event ........................................... 40Well and Surface Water Response during Tropical Storm Fay .............................................. 42Shallow well specific conductivity response during Tropical Storm Fay .............................. 43Slug Tests Shallow and Deep Wells .................................................................................... 43

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6 5 DISCUSSION .................................................................................................................... .....63Slug Tests and Applicability to Matrix Hydraulic Conductivity ............................................ 63Specific conductivity response in shallo w wells: evidence for reactive water ....................... 64Initial well Response: Tropical Storm Fay ...................................................................... 64Shallow Well Response to Peak Flood Level .................................................................. 65Specific Conductivity Signal During March 2008 Event ................................................67Interpretation of Specific Conductivity Response using Groundwater Modeling .................. 702-D Modeling of Conduit-matrix intera ctions during Tropical Storm Fay .....................71Modeled Concentrations of conduit water ...................................................................... 73Modeled concentrations of diffuse recharge ...................................................................75Model applied to the March 2008 Flood event and pumping ......................................... 76Implications .................................................................................................................. ..........78LIST OF REFERENCES ...............................................................................................................92BIOGRAPHICAL SKETCH .........................................................................................................95

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7 LIST OF TABLES Table page 3-1 Summary of well depths, screened inte rvals, d epth to bedrock and ground surface elevation of all wells at OLeno State Park used in this study a nd previous studies. ........ 344-1 Summary of precipitation, recharge, and water levels during the 2008 floods. ................ 444-2 Shortest distances from ne sted wells to known conduits. .................................................. 454-3 Summary of the limestone and water levels during high and low water levels. ................ 45

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8 LIST OF FIGURES Figure page 2-1 Location of study area in north-central Florida ................................................................. 243-1 Rating curve developed by the SRWM D for the Santa Fe River Sink ..............................343-2 Rating curve for Santa Fe River Ri se from Screaton et al. (2004) .................................... 353-3 Head ratio vs. time plot used to determ ine variables in Hvorslev and Bouwer-Rice slug test calculations. .........................................................................................................354-1 Total precipitation and r echarge at OLeno State Pa rk during the study period, 20062008....................................................................................................................................464-2 Precipitation from the OLeno State Park rain gauge ........................................................ 474-3 Water level from the River Rise for the study period 2006-2008 ......................................484-4 Water levels at the River Sink, River Rise, and shallow well s during the March 2008 flood event. ........................................................................................................................494-5 Water levels at the River Sink, River Rise, and shallow wells during Tropical Storm Fay flood event. .................................................................................................................504-6 Head difference between wells 5 and 5A .......................................................................... 514-7 Temperature and specific conductivity cha nges over 18 months in a shallow well and deep well in the study area. ................................................................................................ 524-8 Discharge from the River Si nk and the River Rise for 2008. ............................................ 534-9 Specific conductivity responses and recovery at the shallow wells during low flow.. ...... 534-10 a,b. Water level and specific conductivity response to a diffuse recharge event.. ............. 544-11 Values recorded during pumping at the shallow wells during March 2008. ..................... 554-12 Specific conductivity measurements fr om both loggers and pumping during the March 2008 flood. ............................................................................................................. .564-13 Specific conductivity in well 7 show ing both pumping and logger values ....................... 574-14 Specific conductivity values from both pumping and loggers in well 6A during the March 2008 flood event. .................................................................................................... 584-15 Specific conductivity res ponse at the River Sink and the River Rise during Tropical Storm Fay ..................................................................................................................... ......59

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9 4-16 Specific conductivity response at the deep wells during Tropical Storm Fay ...................604-17 Specific conductivity res ponse in the shallow wells dur ing Tropical Storm Fay ..............614-18 Results of hydraulic conductivity calculations from slug tests .......................................... 625-1 Water levels at the River Sink, River Rise, and Well 4A with specific conductivity from well 4A during Tropical Storm Fay. ......................................................................... 815-2 Close up view of precipitation and calcu lated precipitation at OLeno State Park during Tropical Storm Fay .................................................................................................825-3 Water levels at the River Sink, River Rise, and Well 5A with specific conductivity from well 5A during Tropical Storm Fay. ......................................................................... 835-4 Water Level at the Rive r Sink, River Rise, and well 6A with specific conductivity from well 6A. ................................................................................................................. ....845-5 Close up view of precipitation and recharge during the March 2008 flood ...................... 855-6 Water level from the River Sink, River Rise, and well 4A with specific conductivity from well 4A. ................................................................................................................. ....865-7 Cross sections of groundwater model during Tropical Storm Fay .................................... 875-8 Cross sections of groundwater model during Tropical Storm Fay .................................... 885-9 Figure showing percent conduit water. .............................................................................. 895-10 Cross sections of groundwater model during Tropical Storm Fay .................................... 905-11 Cross sections of groundwater model during March 2008 ................................................ 915-12 Cross sections of groundwater model during March 2008 ................................................ 91

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10 Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science THE RELATIONSHIP BETWEEN SPECIFIC CO NDUCTIVITY AND FLOW PATHS IN A KARST AQUIFER, NORTH-CENTRAL FLORIDA By Abigail L. Langston August 2009 Chair: Elizabeth Screaton Major: Geology The Floridan aquifer system is the primary source of drinking water in north-central Florida and provides a source of recreation where it discharges at Floridas springs. At OLeno State Park, the Santa Fe River flows into the Floridan Aquifer system via a 36-meter-deep sinkhole, flows through a conduit system, and re-emerg es 5 km from its sink at a first magnitude spring. Research conducted at OLeno State Park investigated the respon se of the unconfined upper Floridan aquifer to two flood events on th e Santa Fe River, one in March 2008 and one from Tropical Storm Fay in August 2008. The Marc h 2008 event was largely a result of local diffuse recharge, in contrast to a large flood pulse from upstream during Tropical Storm Fay. The aquifer matrix surrounding the conduit syst em was monitored by 4 nested well pairs equipped with data loggers that recorded water level, temper ature, and specific conductivity. Both diffuse recharge and conduit-influenced res ponses were detected at water table wells, but no recharge response was detected in wells screened at the level of the conduit. This result contrasted with expectations that conduit wa ter would invade the matrix uniformly around the conduit passages. Slug tests conducted as part of this study indicate that the matrix at the water table has hydraulic conductivity up to one order of magnitude higher than deeper in the aquifer. A two-dimensional groundwater model was construc ted to determine the conditions necessary to

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11 observe conduit water flowing in significant quantities to the water table, as indicated by the monitoring results. The model wa s constructed using input parameters based on published total porosities, hydraulic con ductivities calculated for this study, and gradients from collected water level data. The major parameter adjusted in the modeling was effective porosity. Reducing the effective porosity mimics a small conduit or prefer ential flow path, and allows water to move faster along the water table. Th e results of this study alter conceptual models about how allogenic recharge flows through a karst aquifer and the role of th e water table as a dynamic area of water flow. This study also emphasizes the contamination risk to karst aquifers. Contaminants have ample access to the unconfined Floridan Aquife r through diffuse recharge as well as point source contamination. If the higher hydraulic con ductivity and lower effective porosity along the water table is a common feature, it would provide transport paths for the rapid flow of contaminants.

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12 CHAPTER 1 INTRODUCTION The im portance of groundwater stored in ka rstic aquifers around the world cannot be overstated; up to 25% of the global human population depends on these groundwaters (Ford and Williams 2007). In peninsular Florida, the vast majority of water for drinking and industrial purposes comes from karst aquifers, either the Flor idan Aquifer or the Biscayne Aquifer in south Florida. The Floridan Aquifer is one of the most productive aquifers in the world, with 4,020 million gallons/day of water withdrawn in 2000 (Marella and Berndt 2005). The Floridan Aquifer is made of soluble limestone bedrock that is dissolved by acidic ra in water. Dissolution forms conduits in karst aquifers, which quickly a llows water transport over great distances with little filtration. Conduit flow pos es the possibility of contaminants rapidly flowing through a karst aquifer and discharging unfiltered at a well field or spring. Understanding how water flows through karst aquifers and how flow paths change through time is vital to keeping groundwater quality high and determining possible tran sport paths in case of contamination. Flow through karst aquifers is conceptuali zed through a triple-poros ity model; water flows through conduits, fractures, and intergranular matr ix (White 2002). Conduits range from 1 cm to many meters in diameter and generally dominat e water flow paths where present in karst aquifers. Onset of non-Darcian turbulent flow can begin in conduits with a diameter greater than 1 cm. Fracture porosity includes fr actures, joints, and bedding pl anes whose width falls between 50-500 m. These fractures are frequently enlarg ed by dissolution. Intergranular porosity, or matrix porosity, is extremely low in telogeneti c karst aquifers, which have undergone burial and recrystallization, but plays an important role in young, eogenetic aquifers. Telogenetic karst has been well studied, beginni ng with classical Gr eek scholars (Ford and Williams 2007). Research on telogenetic karst became so well developed that karst became

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13 synonymous with low-permeability matrix, conduit dominated flow regimes (e.g. Palmer 1991; White 1999; Klimchouk 2004). In contrast, there was significantly less research on younger, eogenetic carbonate aquifers with higher matr ix porosity and both conduit and matrix flow. Eogenetic karst is found in peninsular Florida, the Yucatan Peninsula, Mexico, the Bahamas and some Caribbean islands. Resear ch towards understanding the uni que functioning of eogenetic aquifers began in earnest ~40 years ago (B ack and Hanshaw 1970), and continues to produce new and important findings (Mylroie and Carew 1995; Martin et al. 2002; Palmer 2002; Vacher and Mylroie 2002; Florea and Vacher 2005). Research at OLeno State Park in north-central Florida has provided further insight into the interactions of conduit and matrix flow in an eogenetic karst aquifer, and the role of dissolution in aquifer evolution. OLeno State Park is situated near the Cody Scarp, the boundary between the confined Floridan Aquifer to the east and the uncon fined aquifer to the west. At OLeno State Park, the Santa Fe River flows into a 36-meter-deep sinkhole and emerges 5 kilometers downstream at the River Rise. Comparisons of water volume discharging into the River Sink and volumes discharging from the Rive r Rise indicates that water leaves the conduit system during high flow into River Sink (Mar tin and Dean 1999, 2001; Sc reaton et al., 2004). Screaton et al. (2004) also addr ess the implications for conduit dissolution when undersaturated water leaves the conduit and comes into contact with the matrix. Ma rtin et al. (2006) and Ritorto (2007) used water level data during storm events from wells at variable distances from the conduit to determine matrix transmissivity and sensitivity to diffuse recharge. Ritorto et al. (2009) estimated the magnitude of dissolution due to diffuse recharge and due to flow from the conduit to the matrix during high flow events. This research raised importa nt questions about the

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14 flow paths of allogenic recharge into the matrix and the role of the water table in the local flow system. This study uses specific conduc tivity in nested we ll pairs to determine how preferential flow paths affect flow velocities. Well monitori ng also allows tracking of inputs from diffuse recharge and the conduit to bette r understand dissolution patterns and aquifer evolution. Specific conductivity responses in the water table wells a nd conduit level wells were monitored for three years, from 2006 2008. During this time, low water levels in the aquifer and minimal change in specific conductivity were followed by two flood events in 2008 that resulted in significant shifts in specific conductivity that re present both diffuse and conduit i nputs. These signals are observed in water table wells, a result not anticipated by th e original conceptual model. A mechanism for conduit water flowing to the shallow wells is presented in a groundwater model that uses hydraulic conductivities cal culated from slugs tests perfor med at OLeno State Park. The findings of this study suggest a significant feedb ack between dissolution due to diffuse recharge and due to conduit influx, and thus improve pr evious conceptual models of conduit-matrix interactions in an e ogenetic karst aquifer.

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15 CHAPTER 2 BACKGROUND Conceptual Models of Karst and Dissolution Karst land scapes can be divided into two distinct groups based on matrix permeability: telogenetic karst (k=1015 1020 m2) that has been deeply buried, diagenetically altered, and lost most primary matrix poros ity and eogenetic karst (k = 1011 1014 m2) which is younger, close to the site of deposition, and has high matrix porosity (V acher and Mylroie 2002). Karst landscapes, and groundwater flow through these systems, is well studied in Paleozoic (telogenetic) karst areas in the United States and Europe. Paleozoic karst is characterized by diagenetically mature rocks with very low in tergranular porosity, but extensive conduit systems that give the aquifers high permeability (Palmer, 2002). Carbonate rocks that are temporally and spatially close to the site of deposition are termed eogenetic karst and may have both higher aquifer permeability from large conduits and high primary porosity. Matrix permeability decreases exponentially with aquife r age, which can be considered a proxy for the likelihood that carbonate has under gone burial the mesogenetic stage and exhumed back close to the surface (Vacher and Mylroie 2002; Florea and Vacher 2 006). Eogenetic karst is often associated with small carbonate islands, eg. the Bahamas, Bermuda, the Florida Keys, but this is not always the case (Vacher and Mylroie 2002). The Biscayne aqui fer in south Florida and the upper Floridan aquifer are also areas of eogenetic karst (V acher and Mylroie 2002; Moore 2009). The idea that older karst has lower permeability holds up through the course of the geologic time scale, but perhaps not on shorter time scales; on shorter time scales the permeability of karst aquifers will increase over time due to disso lution (Vacher and Mylroie 2002). Large scale horizontal hydraulic conductivity increases over the evolution of a small-scal e eogenetic karst landscapes (Vacher and Mylroie 2002). Often principles and concepts devel oped in telogenetic karst cannot

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16 be applied to eogenetic karst systems where inte rgranular matrix porosity is a large factor in groundwater flow and storage, unlike telogenetic karst where storage and transport is largely through fractures and conduits (Palmer 2002). The permeability of both telogenetic karst a nd eogenetic karst is increased by dissolution of the limestone aquifer. The acidity of the water, and therefore the potential to dissolve limestone, is primarily dictated by the amount of CO2 dissolved into water. CO2 dissolves into water exposed to atmospheric conditions until eq uilibrium is reached (Drever 1997) and carbonic acid is formed: CO2 + H2O H2CO3 The carbonic acid (H2CO3) dissociates to provide the H+ ion needed to dissolve carbonates: H2CO3 H + HCO3 With higher amounts of P2 CO, more carbonic acid is produced and results in more acidic water with more potential to aggressively dissolve limestone. Dissolution in Conduits Where surficial lithology changes from in soluble bedrock to limestone (or from a confined to unconfined limestone aquifer), alloge nic or point recharge can occur (Mylroie and Carew 2003). Dissolution in karst systems is generally greatest at the inflow point of undersaturated water into a system. When flow paths are established, higher flow rates through the system can occur, leading to more rapi d dissolution (Singurindy and Berkowitz 2003). As discharge through preferential pathways increases, wall retreat rates of conduits increase to 0.01 0.1 cm/yr (Palmer 1991). These ranges for wall re treat apply to teloge netic carbonates with little intergranular porosity. Maximum wall retrea t is determined by chemical kinetics when

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17 sufficient discharge is provided; kinetics is the limiting factor at this point. The timing required to reach maximum dissolution rate (wall retreat) varies with flow distance and temperature and varies inversely with initial fractur e width, discharge, gradient, and P2 CO (Palmer 1991). The saturation concentration of calcite is an important parameter for determining ability of waters to dissolve carbonate rocks. Temperature and P2 CO are the most important factors in determining the saturation concentration. As initial P2 CO increases, calcite solubility increases and pH decreases; dissolution rates depend on the under-satur ation of the water, but less so on the flow velocity (Palmer 1991). Dissolution from Diffuse Recharge Diffuse recharge and bursts of overla nd flow on a young carbonate platform form a rugged, pitted surface, called epikar st. Diffuse recharge over a scale of hundreds of meters is evenly distributed over the expos ed carbonate rocks. This epikar st surface generally extends through the upper few meters of soluble rock (Mylroie and Ca rew 2003). This weathered zone topping the bed rock also termed the subcutaneous zone is pa rticularly important in karst hydrogeology because of this highly develope d secondary porosity (Williams 1983). The water table is also an important area of dissol ution (Mylroie and Carew 2003; Moore 2009). The dissolution effects of the epikarst and water table are enhanced wh en the two occur in the same location, as in the study area. Epikarst devel opment is linked with soil development and the biogenic processes that occur in the ov erlying soil, due to the addition of CO2 to meteoric water from these biogenic processes. Water stored in the vadose zone and in the soil is close to biogenic sources of CO2 (Ford and Williams 2007), and can mo re aggressively dissolve calcite. The dissolution can be indicated by increased specific conductivity. The CO2 present in soil is one of the most important drivers of carbona te dissolution (Ford and Williams 2007). High soil

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18 porosity (~20% in the field area) allows gases to accumulate and mix. Respiring plants release ~40% of CO2 absorbed from the atmosphere into soil pore spaces below ground (Ford and Williams, 2007). More productive sources of CO2 are respiring micro-flora and micro-fauna: bacteria, actinomycetes (primary bacterial sources of decomposition in soil ), and fungi. Bacteria in the soil are sensitive to temperature and wate r content; most bacteria thrive in warm, wet conditions and increase CO2 in the soil during these times (Ford and Williams 2007). Study Area The Santa F e River basin, in north-central Florida, encompasses 3,585 km of forests, agricultural land, and small town s (Hunn and Slack 1983). The Sant a Fe River can be divided into two distinct stretches along its path: the 60 km stretch from the rivers source at Santa Fe Lake to the River Sink, where the River flow s over the Hawthorn group, and the 45 km stretch from the River Rise to the Suwannee River wher e the Santa Fe River flows over the unconfined Floridan Aquifer. The Cody Scarp marks the bou ndary between the confined highlands to the east and the unconfined lowlands to the west. Th e Central Highlands, to the east of the study area, are underlain by the Hawthorn Group which elevates this area up to 75 meters above sea level (masl). The eastern part of the Santa Fe River Basin is characterized by gently sloping plateaus, rolling hills, and plentiful surface stream s and lakes; the surface streams tend to flow into sink holes as they near the Cody Scarp (Grubbs 1998). The unconfined lowlands in the western part of the Santa Fe Rive r Basin slope gently to the Gulf of Mexico to the west. Some outcroppings of Ocala Limestone are found in the western Santa Fe River Basin, but limestone is generally mantled by unconso lidated sand (Grubbs 1998). North-central Florida has a transitional temp erate-humid subtropical climate. This climate is characterized by short, mild winters with te mperatures ranging from 4-10C, and long humid

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19 summers with temperatures that range from 25-35C (Grubbs 1998). Average yearly precipitation in the Santa Fe River Basin is 140 cm, though this number can vary significantly with location, especially in the summer months. Precipitation is carried to the basin in three ways: through passing fronts, which typically occu r in the winter, throug h convective, localized thunderstorms which produce intense, but genera lly brief afternoon shower s in the summer, and through seasonal tropical storms (Grubbs 1998). Pr ecipitation values vary throughout the Santa Fe River Basin due to localized afternoon thunderstorms in the su mmer months and the transient nature of tropical storms that move through the area. Recharge to the aquifer from precipitation events varies due to seasonal changes in temp erature, wind speeds, solar radiation, and canopy cover (Ritorto et al. 2009), and the spatial vari ability in the Hawthorn Group, which acts as a confining unit in the eastern Santa Fe Basin (Grubbs 1998). Geologic Background Peninsular Florida is underlain by a thick se quen ce of carbonate rocks. In the Santa Fe River Basin, the upper 250-100 meters of limestone is saturated with fres hwater (Hunn and Slack 1983). Because topographic relief on the Floridan Peni nsula is so low, there is little exposure of the underlying strata that make up the Floridan Aquifer. Descriptions of hydrographic and stratigraphic units are based on description of co res, examination of quarries, and investigating the few available outcrops. Absolu te dating of the Floridan Aquifer units is unavailable, so the units are relatively dated usi ng microfossils (Miller 1986). The Paleocene-aged Cedar Keys Formation, th e lowest stratigraphic unit included in the Floridan Aquifer, is a permeable carbonate-evaporite deposit that underlies the Floridan peninsula. The Cedar Keys Formation is made up of fine to coarsely crystalline dolomite, with gypsum or anhydrite filling most pore spaces; th ick, impermeable anhydrite beds are present locally. The Oldsmar Formation overl ies the Cedar Keys Formation a nd is early Eocene in age.

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20 Oldsmar Formation is a mictitic to finely pelloidal limestone with interbedded fine to medium crystalline, often vuggy, dolomite. The middle-Eo cene aged Avon Park Limestone, the oldest stratigraphic unit exposes at the su rface in Florida, is a mostly pelloidal, locally micritic, wellindurated limestone with some dolomitization. The Ocala Limestone is late Eocene in age and is the primary water-bearer for the Floridan aquife r. The Ocala Limestone is buried under up to 365 meters of overburden in southern part of peninsular Florida; bu t in north-central Florida, the Ocala Limestone is much more accessible and often crops out at the surface in the western part of the study area. The Ocala Limestone in divide d into upper and lower sections: the upper Ocala is white, softly indurated, porous coquina with a micritic matrix and the lower Ocala is semiindurated micritic limestone that may be dol omitized in some areas. Horizontal zones of enhanced permeability in the Floridan aquifer are frequent and often correspond with bedding planes enhanced by dissolution or fracturi ng (Miller 1986). The Hawthorn Group is a middleMiocene aged unit and is made up of interbedde d clay, silt, and sand and ranges from gray to green to cream in color. The abundant clay and silt in the Hawthorn Group cause this unit to act as a confining layer when presen t overlying the Floridan aquifer. Quaternary silica sands with trace amounts of mica and car bonate material overly the Hawthorn Group and the Ocala Limestone in the study area with va riable thicknesse s (Miller 1986). Grubbs (1998) determined that recharge rates to the confined Florid an aquifer were less than 30 centimeters per year while recharge to the unconfined Floridan aquifer was between 4080 centimeters per year. The poorly confined regions of the Floridan aquifer are characterized by a leaky confining unit (Grubbs 1998). Recharge in the poorly confined area can equal the recharge in unconfined areas if surface water in the ar ea is absent; when surface streams are not present, precipitation will recharge to the surf icial aquifer and ultimately the Floridan aquifer.

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21 Surface streams are present over th e poorly confined aquifer in some areas, thus a range of recharge rates in poorly confined areas is necessary (Grubbs 1998). Previous Research in the Study Area Hisert (1994) conducted som e of the first re search on the Santa Fe Sink Rise system specifically aimed at groundwater flow paths in the OLeno State Park (Figure 2-1). Using SF6as a tracer, Hisert (1994) establis hed a connection between the River Sink, 7 karst windows, and Sweetwater Lake and Sweetwater Lake. The condu it system in and around OLeno State Park has been partially mapped by cave divers since 1995 (Old Bellamy Cave System, 2009). Cave divers later connected Sweetwater Lake with th e River Rise through a si ngle conduit and mapped a conduit system upstream of Sweetwater Lake that connects to the River Sink. A separate conduit system connects from the east to the O Leno conduit system north of Sweetwater Lake; this conduit system is not sourced from a dir ect allogenic point (Old Bellamy Cave System, 2009). Martin and Dean (1999) used temperature as a natural tracer through the Sink-Rise System to determine residence times of allogenically recharged water in the conduits. Using these estimated travel times (1.3-9 km/day) allowe d sampling and analyzing a package of water entering the River Sink and leavi ng the River Rise. Martin and D ean (2001) also used chemical analyses of surface and ground waters to trace the flow of water within the conduits in OLeno State Park and the matrix. Three surface sites, the River Sink, Sweetwater Lake, and the River Rise were sampled as well as two water suppl y wells: one ~500 m upstr eam from the Sink and one 2 km downstream from the Rise. During low flow on the Santa Fe River (~10.5 masl in 1998) chemical analyses suggests that water discharging at Sweetwater Lake and the River Rise is not directly related to water at the Ri ver Sink. During high wate r conditions (11.90 13.43

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22 masl), chemical compositions for the three su rface sites was similar and composition of well samples suggested conduit water reached a well in the aquifer matrix. Screaton et al. (2004) used te mperature signals at the River Sink, Sweetwater, and the River Rise to determine conduit residence time s and flow velocities, and to estimate conduit dimensions. The average calculated diameter of a single conduit at OLeno is 22 m, which is consistent with reports from cave divers. Discha rge into the River Sink exceeds discharge out of the River Rise for short times during high flow periods, confirming flow from the conduit to the matrix. Martin et al. (2006) used water level data from monitoring well s and the conduits at OLeno State Park to determine matrix response to conduit flooding. Passive monitoring at wells situated at variable distances from the conduit allowed quantification of matrix transmissivity; calculated transmissivity valu es ranged from 950 160,000 m2/d. Martin inferred that with increasing distance from the condui t, preferential flow paths b ecome more important. Martin (2003) also used a one dimensional groundwater mode l to calculate velociti es for water particles leaving the conduit during a st orm event using calculated hydr aulic conductivities, well gradients, and porosity, 0.2 from Palmer (2002) The particle tracing suggested that water particles flowing to two wells traveled between 0.45 and 8.5 meters into the matrix before returning to the conduit. These simple m odels assumed a homogeneous matrix and no preferential flow paths. Precipitation and recharge va lues in north-central Florida vary tremendously due to high evapotranspiration and a soil moisture component that must be satisfied before recharge can occur (Ritorto et al. 2009). Three methods for dete rmining recharge to the Floridan aquifer in the study area were used: a basin-wide water budget method, chloride concentration method, and a water budget method using a modified Penmen -Monteith method. Ritorto (2007) found the

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23 modified Penmen-Monteith most useful as it es timated daily recharge with inputs of daily precipitation and various other daily data which are easily accessibl e for some areas in Florida. Ritorto et al. (2009) used the calculated daily recharge and geochemical modeling (PHREEQC) to assess the amount of calcite bei ng dissolved from diffuse recharge. P2 CO values for groundwater were estimated from alkalinity measurements of the water, and precipitation was assumed to be in equilibrium with atmospheric P2 CO, 105.3 Recharge in eogenetic aquifers occurs through allogenic recharge to conduits and diffuse recharge from the surface (Ritorto et al. 2009); the areas of contact between limestone and undersaturated water are thus the areas that undergo dissolution (Moore 2009). Moore (2009) used the variable geochemist ry of the surface waters and ground waters during low flow and high flow on the Santa Fe River to evaluate sources of water and mixing of these waters in the aquifer and to examine the physical and chemical properties responsible for dissolution in an eogenetic karst conduit. Moore (2009) found that water in the Floridan aquifer within the Santa Fe River basin can be charac terized by mixing of three end-member types of water: shallow matrix water, deep aquifer wa ter, and surface water. Mixing of these three compositionally distinct waters causes spring chem istry to vary with time and supports the idea that flow through the matrix is an important as pect of the groundwater system at OLeno State Park (Moore 2009). Moore (2009) also asserted that dissolution in the conduit during low flow in the river is inhibited by flow of calcium rich wa ter from the matrix to the conduit, potentially creating a barrier between unders aturated surface water and th e conduit walls. Consequently, dissolution in the conduit system would occur primarily during high flow events when conduitmatrix gradients reverse and undersaturated wate r is pushed out of the conduit (Moore, 2009).

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24 Figure 2-1. Location of study area in north-central Florida and two interpretations for boundary of the River Rise spring shed. Detailed map showing location of the River Sink, Sweetwater Lake, the River Rise, mapped c onduits, and wells monitored during this study From Ritorto et al. (2009).

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25 CHAPTER 3 METHODS Data Collection Precipitation Precip itation data was collected by the Su wannee River Water Management District (SRWMD). Precipitation at five st ations in the Santa Fe River basin was recorded daily by the Suwannee River Water Management District us ing a tipping bucket preci pitation collector. The precipitation recorded at the OLe no station during each month is co llected every thirty days. An additional daily precipitation record is kept by OLeno Park staff. This precipitation data is largely a safeguard against missing data and check for spatial variations in precipitation data provided by the Suwannee River Water Management District. Recharge The recharg e for the study area was calculated using a modified Penman-Monteith method to calculate evapotranspiration and subtr acting this value and the amount added to soil moisture storage from precipitation. = slope of relation between satura tion vapor pressure and temperature Rn = net radiation input a = density of air ca = heat capacity of air Cat = atmospheric conductance ea* = saturation vapor pressure in air )1( )1(* anat vw a aataanCC WeCcR ET

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26 Wa = relative humidity w = density of water v = latent heat of vaporization Ccan = canopy conductance = psychrometric constant Air temperature, soil temperature, humidit y, wind speed, and average solar radiation were daily inputs to the evapotrans piration equation; these data were retrieved from Florida Automated Weather Network, FAWN ( http://fawn.ifas.ufl.edu/ ). The Alachua station, 15 m iles south of OLeno State Park, was used. Ritorto et al. (2009) estimated the maximum so il moisture storage for the soil overlying the Floridan aquifer at OLeno State Park by firs t determining the field capacity of the soil, The field capacity of soil is an index of the water cont ent that can be held against the force of gravity (Dingman 2002). This dimensionless number is cal culated in the laboratory by determining the volume of water in the soil/the vol ume of the soil. For sands, this number can be as low at 0.1 and as high at 0.3 for clays (Dingman 2002). A fiel d capacity of 0.1 was c hosen for the soil at OLeno State Park as it is made up almost entirely of siliciclastic sands (Miller 1986). Ritorto et al. (2009) assumed a root zone of 100 cm in the study area. This designation was based on studies that show that tree roots in a variety of forest settings are most abundant in the upper foot of soil and are not common below four feet of soil. Stewart (1988) applied the Penmen-Monteith method to determine evapotranspiration in forest in Norfolk, England. According to this application, the tree roots did not significantly exceed one meter of soil depth. Ritorto et al. (200 9) adopted a root depth of one meter for the mixed pine and oak forest of OLeno State Park. A notable section of the study area is vegetated

PAGE 27

27 with palmetto scrub, which would have a shal lower root depth, and thus 1 m may be an overestimate of root depth. The maximum soil moisture storage capacity is determined by multiplying the field capacity of the soil (0.1) by the depth of the root zone (100 cm). Ten centimeters of precipitation would be needed to fill this soil zone before recharge to the water table can occur. If less than 10 cm of rain fall on completely unsaturated soil, the precipitation will remain in the root zone and be transpired, evaporated, or stored. Precipitation may remain stored in the root zone of the soil and be pushed out to the water table with the following episode of precipitation; thus it is genera lly not necessary to have more than 10 cm of precipitation per event to have recharge to the aquifer. Sink and Rise Discharge Discharge into the River Sink and out of the River Rise ar e based on rating curves that convert water level (m) to discharge (m3/s). The rating curve for the River Sink was created by the Suwannee River Water Management District ba sed on data collected on the Santa Fe River at OLeno State Park (Figure 3-1). This rating curve is used when river stage measurements from a gauge at the OLeno State Park Bridge ~ 1 km upstream from the Sink are available. The rating curve used for the River Rise was deve loped from unpublished data collected by the Suwannee River Water Management District (S creaton et al. 2004; Figur e 3-2). Most of the water level values used in constructing the ra ting curve ranged between 9.5 and 11 meter above sea level, the typical range for base flow at the Santa Fe River Rise, which makes this part of the rating curve most accurate. Values are absent for river stage levels over 12.5 meters, making discharges over this level uncertain (Figure 3-2). It shoul d also be noted that the rating curves for the River Sink and the River Rise are > 5 y ears old. River bed mor phology affects discharge

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28 measurements with relation to cross-sectional ar ea. Scouring and reshaping of the river bed could result in skewed discharge measurements if cro ss sectional area has been significantly changed. Well and Surface Site Monitoring Data downloaded on a monthly basis th roughout this study (2006 2008) included groundwater levels, water tem perature, and specif ic conductivity in the we lls and surface sites, and stage at the River Sink and the River Rise. Ga ps in well and sink data are largely due to logger failure and loggers were repla ced in the wells as available. Eight monitoring wells were to a depth of ~ 30 meters at variable distances from the conduit system. The lower 6 meters is surrounded by 5 cm of sand pack and screened to allow water flow. In January 2006, four wells were dr illed and screened at the water table to form nested pairs with wells screened at 30 meters The drilling reached lim estone bedrock between 2.4 meters and 5.2 meters below the surface. Th e overburden was largely unconsolidated sands, but some clay was present around wells 4A and 5A. The four wells were screened over a 3.3 meter (10 foot) interval spanning the water table (Table 3-1). Water levels in twelve wells and severa l surface water sites at OLeno have been monitored as far back as 2001 (Martin et al. 2006 ; Ritorto et al. 2009). Monitoring in the shallow wells began in February 2006. The wells sites in this study were monitored by Van Essen CTD loggers and In-Situ Mini Troll logge rs which were suspended at the screened interval by a plastic coated cablel. Seven CTD loggers were deployed in the nested well pairs (wells 4, 4A, 5, 5A, 6, 6A, 7, 7A) and the River Sink and the River Rise to monitor water level, specific conductivity, and temperature. Loggers were generally set to log measurements every 10 minutes, but during some periods, loggers recorded data every fi ve minutes. Two types of CTD loggers were deployed in the monitoring wells and surface water sites: loggers designed for depths up to 10 meters were deployed in the shallow wells and surface water sites while loggers designed for

PAGE 29

29 depths up to 30 meters were deployed in the de ep wells. The CTD loggers measure water levels with an accuracy of + 0.1 meter (30 meter loggers) or + 0.03 meters (10 meter loggers). The CTD divers also log conductivity and temperature. Due to limited supply of CTD loggers, wells 1, 2, 8, and 4A were equipped with mini-Troll logge rs which only record water level. The miniTroll loggers measured water level with an accuracy of + 0.02 meters. Conductivity, measured in mS/cm, is the abilit y of a medium to conduct electrical current and is used as a proxy for ion c oncentration in the water. The sensors recorded conductivity with a 30 mS/cm range. Some loggers were initially set in with an 80 mS/cm range. Conductivity is highly dependent on temperature, so a correction for temperature was made to calculate specific conductivity: Specific Conductance (25C) = Conductivity 1+TC*(T-25) Where a temperature coefficient (TC) of 0.0191 is used (Section 5.1 Conductivity). Because the pressure gauges are unvented, water pressure in the monitoring wells and the surface site was corrected using either a barometric pressure logger in eith er well 3 (Mini-troll) or in well 8 (CTD). The corrected pressures were then referenced to a manual water level taken at each site. Manual water levels in the wells were measured by an electronic tape. The water level data at the River Sink was collected by meas uring distance to the water with the electronic water level tape from a benchmark above the wa ter. The water level at Sweetwater Lake was generally taken by surveying from a previously es tablished benchmark to the water level. When the water level was sufficiently elevated, the wate r level tape was used to measure the distance from a marked survey point above the water s surface. The surface water measurement for the River Rise was made by readi ng a gauge ~10 m from the limes tone rim surrounding the spring.

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30 Differences between manually measured water level and logger measured water level were generally less than 0.7 cm, and shifts greater than this are generally attributed to loggers physically drifting in the casing or errors in barometric pressure measurements. Pumping during Drought and Storm Events As part of a related study, the wells and surface sites monitored during this study were pumped and sampled every three months throughout the monitoring period and more frequently during the March 2008 storm event. Although the sampling results ar e not part of this study, the pumping perturbed the specific conductivity signals, and thus is described here. The well samples were obtained using a Grundfos II subm ersible pump that pumps at a rate of two gallons/minute. The volume of water pumped from each well varied with the time it took the water chemistry to stabilize for sampling, whic h ranged from 7 minutes total pumping time to over 30 minutes total pumping time. Water was pumped until pH, dissolved oxygen, temperature and specific conductivity readi ng stabilized, and samples could be collected. Specific conductivity fluctuated by up to 0.40 mS/cm in 6 minutes in the wells during pumping (unpublished field data), while the specific condu ctivity stabilized quickly in the surface sites (River Sink, Rise, and Sweetwater). During pumping, it was often necessary to remo ve loggers from the wells to accommodate the pump. When the logger was removed from th e well, it was placed in a bucket filling with well water from the pump while the chemistry st abilized. During the high resolution pumping during the March 2008 storm event, the loggers were not downloaded, but during some routine pumping expeditions, the data from the loggers were downloaded and the loggers re-launched. Slug Tests Slug tests were performed on eight monitori ng wells at OLeno State Park in order to determine the variability in hydraulic conductivity at th e site. Eight deep wells and 4 shallow

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31 wells were tested using a sl ug-out withdrawal method. Deep wells 1, 2, 7, and 8 and shallow wells 4A, 5A, 6A, and 7Awere tested in this st udy and wells 3, 4, 5, 6, 7 were previously tested by Hamilton (2003 unpublished data). The head recove ry in the well was recorded using a logger placed below the slug, and the recorded data we re analyzed using two different methods to determine hydraulic conductivity of th e formation surrounding the well. The slug tests were conducted by first lowering a pressure transducer into the well and then lowering in the slug, with a diameter of 3.35 cm, length of 152.5 cm and a volume of 1303.67 cm3. After several minutes, when the head in the we ll returned to pre-perturbation level, the slug was withdrawn as rapidly as possible while record ing of the pressure transducer readings below it was simultaneously started. The pressure tran sducer recorded water level three times per second for the first six seconds and recorded at gradually longer intervals following. After the water level approached pretest va lues, the pressure transducer wa s stopped and the test repeated two more times for each well. Two different methods were used for analyzi ng slug test data gather ed in the field: the Hvorslev method, the Bouwer-Rice method. Hvorslev Method The Hvorslev m ethod was the first slug test me thod developed that evaluates the recovery time in a perturbed piezometer (monitoring well) in relation to the hydraulic conductivity of the surrounding formation. Hvorslev (1951) found that well recovery was expone ntial and related to hydraulic conductivity, the radius of the well, and length of the we ll screen. Hvorslevs equation takes different forms depending on the parameters and geometry of the well being tested. In wells where the length of the piezometer is more than 8 times the radius of the well screen, as in this case, the following equation is used:

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32 37 22 )/ln( tL RLr Ke e Where K = hydraulic conductivity r = radius of the well casing R = radius of the well screen eL = length of well screen 37t = time for head to rise 37% of initial change All of the variables in this equation are measurements taken from the geometry of the well, except37t This value is found by plotting the head in the well for a value of time (h), divided by the maximum head difference in the well (h0) on a logarithmic y axis versus time in the x axis (Figure 3.3). Bouwer-Rice method The Bouwer-Rice m ethod was developed specifically for slug tests in unconfined aquifers, but can also be used in confined aquifers. The pa rameters used in this method are similar to those in the Hvorslev method with the addition of a va lue representing the radius of well influence. K = hydraulic conductivity rc = radius of well casing R = radius of sand pack Re = effective radial distance over which head is dissipated Le = length of the screen )ln( 1 2 )/ln(0 2 t e ech h tL RRr K

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33 ho = drawdown at t=0 ht = drawdown at t=t t = time since h = ho Re is effectively the distance surrounding th e well where hydraulic conductivity is being measured. Bower and Rice (1976) developed a me thod to determine the relationship ln(Re/R) when the well being tested is not fully penetrating. Lw = distance from water table to bottom of screen A, B = dimensionless parameters plotte d as a function of Le/R (Bouwer, 1989) The values ht as a function of t were then plotted on a semi-logarith mic plot (Figure 3.3) and two points representing h1, t1, h2, and t2 were chosen for each slug out test and entered in to the above formula. Adjustment for Wells Screened through Sand Pack Four of the eight wells in the study were shal low wells, drilled to depths of 18-32 feet. In each of these wells, the water table crossed the well screen and the eL value was adjusted to reflect the portion of the screen submerged on the day of the slug tests. The radius of well casing,cR was also adjusted where the water table crossed the screen to include the sand pack in the radius of the well casing. The adjustment took both the thickness and porosity of the sand pack into account in the following equation (Bouwer, 1989): Where Ar= adjusted radius 2 1])1[(2 2Rnrnrs s A 1] / ]/)ln[( )/ln( 1.1 [ln RL RLhBA RLR Re w w e

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34 sn = porosity of sand pack Table 3-1. Summary of well depths, screened intervals, depth to bedrock and ground surface elevation of all wells at OLe no State Park used in this st udy and previous studies. Completed Depth (m bgs) Screened Interval (m bgs) Depth to bedrock (m) Ground surface elevation (masl) Well 1 23 23-17 17 14.45 Well 2 30 30-24 6 15.96 Well 3 28 28-22 3 17.87 Well 4 29 29-23 5 17.89 Well 4a 10 10-7 5 17.96 Well 5 30 30-24 5 16.22 Well 5a 8 8-5 3 16.2 Well 6 31 31-25 5 13.51 Well 6a 5 5-2 4 13.55 Well 7 30 30-24 5 15.22 Well 7a 8 8-5 2 15.19 Well 8 100 30-24 3 13.32 Figure 3-1. Rating curve develope d by the SRWMD for the Santa Fe River Sink. Note: at water levels below 10.25 there is no discharge at the Sink.

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35 Figure 3-2. Rating curve for Santa Fe River Rise from Screaton et al. (2004) Figure 3-3. Head ratio vs. time pl ot used to determine variable s in Hvorslev and Bouwer-Rice slug test calculations. 0.001 0.01 0.1 1 -1001020304050Well 4A head ratio vs. time Bhead ratio h/h0Time (s) 3.6667, 0.3761

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36 CHAPTER 4 RESULTS Precipitation and Recharge Historically, the average pr ecipitation in the Santa Fe River basin is 137 cm/yr (Hunn and Slack 1983). During 2006 and 2007, north-central Florida experienced drier than normal conditions with average rain fall of 88 cm/yr and 103 cm/yr, respectively (Figure 4-1). Despite two flood events during 2008, preci pitation for this year was below average with 101cm. Precipitation amounts during Tropical Storm Fay illustrate the variability of rainfall over the Santa Fe River basin, even in a widespread tropical system. Gauging stations in the eastern reaches of the Santa Fe Basin received up to 9. 6 cm of precipitation during Tropical Storm Fay while the OLeno gauging station received 4.7 cm of precipitation (Figure 4-2 b). The gauging stations recorded between 6.58.5 cm of precipitation during th e March 2008 storm event (Figure 4-2 a); this precipitation during th is storm event is more evenly distributed with a smaller flood pulse than precipitation during Trop ical Storm Fay (Figure 4-2). During 2006 to 2008, recharge to the unconfined Santa Fe River basin was largely due to small recharge events under 4 cm (Figure 4-1) There were only three events during the study with daily recharge greater than 4 cm. These thre e larger recharge events occurred in January 2006, July 2007, and March 2008, and did not show any seasonality in th eir timing. Significant recharge occurred during Tropical Storm Fay, but wa s spread out over four days (Table 4.1). The smaller recharge events were seen both duri ng winter months when low evapotranspiration allowed more precipitation to reach the aquifer and during the rainy summer season, despite higher evapotranspiration. Ther e was significantly less rechar ge during 2006 and 2007 compared to average yearly recharge fo r the region, 45-60 cm/yr (Grubbs 1998); 14 cm of recharge was estimated to have entered the Floridan Aquifer in the Santa Fe River Ba sin in 2006 and 27 cm of

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37 recharge during 2007. During 2008, 58 cm of recharge reached the aquifer, the upper part of the range for the yearly average. Water Level, Specific Conductivity, and Temperature Monitoring The water level at the River Rise and throughout OLeno State Park fell during the spring of 2006 from 10.7 masl to a baselin e level of ~9.7 masl (Figure 43). Water levels remained low from August 2006 to March 2008, when a major recharge event and flooding from the River Sink brought water levels up 10.4 masl at the River Rise and ~10.3 masl in the well locations in the park (Figure 4-4). By June 2008, water levels returned to baseline levels and remained low until August 2008 when recharge and a river flood pulse from Tropical Storm Fay caused water levels in the wells to rise to ~11.3 masl (Figure 4-5). Nested Well Pairs Water Level, Specific Conductivity, Temperature The nested shallow and deep well pairs allow differences in hydraulic head to be observed. Water levels in the shallow wells and deep wells were nearly identical during much of the study period when north-central Florida was experiencing drought conditions. The calculated vertical gradient between the shallow and deep wells was less than the typical water level monitoring error, indica ting that the vertical gradient is too small to be detected by our equipment. Significant vertical gradients were present in the nested wells dur ing the Tropical Storm Fay flood event at OLeno. Water levels in both the shallow and deep wells began to rise on the same day at the beginning of the rising limb of the well hydrograph, but the deep well water level rise outpaces the shallow water level, cau sing a maximum upward gradient of 0.007. The gradient is most pronounced in wells 5 and 5A (F igure 4-6). Wells 4 and 4A and 5 and 5A are an estimated 115 and 125 m from the conduit, respectively (Table 4-2).

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38 The specific conductivity values in the deep wells showed generally stable values throughout the study with occasional slow, steady climbs in specific conductivity that do not correlate to any flood event or change in seasonality. Specific conductivity values are occasionally perturbed by data downloads. Fo llowing a data download, measured specific conductivity value may be slightly higher or lower than the valu e recorded before the data download by ~0.020 mS/cm. These changes in specific conductivity seen at data collection times should not necessarily be interpreted as changes in water chemistry or flow patterns unless the changes in specific conductivity are part of a temporally larger pattern. During the spring 2007, we noted that the speci fic conductivities in two of the deep wells were experiencing significant drift. Some loggers drifted to extremely high values over 0.700 mS/cm in a single month long monitoring period. W ith each data down load during this time, the specific conductivity would be re set and rise again to extreme levels during the sampling period (Figure 4-7 a). This problem was resolved in the spring of 2007 by rinsing the loggers periodically with acetic acid. Specific conductivity changes in the shallow wells were more frequent and variable than the deep wells. Well 6A was the only well in the study to show regular response to diffuse recharge events. At well 6A, the water table was close to the limestone-sand boundary, so the screened interval covered both the sand and the limestone (Table 4-3). Some of the drops in specific conductivity seen at well 6A were not related to recharge, but to data downloads. Temperatures at the shallow wells, in contrast with the deep wells, showed significant seasonal variation (Figure 4-7 b). The peak temperature for the shallow wells was reached in late fall to early winter and a nnual lows were reached in early to late spring. The magnitude and timing of the temperature fluctuation at the water table is directly related to the depth of the

PAGE 39

39 water table below the ground surface, with wells screened closer to the surface responding more quickly than deeper wells. The wells screened at 30 meters in this study showed no temperature variation. This delayed seasonal va riation is seen in other shallow monitoring wells in other field areas; temperature responds more dramatically with increasing proximity to the surface (Thiros 2003). Discharge at the River Sink and River Rise Under typical low flow conditions, the discha rge into the River Sink is lower than the discharge out of the River Rise. When this occurs, the discharge from the River Rise is made up in part by groundwater from the matrix flowing into the conduit. During a major storm event, discharge into the Sink can exceed discharge out of the Rise, meaning that some river water is leaving the conduit and entering the matrix (Mar tin et al. 2006). The two flood events in 2008 showed greater discharge at the River Sink than at the River Rise (Figure 4-8). The storm event in March 2008 caused discha rge to increase at the River Sink and the River Rise to 22 m3/s and 19 m3/s, respectively (Figure 4-8). The flow of water from the conduit into the surrounding matrix occurred over a period of 7 days at the flood peak, based on higher discharge at the River Sink. The discharge into the River Sink fell from its peak of 22 m3/s to 2 m3/s, 19 days after the flood peak. The River Ri se discharge also began to decline after cresting the same day at the Sink; the River Rise fell fr om peak discharge of 19 m3/s to 6 m3/s 19 days later (Figure 4-8). The discharge during Tropical Storm Fay rose sharply at both the Sink and Rise, despite only 11 cm of precipitation and 8.6 cm of recharge to the water table dist ributed over four days (Figure 4-1). The discharge at th e River Sink increased from 0 m3/s to 148 m3/s into the conduit over six days, and peaked on August 27. Discha rge at the River Rise increased from 5 m3/s, base

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40 flow for the River Rise, to 99 m3/s over the same six days that the Sink discharge increased, with no observed lag in the discharge curves (Figure 4-8). Sink discha rge remained higher than Rise discharge for 10 days in late August and early September 2008. This reversal indicates that water from the Santa Fe River was entering the Floridan Aquifer as it left the conduit between the River Sink and the River Rise. This finding agrees with observed reversals in head gradients between the conduit and the matrix wells during these two storm events. Well Response to Recharge and Pumping during Drought and Minor Rain Events Routine well sampling took place during June 2006, when north-central Florida was in a drought and a period of declini ng regional water levels. Well sampling on June 15, 2006 caused no perturbation to the specific condu ctivities in the shallow wells the specific condu ctivity of the sampled water match values recorded by loggers Minor perturbations on July 12 were caused either from removing loggers during data downl oad or due to pumping, which occurred on the same day. Specific conductivity returns to previo us levels within a few days (Figure 4-9). Recharge events occurred th roughout the drought in 2006 and 2007; most events resulted in minor increases in water level and no appreciable change in specific co nductivity at the wells. There is one notable exception, which occurs at well 6A. On August 2, 2007, an estimated 6.9 cm of recharge reached the water table. Water le vels in the shallow wells increased by as much as 0.22 meters (Figure 4-10 a), but the speci fic conductivity in wells 5A and 7A remains stagnant, while well 6A experiences drop in specific conductivity, from 0.423 mS/cm to 0.390 mS/cm over 4 days (Figure 4-10 b). Well Response to Recharge and Pumping during a Flood Event Following the March 2008 recharge event, wells 4, 4a, 5, 5a, 6, 6a, 7, 7a, and 2 and three surface sites, River Sink, Sweetwater, and Rive r Rise were pumped to obtain samples for chemical analysis. The wells were pumped 7 times 2-3 days apart, during the rising limb, peak

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41 water levels, and the first part of the rece ssion limb in the well hydrographs. The wells with functioning loggers during pumpi ng 4A, 5A, 6A, 7A, and 7 s howed a distinct specific conductivity response to pumping. The specific conductivity values recorded during pumping showed increases until the fourth or fifth day of sampling, when each well showed a drop in the specific conductivity (Figure 4-11). The specific conductivity values measured during pumping varied from the recorded specifi c conductivity values from the loggers (Figure 4-12); however, since the pumping values were recorded while pumping was still occurr ing, both values may accurately reflect the specific conductivity of the water measured. The specific conductivity signal measured by the loggers in wells 7A, 5A, and 4A showed a distinct specific conductivity patter n following pumping; specific conductivity values measured by the loggers rose by 0.030 and 0.080 mS/cm by the second or third pumping day, but sharply decreased during pumping of the well (Figure 4-13). The specific conductivity measured manually during pumping generally corresponded to lower specific conductivity values than recorded by the loggers immediat ely after pumping. Well 7 was the only deep well that recorded specific conductivity values during this event (Figure 4-13); the othe r wells either were not either equipped with a logger at this time or the specif ic conductivity capability was failing, resulting in erroneous data. The lone deep well showed a rise in specific conductivity fr om a low value of 0.4 mS/cm on March 7 to 0.49 mS/cm at the peak logger reading, April 1. The variation in specific conductivity for manual measurements taken during sampling was similar, with readings ranging from 0.36 to 0.48 mS/cm. The specific conductivity signal at well 6A show s the opposite pattern from the rest of the wells. After pumping, the logger records a spik e of 0.050 mS/cm in speci fic conductivity that decays over two to three days a nd rises again by the same magn itude with the next sampling

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42 event. The logger in well 6A was installed Marc h 14, so there was no previous baseline specific conductivity for comparison; however, specific conductivity levels fo r well 6A tend to fall in the range of 0.3 0.35 mS/cm (Figure 4-14). Duri ng the March 2008 event, pumping during the flood produced complex specific conductivity signal s in the shallow wells and one deep well. Well and Surface Water Response during Tropical Storm Fay Following the passage of Tropical Storm Fay on August 21 and 22, water levels in both surface sites and the wells began to rise on August 23, two days after the main precipitation event. Surface water levels in creased much more rapidly than the well sites; the River Sink crested on August 27, the River Rise crested on August 28, and most of the wells peaked on August 30, with the exception of well 6A wh ich peaked on September 2 (Figure 4-5). The maximum water level of the River Sink was 13.9 meters, and the maximum water level at the River Rise was 12.4 meters. The specific c onductivity at the Sink fell from 0.220 mS/cm to 0.050 mS/cm on August 25, three days after the in itial precipitation from Tropical Storm Fay. Subsequently, specific conductivity graduall y increased to 0.123 mS/cm by September 16 (Figure 4-15). Specific conductivity at the River Rise during Tropical Storm Fa y was artificially high due to algae covering the PVC housing th e logger. Despite this problem, specific conductivity showed a significant drop of 0.1 mS/cm during the fl ood, reflecting an influx of River water flowing from the conduit. An increase in specific conductivity of 0.04 mS/cm is seen directly before the drop in specific conductivity be gins, possibly reflecting the flushing of higher specific conductivity water through the system (eg. Grasso and Jeannin 2002). Despite the flow from the conduit to the ma trix and evidence of conduit influence on well water level, no evidence shows that conduit water reached the deep wells. The specific conductivity at the deep wells screened at the conduit showed only minor changes throughout the event, even with significant increas es in water level (Figure 4-16).

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43 Shallow well specific conductivity re sponse during Tropical Storm Fay The shallow wells showed a range of responses to the recharge associated with Tropical Storm Fay. Two days after the in itial recharge associated with Fay, the specific conductivity in well 6A increased by 0.054 mS/cm over one day, then dropped by 0.100 mS/cm within hours (Figure 4-17). The specific c onductivity remained low for two days, and again rose by 0.1 mS/cm within hours. From August 25-26, well 7A showed an undulatory pattern in specific conductivity that varied by 0.07 mS/cm (Fig 4-17). During this short time period, wells 4A and 5A showed no significant respons e to the recharge event. Water levels continued to rise in the wells until a peak around August 31 (Figure 4-5). As water level in the conduit reached its maximum on August 28, specific conductivity in well 4A fell within 30 minutes by 0.260 mS/cm (Figure 4-17). This large drop in specific conductivity, the largest recorded in a well in this study area, was followed by a rapid rise in specific conductivity. The increasing specif ic conductivity at well 4A progr essed through two stages: the first stage lasted for four days with a gra dual increase, followed by the second stage lasting another four days with a much faster increa se in specific conductivity. During the same time period, specific conductivity at well 5A experi enced gradual increases over 4 days. Following this gradual rise, specific c onductivity began to increase rapi dly in well 5A beginning on September 2, reaching specific conductivity valu es of 0.128 mS/cm over baseline value (Figure 4-17). Starting on September 3, specific conduc tivity in well 6a increased by 0.118 mS/cm over two days. Following four days of relatively st eady specific conductivity in well 6A, values fell by 0.154 mS/cm over four days, leveling off near values seen before the storm event. Slug Tests Shallow and Deep Wells The slug tests were analyzed using two methods, the Hvorslev method and the BouwerRice method. There was generally good agreement between the two methods for each individual

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44 test run. We saw two ranges of hydraulic conduct ivity in the study area for the shallow wells and the deep wells (Figure 4-18). The Hvorslev method showed higher calcu lated hydraulic con ductivities than the Bouwer-Rice method in the deep wells, while the Bouwer-Rice method generally showed higher calculated hydraulic conductivities in the shallow wells. The greatest difference between methods results in the deep wells was found at well 1 with the Hvorslev method giving 5.47 meters/day (6.34 x 105 m/s) and the Bouwer-Rice method giving 3.56 m/d (4.13 x 105 m/s). The largest difference between methods in the sha llow wells was in well 4a and the only test run for the shallow wells where the Hvorslev met hod showed a higher result than the Bouwer-Rice method: the Hvorslev method calculated 96.77 m/d (1.1 x 103 m/s) and the Bouwer-Rice method calculated 56.76 m/d (6.5 x 104 m/s). The hydraulic conductivity calculations for both tests were very similar in the remaining shallow wells. Average hydraulic conductivity for the shallow wells was calculated to be more than an order of magnitude greater than the deep wells (Figure 4-18). The hydraulic conductivity for the shallow wells averaged 90 m/d, excluding well 6A. Due to its unique well construction, the slug tests for well 6A measured some of the sand that mantles the limestone, and is not considered an accurate representation of limestone matrix hydr aulic conductivity. Hydraulic conductivity range for the deep wells averaged ~4 m/d. Table 4-1. Summary of precipitation, rech arge, and water levels during the 2008 floods. Mar-08 Fay Aug 2008 Precip (cm) 7.2 11 Recharge (cm) 6.9 9 Sink (masl) 10.7 13.9 Rise (masl) 10.45 12.4 Wells (masl 10.36 11.3

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45 Table 4-2. Shortest distances fr om nested wells to known conduits. Table 4-3 Summary the top of the limestone and water levels during high and low water levels. Well # Land Surface (masl) Top of Limestone (masl) Water Table Feb 2008 (masl) Water Table Peak March 2008 Water Table July 2008 Water Table Peak Fay 2008 4, 4A 17.89 13.32 9.8 10.32 9.6 11.25 5, 5A 16.2 13.15 9.79 10.32 9.6 11.27 6, 6A 13.51 9.55 9.79 10.32 9.6 11.07 7, 7A 15.22 9.73 9.74 10.21 9.6 10.8 Well Number Distance from Conduit (m) 4, 4A 115 5, 5A 125 6, 6A 140 7, 7A 1025

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46 Figure 4-1. Total precipitation and recharge at OLeno State Park during the study period, 20062008. The two flood events discussed, March Flood and Tropical Storm Fay, are noted. 0 2 4 6 8 10 Jan/1/2006Jan/1/2007Jan/1/2008Jan/1/2009Precipitation and Recharge 2006-2008 precip rechargeCentimeters Tropical Storm Fay March Flood

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47 Figure 4-2. Precipitation from the OLeno State Park rain gauge and other stations in the Santa Fe River Basin during the two flood even ts, March 2008 and Tropical Storm Fay.

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48 Figure 4-3. Water level from the River Rise for the study period 2006-2008. The flood events studied are marked and times of logger malfunction are noted. 9 9.5 10 10.5 11 11.5 12 12.5 Jan/1/2006 Jan/1/2007 Jan/1/2008 Jan/1/2009River Rise Water Level 2006-2008masl Logger Malfunction Tropical Storm Fay March 2008 Flood

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49 Figure 4-4. Water levels at th e River Sink, River Rise, and sh allow wells during the March 2008 flood event. 9.5 10 10.5 11 Feb/29/2008Mar/8/2008Mar/16/2008Mar/24/2008Apr/1/2008Water Levels March 2008 River Sink River Rise Well 4A Well 5A Well 6A Well 7A water level (masl)

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50 Figure 4-5. Water levels at the River Sink, River Rise, and sha llow wells during Tropical Storm Fay flood event. 9 10 11 12 13 14 Aug/17/2008Aug/27/2008Sep/6/2008Sep/16/2008Water Level Tropical Storm Fay Sink Rise Well 4A Well 5A Well 6A Well 7Awater level (masl)

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51 Figure 4-6. Head difference between wells 5 and 5A showing vertical gr adients during the flood pulse of Tropical Storm Fay. 9.5 10 10.5 11 11.5 Aug/17/2008Aug/27/2008Sep/6/2008Sep/16/2008Water Levels Wells 5&5A Well 5 Well 5AWater Level (m)

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52 Figure 4-7. Temperature and speci fic conductivity changes over 18 months in a shallow well and deep well in the study area. 18 18.5 19 19.5 20 20.5 21 21.5 Feb/1/2006Aug/1/2006Feb/1/2007Aug/1/2007Temperature Well 6&6A Well 6A Well 6Temperature (C) 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Dec/31/2005Jul/1/2006Dec/31/2006Jul/1/2007Dec/31/2007Conductivity, Well 6&6A Well 6a Well 6Condcutivity (mS/cm)

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53 Figure 4-8. Discharge from the Rive r Sink and the River Rise for 2008. Figure 4-9. Specific conductivity responses and r ecovery at the shallow wells during low flow. Specific conductivity values measured during pumping are plotted and pumping periods are marked. 0 20 40 60 80 100 120 140 160 Sink Discharge (cms) Rise Discharge (cms) 0.3 0.35 0.4 0.45 0.5 0.55 0.6 May/11/2006Jun/22/2006Aug/3/2006Pumping effects on specific conductivity during low flow 5A 6A 7A 5A-pumping 6A-pumping 7A -pumping 6A pumping 5A-pumping 7A pumpingspecific conductivity (mS/cm)

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54 A B Figure 4-10 a,b. Water level and specific conductivity response to a diffuse recharge event. Well 6A shows the only discernable specific conduc tivity response to the diffuse recharge. 9.4 9.5 9.6 9.7 9.8 9.9 Jul/9/2007Jul/19/2007Jul/29/2007Aug/8/2007Aug/18/2007Recharge Event-August 2007 5a 6a 7aWater Level (masl) 0.25 0.3 0.35 0.4 0.45 0.5 Jul/11/2007Jul/21/2007Jul/31/2007Aug/10/2007Specific Conductivity-August 2007 Event Well 6 Well 5 Well 5a Well 6a Well 7 Well 7aspecific conductivity (mS/cm)

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55 Figure 4-11. Values recorded during pumpi ng at the shallow wells during March 2008. 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 Mar/10/2008 Mar/20/2008 Mar/30/2008 4A 5A 6A 7ASpecific Conductivity (mS/cm)

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56 Figure 4-12. Specific conductivity measurements from both loggers and pumping during the March 2008 flood. 0.2 0.3 0.4 0.5 0.6 0.7 Feb/24/2008Mar/30/2008May/4/2008Jun/8/2008Jul/13/2008Logger and Pumping Specific Conductivity Values Well 4A Logger Well 5A Logger Well 7A Logger Well 4A Pumping Well 5A Pumping Well 7A Pumpingspecific conductivity (mS/cm)

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57 Figure 4-13. Specific conductivity in well 7 showing both pumping and logger values. Well 7 was the only deep well with a function ing logger during the March 2008 event. 0.3 0.35 0.4 0.45 0.5Mar/5/2008Apr/2/2008Apr/30/2008 Well 7 Pumping and Loggers Well 7 sp.cond 7

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58 Figure 4-14. Specific conductivity values from bo th pumping and loggers in well 6A during the March 2008 flood event. 0.25 0.3 0.35 0.4 0.45 0.5 0.55 Mar/10/2008Mar/20/2008Mar/30/2008Apr/9/2008Apr/19/2008Well 6A Pumping and Loggers Well 6A Logger Well 6A Pumpingspecific conductivity (mS/cm)

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59 Figure 4-15. Specific conductivity re sponse at the River Sink and the River Rise during Tropical Storm Fay. Note that the River Rise wa s likely reading artificially high specific conductivities due to algae grow th on the logger housing. 0 0.1 0.2 0.3 0.4 0.5 Aug/17Aug/22Aug/27Sep/1Sep/6Sep/11Sep/16 Sink Rise specific conductivity mS/cm

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60 Figure 4-16. Specific conductivity response at the deep wells during Tropical Storm Fay. Specific conductivity fluctuations if any appear to be minor. 0.3 0.35 0.4 0.45 0.5 0.55 Well 4 Well 5 Well 7 Aug/17/2008Aug/25/2008Sep/2/2008Sep/10/2008Specific Conductivity (mS/cm)

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61 Figure 4-17. Specific conductivity response in the shallow wells duri ng Tropical Storm Fay 0.3 0.4 0.5 0.6 0.7 Aug/17/2008Aug/27/2008Sep/6/2008Sep/16/2008Specific Conductivity-Shallow Wells 4A 5A 6A 7A specific conductivity (mS/cm)

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62 Figure 4-18. Results of hydraulic co nductivity calculations from slug tests. Note y axis is in log scale. 1 10 100 1000 Hvorslev (m/day) Bouwer Rice (m/day)

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63 CHAPTER 5 DISCUSSION Integration of the slug test results and the specific c onductivity observations provides insight into the feedback e ffects between perm eability enha ncement and dissolution in the unconfined upper Floridan aquifer. In this sectio n, the timing of specifi c conductivity variations is used to identify arri val of diffuse and conduit recharge at the wells. Then, a 2-D groundwater model is used to understand whether the known variations in hydrauli c conductivity could be responsible for the inferred patterns of diffuse and conduit water migration. Slug Tests and Applicability to Matrix Hydraulic Conductivity Calculations using both the Hvorslev Method and the Bouw er-Rice method to interpret slug tests conducted at OLeno Stat e Park show that matrix hydr aulic conductivity is higher at the water table than deeper in the aquifer (Figure 4-19). This result affirm s previous findings that hydraulic conductivity at the top of the limestone often has hi gher hydraulic conductivity than the rest of the aquifer (Williams 1983; Mylroie and Carew 2003). A likely cau se of dissolution at the water table is diffuse recharge from precipita tion, which is undersaturated with respect to carbonate minerals. Dissolution at the top of the limestone forms a higher permeability zone, called epikarst (Williams 1983). The dissolution can be especially vigorous when diffuse recharge passes through a so il zone that has higher CO2 (Mylroie and Carew 2003). Epikarst development will be further advanced by the pres ence of the water table near the top of the limestone (Mylroie and Carew 1995). Lower hydraulic conductivity at well 6A, relative to the other shallow wells, may be related to lithology (Table 4-3). Because well 6A is screened in the sands above the water table, the calculated hydraulic conductivity value may partially reflect the value of the sands rather than the underlying limestone. Typical hydraulic conductivity values for sand are 0.01-10 m/d or

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64 1.1x107 -1.1x104 m/s (Schwartz and Zhang 2003), lower than the hydraulic conductivity calculated at well 6A (3.3x104 ). Alternatively, the limestone near well 6A may have less primary porosity, a depositional artifact, or this area could have fewer dissolution produced preferential flow paths. Well 2 showed an oscillatory response to th e slug tests, indicati ng very high hydraulic conductivity (Weight and Sondregger 2000). Well 2 has chemistry that is characteristic of water upwelling from deep in the aquifer (Moore 2009). Higher hydraulic conductivity and upwelling water may be related in this case, but its un clear if upwelling causes dissolution that creates higher hydraulic conductivity or if the upwelli ng preferentially flows into higher hydraulic conductivity areas. The calculated hy draulic conductivity in well 7 is higher than the other deep wells that were analyzed (Figure 4-19). Well 7 is the furthest well from the conduit and may sit near the shifting spring shed boundary for the Rive r Rise (Figure 2-1, Table 4-2). Well 7 is characterized by the smell of sulfur during pumping and has a unique chemistry compared to other wells in the study area (Moore 2009). Moor e (2009) suggests that upwelling water from deep in the Floridan aquifer influences th e chemistry of well 7.Upwelling water and higher hydraulic conductivity may be re lated in this location. Specific conductivity response in sh allow wells: evidence for reactive water Initial well Response: Tropical Storm Fay The rapid rise and subsequent fall of specific conductivity in wells 6A and 7A on August 23 and 24 is interpreted as a piston flow response from diffuse recharge in which high specific conductivity water stored in the soil zone being pushed out of storage (Figure 4-18). The soil zone above the aquifer is rich in CO2 from biogenic production of CO2 in the soil. CO2 produced in the soil by microand macro-soil flor a and fauna tends to circulate in the sandy soil

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65 and acidify the water stored in the soil. During a diffuse recharge event, the first water to reach the water table is the more acidic water stored in the soil zone. This acidic water is pushed out of the soil zone when precipitation fills the soil to its field capacity, 10 cm in OLeno State Park (Ritorto et al. 2009). When the water from the soil zone reaches the water table it will begin to dissolving the surrounding limestone, increasing specific conductivity. The arrival of lower specific conductivity water suggest that after the soil zone is flus hed of stored water, dilute meteoric water can reach the water table and mix with the matrix water (Figure 4-18). This effect should be widespread across the water table. The timing of the specific conductivity response in well 7A lagged one day behind the response in well 6A, which may be because the water table is farther from the surface at well 7A (Table 4.3). Shallow Well Response to Peak Flood Level The possible sources of dilute water to well 4A are diffuse recharge from precipitation, recharge from overland flow, or influx of conduit water. The timing of the dilute water suggests that it is not from diffuse rech arge (Figure 5-1). The specific conductivity response in well 4A on August 29 occurs five days after the specific cond uctivity drops seen in wells 6A and 7A which are attributed to diffuse meteoric recharge. No precipitation or diffuse recharge occurs after August 25, except 0.4 cm of precipitation that c ontributed no calculated recharge (Figure 5-2). Overland flow between the River Sink and River Rise has occurred during major floods, notably the flood event during March 2003 when the stage at the River Sink reached 14.4 masl (Martin et al., 2006). Martin and Dean (2001) stat e that overland flow can occur when the Santa Fe River reaches 14.20 meters above sea level. The maximum height for the River Sink from 2006-2008 was 13.9 masl in response to Tropical Storm Fay. Field observations support some overland flooding at OLeno State Park during Tr opical Storm Fay, especially near the River Sink. Well 4A is closer to the River Rise and th is area is locally at hi gher elevation (17.89 masl;

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66 Table 4-3) than surrounding areas (13-15 masl; Table 4-3), and patchy overland flow from the River Sink would be unlikely to flow over this minor topographic high; a ny overland flow would have flowed in low-lying swamps or ditches leading to the River Rise. Because the diffuse recharge and overland fl ow seem unlikely explanations, the lowered specific conductivity response at well 4A is attributed to migra tion of conduit water. Allogenic recharge from the conduit into the matrix be gan on August 25 and continued to ~September 7 (Figure 4-5, Figure 4-8). The matrix area surrounding well 4A appears to have a direct hydrologic connection to the conduit through preferential flow paths or smaller, centimeter scale conduits, allowing dilute conduit water to reach th e well quickly without equilibrating with the surrounding matrix. Well 5A shows specific conductivity that increases from baselin e levels on September 1, three days following the drop in specific conductivit y in well 4A, while water levels in the wells were still near peak levels (Figure 5-3). Well 6A shows similar increased specific conductivity two days after well 5A (Figure 5-4). Both well 5A and 6A show a gradual, but significant rise in specific conductivity. Similar to well 4A, these specific conductivity responses in wells 5A and 6A may reflect conduit water reaching the water table wells. Conduit water apparently reacts with the formation prior to arriving at wells 5A and 6A, increasing th e specific conductivity. This contrasts with well 4A, where a low speci fic conductivity signal was observed prior to the elevated specific conductivity (Figure 4-18). Th e elevated specific condu ctivity signal suggests that conduit water arriving at we lls 5A and 6A has already begun significant dissolution in the matrix as the water flowed through the matrix, rather than moving thr ough preferential flow paths, as inferred for conduit water migration to well 4A. The large pulse of conduit water would likely have higher P2 CO than the water in the matrix and therefore greater potential to dissolve

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67 the limestone. Water originating from the surfac e is assumed to equilibrate with atmospheric levels of CO2, giving surface water higher P2 COthan groundwater. In contrast, water in the matrix is not in connection with the at mosphere and has no biogenic sources of CO2, resulting in a comparatively lower P2 CO in the matrix water (Ford and Williams 2007). The higher P2 CO of the conduit water allows greater dissolution than baseline levels in the wells. Specific Conductivity Signal During the March 2008 Event Sources of water, flow paths, and resulti ng specific conductivity signals are complex during the March 2008 flood event. The most significant cause of the difficulty interpreting the results is the seven pumping periods in the wells during the rising limb, flood crest, and recession curve. An immediate response to the 7 cm of diffuse recharge on March 7 to the aquifer was seen at one shallow well. At well 7A, the slight incr ease and subsequent drop in specific conductivity on March 7-8 is interpreted as diffuse recharge reaching the water table (F igure 4-13). The initial rise in specific conductivity fr om a diffuse recharge event seen at wells 6A and 7A during Tropical Storm Fay is not clearly present in this storm event. This may be due to seasonality in presence of CO2 in the soil zone (Ford and Williams 2007) that causes lower P2 CO in water stored in the soil zone during cool er months. In addition, residen ce time of water stored in the soil zone could be a factor in specific conductivi ty of water reaching the water table. The soil zone was flushed with 3 cm of recharge two weeks before the March event and flushed with 5 cm of recharge five weeks befo re the Fay event (Figure 5-5). Pumping at the wells in OLe no State Park began on March 11, 3 days before the flood peak in the river and conduit system. On March 16, two days after a round of pumping, specific conductivity fell sign ificantly at well 4A, from 0.514 mS /cm 0.382 mS/cm (Figure 5-6). As

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68 discussed earlier, a similar spec ific conductivity drop though of a greater magnitude was seen at well 4A during flooding from Tropical Storm Fa y. As with the response to Fay, the lower specific conductivity response was likely sourced from the conduit. This water was pushed from the conduit near maximum gradient between the conduit and the matrix, on March 14 (Figure 56). There was no precipitation or recharge in the O Leno area other than the 7 centimeters of rain that initiated the high water le vels in March 2008 (Figure 5-5) minimizing the possibility of diffuse recharge as a source of undersaturated water. The peak water level in the River Sink was 10.6 meters, well below the threshold for overland flow established by Martin and Dean (2001). There was no overland flow between the River Sink and the River Rise observed during field work during the flood event. Thus, conduit water appears the most likely source. Pumping in karst aquifers can preferentially draw water from conduits or high permeability zones (Marechal et al., 2008), which do not necessa rily have the same chemical composition as water stored in the matrix. Specific conductivity monitoring at OLeno State Park provides insight into aquifer chemical he terogeneity and flow paths. Duri ng periods of low flow and low diffuse recharge, specific conductivity measurem ents taken during pumping were very close to values read by the loggers (Figure 4-9) and the loggers did not record si gnificant perturbations due to the pumping. The matching specific conduc tivities suggest that dur ing low flow the water stored in the matrix is similar to that of the conduit. In contrast, signif icant specific conductivity fluctuations were observed during and following pumping during the March 2008 flood event, suggesting compositional differences between conduit and matrix water. Beginning on March 17, pumping in the wells began to perturb the recorded specific conductivity signal (Figures 4-13). This water may come from the conduit, which began to flow into the matrix on March 12. The conduit water is the only source of water that is undersaturated

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69 with respect to calcite and has higher P2 CO following the diffuse recharge event. The rise in specific conductivity following pumping periods suggests dissolution due to the circulation of the undersaturated conduit water. Following the pumping period on March 17, spec ific conductivity in well 4A rose by 0.200 mS/cm in four days. The increase in specifi c conductivity began imme diately after pumping ended, suggesting that the pumpi ng drew in water that began a ggressive dissolution at well 4A. A pattern of rising specific conductivity between pumping peri ods, followed by lowered specific conductivities during pumping, was also seen at well 5A and well 7A, although there was no drop in specific conductivity from conduit sourced water in well 5A or 7A as seen on March 16th in well 4A. Specific conductivities measured during pumping confirm the record from the loggers; the specific con ductivity measured during pumping at both 4A and 5A is well below logger measurements (Figure 4-13) indicating pumping draws in d ilute water. This may have driven dissolution around the well. Following the last pumping period in wells 4A, 5A, and 7A on April 1, specific conductivity returned to pre-pumping levels (Figure 4-13), indicating that the specific conductivity fluctuations were due to conduit influenced flow brought to the wells by pumping during the flood on the Santa Fe River. While wells 4A, 5A, and 7A showed decreasing specific conductivity responses to pumping followed by increasing specific conductiv ity, well 6A showed the opposite response. Rising specific conductivity in well 6A during pumping show s that water pulled in from pumping did not come from the same dilute source as seen in other shallow wells pumped in this study. This result emphasized the chemical hete rogeneity in karst aquifers and the various sources of water that may be tapped during pumping.

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70 Interpretation of Specific Conductivity Response using Groundwater Modeling Prior to this study, the conceptual model for this system was that when water flowed from the conduit into the matrix, it would flow in to the matrix surroundi ng the conduit and along preferential flow paths at the level of the conduit. Seeing a signifi cant specific conductivity response at the water table but no t at the deeper wells days afte r an allogenic recharge event requires that the conceptual model be modified. A two-dimensional model was construc ted in MODFLOW (McDonald and Harbaugh 1984) using known aquifer parameter values to visualize the possible flow paths from the conduit into the matrix. Additiona lly, modular three-dimensional transport (MT3D) simulations were run to show transport paths of recharged water from both allogeni c recharge and diffuse recharge. The MT3D program uses results of the MODFLOW simulation to model the transport vectors and velocities into and out of cells. MT3D is generall y used to model contaminant transport, but in this case a concentration of 100 is assigne d to the conduit water to allow concentrations to be interpreted as percentages of recharged wate r, rather than concentrations. No reactions between river water and matrix wate r or diffusion or dispersion within the matrix were considered in this simulation. A grid of 50 columns and 10 layers was c onstructed with the condu it represented at the west end of the model, and the eastern edge representing a no-flow boundary. Each column is 25 meters wide at near the conduit, grading to 100 me ters in width at the di stal end of the model. The thickness of the model is set at 100 metersequa l to the estimated thickness of active flow in the upper Floridan aquifer in the Santa Fe Rive r Basinand divided into 10 layers to which variable hydraulic condu ctivities and recharge amounts can be applied. Hydraulic conductivities were assigned based on actual values measured by slug tests. The hydraulic conductivity for the top two layers, which includes the water table, was set at 120 meters per day (the maximum

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71 value of the hydraulic conductivity calculated from slug tests at the shallow wells; Figure 4-19) and the remaining eight layers were assigned a hydraulic conduc tivity of 4 m/d (the average value of the hydraulic conductivity calculated from slug tests at the deep wells; Figure 4-19). Porosity for the model was set at 0.3 and sp ecific yield the water drained from a porous medium by gravity is 0.2 (Palmer 2002). Effectiv e porosity was adjusted during the simulation, because this value is difficult to assess in karst aquifers (Renken et al. 2005). The conduit was placed in layer five of the m odel, corresponding to a depth of 40 meters below the water table. The conduit was simulated by placing a single cell constant head boundary in layer five, using water level values from the River Rise to approximate head in the conduit. Daily recharge values calc ulated for this study (Figure 4-1) were applied to the top layer of the model. Initial head values for the matrix were set at 9.8 meters, the average water level in the monitoring wells on June 1, and then allowed to fluctuate in response to recharge and changing head in the conduit. Two separate models were run to simulate the flood events for March 2008 and Tropical Storm Fay. The initial rain event that induced flooding on the Santa Fe River in March 2008, occurred on March 7, but model simulation bega n on January 1, 2008 in order to establish a typical, low-flow matrix-to-condu it flow regime in the model before perturbing the system. The model simulation for Tropical Storm Fay began on June 1 to establish antecedent conditions during the low-flow months during the summer leading up to the Fay flood event. 2-D Modeling of Conduit-matrix interactions during Tropical Storm Fay During Tropical Storm Fay, elevated specific co nductivity values were seen at the shallow water table wells, but not at the wells screened on the level of the conduit. An explanation for this effect is demonstrated by 2-D modeling in a cross-sectional gr oundwater model of the Floridan aquifer at OLeno State Park.

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72 Flow vectors in the model for August 17 show water moving from the matrix into the conduit, as the head in the matrix is higher than the head in the conduit at this point (Figure 5-7 a.). Relative flow velocities are indicated by the size of the arrows ; faster flow velocities have larger arrows. Velocities can be compared in the each model diagram, but not between model diagrams, as the vectors are scaled differently for each time step. The fastest flow velocities are in the top two layers of the model, which have a higher hydraulic conductivity (120 m/d) than the rest of the layers. On August 22, the first day of recharge occurred at OLeno State Park. The recharge added to the aquifer caused the head contours (shown in blue) to become slightly more horizontal in the lower part of the model (Figure 5.7 b.). The shift in head contours means that recharge has shifted gradients to direct water down in the lower part of the model, but head contours remain vertical in the upper layer of the model. This m eans that even with recharge, horizontal flow paths towards the conduit still dominate in the upper part of the model. On August 28, peak water levels were reached in the River Sink and the River Rise and maximum gradients occurred between the conduit a nd the matrix (Figure 5-7 c). Numerous head contours surrounding the conduit show the large gradient between the conduit and the matrix on this day. Flow vectors are directed up towa rd the high hydraulic conductivity layers throughout the model, but velocities in the lower layers re main very small compared to velocities in the upper layers. These lower velocities indicate th at though water is moving through the lower area of the model, the velocity at depth is much lower than at the water table. Vertical hydraulic gradients indicate upward flow between th e deeper layers and the upper layers beginning on August 24, the first day c onduit water entered the matrix. These upward vertical gradients, which were also seen in actu al water levels in the shallow and deep wells at

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73 OLeno, are indicated by head c ontours reaching farther into th e deeper layers than in the shallow layers. A vertical gradient, with hydraulic head higher in the deeper part of the aquifer, will move water up from depth. The vertical gradient assists in moving water to the water table, but flow velocities in the matrix are very sm all, which can explain why no specific conductivity response was seen at the deep wells. On September 5, the gradient reversed and water began to flow from the matrix into the conduit (5-7 d). The model dates of gradient reversals match well with actual discharge measurements at the River Sink a nd River Rise (Figure 4-8) and wa ter levels at the surface water sites and the monitoring wells (Figure 4-5). This simulation showing head contours and fl ow vectors and velocitie s show possible flow paths for water sourced from centrally located conduit in an aquifer with a higher hydraulic conductivity zone near the top. These results support the interpretation th at specific conductivity fluctuations in shallow wells at OLeno during Tropical Stor m Fay could be due to conduit influence. Flow paths for water in this system have been established, but the next step is determining if significant quantities of river wate r could be able to reach shallow wells using MT3D. Modeled Concentrations of conduit water The modeled aquifer has 0% conduit water in it until water flowed from the conduit to the matrix on August 24. The first conduit water leaves the conduit on a ll sides, though conduit water travels further up towards the water table. This initial step s hows some conduit water moving out 25 meters from the conduit (Figure 5-8, a). On August 26, river water reaches the water table and begins to move along the top layers of the model much more rapidly than river water in the lower matrix (Figure 5-8, b). On September 4, the last day that water leaves the conduit, the extent of river water reaches its maxi mum at the water table (F igure 5-8, c). At its

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74 maximum extent, river water reaches over 300 me ters from the conduit into the upper matrix. The concentrations do not dissipat e quickly; rather they tend to linger in the upper part of the aquifer. The presence of river water in upper layers of the model demonstrates a possible explanation of why there was a significant change in specific conductivity in the shallow wells. By the end of the simulation, there are still signi ficant conduit concentrati ons in the aquifer, but in the actual aquifer, this conduit-derived wate r would have induced dissolution and taken on a higher specific conductivity signal (Figure 5-8, d). The primary factor controlling the distance c onduit water flows through the matrix is the effective porosity (Figure 5-9). Fo r river water to reach the wells, an effec tive porosity used in this model is 0.01, meaning that the majority of the flow moves through 1 percent of the total volume of rock. A block of rock with equal volume can have similar permeability and total porosity, but can have very different effec tive porosities depending on the interconnections between small conduits or preferen tial flow paths. D ecreasing the effective porosity in the model decreases the available space for the water to flow through. When no other factor is changed (eg. discharge from the conduit), water is forced to fl ow through the available por e spaces at a greater velocity and can flow further into the aquife r. Lowering the effectiv e porosity to 0.01 is comparable to simulating a conduit with a 10 cm di ameter in a zone 10 meters thick, the same thickness of the higher hydrau lic conductivity area of the model. Changing hydraulic conductivity in the model did not elevate conduit water concentra tions beyond what is thought to be necessary to produce specific conductivity res ponses seen at the shallow wells (> 10% conduit water). Hydraulic conductivity appears to influenc e head contours, while effective porosity has no effect observable effect on head contours in the model.

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75 The approach of lowering effective porosity well below total porosity has been used to explain observed tracer velocities in the karstic Bi scayne aquifer in south Florida. Renken et al. (2005) found that effective porosity in the Biscay ne aquifer was an order of magnitude lower than previously assumed. Renken et al. (2005) used effective porosity to describe the velocity of a conservative tracer introduced at an injection well in the Biscayne aquifer. The velocity of the tracer was one two orders of magnitude greate r than previously measured. To reproduce field observations, Renken et al. (2005) modified a mass balance equation for a radially converging flow regime to calculate effective porosity at 2-4% of total porosity. Modeled concentrations of diffuse recharge A model simulation was run to show the move ment and percentages of recharge at the water table during the Tropical St orm Fay model simulation. To examine only the movement of diffuse recharge, the conduit water concentration wa s assigned a value of 0, and a concentration of 100 was assigned to the incoming diffuse rechar ge. Because no reactions were modeled in this simulation, recharge in the model does not equ ilibrate with the surroundin g matrix water; it only mixes with the matrix water. When water enters the top of the aquifer as diffuse recharge, it flows with the local gradient along the water tabl e from the matrix to the conduit (Figure 5.10, a). The diffuse recharge makes its way into the lo wer layers of the aquifer over tens of meters near the conduit forming a wedge of down welling water from the water table. On August 29, the gradient in the conduit had reversed and water wa s flowing into the matrix (Figure 5.10, b). The river water flowing out of the conduit pushes th e diffuse recharge away from the conduit as conduit water (here in blue) floods the water table. This supports the previous conclusion that a drop in specific conductivity at well 4A during Fay is not likely to be due to diffuse recharge or overland flow. The model shows that these sources of water were being pushed away from the wells, rather than flowing towards them. On the last day of the modeling simulation, October 14,

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76 water is flowing from the matrix into the condui t and the diffuse recharge is flowing into the conduit (Figure 5.10, c). The last diffuse recharge into the aquife r at this point was one month previously. The diffuse recharge appears to be long lasting at the water table and shows very little mixing with the lower layers. This could e xplain the differences in specific conductivity we see consistently between the shallow and deep wells (Figure 4-17; Figure 4-18). The higher hydraulic conductivity in the upper layers moves water horizontall y to the conduit, overpowering any vertical gradient that is presen t between the shallow and deep wells. Model applied to the March 2008 Flood event and pumping A model with the same dimensions and aquifer parameters as the model used to simulate the Fay storm event was used to visualize flow paths and conduit water penetration into the conduit. The March 2008 flood event showed flow paths and flow vectors similar to the flow paths seen in the Tropical Storm Fay event, but the movement of river water through the matrix was much more limited. The March 2008 event begins with water flow ing from the matrix into the conduit, a typical occurrence during low-flow times. On March 7, the single largest day of recharge in 2008 is shown in the model (Figure 5-11, a). The rechar ge creates strong vertical gradients that cause recharged water to flow down in the lower layers. Flow vectors in the upper part of the model are angled slightly downward, but ve locities are comparatively large. This suggests that the primary direction for water flow, even with significant re charge, is horizontal. Peak water level in the conduit was reached on March 14 (Figure 5-11, b). Head contours do not show the large gradient present during Fay, but flow vectors show wa ter moving from the c onduit towards the water table. Following the peak flow of water from the conduit to the matrix, the gradient reverses quickly; water begins flowing back into the conduit from the matrix on March 17 (Figure 5-11, c).

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77 The flood event was largely influenced by diffu se recharge, rather than overwhelmed by a large pulse of flood water from the Santa Fe Ri ver. Precipitation in Santa Fe River Basin was evenly distributed on March 7 and runoff from upstream did not produce a large flood pulse on the River. Water level in the aquifer responded to the diffuse recharge and rose approximately at the same rate as the River Sink and the River Rise so hydraulic head in the conduit exceeded hydraulic head in the matrix for only a few days. An MT3D simulation was run with the cell-by-cell flow data calculated by MODFLOW for the March 2008 storm event. The MT3D model uses a concentration of 100 applied to the conduit water, to estimate percentages of river wa ter that may have reached the monitoring wells. Simulations show that on March 14, river wate r left the conduit and flowed into the cells surrounding the conduit. The cell directly east of the conduit had a maximum of 5% of river water during the modeling run. Gradients between the conduit and the matrix were fairly small, so significant amounts conduit wate r did not reach the sh allow well 125 meters away, or even to the water table directly above the conduit (Figure 5-11). The pump ing at representative shallow and deep wells was modeled, but pumping rates we re too small (7.5 liters/min) to affect flow lines, flow vectors, or concentrations. The m odel simulations during Trop ical Storm Fay showed good agreement with timing of gradient reversal s between the conduit and the matrix. The model also seems to be capturing the effect of c onduit water moving through the aquifer during the simulation of the Fay flood. This further suggest s that the effect of pumping is not being captured by the model. Pumping of the shallow wells during the March 2008 flood, rather than the gradient between the condu it and the matrix remains the most likely cause for specific conductivity changes seen at the sha llow wells during pumping in March 2008.

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78 Implications The chemical state of the matrix waters will be addressed when samples taken during the March 2008 are analyzed and interp reted. Integration of the sa mpling results and the results presented here using specific conductivity a nd groundwater modeling wi ll further test the interpretation of conduit water flowing to the shallow wells. Dissolution at the top of the limestone is often thought to be primarily influenced by diffuse recharge (Mylroie and Carew 1995); it is frequently thought of as a top-down process. But these findings suggest that dissolution can occur at the water tabl e from allogenic source injected deep in the aquifer that flows up to the water table. The higher permeability layers created by diffuse recharge focus flow along the water table, resulting in a feedback effect between the dissolution caused by di ffuse and allogenic recharge. Diffuse recharge events are credited with di ssolution that occurs uniformly at the water table in mantled unconfined karst aq uifers (Ritorto et al. 2009). If dissolution occurs at the water table from the influence of conduit water, as the results from this study s uggest, the magnitude of dissolution at the water table would be incr eased significantly. Though the volume of water reaching the shallow wells is not known, it is si gnificant enough to cause a persistent specific conductivity perturbation in the wells, whereas the majority of diffuse recharge events at OLeno do not show specific conductivity re sponses. Yet if dilute precipita tion is entering the aquifer, the water is coming to equilibrium by dissolving ca rbonate. Ritorto et al. (2009) found that the magnitude of dissolution of limest one at the water table is similar to the magnitude of dissolution at the conduit. But with an addi tional influx of dilute conduit water to the wa ter table, the water table could be the primary site of denudation in the aquifer. Groundwater modeling in this study suggests that diffuse recharge to the model does not readily mix with the lower layers in the c onduit, but remains in th e upper, higher hydraulic

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79 conductivity layers (Figure 5-10). The diffuse recharge tends to move horizontally along the top of the water table until it n ears the conduit a nd then flows down toward the conduit, along the same paths that water leaving the conduit and flowing towards the water table would follow. This raises the possibility that dissolution-enhanced preferential flow paths could develop in the area connecting the conduit with the water table, due to two sources of recharge, which are at times undersaturated with respect to calcite. If these pr eferential flow paths occur leading to and from the conduit and water table, it may offer an explanation for why a low specific conductivity response was seen at well 4A (the closest well to the conduit) and why this signal was not seen at the wells further from the conduit. The concept of water flowing primarily through high hydraulic c onductivity zones could be applied to other zones of high hydraulic conduc tivity at various levels in the aquifer. The Floridan Aquifer, for example, ha s several layers of very permeable vertically limited zones that are generally associated with dissolution enhanced bedding planes (Miller 1986). That no significant specific conductivity response was seen at the wells screened at the level of the conduits could have two possible causes. There ma y not be a high hydraulic conductivity layer at the level of the conduit; if there was a high hydraulic conductivity z one, conduit water should have flowed through this zone and produced a sp ecific conductivity respon se in the deep wells. Its also possible that a high hydraulic conductivity layer or pr oto-conduit exists, but the logger is too far removed from the specific conductivity to detect it. The deep wells are screened at the average level of the conduit (24-30 mbgs), but the conduit may be up to 36 m below ground surface (Old Bellamy Cave System, 2009). The groundwater model was created to show how water from the conduit can influence wells at the water table used known parameters about the conditions during the floods and about

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80 the Floridan aquifer: gradient, hydraulic conductivity, total porosity. Effective porosity is not well known in the Floridan Aquifer and was theref ore adjusted during the model simulations. We found that to bring conduit wate r to a well 125-150 meters away water velocities needed to increase significantly. Lowering the effectiv e porosity to reflect water flowing only through interconnected preferential flow zones or small conduits produced gr eater velocities. The role of effective porosity and water velocity in this study and other studies (Renke n et al. 2005), indicate the vulnerability to rapid transport of contamin ants in karst aquifers. This risk of aquifer contamination is further increased by the inab ility to map or defin itively investigate small conduits and the many sources for contaminants th rough both diffuse and allogenic recharge into the Floridan Aquifer.

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81 Figure 5-1. Water levels at th e River Sink, River Rise, and We ll 4A with specific conductivity from well 4A during Tropical Storm Fay. Diffu se recharge seen at other wells noted. 9 10 11 12 13 14 0.2 0.3 0.4 0.5 0.6 0.7 Aug/17/2008Aug/27/2008Sep/6/2008Sep/16/2008Water Levels Sink, Rise, Well 4A Specific Conductivity Well 4A Water Level Sink Water Level Rise Water Level 4A Sp.Conductivity Well 4Awater level (masl)specific conductivity (mS/cm)

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82 Figure 5-2. Close up view of pr ecipitation and calculated precip itation at OLeno State Park during Tropical Storm Fay 0 1 2 3 4 5 608/15/2008 08/17/2008 08/19/2008 08/21/2008 08/23/2008 08/25/2008 08/27/2008 08/29/2008 08/31/2008 09/02/2008 09/04/2008 09/06/2008 09/08/2008 09/10/2008 09/12/2008 09/14/2008 Precipitation (cm) Recharge (cm)

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83 Figure 5-3. Water levels at th e River Sink, River Rise, and We ll 5A with specific conductivity from well 5A during Tropical Storm Fay. Diffu se recharge seen at other wells noted. 9 10 11 12 13 14 0.45 0.5 0.55 0.6 0.65 0.7 Aug/17/2008Aug/27/2008Sep/6/2008Sep/16/2008Water Levels Sink, Rise, Well 5A Specific Conductivity Well 5A Water Level Sink Water Level Rise Water Level Well 5A Sp Conductivity Well 5Awater level (masl)specific conductivity (mS/cm)

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84 Figure 5-4. Water Level at the River Sink, River Rise, and well 6A with specific conductivity from well 6A. Response attributed to diffuse recharge also noted. 9 10 11 12 13 14 0.2 0.3 0.4 0.5 0.6 0.7 Aug/17/2008Aug/27/2008Sep/6/2008Sep/16/2008Water Levels-Sink, Rise, Well 6A Specific Conductivity-Well 6A Sink WL Rise WL 6A WL 6Awater level (masl)specific conductivity (mS/cm) diffuse recharge response

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85 Figure 5-5. Close up view of precipitation and recharge during the March 2008 flood 0 1 2 3 4 5 6 7 802/20/2008 02/22/2008 02/24/2008 02/26/2008 02/28/2008 03/01/2008 03/03/2008 03/05/2008 03/07/2008 03/09/2008 03/11/2008 03/13/2008 03/15/2008 03/17/2008 03/19/2008 Precipitation (cm) Recharge (cm)

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86 Figure 5-6. Water level from the River Sink, Ri ver Rise, and well 4A with specific conductivity from well 4A. Date of diffuse recharge is noted. Lines coming from the water level in well 4A indicate when pumping occurred. 9.5 10 10.5 0.4 0.45 0.5 0.55 0.6 0.65 0.7 Feb/27/2008Mar/8/2008Mar/18/2008Mar/28/2008Sink, Rise, Well 4A Water Level Well 4A Specific Conductivity Water Level Sink Water Level Rise Water Level Well 4A SpConductivity Well 4AWater Level (masl)specific conductivity (mS/cm) diffuse recharge

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87 Figure 5-7. Cross sections of groundwater mode l during Tropical Storm Fay showing the conduit on the left in blue, the nested wells 125150 meters from the conduit, head contours, and water flow vectors. The size of the a rrow indicates the magnitude of velocity within each panel. Velociti es should not be compared be tween time steps as they are not consistently scaled. Le ngth of the model is 800 m.

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88 Figure 5-8. Cross sections of groundwater mode l during Tropical Storm Fay showing amounts of conduit water, contours of concentration, flow vectors, and monitoring wells 125-150 meters from the conduit. The lowest values of conduit water are blue and the highest values are red. Length of the model is 800 m.

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89 Figure 5-9. Figure showing percent conduit water th at reached the shallow monitoring well in a groundwater model of Tropical Storm Fay. Different values of hydraulic conductivity (K) and effective porosity (ne) were used for four different model runs. 0 10 20 30 40 50 60 70 80 Jun/1/2008Aug/10/2008Oct/19/2008hydraulic conductivity vs. effective porosity K = 120 m/d, ne = 0.01 K = 120 m/d; ne = 0.02 K = 90 m/d; ne = 0.01 K = 90 m/d; ne = 0.02Percent Conduit Water

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90 Figure 5-10. Cross sections of groundwater m odel during Tropical Storm Fay showing amounts of diffuse recharge, contours of concentra tion, flow vectors, and monitoring wells 125-150 meters from the conduit. The matrix water and conduit water are dark blue (0 concentration) and diffuse rechar ge is light blue, green, and red (100 concentration). Length of the model is 1200 m.

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91 Figure 5-11. Cross sections of groundwater model during March 2008 showing the conduit on the left in blue, the nested wells 125-150 me ters from the conduit, head contours, and water flow vectors. The size of the arrow i ndicates the magnitude of velocity within each panel. Velocities should not be compar ed between time steps as they are not consistently scaled. Length of model is 600 m. Figure 5-12. Cross sections of groundwater model during March 2008 showing amounts of conduit water, contours of concentration, flow vectors, and monitoring wells 125-150 meters from the conduit. The lowest values of conduit water are dark blue and the higher values are light blue and green. Length of model is 600 m.

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92 LIST OF REFERENCES Back, W and Hanshaw, B. B., 1970, Compar ison of chemical hydrology of the carbonate peninsulas of Florida and Yucatan. Journal of Hydrology, 10: 330-368. Bouwer, H., 1989. The Bouwe r-Rice Slug Test: an update. Ground Water 27 (3): 304-309. Bower, H. and Rice, R.C., 1976. Slug Test for Determining Hydraulic Conductivity of Unconfined Aquifers with completely or partially penetrating wells. Water Resources Research 12(3):423-428. Budd, D.A. and Vacher, H.L., 2004. Matrix Perm eability of the Confined Floridan Aquifer, Florida, USA. Hydrogeology Journal 12: 531-549. Dingman, S.L., 2002. Physical Hydrology Prentice Hall, Upper Saddle River, New Jersey, 646 pp. Drever, J.I., 1997 The Geochemistry of Natural Waters Prentice-Hall, Upper Saddle River, New Jersey, 437 pp. Florea, L.J. and Vacher, H.L., 2006. Springflow hydrographs: Eogenetic vs. telogenetic karst. Ground Water 44(3): 352-361. Ford, D. and Williams, P., 2007. Karst Hydrogeology and Geomorphology John Wiley and Sons, Ltd., Chichester, 562 pp. Grosso, D.A. and Jeannin, P.Y., 2002. A Globa l Experimental System Approach of Karst Springs' Hydrographs and Chemographs. Ground Water, 40(6): 608-617. Grubbs, J.W., 1998. Recharge Rates to the Upper Floridan Aquifer in the Suwannee River Water Management District, Florida. In: U.S.G. Survey (Editor). Water-Resources Investigations Report 97-4283 Tallahassee. Hamilton, M.K., 2003. Well Tests at OLeno Stat e Park and their Implication for Matrix Hydraulic Conductivity of the Flor idan Aquifer, University of Florida, Gainesville, 14 pp. Hisert, R.A., 1994. A Multiple Tracer Approach to Determine the Ground and Surface Water Relationships in the Western Santa Fe River, Columbia county, Florida., University of Florida, Gainesville, 212 pp. Hunn, J.D. and Slack, L.J., 1983. Water Resources of the Santa Fe River Basin, Florida. In: U.S.G. Survey (Editor). Water Resources Investigations Report 83-4075 Tallahassee. Hvorslev, M.J., 1951. Time Lag and Soil Permeab ility in Groundwater Observations. Water Ways Experiment Station, U.S. Army Corps of Engineers, Vicksburg, MS. Bulletin No. 36.

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93 Klimchouck, A., 2004. Towards defining, delimiting and classifying epikarst: Its origin, processes, and variants of geomorphic evolution. Karst Waters Institute Special Publication, 9 23-25: 1-13. Marella, R.L. and Berndt,M.P., 2005. Water Withdrawals and Trends from the Floridan Aquifer System in the Southeastern United States, 1950-2000. U.S. Geological Survey Circular 1278. Martin, J.B. and Dean, R.W., 1999. Temperature and a Natural Tracer of Short Residence Times for Groundwater in Karst Aquifers. Karst Waters Institute Special Publication, 5 : 236-242. Martin, J.B. and Dean, R.W., 2001. Exchange of Water Between Conduits and Matrix in the Floridan Aquifer. Chemical Geology 179: 145-165. Martin, J.M., 2003. Quantification of the Matrix Hydraulic Conduc tivity in the Santa Fe River Sink/Rise system with Implications for the Exchange of Water between the Matrix and Conduits, University of Florida, Gainesville, 80 pp. Martin, J.M., Screaton, E.J. and Martin, J.B., 2006. Monitoring Well Responses to Karst Conduit Head Fluctuations: Implications for Fluid Exchange and Matrix Transmissivity in the Floridan Aquifer. Geological Society of America Special Paper, 404. McDonald, MG, Harbaugh, AW., 1984. A modular three-dimensiona l finite-difference groundwater model, US Geol Survey Open-File Rep 83-875 607 Moore, P.J., 2009. Controls on the Generation of Secondary Porosity in eogenetic Karst: examples from San Salvador Island, Bahamas and north-central Florida, USA, University of Florida, Gainesville, 141 pp. Mylroie, J.E. and Carew, J.L., 1995. Karst development on carbonate islands, in Budd, D.A., Harris, P.M., and Saller, A., eds., Unconfor mities and Porosity in Carbonate Strata: American Association of Petroleum Geologists Memoir 63: 55-76. Mylroie, J.E. and Carew, J.L., 2003. Karst Development on Carbonate Islands. Speleogenesis and Evolution of Karst Aquifers 1 (2): 1-21. Old Bellamy Cave System, 2009. http://divefloridacaves.com/ Santa%20Fe%20Underground.htm l cited April 14, 2009 Palmer, A.N., 1991 Origin and morphology of limestone caves. Geological Society of America Bulletin 103: 1-21. Palmer, A.N., 2002. Karst in Paleozoic Ro cks: How Does it Differ from Florida? Karst Waters Institute Special Publication 7: 185-190.

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94 Renken, R.A, Cunningham, K.J, Zygnerski, M.R., Wacker, M.A., Shapiro, A.M., Harvey, R.W., Metge, D.W., Osborn, C.L., and Ryan, J.N., 2005. Assessing the vulnerability of a municipal well field to contam ination in a karst aquifer. Environmental and Engineering Geoscience 11(4): 319-331. Ritorto, M.J., 2007. Impacts of Diffuse R echarge on Transmissivity and Water Budget Calculations in the Unconfined Karst Aquifer of the Santa Fe River Basin, University of Florida, Gainesville, 145 pp. Ritorto, M., Screaton, E.J., Ma rtin, J.B., and Moore, 2009. Magn itudes and chemical effects of diffuse and focused recharge in an eogene tic karst aquifer: An example from the unconfined Floridan aquifer: Hydrogeology Journal DOI 10.1007/s10040-009-0460-0. Rovey, C.W. and Cherkauer, D.S., 1995. Scale Dependency of Hydraulic Conductivity Measurements. Ground Water, 33(5): 769-780. Schwartz, F.W. and Zhang, H., 2003. Fundament als of Ground Water. John Wiley and Sons, Inc., New York, 583 pp. Screaton, E., Martin, J.B., Ginn, B. and Smith, L., 2004. Conduit Properties and Karstification in the Unconfined Floridan Aquifer. Ground Water, 42(3): 338-346. Section 5.1 Conductivity, Principles of Operatio n. YSI Incorporated Environmental Systems Manual. Singurindy, O. and Berkowitz, B ., 2003. Evolution of hydraulic c onductivity by precipitation and dissolution in carbonate rock. Water Resources Research 39(1). Stewart, J.B., 1988. Modelling Surface Conductance of Pine Forest. Agricultural and Forest Meteorology 43: 19-35. Thiros, S.A., 2003. Hydrogeology of Shallow Basinfill Deposits in Areas of Salt Lake Valley, Salt Lake County, Utah. In: U.S. Geological Survey, Water Resources Investigations Report 03-4029 Salt Lake City. Vacher, H.L. and Mylroie, J.E., 2002. Eogenetic Ka rst from the Perspective of an Equivalent Porous Medium. Carbonates and Evaporites 17(2): 182-196. Weight, W.D. and Sondregger, J.L., 2000. Manual of Applied Field Hydrology. McGraw-Hill, New York, 608 pp. White, W.B., 1999. Conceptual Models for Karstic Aquifers. Karst Waters Institute Special Publication 5: 11-15. White, W.B., 2002. Karst Hydrology: Recent Developments and Open Questions. Engineering Geology 65: 85-10.

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95 BIOGRAPHICAL SKETCH Abigail Lan gston was born and raised in the heart of the Ozarks, Fayetteville, AR. With her parents Marc Langston, Crystal Langston, a nd younger sister Allison, Abby spent her first 18 years exploring the natural beauty of north Arkansas. Abby graduated from Fayetteville High School in 2000 and began college at Tulane Univ ersity. At Tulane in an introductory geology class taught by Dr. Franco Mar cantonio, Abby found her profe ssional calling. She graduated from the University of Maryland in 2006 with a BS in environmental management and began her masters in geological sciences at the University of Florida. Abby worked with Dr. Liz Screaton on groundwater flow in the Floridan aquifer. Abby will continue her education and begin research for her PhD at the University of Co lorado, Boulder in the fall of 2009. She looks forward to continuing to exploring and enjoying life in the Rocky Mountains accompanied as always by her two children, Ethan and Zoe.