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1 HYDROBIOGEOMORPHOLOGY OF FLUVIAL SYSTEMS IN PENINSULAR FLORIDA: IMPLICATIONS TO CLASSIFICATION, CONSERVATION, AND RESTORATION By JOHN H. KIEFER II A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2010
2 2010 John H. Kiefer II
3 To Mom, Sarah, and Nolan
4 ACKNOWLEDGMENTS I thank Bill Wise, Joann Mossa, Tom Crism an, and Ken Portier, my supervisory committee, for their insight and mentoring. I thank the Flor ida Institute of Phosphate Research for funding this research. I thank numerous landowners for opening their gates so our team could access some of th e most amazing natural properties remaining in Florida. I thank Rick Powers and Walt Re igner of BCI Engineers and Scientists, Inc. for allowing me to work fu ll-time while pursuing a degree with some professional latitude. I dearly thank my wife Sarah and s on Nolan for their patience and for chipping in to help out in the field from time to time. To give a sens e of how integrated this effort became with our family, young Nolan thinks hi s sandbox is a sediment transport flume and he wants to see a Rosgen A2 stream ty pe on our next vacation because we do not have any of those in Florida. I thank Kristen Blanton for her diligence, leadership and outstanding common sense, Jacque Levine for her MacGyver-like ab ility to make things work, and Jessie Taft and Kory Baxley for all their help whenever called upon. I thank st ream team member Aziza Khan for her assistance with GIS analyses and her amazing ability to always meet last-minute requests with a smile. This study was successful on the merits of those five people, which is not always ea sy in the wet sub-tropics given the sudden electrical storms, jet-black waters with lu rking alligators, thick vine-tangled vegetation sheltering various vipers, and other unmenti onables. We surveyed streams often more by feel than by sight and the team seemed to fall in love with Floridas wonderful array of fluvial forms while doing so. We learned some valuable scientific lessons together, especially the importance of humor to sanity.
5 TABLE OF CONTENTS page ACKNOWLEDG MENTS .................................................................................................. 4 LIST OF TABLES............................................................................................................ 8 LIST OF FIGURES ........................................................................................................ 10 ABSTRACT................................................................................................................... 18 CHA PTER 1 INTRODUCTION.................................................................................................... 20 Need for Research .................................................................................................. 20 General Ap proach ................................................................................................... 22 Study Area De scription ..................................................................................... 22 Site Sele ction ................................................................................................... 23 Metrics and Hierarchy of Scale ......................................................................... 26 General Use of Expl or atory St atistics............................................................... 28 Document Or ganization .......................................................................................... 29 2 HYDROBIOGEOMORPHOLOGY OF BLAC KWATER STREAMS AND SPRING RUNS IN SUB-TROP ICAL FLORIDA ..................................................................... 33 Introduc tion ............................................................................................................. 33 Purpose............................................................................................................ 33 Study Area and General Site Desc riptions ....................................................... 35 Existing Limnological Classific ation of Flor ida Str eams .................................... 37 Methods.................................................................................................................. 41 Data Availability and Site Se lection .................................................................. 41 Field and Deskt op Meas ures ............................................................................ 42 Exploratory Statistics ........................................................................................ 50 Results and Discussion........................................................................................... 51 Basin Types and Flow Ex ceedance Curves..................................................... 51 Partial Duration Frequ ency of Di scharge .......................................................... 53 Basin Flashiness and the Hydraulics of Open Channels and Floodplains ........ 56 Biologically Mediated Morpholog y and Grou ndwater Regimes........................ 61 Effect of Basin Water Source on Stream Sediment Ori gins.............................. 66 Conclusi ons ............................................................................................................ 69 Ramifications for Domi nant Discharge Concepts ............................................. 69 Biota as a Groundwater D ependant Geomo r phic A gent.................................. 69 Populations of Florida Streams a s a Function of Water Source....................... 70 Research Needed ............................................................................................ 71
6 3 ALLUVIAL AND GEOLOGICAL CONTRO L THRESHOLDS IN FLORIDAS DERANGED STR EAM VALLEYS ......................................................................... 105 Introduc tion ........................................................................................................... 105 Purpose.......................................................................................................... 105 General Classification of Dr ainage Networks and Valley Forms .................... 106 Peninsular Floridas G eomorphology and Quaternary Climate Flu ctuations.. 108 General Longitudinal Concept s: Clinal ve rsus Zonal ...................................... 112 Methods................................................................................................................ 116 Results and Discussion......................................................................................... 116 Planview Valley Network Patte rn s and Landscape As sociations................... 117 Longitudinal Valley Patterns and Landscape A ssociations ............................ 124 Lateral Valley Patterns and Landscape Asso ciations ..................................... 130 Channel and Floodplain Hydrau lics and Alluvial Features.............................. 133 Conclusi ons .......................................................................................................... 137 Application of Clinal and Func tional Process Zone Conc epts ........................ 137 Descriptions of Valley Types and Their Landscape Associations ................... 139 Research Needed .......................................................................................... 144 4 A CLASSIFICATION SYSTEM FOR THE CONSERVATION AND RESTORATION OF F LORID AS FLUVIAL SYSTEMS......................................... 177 Introduc tion ........................................................................................................... 177 Purpose.......................................................................................................... 178 General Approaches to Stream C lassification................................................ 179 Florida Fluvial Geomorphology and Stream Cla ssification ............................. 187 Methods................................................................................................................ 194 Site Inclusion, Field and Desktop Measures................................................... 194 Exploratory Statistics ...................................................................................... 194 Results and Discussion......................................................................................... 197 Clusters of Streams in Two Size Classes ....................................................... 198 Clusters of Streams Am ong Physiographic Settings ...................................... 208 Clusters of Streams Based on Variables fr om Four Sc ales............................ 216 Clusters of Streams on Dim ensionless Va riables ........................................... 224 Descriptions of Natural Kinds of Flor ida Streams with Delineative Criteria..... 232 Streams draini ng flat woods ...................................................................... 240 Streams draining areas of sandy highl ands ............................................. 257 Streams draining karst aquifers ............................................................... 265 Less common streams and unique sit uations .......................................... 278 Conclusi ons .......................................................................................................... 279 General Benefits of Multi-Scale, Hierarchi cal Classif ication ........................... 280 Research Needed .......................................................................................... 282 5 SUMMARY AND POTENT IAL APPLICA TIONS ................................................... 321 Summary of Findi ngs ............................................................................................ 321 Implications for Stream Resource Managem ent ................................................... 324
7 Conservation .................................................................................................. 325 Water Resour ce M anagement ........................................................................ 327 Land Devel opment ......................................................................................... 328 Farming and Groves ....................................................................................... 329 Cow-Calf O perati ons ...................................................................................... 330 Mining............................................................................................................. 330 Restorat ion ..................................................................................................... 331 Scientific Exchange and Technology Transfer ...................................................... 331 APPENDIX A FLUVIAL GEOMORPHIC VAR IABLE DESC RIPTIONS ....................................... 333 B HYDROLOGIC VARIABL E DESCRI PTIONS ....................................................... 343 C STREAM CROSS SECTIONS .............................................................................. 352 D CLUSTER ANALYSES DENDOGRAMS .............................................................. 390 E PRINCIPAL COMPONENTS ANALYSIS TABLES ............................................... 402 LIST OF RE FERENCES ............................................................................................. 427 BIOGRAPHICAL SKETCH .......................................................................................... 436
8 LIST OF TABLES Table page 2-1 Discharge calculation methods by locati on ......................................................... 74 2-2 Bankfull and flood channel discharge summa ries............................................... 75 2-3 ANOVA summaries ............................................................................................ 76 2-4 Regression summarie s....................................................................................... 77 3-1 ANOVA summaries .......................................................................................... 146 3-2 Regression summarie s..................................................................................... 147 4-1 Site physiography, dr ainage area, and valley slope......................................... 286 4-2 Bankfull channel dimensions ............................................................................ 287 4-3 Flood channel dimensions and bankfull com parison ra tios .............................. 288 4-4 Valley descrip tions ............................................................................................ 289 4-5 Principal components from dimensionle ss vari ables ........................................ 290 4-6 Selected variable comparisons among dimensionl ess clusters ........................ 291 4-7 Summary of flatwoods and hi ghlands riparia n system ty pes............................ 292 4-8 Summary of karst riparian syst em types ........................................................... 293 E-1 All cases with all variable s, rotate d com ponent ma trix..................................... 402 E-2 Large sites with all variabl es, rota ted co mponent ma trix.................................. 405 E-3 Small sites with all variabl es, rotated com ponent matrix .................................. 408 E-4 Flatwoods sites with all vari ables, rotated co mponent matrix........................... 411 E-5 Highlands sites with all variab les, rotated co mponent matrix ........................... 414 E-6 Karst sites with all variabl es, rotated com ponent matrix ................................... 417 E-7 All sites with watershed vari ables, rotated co mponent matrix.......................... 421 E-8 All sites with valley variabl es, rota ted co mponent ma trix.................................. 422 E-9 All sites with reach variabl es, rota ted co mponent ma trix.................................. 423
9 E-10 All sites with habitat patch va riables, rotated component matrix...................... 425 E-11 All sites with dimensionless vari ables, rotate d co mponent matrix.................... 426
10 LIST OF FIGURES Figure page 1-1 Reference reach study site locations ( 56 str eams)............................................. 31 1-2 Gaged study site locations (18 st reams). ........................................................... 32 2-1 Florida Department of Environmental Protection ecoregions in the study area. ................................................................................................................... 78 2-2 Florida Geological Survey geol ogic regions in the study area. ........................... 79 2-3 Example of a karst sp ring run at bank full stage .................................................. 80 2-4 Example of a blackwater st ream a t wet s eason flood stage............................... 81 2-5 Example of a flatwoods stream near bank full stage ........................................... 82 2-6 Example of a highlands stream at bankfull stage ............................................... 83 2-7 Example of a highlands stream at bas eflow stage. ............................................. 84 2-8 Seasonal flow flashiness versus x eric soils in the drai nage ar ea....................... 85 2-9 Karst spring run fl ow duration curves. ................................................................ 86 2-10 Highland stream flow duration curves. ................................................................ 87 2-11 Flatwoods stream flow duration curves. ............................................................. 88 2-12 Seasonal flow slope (SFS) of different basin types. ........................................... 89 2-13 Bankfull discharge versus the dominant ca tchment area ................................... 90 2-14 Flood discharge versus the dominant catc hment area. ...................................... 91 2-15 Flood/bankfull discharge power ratios fo r perennial streams in different basin types. .................................................................................................................. 92 2-16 Channel width versus bankfull di scharge in different bas in types....................... 93 2-17 Radius of curvature/channel width ra tio for perennial streams in different basin ty pes. ........................................................................................................ 94 2-18 Submerged aquat ic veget ation. .......................................................................... 95 2-19 Frequency percentage of in-stream submerged aquatic vegetation for perennial streams in d i fferent basin types.......................................................... 96
11 2-20 Channel resistance (n) comparisons for narrow and wide streams fed mainly by groundwater vers us surface wate r runoff....................................................... 97 2-21 Root st ep channel ............................................................................................... 98 2-22 Alluvial features of the channel and floodplain for perennial streams i n different basin types........................................................................................... 99 2-23 Biologica l banks ................................................................................................ 100 2-24 Percent dominance of biological ban ks for perennial streams in different basin ty pes. ...................................................................................................... 101 2-25 Shell and detrital floc sedim ent under a thin v eneer of sand............................ 102 2-26 Sandy alluvium with thin organic laye rs fro m a flatwoods stream point bar...... 103 2-27 Dendogram of hydrologic clusters of s treams................................................... 104 3-1 Dendritic and deranged drainage networks with exampl e of Strahlers (1957) ordering system. ............................................................................................... 148 3-2 Drainage area associated with stream order for th ree physiographic regions.. 149 3-3 Shreve (1966) cumulative network magnitude versus drainage area for three physiographic regions. ...................................................................................... 150 3-4 Drainage density associated with stream order for three physiographic regions .............................................................................................................. 151 3-5 Proportions of waterbody type occurri ng downstream of the channel reach for three physiographi c regions. ............................................................................ 152 3-6 Proportions of waterbody type occurri ng upstream of the channel reach for three physiographi c regions. ............................................................................ 153 3-7 Proportions of riparian wetland type dominant in the channel meander belt for three physiographi c regions............................................................................. 154 3-8 Proportions of riparian plant comm unities dominant in the channel meander belt by Strahler stream order............................................................................ 155 3-9 Meander belt width versus catchment area for three physiographic regions.... 156 3-10 Catfish Creek stream channel wit h alternating unconfined and well-adjusted meander bel ts................................................................................................... 157 3-11 Valley slope versus drainage ar ea for three physiogr aphic regions. ................. 158
12 3-12 Longitudinal valley shape distribution by Strahler stream order. ...................... 159 3-13 Valley segment lengths between inline wat erbodies or stream junctions versus drainage area for thr ee physiographic regions...................................... 160 3-14 Number of valley segm ent transitions per valley mile versus drainage area for th ree physiogr aphic r egions ........................................................................ 161 3-15 Valley width versus catchment ar ea for three physi ographic regions............... 162 3-16 Types of va lley conf inement ............................................................................. 163 3-17 Valley confinement distribution by Strahler stream order ................................. 164 3-18 Valley confinement distribution by ph ysiography. ............................................. 165 3-19 Dominant meander belt sediment distri bution by Strahler stream o rder........... 166 3-20 Valley confinement distribution by ph ysiography. ............................................. 167 3-21 Total alluvial features versus catchment area for three physiographic regions .. ............................................................................................................ 168 3-22 Ratio of flood channel to bankfull channel stream power versus catchment area for two physi ogr aphic regions................................................................... 169 3-23 Ratio of flood channel to bankfull channel width versus catchment area for two physiographi c regions. ............................................................................... 170 3-24 Bankfull channel friction factor versus local v alley slope for two physiographic regions .............................................................................................................. 171 3-25 Valley bankfull and floodscape ch annel com parisons by drainage area and physiogr aphy.................................................................................................... 172 3-26 Sapping valleys with seepage ravines .............................................................. 173 3-27 Chain-of-wetlands with upl and and wetland c onfined ch annels ....................... 174 3-28 Well-adjusted channel wit hin a high-gradient alluvi al bottomland forest........... 175 3-29 Unconfined channel within an immense botto mland fo rest ............................... 176 4-1 Single channel blackwater strea m zone of confi dence .................................... 294 4-2 Single-channel spring runs zone of confidence. ............................................... 295 4-3 Continuous alluvial versus colluv ial floodscapes associated with drainage area for three ph ysiographies........................................................................... 296
13 4-4 Distribution of flatw oods riparian system classes by drainage area and valley slope. ................................................................................................................ 297 4-5 Example of riparian system type FW-AFS-HG, Manatee Riv er. ....................... 298 4-6 Example of riparian system type FW-AFS-LG, Fi sheating Creek ..................... 299 4-7 Example of riparian system type FW-AF-WF Rice Creek ................................ 300 4-8 Example of riparian system type FW-AF-CC, Tenmile Creek ........................... 301 4-9 Example of riparian system ty pe FW-CV-NC, Weki va F orest UT..................... 302 4-10 Distribution of large and small flat woods riparian system classes by W/D and valley sl ope. ...................................................................................................... 303 4-11 Example of riparian system type FW-CV-WC, Lower Myakka UT 3 ................. 304 4-12 Typical landscape positions and valley profile distributi on of flatwoods colluvial ripa rian syst ems. ................................................................................. 305 4-13 Partially exposed shallow root discs on a FW-CVWC channel bed ................. 306 4-14 Distribution of flatw oods riparian system classes by drainage area and valley slope. ................................................................................................................ 307 4-15 Example of riparian system type HL-AFS, Catfish Creek ................................. 308 4-16 Example of riparian system type HL-BFC dominated by seepage, Tiger UT .... 309 4-17 Example of riparian system type HL-B FC with blackwat er sources, Hammock Branch.............................................................................................................. 310 4-18 Example of riparian system type HL-RSC, Lowry Lak e UT .............................. 311 4-19 Root-step and biological bank detail, Tuscawil la Lake UT. ............................... 312 4-20 Distribution of karst riparian system classes by bankfull discharge and valley slope. ................................................................................................................ 313 4-21 Example of riparian system type K-GM-WC, Alex ander Spring Run................ 314 4-22 Example of riparian system ty pe K-GM-DC, Week i Wachee River ................... 315 4-23 Example of riparian system type K-HM, Juniper Creek Spring Run ................. 316 4-24 Distribution of karst riparian syst em classes by bankfull discharge and submerged aquatic vegetat ion. ......................................................................... 317
14 4-25 Example of riparian system ty pe K-MM, Cedar H ead Spring Run .................... 318 4-26 Example of riparian system type K-LM, Kittri dge Spring Run ........................... 319 4-27 Example of riparian syst em type CV-CG, Blues Creek ..................................... 320 C-1 Alexander Sp ring Run valle y. ........................................................................... 353 C-2 Alexander Sp ring Run channel. ........................................................................ 353 C-3 Alligator Sp ring Run valley. .............................................................................. 354 C-4 Alligator Sp ring Run channel. ........................................................................... 354 C-5 Cedar Head Run channel and valley. ............................................................... 355 C-6 Forest Run c hannel and valle y. ........................................................................ 355 C-7 Gum Slough R un valley. ................................................................................... 356 C-8 Gum Slough R un chan nel. ............................................................................... 356 C-9 Juniper Run c hannel. ........................................................................................ 357 C-10 Kittridge Run channel. ...................................................................................... 357 C-11 Little Levy Bl ue Run c hannel. ........................................................................... 358 C-12 Morman Branc h UT ch annel. ............................................................................ 358 C-13 Rock Spring Run chan nel. ................................................................................ 359 C-14 Silver Glen UT va lley. ....................................................................................... 359 C-15 Weeki Wachee River va lley. ............................................................................. 360 C-16 Weeki Wachee River c hannel. .......................................................................... 360 C-17 Alexander UT2 c hannel and va lley. .................................................................. 361 C-18 Bell Cree k channe l. .......................................................................................... 361 C-19 Bell Creek UT channel and valle y. .................................................................... 362 C-20 Blackwater Creek va lley. .................................................................................. 362 C-21 Blackwater Creek c hannel. ............................................................................... 363 C-22 Blues Creek c hannel and valle y. ...................................................................... 363
15 C-23 Bowlegs Cr eek va lley. ...................................................................................... 364 C-24 Bowlegs Cr eek chann el. ................................................................................... 364 C-25 Carter Creek channel and va lley. ..................................................................... 365 C-26 Catfish Cr eek va lley. ......................................................................................... 365 C-27 Catfish Cr eek c hannel. ..................................................................................... 366 C-28 Coons Ba y channel. ......................................................................................... 366 C-29 Cow Creek channel. ......................................................................................... 367 C-30 Cypress Slas h UT va lley. ................................................................................. 367 C-31 Cypress Slas h UT ch annel. .............................................................................. 368 C-32 East Fork Manatee UT1 valley a nd channe l. .................................................... 368 C-33 East Fork Manatee UT2 channel and valle y. .................................................... 369 C-34 Fisheating Creek va lley. ................................................................................... 369 C-35 Fisheating Cr eek chan nel. ................................................................................ 370 C-36 Goldhead Branch ch annel and valley. .............................................................. 370 C-37 Grasshopper Slough c hannel. .......................................................................... 371 C-38 Grassy Cree k UT va lley. ................................................................................... 371 C-39 Grassy Creek UT chan nel. ............................................................................... 372 C-40 Hammock Branch ch annel and valley. ............................................................. 372 C-41 Hillsborough UT chan nel. ................................................................................. 373 C-42 Horse Cr eek valley. .......................................................................................... 373 C-43 Horse Cr eek c hannel. ....................................................................................... 374 C-44 Jack Creek c hannel and valle y. ........................................................................ 374 C-45 Jumping Gully channel and va lley. ................................................................... 375 C-46 Lake June-In-Winter U T channel and valley..................................................... 375 C-47 Little Haw Cr eek chan nel. ................................................................................. 376
16 C-48 Livingston Creek va lley. .................................................................................... 376 C-49 Livingston Cr eek chan nel. ................................................................................ 377 C-50 Lower Myakka UT 2 channel an d valle y. ........................................................... 377 C-51 Lower Myakka UT 3 channel an d valle y. ........................................................... 378 C-52 Lowry Lake UT c hannel and va lley. .................................................................. 378 C-53 Manatee Ri ver va lley. ....................................................................................... 379 C-54 Manatee Ri ver c hannel. .................................................................................... 379 C-55 Manatee UT c hannel and va lley. ...................................................................... 380 C-56 Morgan Hole Creek c hannel. ............................................................................ 380 C-57 Moses Cr eek va lley. ......................................................................................... 381 C-58 Moses Cr eek c hannel. ...................................................................................... 381 C-59 Ninemile Creek c hannel and va lley. ................................................................. 382 C-60 Rice Creek valley. ............................................................................................. 382 C-61 Rice Creek channel. ......................................................................................... 383 C-62 Santa Fe River va lley. ...................................................................................... 383 C-63 Santa Fe River chann el. ................................................................................... 384 C-64 Shiloh Creek c hannel and va lley. ..................................................................... 384 C-65 Snell Creek c hannel and valle y. ....................................................................... 385 C-66 South Fork Bl ack Creek channel. ..................................................................... 385 C-67 Ten Mile c hannel and valle y. ............................................................................ 386 C-68 Tiger Cr eek valley. ............................................................................................ 386 C-69 Tiger Cr eek c hannel. ........................................................................................ 387 C-70 Tiger UT channel. ............................................................................................. 387 C-71 Tuscawilla UT channel and valle y. ................................................................... 388 C-72 Tyson Creek channel and va lley. ...................................................................... 388
17 C-73 Wekiva Forest UT channel and valle y. ............................................................. 389 D-1 Dendogram for all si tes on all va riables. ........................................................... 390 D-2 Dendogram for large sites on all variables. ...................................................... 391 D-3 Dendogram for small sites on all variables. ...................................................... 392 D-4 Dendogram for flatwoods sites on all variables. ............................................... 393 D-5 Dendogram for highlands sites on all variables. ............................................... 394 D-6 Dendogram for karst sites on all variables. ....................................................... 395 D-7 Dendogram for all sites on watershed variabl es. .............................................. 396 D-8 Dendogram for all si tes on valley variables. ..................................................... 397 D-9 Dendogram for all si tes on reach variables. ..................................................... 398 D-10 Dendogram for all sites on habitat patch va riabl es........................................... 399 D-11 Dendogram for all sites on di mensionless and unit vari ables. .......................... 400 D-12 Dendogram for all sites on dimensionless variabl es. ........................................ 401
18 Abstract of Dissertation Pr esented to the Graduate School of the University of Florida in Partial Fulf illment of the Requirements for t he Degree of Doctor of Philosophy HYDROBIOGEOMORPHOLOGY OF FLUVIAL SYSTEMS IN PENINSULAR FLORIDA: IMPLICATIONS TO CLASSIFICATION, CONSERVATION, AND RESTORATION By John H. Kiefer II May 2010 Chair: William R. Wise Cochair: Joann Mossa Major: Environmental Engineering Sciences Florida has a unique combination of a wet sub-tropical climate and a geologic history that involved comparatively recent marine processes on what is now the terrestrial landscape of the peninsula. This combination has led to three distinctly different water delivery systems to Flori da streams, copious and steady groundwater emitted through limestone springs under pr essure, unconfined lateral groundwater seepage through thick columns of sand through relict dunes, and surface water runoff coursing through and over combinations of shallow organic and sandy soils. These sources substantially impact the character of flow regimes. Florida stream valleys generally have m odest relief, but changes in grade appear to be associated with substantial differences in channel shape. Florida streams often course through complex valleys that can repeatedly alternate bet ween confining sandy bluffs and broad flat swamps. In-li ne lakes and wetlands are common. Existing stream classification schemes in Florida focus either generically on stream channel shape or on associations of water quality with aquatic biota. There existed a pressing need for systematic and quantitative study of the fluvial
19 geomorphology of Florida str eams and their associations with their watersheds. Such information is vital for the conservation, restoration and management of this resource. This study provides a first attempt at de scribing an array of Florida fluvial forms based not only on their channel shape and wa ter quality, but also on important thresholds concerning their landscape associations at the watershed and valley scales. These descriptions of Florida stream types are based on quantified channel and floodplain characteristics, valley shape, watershed soil characteristics and potential functional associations concerning stream hydrology, sediment transport, riparian vegetation, and aquatic habitat. Streams chosen for study were of a near-to-natural character and represented some of the healthiest stream settings in the peninsula. The main purpose of the study was to determi ne how a stream fits its landscape and how a restorationist tasked with recreating a damaged system would determine restoration objectives. At least 15 types of Florida streams can be systematica lly described based on metrics related to flow variability and flow source, power to transport sediment, conveyance shape and size, and posit ion in the drainage network.
20 CHAPTER 1 INTRODUCTION Need for Research Despite having a variety of fluvial forms, so me of which are comparatively rare in other regions of North America, no physi cal classification system based on modern concepts of fluvial geomorphology has been developed for the Florida peninsula. This is important because stream classifications de veloped elsewhere may not apply very well to Floridas unique combination of humid subtropical climate, carbonate geology, sandy soils, and low relief. Across humid temperate regions, streams are often classified and evaluated based predominantly on their shape at the re ach scale, generally covering distances of less than a few hundred feet (Rosgen, 1996; Harrelson et al ., 1994; Barbour et al ., 1999). This approach to fluvial geomorphic cl assification rests on assumptions that channel shape at that particular scale is as sociated rather strongly with processes of interest to stream restoration designer s and riparian systems managers tasked with protecting streams. Those assumptions are probably most valid fo r streams that are relatively deformable under dominant alluvial control. In other wo rds, streams whose shape is a strongly dictated as a function of sediment transport. Peninsular Florida has fluvial forms that are under variable degrees of alluvial control, raising questions concerning the indiscriminate applicability of shape-based classification at the reach scale. The propos ed research is intended to determine the merits of classifying peninsular Florida st reams based on metrics collected at multiple scales, including the reach. The premise of this research is to test the concept that not all Florida streams lend themselves to the types of reach-scale, form-based
21 classification now widely us ed across much of the rest of North America and that classification will improve by incorpor ating basin-scale forms and process-based factors. In other words, this assessment of diffe rent classification approaches and the use of classification for improved understanding of associations among independent and dependant variables is anticipated to facilit ate restoration activities that allow practitioners to better restore damaged str eams to their waters hed, or to guide watershed management plans for the protection of relatively intact riparian systems. Existing stream classification schemes in Florida focus either generically on stream channel shape or on associations of water quality with aquatic biota. No systematic and quantitativ e study of the fluvial geomorph ology of Florida streams and their associations with their waters heds and valleys has been conducted. Such information is vital for the conservation, restoration and management of this resource. The lack of current information holds especially true of small wadabl e streams draining headwater positions in the landscape (low-o rder streams) and th e streams formed downstream of low-order channel junctions (mid-order str eams). In comparison, the geomorphology, hydrology, floodplain habitats, and aquatic habitats of higher-order systems comprised of rivers located downstream of two or more mid-order catchments are fairly well studied (Inter-Fluve, 1997; Warne et al ., 2000; and Darst, et al ., 2002). There are many more low-order and mid-or der streams than higher-order rivers. For these reasons our team focused on lowand mid-order systems. This study provides a first attempt at de scribing an array of Florida fluvial forms based not only on their channel shape and source of water, but also on important
22 thresholds concerning their landscape associations at the watershed and valley scales. These descriptions of Florida stream types are based on quantified channel and floodplain characteristics, valley shape, watershed soil characteristics and potential functional associations concerning stream hydrology, sediment transport, riparian vegetation, and aquatic habitat. The main purpos e of the study was to determine how a stream fits its landscape and how a rest orationist tasked with recreating a damaged system would determine the appropria te restoration objectives. General Approach Streams were sampled from several types of natural kinds ranging across distinctly different hydrologic regimes and physiographic settings within peninsular Florida. Variables com monly associated wit h important forms in fluvial geomorphology were measured across a hierarchy of scales including the catchment, valley, reach, and in-stream patch. Process variables relat ed to hydrology and hydraulics, including tractive forces important for sediment transport, were determined as well. Study Area Description Compared to most of North America, Florida has a unique combination of a seasonally wet and dry sub-tropical clim ate and a geologic history that involved Neogene marine processes on what is now the terrestrial lands cape of the peninsula. This combination has led to three distinctly different water delivery systems to Florida streams, copious and steady groundwater emitted through limestone springs under pressure, unconfined lateral groundwater seepage through thick columns of sand through relict dunes, and surface water r unoff seasonally coursing through and over combinations of flat sha llow organic and sandy soils.
23 The climate varies across the state, especially in terms of the timing and annual volume of precipitation and in the magnitude of monthly potential evapotranspiration. Most of the peninsula exhibits a fairly pronounced wet and dry season pattern, with intense and frequent summer rains. The panhandle and northern Florida are more affected by the continental land mass than the peninsula and the seasonal pattern is different as a result (Henry et al ., 1994). Although most Flor ida peninsular streams exhibit pronounced seasonal flow patterns with higher pulses during the wet season (June through October) versus the dry (N ovember through May), the three basin physiographies substantially im pact the variability of flow. Chapter 2 provides more detail concerning this characteristic of Florida landscapes. Florida stream valleys generally have m odest relief, but changes in grade can be associated with substantial differences in channel shape. The stream channels often course through complex valleys that can repeatedly alternate bet ween confining sandy bluffs and broad flat swamps. In-line lake s and wetlands are common. These valley forms reflect the marine history of the peni nsula and its interaction with more modern fluvial forces. Continental streams are comparatively well-studied versus those of peninsular Florida. Our team was interested in the pot entially unique attributes of peninsular, seasonally wet, sub-tropical str eams. From this point forwar d, when the term Florida is used, generally the context is the peninsula and not the panhandle or areas close to Georgia. Site Selection Site selections were limited to str eams located roughly between the Santa Fe River watershed and Lake Okeechobee to assu re that the str eam population was
24 peninsular rather than continent al. All sites were surveyed at positions above the 5-foot contour line (National Geodet ic Vertical Datum), as mapped on USGS 1:24,000 7.5 Minute Series Topographic Maps, to assure t hey were non-tidal. First, the USGS Florida site inventory was used to select as many gaged sites as possible that met the initial inclusionary criteria: At least ten years of conti nuous or peak discharge measurements No direct alteration to the reach with wa ter control structures ditches, or canals Less than 20% of basin is impervious cover Less than 20% of basin is ditched or has induced discharge (for example, agricultural tail water) Less than 10% of basin is mined No significant land use changes during or since the gaging period, which was determined by examining historical aerial pho tographs at the University of Floridas Map and Imagery Library. Twenty-seven candidate sites reported with gages were initially selected using this method. To supplement the gaged sites, areas defined by the Cadastral Sectional grid were randomly selected to fill the roster with ungaged sites. If the selected Section contained more than one stream segment, it was successively quartered, and one of the quarters was then randomly selected until the selected polygon contained just one stream. A stream was then reje cted if it did not meet t he above inclusionary criteria (minus the minimum gage record criterion). Of the first 100 ungag ed sites selected in this fashion, 75 streams were reject ed and a clear trend em erged when it became apparent that all but four of the pre-selected sites were draining large tracts of public conservation lands. Therefore, to select si tes more efficiently, Cadastral Sections were restricted to public landholdings, such as st ate parks, state and national forests, water
25 management district lands, stat e wildlife lands, military bases, and county preserves, and to large private landholdings not subject to future development, such as those owned by the Nature Conservancy and thos e under conservation easement. Once 70% of the sites had been selected, these were graphically plotted based on their drainage area and valley slope to ensure that the samp le was not skewed towards a clustered regression. Sites continued to be selected r andomly, but were rejected if they fit a redundant drainage area to valley slope bin. Eight y-three sites were selected in this manner. Once site access permission was obtained, initial field investigations were conducted. Sites were ultimately excluded from the study if they had negative local effects (such as cattle grazing, ditching, ev idence of logging, bridge or road effects, altered hydrology), were not single-th readed channels or had poorly defined channels (such as braided or anastomosed stream types, sloughs, strands ), or had uncooperative landowners. Twenty-seven of the originally selected sites we re rejected, including Warm Mineral Springs Run (artificial weirs and bank clearing), Bugg Spring Run (stage declining since 1960s), Otter Spring Run (u ncooperative landowner), Camp-La-No-Che Run (drowned or embayed by Lake Norris at time of visit), Gopher Bank Gully (slough), Spoil Bank Tributary (uncooperat ive landowner), Myakka River Tributary (local ditching), Oak Creek Tributary (uncooper ative landowner), Wolf Cr eek (slough), Bull Creek Tributary (anastomosed), Big Jones Creek ( anastomosed), Alexander Springs Tributary 1 (road eroded and impassabl e), Lake Arbuckle Tribut ary (strand), Hog Branch (wastewater plant discharge), Mud Prai rie Distributary (strand), Gobbler Lake Distributary (strand), Cow Creek Tributary (banks impacted by logging), Charlie Creek
26 near Gardner (uncooperative landowner), Littl e Charlie Bowlegs Creek (slough), Fort Drum Creek (anastomosed and with large f earless alligator), Jane Creek (slough), Anclote River (potential dewater ing from wellfield), New Riv er near Zephyrhills (recent urbanization and unstable banks), Little Withla coochee River near Tarrytown (slough), Lake Placid Tributary (tree falls from hurricanes precluded access), South Fork of Blackwater Creek near Penney Farms (unc ooperative landowner), and Hickory Creek (local ditching). Fifty-six of the originally selected sites were surveyed and included in the study (Figure 1-1), 18 of which were gaged with reliable long-term records (Figure 12). Metrics and Hierarchy of Scale The hierarchical cons iderations behind the sampling classes included aspects of the physical catchment (basin capture and dominant delivery of water as runoff or groundwater), hydrology (water volume and flow frequency patterns in the stream), hydraulics and reach boundaries (potential relationships among valley and channel form, substrate, and processes), and physical habi tat (patch scale features important to aquatic fauna that derive from the fluvial geo morphology of the system and, in some cases, reinforce it). This construct embodied key concepts in applied fluvial geomorphology, some of which were assumptions explored further by this research: Humans can impact various stream com ponent variables across multiple scales. Channel shape alone may not be sufficiently delineative to classify streams in Florida to facilitate proper restoration or management activities because form may be convergent with mu ltiple processes. Climate, catchment and hydrology components are downhill relationships. They are independent variables that affect t he lower hierarchy components without
27 feedback loops. Such loops, if they occu r, operate on very long timescales that are unimportant to stream rest orationists or watershed managers. Basin/catchment components deliver water to a valley. Once in the valley, interactions among hydraulics, sediment s, vegetation, and channel form reach a dynamic equilibrium that is impacted or maintained on a time scale relevant to human activities. Channel and floodplain form are maintained by proc esses and complex feedback loops operating at the patch, valley, and reach scales. Given the construct of interest, the sample selection was designed to capture differences across three physical-scale hier archies, 1) basin/catchment, 2) valley and reach, and 3) patch/sub-reach. It also captured process variability by means of hydrology and hydraulics data across flow regimes ranging from intermittent to perennial and from low to high energy pulses. Morphology surveys at the reach scale were expected to capture virtually all of the common and uncommon channel and valley forms given the large number of sites in t he study. In addition to channel shape and hydraulic relationships, this included the r ange of normal condition s exhibited by the important boundary quality of substrate type (sand, rock/cla y, and detritus). Different dominant controls on fluvial form boundaries such as alluvial (transport), bedrock (geological), imposed (vegetation and snags), and colluvial (hillslope) were captured. The main physical habitat types recogniz ed by limnologists as most important to Floridas aquatic macroinvertebrate and fish fauna were captured as well. A reference reach survey was conducted at each site according to Harrelson et al. (1994). Cross-sectional and l ongitudinal surveys were completed along a minimum reach length of 20 times the channel width (top-of-bank to top-of-bank) to determine bankfull width, mean bankfull depth, maximum bankfull depth, bankfull cross-sectional area, slope, and sinuosity of the channel. A Leica Total Station and a handheld data
28 collector running Carlson SurvCE (Carlson) were used to record measurements to 100th of a foot, as per accuracy of the equi pment. Depth of water at the thalweg was recorded to the nearest 10th of a foot. Plan, longitudinal, and cross-section profiles were derived from the survey data using RiverMo rph 4.0.1 Stream Re storation Software. General Use of Exploratory Statistics The research questions boiled down to interests concerning the prediction of group membership, structure of the data, and relationshi ps among variables. Basic a priori decisions included whether to proc eed using controlled versus uncontrolled multivariate analyses, features (discrete data) in additio n to properties (continuous data), and simple random sampli ng versus structured sampling. Simple random sampling of roughly 50 site s from the populatio n of all Florida streams was unlikely to lead to a sufficient representation of all major stream types, some of which are clearly not random in their distribution and have much more limited distributions than others. Plus, much can be inferred from examination of the sensitivity of the association between independent vari ables and their potential effects on a dependent variable using regression, within and among classes. Regression works best when samples cover a range of variables of interest across as much of the population as possible. Therefore a more structured site selection approach was required to assure that the limited number of samples covered the potential fluvial forms and also would cover a relatively wide range of potential independent variables for use in regression. Some statistical analyses of multivariate datasets are more sensitive to outliers, and more reliant on normality, linearity, and homoscedastcity than others. Data screening started with looking for missing or mis-entered data and proceeded to
29 screening for the aforementioned conditions. Decisions re lated to treatments for outliers favored use of techniques less sensit ive to them rather than eliminating them from the dataset when feasible. Transforma tions of non-normal data were utilized to overcome some parametric limitations in the raw data. Inflated correlation is a real and somewhat unavoidable issue in fluvial geom orphology. Use of composite variables was carefully considered and alternatives were used as deemed allowable. Data centering was used to address collinearity in regressi ons. Deflated correlation was unlikely given the sampling design. The research plan was designed with several di fferent statistical techniques to be invoked on various components of the datas et, including principal components analysis (PCA) for exploration, linear regression fo r exploration and pr ediction, multiple regression for prediction and class comparisons, and hierarchical cluster analysis for exploring classification (Tabachnick and Fidell, 2007). Document Organization This document provides three special purpose chapters in addition to the introduction and summary. Chapter 2 focuse s on the watershed scale, with particular emphasis on comparing the geomorphic di fferences between streams fed by two different aquifer types versus stream s fed mostly by rainfall runoff. Chapter 3 focuses on the valley s cale, wit h emphasis on describing the clinal and patchy patterns of Floridas riparian corridor morphology within the drainage networks of different physiographic regions of the state. It overview s Floridas deranged drainage networks, which are frequently p unctuated with in-line wetlands and lakes. This chapter also discusses applications of functional process zone (FPZ) concepts. FPZ concepts are used to describe and classify rivers as habitat patches with abrupt lateral and
30 longitudinal edges that can repeat along the drainage network. The habitat patches are not completely random or static, however and they are usually organized at a landscape level (Thorp et al., 2008). FPZ concepts are further explored as part of Chapter 4, which provides descriptions of latent variables suggesting as sociations between fluv ial form, in-stream habitat patches and fluvial processes that s eem to depend on hierarchical interactions of the watershed scale and its hydrogeology, valley confinement characteristics, and bankfull channel hydraulics. This chapter prov ides descriptions of the apparent natural kinds of streams in Florida, as partially ev idenced by a series of hierarchical cluster analyses on all the available metrics for 56 sites. Chapter 5 briefly summarizes the findings while placing them in the context of potential management decisions to promot e enhanced stream protection, better restoration strategies, and proper mitigation approaches. The need for future multidisciplinary research is also emphasized.
31 Figure 1-1. Reference reach stud y site locations (56 streams).
32 Figure 1-2. Gaged study site locations (18 streams).
33 CHAPTER 2 HYDROBIOGEOMORPHOLOGY OF BLACKWATER STREAMS AND SPRING RUNS IN SUB-TROPICAL FLORIDA Introduction Purpose Streams belong to their watersheds. The pur pose of this chapter is to further describe this association in the wadable per ennial streams of peninsular Florida by comparing the hydropatterns and basin charac teristics among streams draining three different kinds of water supply systems comm only found in the sta te. These include two types of groundwater dominated systems, one that provides perennial discharge from a confined aquifer consisting of carbonate ro ck in karst terrains and the other which provides baseflow discharge predominatel y via lateral seepage from a deep sandy unconfined aquifer with high infiltration capacity. The seepage basins typically have some internal drainage and often have large lakes (Myers and Ewel, 1990; FNAI, 1990). We observed that seepage stream watersheds al so provided runoff during intense, high volume rain events. The seepage basins occurred on high sandy ridges consisting of relict dunes (White, 1970). These areas, when undisturbed, support upland habitats consisting of xeric plant communities that have special adaptations to droughty sands with low groundwater tables (Myers and Ew el, 1990; FNAI, 1990). The third water supply system consists of comparatively flat basins that have low infiltration capacity during the wet season with very high wa ter tables (Myers and Ewel, 1990). They routinely deliver most of t heir total discharge volume via surface water runoff events, often through a series of wetland depressions and sloughs (FNAI, 1990). These landscapes support pine savannas and wood lands, grasslands with palmettos, and
34 prairies adapted to seasonally wet conditions, often referred to as flatwoods (Myers and Ewel, 1990; FNAI, 1990). The fundamental question is, Should we consider water source as part of a hierarchical classification system of Florida streams and if so, why? The second question centers on what hydrologic and waters hed variables are important to consider based on their association with channel and floodplain morphology. This is an important question related to stream management and restor ation because hydrologic variability is complex and many restor ation and management approache s seek simplifications. One common simplification rests on the c oncept of effective discharge, which states that channel dim ension and pattern result mainly from the actions of the single discharge that does the most overall work transporting sediment (Andrews, 1980). The theory of dominant discharge states that if a stream were to fl ow only at its most effective discharge rate, it would achieve the same overall cross-section dimension and planform pattern that it exhibited under its natur ally variable flow regime (Harvey, 1969). This is not as simple a concept as it appears and it is also potentially misleading if taken too literally by stream m anagers because biological systems can influence morphology and the associated plant communities respond to different flooding regimes in riparian corridors. Furthermore, comparatively ra re events may provide important pulsed disturbances that breakup c hannel evolution trends by es tablishing a hierarchical component to equilibrium conditions akin to pressing a reset button. Uncommon floods also do work in the floodplain at thresh olds that the effective discharge does not attain.
35 Because Floridas karst spring runs provide as close to a constant discharge as one can find in nature, they of fer the potential to explore t he literal truth of dominant discharge concepts. Or put another way, W hat would happen in nature to a stream channel and its floodplain geomor phology if it only modestly deviates from its dominant discharge rate? Streams draining flatwoods basins have much more variable flow regimes and serve as an excellent comparison within the sa me climate. However, this comparison is potentially confounded by differences in the wa ter quality of these tw o types of streams important to aquatic biota, especially hardness and color. Therefore, seepage streams draining Floridas sandy highlands were included to determine if they provide an intermediate degree of flow variability and could offer an opportunity to explore the intermediate effects between the highly vari able flatwoods flows and the very steady karst flows but with a smaller degree of c onfounding water quality issues. This is because the highlands streams are usually bl ackwater streams wit h wet-season water quality more similar to flatwoods streams than to the spring runs. Study Area and General Site Descriptions The geomorphology of Florida has been described and mapped based largely on its marine-derived geology and variable submergence history due to sea-level fluctuations. The peninsula consists of a re latively thin veneer of reworked sand and clay of varying thicknesses over a thick m antle of porous limestone bedrock. Sea level changes have led to the formation of severa l relect marine terraces and a distinct sandy central ridge running down the interior of t he peninsula. Large portion s of the state are pocked with lakes and wetland depressions orig inating from the solution of carbonate rockgenerally referred to as karst terrain. The areas with the most obvious karst
36 features tend to be along the highest ridges and are internally drained with relatively few streams compared to areas with more limited karst-derived lakes. The areas with limited karst expressions tend to have fewer la kes and more streams. This has led to two basic physiographies in the state supporti ng streams: 1) highlands (generally with lots of lakes, relict sand dunes, low wate r tables, rolling topography and few streams) and 2) flatwoods (generally with lots of wetlands, high water tables, flat topography and many streams). Although the highlands have lower overall drainage densities, a patchy distribution of streams occu r on these ridges and some of those patches can provide localized drainage densities sim ilar to those of the flatwoods This is discussed in more detail in Chapter 3. Most geomorphic classifications used in t he state are based on t he work of William White (White, 1958; White, 1970). Understandi ng the geological/geomorphic setting of streams in Florida is important because the lithology exerts significant controls on the distribution of flow among surface water and groundwater systems. The major geomorphic divisions exhibit a variety of watershed sizes, valley slopes, valley lengths, stream network patterns, and groundwater/s urface water interactions. Griffith et al. (1994) mapped 20 ecoregions in the state bas ed on a combination of the effects of geomorphology, climate, soils, and ecological communities with some significant deference to the natural vegetation (Figur e 2-1). The NRCS has produced land form classes and maps resulting in four Fl orida peninsula categories based on soils, geomorphology, and climate (NRCS, 2006). Thes e classifications inherently reflect Floridas marine geological history, whic h has left a complex milieu of geological exposures and shallow lithological layers acro ss the state comprised of unconsolidated
37 sands, stiff clay, and limestone (Figure 22). The scale of these deposits and their frequent re-working due to sea level changes, as recently as the Pleistocene and early Holocene, means that long Fl orida stream valleys typically flow through multiple exposures. Also, more than one ecoregion can occur in a watershed (surface drainage basin) or springshed (area of rechar ge and potentiometric influence to a spring run). Inclusions of the vegetation and soils assemblages common to one ecoregion can be found in the broad areas mapped as a different ecoregion. For example, it is pretty common to have up to 40% of a watershed in a xeric highlan d ecoregion comprised of flatwoods plant communities or to have small watersheds almost completely dominated by xeric highland communities within a flatwoods ecor egion. Ecoregions likely warrant careful consideration for Florida fluvial geomor phology, mainly because they have a strong association with geomorphic hi story of the landscape, but ecoregions alone are not likely to be robust predictors of stream ty pes or functions as typically mapped at a statewide scale. Existing Limnological Classifi cation of Florida Streams There have been limited attempts to derive a comprehensive physic al classification of Floridas freshwater streams. Ecologists interested in stream limnology and aquatic fauna developed the only attempts at general stream classifications in Florida. These were based pr imarily on faunal metrics, water quality, and in some instances sediment type. Rogers (1933) offer ed one of the earliest classifications based on his crane-fly research in northern Florida, describing five classes of streams based on their water quality, sediment type, si ze, and position along the drainage network. These included 1) small str eams defined by the presence of alluvial bed forms of
38 rolling sand, 2) larger calc areous streams with water de rived from huge springs and calcareous lakes with clean swept limes tone beds and ranks of submerged aquatic vegetation, 3) swamp and bog streams with sluggish flow through swamps with poorly defined banks and organic bottoms, 4) lower st reams were generally rivers with highly variable seasonal flow and bottomland floodplains, and 5) seepage areas and small rills typically were small seepage outlets from the surficial aquifer, often less than a few square yards in size. Occurring along mo st small streams these seepage areas exhibited concentrations of unique crane-flies, perhaps warranting sp ecial consideration from this particular researcher. Rogers stated that the small stre ams were the most common type. Building on the work of Rogers, Beck ( 1965) provided perhaps the most influential of the attempts at developing a statewide str eam classification in Florida, resulting in five limnological classes of streams based on their chemical, physical, and biological characteristics and matters of convenienc e. Beck, perhaps unfortunately, reduced Rogers attention to stream size and l andscape position and added two nominal classes as matters of convenience (Large Rivers and Canals). Beck largely validated certain natural kinds of classes by statistically si gnificant differences in faunal distribution. Beck described natural kind classes for SandBottomed Streams, Ca lcareous Streams, and Swamp-and-Bog Streams, which corresponded rather similarly to those described by Rogers. The characteristics separating the thr ee natural kinds of streams in Becks classification were mainly pH, hardness, co lor, velocity, substrate, and aquatic fauna (especially rheophilic macroi nvertebrates, mollusks, and fishes). Sand-bottomed
39 streams had low to neutral pH, moderate to high color, low to moderate hardness, moderate to swift velocity, beds dominated by fine sand, and rheophilic/rheobiontic macroinvertebrate fauna. Calc areous streams had neutral to slightly alkaline pH, were colorless, had moderate hardness, low to s wift velocities, sand, clay, limestone and organic beds, mollusk fauna, and submerged aquatic vegetation. Swamp-and-Bog streams had low pH, high color, low hardnes s, low velocity, organic silt beds, no rheophiles, almost no mollusks, and fi sh fauna with sunfish and darters. Scientists working for the Florida Natu ral Areas Inventory (FNAI, 1990) refined Becks classification by adding descriptions of landscape settings and water sources. They also categorized vegetat ed Swamp-and-Bog conveyances as wetlands rather than streams (as strands, sloughs, swales). FNAI listed four riverine ecosystem types: Alluvial Streams, Blackwater Streams, Spring-Run Streams, and Seepage Streams. Alluvial Streams originate in high upl ands and carry high sediment loads. They have intermittent to perennial flow. They are generally confined to large streams and rivers originating from the continental l andmass. This name is potentially misleading, because it implies that all other stream channels in Florida are non-alluvial which is not true. It would be more accura te to think of them as W ash-Load streams given their perennial turbidity or Continen tal River given their origin. Blackwater Streams, the most common type in the state, originate from sandy lowlands with wetland reservoirs discharging t annic waters to the channel. They can be intermittent or perennial and often, but not a lways, are characterized by acidic waters. FNAI makes no reference to their practically ubiquitous sandy alluvial bed forms and seems to be lumping quite a number of different types of entrenched and non-
40 entrenched forms with very differe nt floodplain configurations. In fact, contrary to FNAIs descriptions, most larger bla ckwater rivers in Florida do have strong alluvial indictors such as natural levees (for example, the Peace River) and anastomosing plan-forms (for example, the Kissimmee River). Stream s ranging across a fantastic array of basin sizes and hydrologic regimes are also lumped For example, this class would include both of the following streams: An unnamed headwater tributar y six feet wide, 900 feet long, that flows for four months a year, drains a 0. 8 square mile watershed, lacks a wetland floodplain, its banks consist of upland soils held tightly by palmettos, and bankfull flow is two cubic feet per second (cfs) An open channel 50 feet wide that is par t of a valley more than 40 miles long, flows perennially, drains more than 200 s quare miles, has banks of alluvium held tightly by wetland tree and shrub species across a wetland floodplain more than 500 wide, and bankfull flow is about 200 cfs. This comparison illustrates systems with some key limnological similarities that differ substantially in their fluvial form and processes. They have different protective management requirements and, if damaged by human activities, would have far different restoration designs. FNAIs Seepage Streams originate from shallow ground waters that have percolated through deep, sandy uplan d soils. They can be in termittent or perennial with either clear or tannic waters. They are us ually short, shallow and narrow or they may form the headwaters of Alluvial and Blackwater Streams. Based on these descriptors it is difficult to separate quite a few stream s with different fluvial forms and processes between the Blackwater and Seepage classes using FNAIs qualitative descriptions, especially some of the lar ger streams draining sandy highlands associated with the Lake Wales Ridge and many small headwater streams in the sandi er flatwoods with slight xeric upland inclusions. Furthermore, the Seepage Stream class also fails to
41 distinguish between sapping streams (steepheads) with sandy bottoms and bayhead runs with organic beds, two generally small stream systems with fundamentally different valley formations and s ediment transport mechanisms. FNAIs Spring-Run Streams are perennial water courses deri ving most of their flow from artesian vents. Water is clear with neutral to slightly alkaline pH. They have sand bottoms, sometimes with exposed limestone. This characterization of the bottom sediment is incomplete as it ignores one of the most common b ed materials in these runs, referred to by Odum (1957) as gyttja. Gyttja is an organic sediment derived from biota within the spring run. The FNAI classification seems reasonable for certain nominal purposes and does adequately describe many streams in the state. The main delineative criteria are based on water quality (especially suspended solids, pH, color) and on the dominant source of water and the media through which it passes before reaching the c hannel. Blackwater Streams get their water via wetlands, Alluvial Streams from conti nental runoff, Seepage Streams from thick upland sands, and Spring-Runs from the artesian limestone aquifer. While they were conceived based on importanc e to aquatic flora and fauna, these could also be very important distinctions related to the fluvial functions of Florida streams. Figures 2-3 through 2-7 depict photographs co mparing perennial spring runs, flatwoods and highlands streams under varying flow conditions. Methods Data Availability and Site Selection In addition to on-line queries of USGS records, data managers at the South, Southwest, Suwannee, and St. Johns River Water Management Districts were contacted to identify which of the 56 streams selected for this study had reliable long-
42 term discharge records. We also queried these sources for additional sites draining small watersheds, but identified a rather cons istent bias toward mid-order and larger streams. For example, 1.9% of the USGS gage sites with at least 10 years of daily records in Florida were from streams with less than two square mile watersheds, despite the fact that the ma jority of streams drain such watersheds. Only one of the eight available gaged low-order streams identified met the incl usionary criteria of the study, usually because of urban landscapes or di rect alteration by channelization or with a hydraulic control structur e. The nature of the availa ble data restricted long-term hydrologic assessments to a subs et of the perennial streams in our study A total of 18 of the 56 reference reach sites (32%) had us eful records. This included five karst streams, six highlands streams, and seven flatwoods streams. Field and Desktop Measures Drainage area was calculated for each site in the study. This analys is used local surface topography to delineate watersheds for the highlands and flatwoods streams. Surface divides in some of the lowest-relief areas of Florida can be subtle and can even be crossed by wet-season sheet flow afte r extreme rainfall events. Furthermore, groundwater divides providing baseflow can shift seasonally. Therefore, basin divides should be viewed as approximate in Florida. This is further complicated for spring runs which can have a local t opographic basin that is very different in location and size from the main source of water to the run, its springshed. Springsheds are the land areas that catch the rainfall infiltration which discharges to spring runs. Their location can be poor ly associated with topographic divides and usually varies spatially on a seasonal basis depending on t he geometry of the potentiometric surface of t he Floridan aquifer. Springsheds are necessarily a rough
43 approximation of the actual extent of the groundwater catchment and are often estimated using a combination of well data and numerical modeling. Publications aimed at delineating springsheds or calculating rechar ge for specific springs or spring clusters were used to assign springshed dimensio n for the spring runs studied. Shoemaker et al (2004) delineated Alexander Sp ring Runs springshed using particle-tracking models and their value was adopt ed directly in this study. In most other cases, the springshed consisted of a rechar ge zone that distributed groundwater flow to multiple spring runs and the authors provi ded a recharge rate (usually expressed in inches/year) as part of the water budget. When the spring run mean discharge is known in addition to the springsheds average annual recharge rate, the average size of the springshed can be calculated for a given run. For the purposes of this study, spring runs belonging to springsheds feeding multiple r uns were simply assigned an area directly proportional to the relative discharge of the run studied versus the total discharge of all the runs sourced from the co mmon recharge area. Shoemaker et al (2004) provided relevant data for Silver Glen Springs, of wh ich the Silver Glen U nnamed Tributary (UT) run was a tributary, enabling this met hod to be used for that site. Shoemaker et al .s (2004) data for the northern part of the St. Johns River Water Management District (SJRWMD) were used to estimate the springshed size for Forest Spring Run. Knochemus and Yobbi (2001) provided data us ed to calculate the springshed size for the Weeki Wachee River. Wanielista et al (2005) provided data used to calculate springsheds for Rock and Kittridge Runs. Hirths (1995) recharge study and water balance for the Ichetucknee River was used to derive a proportional springshed for its tributary in this study, Cedar Head Run. Knowles et al (2002) study of the recharge
44 areas of Lake County and the Ocala Nation al Forest was used to estimate the springshed size for Morman Branch UT. P helps (1994) provided a recharge map and potentiometric surface that was used to delineate the springshed for Juniper Run. SWFWMD (1993) provided data used to calc ulate the springshed sizes for the Gum Slough and Alligator Runs. Little Levy Blue Spring Runs springshed was estimated from recharge rates repor ted for the Suwannee River Water Management District (SRWMD) (Grubbs, 1998). Detailed field surveys were made at the reach scale to map the stream channel topography, in-stream habitat patches, and bankfu ll indicators using a twoor threeperson crew and Leica total station. See Blanton (2008) for additional method details. Each of the 56 sites was visited twice, some multiple times during a three-year period. The survey point files and rendering results were reviewed prior to the follow-up visits to verify their reliability and interpretation. Du ring the follow-up visits shallow sediment cores were extracted to determine the alluvi al history of the floodplain, the dominant bank and floodplain plant species were inventoried, as were the alluvial channel features and alluvial floodplain features. The width of the we tland, relative elevation of biological flood indicators, connecting upstr eam and downstream waterbody junctions, channel grade and channel bank controls, and potential transport mechanisms (such as scour versus sapping) were explored and docum ented. This suite of multi-disciplinary observations (soils, vegetation, geomorphology, hydroecology) enabled an improved understanding of potential site processes associated with geomorphology compared to what the geomorphic survey data alone could provide.
45 Bankfull discharges were calculated by re lating field indicators at the surveyed reference reaches to the gage height data in the manner described by Blanton (2008). This method was applicable to all gaged site s except two (Gum Slough and Lowry Lake UT). These two streams required different treatments because their gage records were disjunct from the reference reach and their flow data required adjustment to be more applicable to the conditions in the reach due to intervening sources of discharge between the research site and the gage. The Gum Slough Spring Runs bankfull discharge was determined by conducting standard USGS velocity-area measurements using a Sontek Acoustic Doppler Velocimeter (ADV) at a near bankfull conditi on (within 0.1 feet). Mannings n was calculated from this event and then Manni ngs equation was used to calculate the bankfull discharge at the surveyed bankfull stage and hydraulic grade line. The Gum Slough gage was located a few hundred feet dow nstream of the reference reach, shortly after the str eam entered an anastomosing zone with numerous mature tree islands. Our study was devoted to single thread reaches, so this was not an appropriate area to survey. A cluster of high volume spring vents added flow to the run between the surveyed reach and the gage. Ther efore the available record had to be adjusted. Based on several measur ements taken in 1932, 1972 and in 1999 (as referenced in Champion and Starks, 2001), and a single measurement made in 2008 by our team, the flow from the springs upstream of the reference r each averaged 33.5% of the flow at the gage (range of 31 to 38%). Th erefore, the measured daily flow record was multiplied by 0.335 to provide a simu lated record for the reference reach.
46 Lowry Lake UT was the smallest tributary in the hydrologic analyses. It was a four foot wide seepage stream that drained a sandhill community. The channel had significant bed roughness from a series of steps and pools cascading over live root systems that completely s panned the channel. Bankfull disch arge was estimated at Lowry Lake UT using Mannings equation in a slope-area solution. The slope was based on the average water surface profile through the surveyed reference reach at the field indicators for bankfull stage. Cross-section dimensions were derived from the same survey at a riffle and the flow was calcul ated from bankfull stage using a value of n (0.25) estimated from values that were tak en from flows measured at two very similarly narrow root-step streams (Lake June-In-Win ter UT and Ninemile Creek) taken during bankfull conditions. Lowry Lake UTs gage was located about one mile downstream of the reference reach and two seepage streams c ontributed flow to the gage downstream of the survey reach. The reference reach basin was about 22% of the total gage drainage area. Physiography, land use, and channel incision were nearly identical for the gage and reference reach basins, so the available record was adjusted by simply multiplying it by 0.22 to simulate a long-term record for the surveyed area. The adjustments made to these two sites to capture their records ar e likely to be imperfect approximations of actual daily flow conditions, but based on the commonalities of the source areas, are likely to provide good indication of properly sca led, long-term flow variability of these sites. Given the small number of sites in the study with long-term flow records, these were justifiable inclusions.
47 For all sites in the study, indicators of biologically relevant overbank flow levels were used to define flood discharge stages. Typically, these were the lower limits of lichen and/or water stain lines on trees on the bank and in t he floodplain. In most cases these indicators coincided within a few vert ical inches of the wetland edge, typically extending at least a few feet laterally into the dense palmettos lining the wetland corridor. For many streams with entrenched channels and rare overbank flooding, the lichen line was at the base of trees and thick moss collars replaced the lichens below the top of bank, so other indicators were us ed. They usually were the upper limits of thick moss collars, the upper limits of wetl and vegetation on the bank at a pronounced inflection, or simply the top of bank in the absence of these indicators. For sites with gage height records applicab le to the surveyed reach, flood discharge was determined from the stage-disc harge curve using techniques analogous to those deployed to calculate bankfull disch arge. This could not be done for Lowry Lake UT and Gum Slough Run and their flood discharges were calculated using Mannings equation and lit erature values for the floodplain friction factor based on the type and density of floodplain vegetation (Arcement and Schneider, 1989). The long term gage records were evaluated, in part, with GeoTools Version 4 software (Raff et al ., 2007). The software was used to calculate the available 105 hydropattern metrics to assess five key components of the flow regime: magnitude, frequency, duration, timing, and rate of change (Poff et al., 1997). Appendix B provides a list and brief description of each metric, plus some additional metrics calculated independently of the software.
48 GeoTools was also used to calculate fl ood frequencies. Partial duration series were used instead of annual maximum seri es because bankfull flood frequencies are typically more frequent than once a year in Florida (Metcalf et al ., 2009; Warne et al ., 2000; Blanton, 2008) and also in other blackwat er streams of the southeastern coastal plain of the United States (Sweet and Geratz, 2003; H upp, 2000). The method was standardized by specifying minimum dischar ge at one-half bankfull flow, the Cunane empirical distribution function, and a minimu m inter-event duration of seven days for each site. The flood frequency was then dete rmined from the output table for the bankfull and seasonal flood discharges. The gage data were prepared for use in t he evaluation software first by careful examination for missing record s. Few occurred and these were substituted by inserting values that were an average of the adjacent values in the record. The spring runs had records from five to 11 years long, while some of the blackwater streams had continuous records dating back to the 1950s Because the main interest was to compare metrics related to flow variabilit y among basin classes, the longer records were truncated to their most recent ava ilable 11 year period through calendar year 2008 to reduce potential bias from the longest term s all being in large blackwater streams. Flow duration exceedance curves were developed in MS Excel 2003 and then were plotted using SigmaPlot Version 11. Thes e data were used to calculate the median discharge and to determine the percent of ti me the bankfull and flood discharges were equaled or exceeded. GIS layers were developed for LiDARderived topography where available to delineate watersheds and develop large-scale transects bigger than the reference reach
49 surveys. Most of these data were from the Southwest Florida Water Management District (SWFWMD) and some was available from the SJRWMD and Alachua County. For areas without LiDAR topo, the USGS 1:24000 orthoquads maps were used. Drainage densities were calculated from t he National Hydrologic Database as digitized for Florida from the 1:24000 USGS quads. NRCS (2007a) hydrologic soils groups were determined for each basin using the shapefil es available from the Florida Geographic Digital Library (FGDL), as were land use distributions (such as percent lakes and wetlands) from Florida Land and Cover Classification Codes (FLUCCS). Bankfull discharges were derived from fiel d measurements of flow at or near bankfull stage for 35 of the 56 study sites (T able 2-1). For 14 of these sites with USGS or SJRWMD gages, the agency field measurements and their stage-discharge records were used to calculate the average long-term discharge reported at bankfull stage. Our team developed stage-discharge relationships for an additional eight low-order streams in the study from 2007-2009 and used these dat a to help verify bankfull discharge. For 27 sites, our team was able to measure the discharge during a single event within 75% of bankfull stage using the USGS velocity -area method and these discharge values were adjusted to bankfull stage using Manning s equation and the same hydraulic slope and n taken during the measurement. For the 21 of 56 sites wit hout measured bankfull condi tions, the discharge was calculated using Mannings equation, field in dicators of dominant discharge (flood and bankfull stages), and topographic survey data (cross-sections and profiles). The Mannings n values calculated for 35 the 56 study sites using measured discharges and surveyed hydraulic grade lines (or field indicato rs of bankfull grade line) close to bankfull
50 conditions provided a library of reference c onditions for sites where those data could not be measured but were with similar bed and bank dimensions, reach slope, vegetation and debris loads. Mannings n for flood flows was calc ulated from gage record stage-discharge relationships using an assumed hydraulic slo pe equivalent to the va lley slope along the segment encompassing the reference reach. The values calculated in this manner typically met expected literature values fo r the floodplain depths and vegetation. Data from similar sites in the study were again used to assign floodplain n values to ungaged sites to calculate flood discharges based on field indicators of flood stage and valley slope topography as a surrogate for hydraulic slope at flood condition. The approaches taken are expected to provi de an order of magnitude estima te of flood flows, while typically providing much better estima tes of bankfull discharge for each site. Exploratory Statistics The hydropattern metri cs from GeoTool s were reduced and examined for potential latent variables using principal com ponents analysis (PCA). The sites were hierarchically clustered on the z-scores of the raw data for all hydropattern metrics using Wards method. Box plots and one-way analysis of variance (ANOVA) were used to explore potential differences in several metrics hypothesized to differ among physiographies (mean alluvial features, flood power to bankfu ll power ratios, and channel resistance as Mannings n). Regressions are useful to det ect differences that tests of means like ANOVA may fail to illustrate. Therefore power function regressions were performed on data that were normally expected to be hi ghly dependant on scale of the drainage area or volume of dominant discharge. These data were typically linearized by log-log
51 transformations, which were pl otted to examine different trends in geomorphic variables associated with drainage area or discharge, corrected for physiography. The regression and ANOVA explorations used metrics that were available from all 56 sites in the study enabling evaluation of sites drai ning a wide array of basin sizes, many of which are not perennial, but was necessarily limited to do minant discharges in the absence of long term flow records. The PCA and cluster analyse s were applied to the metrics available from the 18 sites with perennial discharge reco rds enabling a more detailed look at flow variability on a more limited number of si tes and smaller range of flow regimes. Results and Discussion Basin Types and Flow Exceedance Curves The 18 streams with perennial flow data were grouped based on their physiographic region prior to statistical testing. This grouping consisted of three basin classes consistent with their perceived domi nant water sources (karst springs, xeric highlands, and flatwoods). The groupings were vetted based on the soils, vegetation, and hydrogeomorphology of t he drainage basin of each site. This was neces sary because these water sources can intergrade. The study design focused on the upper part of spring runs, close to their vents but in areas with hydraulically adjustable bed features, to minimize confoundi ng factors related to surfac e drainage contributions far downstream of the headspring and to avoid reaches clearly dominated by geologic controls. Highlands and flatwoods water sources wit hin basins, especially for mid-order sites, were unavoidably mixed. So a means for separating these two groups was devised by plotting a simple index of flow variability based on data from flow exceedance probability curves vers us a simple index for basin characteristics likely to
52 be highly associated with basin infiltration c apacity. The basin soil index was the sum of two NRCS soil hydrologic groupings associated with sandy xeric uplands that allow very high to moderately high wet season infiltration and modest to little runoff (A and C soils). This sum was calculated as the percentage of the total drainage area covered by those soil classes. NRCS did not map any B soils in the study areas. Based upon examination of 2004 true-color one-meter aerials avai lable from the Flor ida Department of Environmental Protection (FDEP) and groundtru thing during the various site visits, areas mapped by the NRCS with A soils appeared to be associated with longleaf pine sandhill, xeric oak scrub, and sand pine scrubs while C soils appeared to correspond to scrubby flatwoods and xeric oak scrubs for th e study areas. Therefore, the A+C soil percentage of the basin wa s considered to be a good index for the drainage areas groundwater flow delivery capacity versus surface runoff. Flow exceedance curves offer a visual interpretation of the discharge variability. Curves with steep slopes and wide vertical r anges represent flashy streams with more variable flow regimes. Systems with very steady flow have relatively flat curves. To facilitate comparison among site s, the average daily flows were divided by the sites median discharge. The information was pres ented in the conventional USGS fashion with a horizontal exceedance pr obability axis and vertical discharge logarithmic axis. A simple metric was calculated as a flashines s index from the data used to produce these curves. In various wetlands throughout the st ate, the upland ecotone often occurs at a seasonal high water elevation that has at least a two-month hydroperiod (Myers and Ewel, 1990). This is slightly more than a 15% exceedance, which in the authors experience as a professional we tland scientist, is a convenient starting point for defining
53 seasonal high water levels in Florida wetland s. Median flow could be considered the normal value and, by analogy, the 85% exceedance could be considered the seasonal low water. Therefore, t he slope of the unit discharge between the 15th and 85th flow percentiles represents an index of the routine inte rannual or seasonal flow differences for Florida waters. This seasonal flow slope (SFS) was calculated for the 18 gaged sites and was plotted against the A+C soil in dex in their watersheds (Figure 2-8). This plot is linear when plotted as an exponential function su ggesting that highlands and flatwoods streams were part of a nonli near continuum, but one that had a transition at about 40% to 45% A+C soils when raw data were plo tted. Streams above that threshold behaved mostly like groundwater-dominated systems with comparatively steady flow and streams below it were increasingly surfac e water dominated and more seasonally flashy. As expected, the spring runs provi ded flatter flow exceedance curves in association with their comparatively cons tant discharge regimes than the flatwoods streams and the highlands str eams, which receive baseflow from a different aquifer and flood flows from basin runoff are indeed interm ediate in pattern between the karst-fed and flatwoods streams (Figures 2-9 through 211). Therefore, it appears that flatwoods, highlands, and karst basin types are useful distinctions but that they do not necessarily offer completely disjunct hydrologic cla sses and also could be viewed to merely represent some useful distinctions along a natural gradient of gr oundwater influence. Partial Duration Frequency of Discharge Bankfull flow is a frequent occurrence in Fl orida. Blanton (2008) confirmed that it routinely oc curs more frequently than an annual return interval (ARI) of 1.5 years, in
54 perennial and non-perennial streams, based on an annual maximum series (AMS). This is an important threshold because it means that Florida str eams do not fit norms reported for most, but by no means all, perenni al streams in temperate humid climates (Williams, 1978; Leopold et al ., 1964). Many Florida streams have very low bankfull ARIs (approaching 1.01 years). Such low ARI numbers are difficult to interpret, because the ARI is the inverse of the number of ti mes the flow threshol d is exceeded per year (annual flow frequency), and by using the AMS to calculate the ARI one cannot derive values corresponding to multip le floods within a year. For that reason, and also because the AMS often starts to distor t the flow distributi on for many flow regimes below even a 10-year return interval, a partial duration se ries was used to more accurately calculate the annual bankfull and flood flow frequenc ies for the 18 gaged study sites. The 18 perennial study sites met or exc eeded bankfull discharge conditions at least eight times per year (Table 2-2). ANOVA indicated average bankfull frequencies differed significantly (p<0.05) between kars t streams versus the other basin types (Table 2-3). Mean bankfull frequencies were 19 ev ents/year for flatwoods streams, 21 events per year for highlands, and 33 for sp ring runs. Perhaps karst streams retain more in-channel volume through the year due to their steady flow and are able to more routinely pulse above the bankfull stage versus blackwater streams (highland and karst) that have a lot more water level variability an d further to rise and fall between events. It should also be noted that bankfull flow in karst streams is often entrenched; meaning bankfull discharge is not necessarily exceeding the elevation of the valley floor. These are not runoff streams wit h alluvial floodplains.
55 Upon reaching bankfull discharge, spring fed streams tended to stay above it longer than the perennial str eams of other basin types as suggested by statistically significant (p<0.05) ANOVA tests on the fl ow exceedance percentiles (Table 2-3). Karst streams discharged at or above bankfull flow nearly 41% of the year on average versus 23% and 28% for the flatwoods and highlands streams. In this case, highlands and flatwoods streams were indistinguishable. There were no statistically significant di fferences among basin groups for either their flood flow frequencies or flood flow durations (Table 2-3). The flood discharge was not a rare event because it was defined in a manner to approximate th e lateral limits of the heavily vegetated wet season channel usi ng a combination of hydroecological and geomorphic indicators to delineate such c hannels where they occur. Not all Florida streams had such features above the top-of -bank, while others had readily observable bankfull channels embedded within a flood channel that existed above the top of the bankfull channel. Such dual-tier conveyanc es with an open alluvial channel embedded within a wider heavily vegetated wet season channel are common in the seasonal tropics (Mossa et al., 2002; Junk et al., 1989; Gupta, 1995). Tockner et al. (2000) found that aspects of flood-pulse hydrology apply to some large unregulated rivers outside the tropics as well. This raises an interesting question for Florida, which has a distinct wet and dry season, but does not have annual aver age precipitation volumes as high as much of the humid tropics, Do Florida s perennial streams behave more like temperate humid streams with an alluvial channel and floodplain that is rarely flooded, or do they behave more like seasonal tropical streams t hat have a routinely flooded vegetated upper channel and an open alluvial transport channel?
56 Basin Flashiness and the Hydraulics of Open Chan nels and Floodplains The answer to the question posed above wo uld seem to be, It depends on basin physiography and basin scale. First the flashi ness of the flow duration data of the 18 perennial streams are discussed, followed by event hydraulics data from all 56 sites. As previously mentioned, seasonal flow slope wa s calculated as an index of the overall slope of the unit flow duration curve between the 15th and 85th discharge percentiles. Flow is within this range, on average, for 70% of the year and t he endpoints nominally represent the seasonal high and seasonal lo w flow limits. SFS scores are higher for systems with comparatively greater seasonal flow variability. To eliminate scale effects, flows were rendered dimensionless by divi ding each daily value by the median discharge of the sites full record and, rat her than analyze the raw differences in unit seasonal discharge magnitude, t he SFS was indexed as a slope of the curve by simply dividing the difference in unit seasonal fl ows by 70 (the seasona l percentile range). Greater SFS values correspond to greater seasonal range, implyi ng greater seasonal pulses or flashiness. The seasonal pulses of perennial Florida streams differed by substantial magnitude among basin types and in a statistically significant manner. Each basin type differed from the other two (ANOVA, p<0.05) (Table 2-3, Figure 2-12). Flatwoods sites averaged seasonal flow variabi lity roughly three time s greater than that of the highlands, which in turn averaged about three times more se asonal fluctuation than the spring runs. To put this into perspective, the total flow fluctuation fo r perennial flatwoods streams typically ranged across f our or five orders of magnitu de (Figures 2-11). A site with a median discharge of 20 cfs would experienc e flows ranging from a trickle at 0.02 cfs to flood pulses with 2,000 cfs (Figure 2-11). Spring runs fluctuated a lot less,
57 typically within a single order of magnitude (Figure 2-9). So, a spring run with the same median discharge of 20 cfs would typically exper ience a range of flows from 15 to 40 cfs. Regression lines on scatter plots of bank full and flood flows versus drainage area were compared among physiographic classes. Tests of bankfull discharge coefficients (regression constant and slope) between flatw oods and highlands were not statistically significant (p>0.05). The kars t systems differed fr om the other two physiographies for slope and from the flatwoods for intercept (T able 2-4, Figure 2-13). This implies that highlands and flatwoods basins differ little in their capacity to deliver bankfull discharge thresholds, but that karst sys tems differ, especially from the flatwoods. The data scatter suggested that the karst differences mainly occurred for the smalle r contributing areas. For larger systems it does not matter much whether the wate r is sourced via temporally long underground pathways or short surface pat hs. This implies that bankfull discharge is a routine and sustained occurrence for most Florida streams, but that it may be less routine and more peaked for runof f dominated low-order streams. Flood flows were different and appeared to s how a consistent tr end of flatwoods basins delivering greater floods per basin area than the highlands streams, which in turn produced greater flood yields than the spring runs (Table 2-4, Figure 2-14). These facts suggested that, while drainage area played a func tionally significant role in flood pulse delivery, it was sign ificantly moderated by the groundwat er infiltration capacity of the landscape. Flood pulses were not only more pronounc ed in the runoff dominated systems; they also produced disproportionately large increases in flood power compared to
58 bankfull power. For example, the average flood/bankfull pow er ratio of flatwoods streams was almost twice that of highlands streams, and this ratio for highlands streams was almost three times higher than spring r uns (Table 2-3, Figure 2-15). This implies that more alluvial work can typically be done in the wet season channels of perennial flatwoods streams than other basin types and that the least am ount of such work capacity occurs in association with karst basins. Greater similarities among basin types for bankfull flow versus drainage area suggested that in-stream hydraulics may be mo re similar than it is for flood flows. However, regression lines through scatter pl ots of channel width versus bankfull discharge indicated that the spring runs t ended to be wider than highlands or flatwoods streams versus bankfull discharge. This s uggests that different in-channel processes are at work at sub-bankfull levels for the karst systems as well (Table 2-4, Figure 2-16). The channel planform of spring runs also di ffered from the other stream types with a wider range of radius of cu rvature/width ratios that were skewed toward the highest such ratios in the study (Figure 2-17). In general, but by no means universally, spring runs were wider and more gradually sinuous than the other two stream basin types, which did not differ much fr om each other regarding bankfull channel dimension or shape. Comparatively broad, straight and shallow channels were consistent features of spring runs in at least one other setting, the volcanic soils of the Pacific northwestern United States (Whiting and Moog, 2001; Wh iting and Stamm, 1995). The scientists working in that region attributed such geomor phic differences versus the regions runoff streams to the effects of bi ologically mediated processe s, including the anchoring of
59 otherwise mobile sediments by vegetative islands and submerged aquatic vegetation (SAV) and to the comparatively large loads of snags in the runs. The spring runs lacked big spates to flush the vegetation and w oody debris and the flow simply eroded broad channels around the obstructions instead. Flor ida spring runs appear to have a general convergence of form with sp ring fed streams in the Pacific Northwest. While the mechanisms of this convergence may also be biologically mediated, they appear to differ in some important ways. For example, differences in mean snag densities (pieces of large woody debris per 100 linear feet of channel) were stat istically non-significant (P = 0.556) among the gaged perennial streams studied in Florida. Snag densities were highly variable with means of 1.9 snags /100 LF for flatwoods, 2.9 snags/LF for highlands, and 2.7 snags/LF for karst sites (Tabl e 2-3). More detail concerning Florida biogeomorphology, including that of spring runs, is provided in the next section. Overall, statistically indistinguishable fr actions of annual rainfall were captured as discharge to Florida stream channels among the three basin types (Table 2-3). An average of 22% of rainfall became discharge in flatwoods streams with values of 23% and 28% for the highlands and karst streams. So the total amount of water reaching these streams did not differ near ly as much as the timing and variability of that delivery within the year. Keep in mind that while bankfull discharge does not differ much as a function of basin size am ong physiographies, that t he bankfull flow frequency and bankfull flow duration of karst streams did di ffer significantly from flatwoods streams. This means that it is likely a more consis tent and more highly effective threshold for providing a specific level of work on the channel.
60 That steady concentration of comparativ ely invariable work seemed to carve and maintain a bankfull channel forms that were wider (especially relative to hydraulic depth) and straighter than streams draining more va riable flow regimes. Variability in flow appeared to lead to narrower channel cross-sections with tighter bends, perhaps so they can carry a wider range of flows without mean velocity changing too much as a function of channel stage. Not all spring fed streams are as st eady as Floridas and wide, gradually meandering conditions are by no means unive rsal to spring runs worldwide. For example, small spring runs in a semi-arid climate in Arizona were found to be narrower than their runoff dominated counterparts (Griffiths et al ., 2008). The reason cited for this was that the valley flats of the runs were extensively re-worked by alluviation during occasional flash-floods and that the smalle r constant spring flows subsequently headcut through the newly deposited material as it was quickly re-vegetated and stabilized given the moist conditions of the valley. Interestingl y, these sites also exhibited significant and rapid biological-groundwater flow interact ions, but with a differ ent outcome on channel morphology seemingly associ ated with an inherent variability in the frequency and intensity of sediment and water discharge operating on two different times scales. Variable flow could also be associated with tighter bends due to differences in sediment yields that are correlated with fl ow variability. Greater amounts of alluvial sediment can enhance bends by building point bars and some theories of bend formation follow a premise that streams meander in response to the competing efficiencies of channel form related to sedi ment transport versus clear water transport (Langbein and Leopold, 1966; Leopold and Wolman, 1957). The spring runs tend to
61 carry less total and variable solids loads and have less associated point bar formation with a lower sinuosity planform. Biologically Mediated Morphology and Groundwater Regimes The pulsed disturbances created by flow variability appear to have physical and biological ramifications that can affect channel geomorphol ogy. One of the working hypotheses was that biological systems in Fl oridas virtually year round growing season could offer substantial resistance to changes normally wrought by erosive forces. If this hypothesis is correct, one would expect to s ee increasing evidence of biological control as a function of the steadying influence of gr oundwater discharge. If true, this raises the question regarding what thresholds in the flow regime may trigger biological versus alluvial control of various components of geomorphology and how these thresholds might differ among basin types. Larger spring runs in Florida, generally at least 30 feet wide with typically less than 70% of the channel canopied (as measured using a spherical densitometer), normally supported varying amounts of SAV meadows on their bed (Figure 2-18). SAV meadows were not ubiquitous in spring runs because they require lots of light penetration and are sensitive to a variety of human impacts. Light penetration requirements, and perhaps other factors, tended to reduce SAV cover in t he blackwater stream types versus spring runs (Figure 2-19). SAV meadows greatly reduce flow velociti es, setting up a two tiered velocity regime in the channel, the laye r within the tape grasses and the one above them (Odum, 1957). Mannings fr iction factors (n) averaged about 0.14 in karst streams at least 30 feet wide (which are those most likely to have pronounced SAV patches). This was statistically and functionally gr eater than the n-values of similarly wide blackwater streams, wh ich averaged about 0.07 (Tabl e 2-3, Figure 2-20).
62 The seepage dominated headwater streams of the highl ands developed very high friction factors (mean 0.23). These seepage str eams were typically narrow, less than 10 feet wide. They had significantly higher n values than the spring runs and flatwoods (collective mean 0.07) of similar widths because they form living root weirs across the entire stream channel bed that create a resi stant series of steps and pools (Figure 221). To avoid confusion with the more ph ysically derived and uniformly organized clast weirs of step-pool channels in mountainous regions, we refer to Floridas biologically derived analogues as root-st ep streams. These fascinati ng little streams are discussed in more detail in Chapters 3 and 4. For now it is important to note that fr iction factors are higher in groundwater dominated systems than in runo ff dominated systems for t he largest and smallest streams in this study. One key aspect of this is that highly variable flow regimes seem to shift geomorphic controls toward physical proc esses related to alluvial transport and deposition. For example, boxplots of the total alluvial feat ures inventoried for flatwoods, highlands, and karst streams displayed decreas ing alluvial inventories with basin types of increasing dominance of groundwater flow process (T able 2-3, Figure 2-22). It appears to take a significant dominance of groundwater flow source to reduce flow variability at thresholds necessary to a llow for living biological systems to remain established at sufficient scales to directly control the main channel flow resistance. Fundamentally different biological mechani sms are responsible for increasing friction factors in the groundwater dom inated flow systems, dependant on channel width, valley slope, and shade. The physical te mplate that determines which species can provide the increased friction depends on the general fluvial geomorphic
63 association of greater channe l width as a function of greater dominant discharge and relative channel depth as a function of valle y relief. This is part of the reason why narrow headwater seeps with low flow volume s and steep slopes have different friction generating plant species than wid e spring runs with comparatively copious groundwater discharge flowing through relatively flat valleys. The fundamentally different growth habits of the plant species occurring in these two extremes of light limitation indicate that if the physics allo w, biology will find a way to exert its self-serving will on channel shape. For example, SAV meadows require light rich environments unshaded by competing tree canopies growing on the banks. The SAV species hold shallow sediments in plac e, perhaps forcing wider planforms than what would have formed without their presence that in turn provid e more substrate for SAV meadows. In virtually a ll ecosystems, this genetically self-serving positive feedback loop is limited by competing species. In th is case, the competitor s include a panoply of shade producing wetland tree and shrub species that grow on the channel banks. When channels are sufficiently narrow, these wood y species preclude the establishment of SAV by shade, limiting the establishment of competing agents that may otherwise widen the channel at the trees expense. When the channels are very narrow with small seepage volumes, the trees prevent further bed erosion and downcutting by creating intense grade controls in the form of living root weirs across the entire c hannel bed. This occurs in areas with the steepest channel slopes in Florida, typica lly between 1.0% and 2.5% grade. Grade control by root weirs may serve as a defense mechanism by the wetland trees to prevent excessive bed erosion and subsequent dewatering of seepage wetlands
64 flanking the stream channel. It is a self-re inforcing habit by tree species associated strongly with saturated seepage conditions. Mo st root steps were observed to be formed by sweet bay trees ( Magnolia virginiana ) and blackgum (Nyssa silvatica var. biflora), and less frequently by loblolly bay ( Gordonia lasianthus ) and dahoon holly ( Ilex cassine). All of these species are dominant or common associates of seepage swamps and frequent channel bank associates. This assemblage of wetland trees maintain and perhaps enhance the lateral and longitudinal ex tent of saturated soil conditions by creating living dams. In Floridas groundwater dominated stream s of all widths, the channel banks become living boundaries that ar e fundamentally different fr om the wooded banks of channels under more intense alluvial controls To understand this distinction, first note that vegetation, particularly woody vegetation, is well documented for adding shear strength to stream channel ban ks that can greatly resist erosion in humid climates around the world with channel forms that are otherwise dominat ed by alluvial controls (Ikeda and Izumi, 1990; Andrews, 1984; He y and Thorne, 1986; Ebisemiju, 1994). These roots systems help to hold the bank together, resisting mass wasting and gravitational failure. That benefits the plants by giving them great access to a source of water at a light gap and their r oot structures assure the st ability of their own growing medium. Some riparian bank plants also help to deflect flow forces reducing erosion. Florida is no exception. For example, sa w palmetto roots provide significant shear strength to sandy stream em bankments and their long thick rhizomes often drape over the bank crests, armoring many Florida st ream banks. Florida has numerous woody riparian tree species that fix banks in a very conventional manner. An important
65 distinction of this general and very common ty pe of stream bank condition is that these banks are built by alluvial process and their subsequent erosion by fluvial forces is resisted by biological agents gr owing in the inorganic alluvium which consists mainly of sandy deposits in most Florida streams. However, some stream banks in Florida are not comprised of alluvial mineral materials being held together by roots. Instead, the banks themselves consist of dense masses of thick, intertwined roots holding together decaying leaf litter and older peaty parent materials (Figure 2-23). These living or biological banks build themselves up and smother the inorganic sub-laye r, raising the bank height fr om a few inches to a few feet higher than it might other wise achieve. The biological bank also extends laterally over alluvium, narrowing the channel. Such ban ks were usually dominant to ubiquitous along spring runs and root-step seeps, were often found along portions of highlands stream banks, and were generally rare along flatwoods stream banks (Table 2-3, Figure 2-24). They appear to be strongly a ssociated with groundwater flow. The stream channels appeared to hydraulical ly prune their roots at the base and as a result some larger biological banks formed overhanging ledges that water flowed beneath for up to several feet beyond the appar ent bank edge. Natural tree falls can leave persistent gaps along t he embankment that are gradual ly filled by living bank growth rather than rapid fill from copi ous sediment transport. The comparatively sediment-starved groundwater systems simp ly do not have enough inorganic material available to mechanically rebuild the banks with alluvium. This lack of a rapid bank recovery mechanism may contribute to c hannel widening in spring runs and to the rough edges commonly observed along t he root-step channel margins.
66 Although the woody biological banks could shrink the channe ls of large spring runs by enlargement of their ow n growing platforms into and over the channel, the SAV meadows stabilize the bed and increase friction wh ich could counter this and result in channel widening. Wider channels offer more gr owth media in shallow clear water for SAV species. Some of the variability among spring run geomorphology may be due to the unique ways these two assemblages compete for a share of the steady supply of water and sunlight provided by the run. In contrast to the steady spring runs, highly variable flow regimes of blackwater systems appear to disrupt this competition and the channels are able to overcome biological contro ls to achieve hydraulically more efficient flow and sediment transport regimes. As a result, their bed and banks were dominated by inorganic substrates, especially sand. Effect of Basin Water Source on Stream Sediment Origins Drainage basins of spring runs are unique in that the area receiving recharge to the artesian aquifer may be a long linear dist ance from the local surface water basin. As a result many, but not all, spring runs hav e remote or disjunct springsheds that are much larger than their local surface basins. This was true for 10 of the 12 runs studied. Such an arrangement means that spring runs receive water yield disproportionately larger than their external sediment yield. Recalling that alluvial f eatures were most common in the more highly pulsed flatwoods systems, it is important to understand that spring runs generally lacked alluvial floodplains, but did routinely exhibit alluvial bed fo rms such as sediment shoals and sandy ripples, and occasionally bend pool s and point bars. They obviously must have some sediment yield or they would all eventually degrade to resistant lithological
67 layers or would achieve relatively levelbottomed grade as linear embayments of their receiving waters. So where does their sediment come from? Some of it likely does come from spor adic erosion in their sandy local basins. Sand is commonly found as part of the alluvi al bed materials and some of this can be washed into the runs at points where high sandy bluffs border the run channel. Often a thin veneer of sand covered finer bed mate rials giving the misleading appearance of a ubiquitous sand bed along the run. In reality, much of the bed material of most spring runs in our study was comprised of deposits of organic sediment several inches to several feet thick that Odum (1957) referred to as gyttja in his landmark eco system study of the Silv er River. The Silver River is widely believed to be t he largest karst spring river in the world. Its dominant bed material, particularly in its upper reaches is fine organic sediment with very high water content, usually derived from algae and ot her detritus. Prugh (1969) described and mapped similar sediments in survey ed cross-sections of another 1st magnitude spring run, the Ichetucknee River. All but two of the smalle st of the 12 spring runs in this study had substantial amounts of similar fine organic sediments on t he bed and seven sites had bed materials either dominated by it or co-dominant with sand. Because the term gyttja is more generally us ed to describe a particular kind of lake sediment, the term detrital floc was adopted for the purposes of this study to describe these common organic sediments in Florida sp ring runs. In streams where t he detrital floc was found in association with substantial am ounts of sand bed material, the organic sediments were typically found away from the channel center cl oser to the bank margins. This suggests hydraulic sorting of these materials of variabl e density. In some cases, the detrital floc
68 margins formed shallow channel shelves with dense SAV meadows that the deeper sandy channel center lacked. To give a sense of the characteristics of these materials, during the survey it was easy to walk downstream on the firmly-pa cked center bed sands and one could easily feel the stream power of the flow walking up stream in this zone. A wader would sink deeply into the detrital floc layer however sending plumes of turbid brown organics downstream. Little force of flow would be felt in the shallo w channel margin. The detrital floc is slightly cohesive and, despite very high water content, holds its shape well and can easily be grabbed and partially molded (Figur e 2-25). For comparison, Figure 2-26 shows a typical sandy alluvium from a flatwoods stream channel. Mollusk shells and shell fragments, parti cularly from snails, were variably significant components of the bed materials of the seven largest runs studied. Many Florida spring runs, probably because of hi gh carbonate levels, support abundant and diverse mollusk populations (Shelton, 2005). Light levels in the clear water allow periphyton growth on the SAV and other s ubstrates that are grazed by an abundant and diverse array of snail species. As these anima ls die, their shells become sediment load. In essence the spring run mollusks convert dissolved minerals to solids that form some part of the internal sediment yield to spring runs. Much of the inte rnal yield comes from periphyton and other plant materi al detritus. Shelly detrita l floc was quite common on the beds of larger spring runs, suggesting that much of their fluvial form depends on internal (autochthonous), biologically-mediated s ediment yields that at least partially offset the reduced external (allochthonous) yiel ds from their compar atively small local
69 surface basins. In essence, larger spring ru ns course over valle y fills of their own making. Conclusions Ramifications for Dominant Discharge Concepts The primary ramification is not to take the concept of dominant dis charge too literally. In Florida, streams with steady groundwater flow and very rare spates had fundamentally different open channel and wet-season channel geomorphology than streams with similar bankfull discharge draining flatwoods basins with flashy flow regimes. Within the region, the overa ll channel pattern and dimension was highly dependent not only upon the dominant disch arge and the total annual volume of discharge, but also on flow variability and the associated flow delivery medium. Sediment sources were different in asso ciation with flow regime and, in general, biological mechanisms grew in importance versus physical cont rols as flow variability decreased. The concept of dominant discharge is a very useful restoration design tool, but it is only part of the complete kit, whic h must necessarily also account for flow variability. Biota as a Groundwater Dependant Geomorphic Agent Floridas sub-tropical climate, virtually year-long growing season, ample moisture and high gr oundwater tables provide a setting that is ideal for the growth of dense luxuriant vegetation within its fluvial corridor s. The nearly constant saturation promoted formation of rich organic soil layers. In systems with comparatively steady flow, particularly systems dominated by groundwater di scharge such as large spring runs and diminutive seeps, biology exerte d geomorphic controls that were at least as important as alluvial control. In the flashier systems dominated by surface water runoff in the
70 flatwoods and the larger st reams of the highl ands basins, physics exerted a greater degree of control and alluvial features were more abundant and diverse. In the battle between biology and physics, st eady groundwater flow in the absence of routine powerful floods can tip the scale toward biology. Populations of Florida Stream s as a Function of Water Source A hierarchical cluster analys is of sites using 108 flow metrics properly assigned 89% (16 of 18) of perennial streams to their respective physiographic settings (Figure 227). One exception, the flatw oods stream Little Haw Creek, clustered as a closer associate of the highlands str eams than its flatwoods counter parts. The other exception, Lowry Lake UT, was a tiny root-step seepag e stream draining a highlands landscape that clustered with the artesian spring runs. It had a fundamentally different geomorphology and water source. While the cluster generally confirms that flow variability and associated physiographic settings can provide valuable information for cla ssifying Floridas perennial streams, the necessary long-term di scharge record is not available for very many non-perennial (intermittent or ephemeral) streams. Also, the fact that 11% of the perennial sites with long-term re cords clustered inconsistently with their physiographic setting suggests factors other than groundwater influence and basin physiography are important for proper stream classification. For example, some geologic controls related to valley form are discussed in Chapter 3 and an approach that integrates geomorphic features existing at the watershed, valle y, reach, and in-stream patch scales is discussed in Chapter 4.
71 Research Needed The fact that Florida spring runs have mo rphology that in some key respects i s more similar to the morphology of spring runs in the Pacific Northwest than they are to runoff dominated streams close by is intrigui ng. In both regions biological mechanisms seemed to be important, but they differed. S nags played a key role in Washington and Oregon, but not among perennial streams in Florida. Sub-tr opical snails and periphyton species played important roles in generating inter nal sediment yields in Florida, but this mechanism has not been reported elsewhere. SAV appeared to play a role in both regions. This convergence of fluvial form and basic process raises the question, Do spring runs in other settings around the world have similar form factors with biological control agents and why or why not? This study explicitly measured short reaches of 12 different spring runs, deliberately sampling single thread portions of these runs with alluvial bed materials as opposed to channel segments with geologic controls or porti ons of runs with multithreaded channels and islands. Even casual obser vation of the longer runs in our study, such as Alexander Spring Run, Juniper Spring Run, Gum Slough Spring Run, Weeki Wachee River, and Rock Springs Run (and other s we are familiar with that were not included in our study such as the Silver River and Ichetucknee River) suggests common occurrences of repeating channel forms wit h deep segments under geologic controls and very broad multi-threaded channels with shoals and tree islands that were not included in our surveys. These features o ften repeat and alternate with single thread sections under alluvial bed controls along t he run. Furthermore, some runs such as Alexander and Juniper are so long that they pick up subs tantial amounts of surface drainage and flow with high volumes of blackwater during the wet season at their mid-
72 reach and lower sections. Perhaps higher degr ees of flow variability and greater yields of external inorganic sediments explain the rather sinuous middle and lower sections of these two runs. Full-length fluv ial geomorphic studies of all Fl oridas longer spring runs are necessary to systematically learn more about the longitudinal patterns in channel form and their associated controls in t hese uniquely complex fluvial systems. Florida scientific and regulatory program s need to support the development of more systematic long-term records from r easonably intact low-order and mid-order streams in rural areas in all physiographic categories. More such gages have been established in urban basins by the USGS, but there is little baseline information to compare those with intact rural streams. As Florida continues to urbanize, intact lowerorder streams could likely continue to be functionally diminished and we may never quite know what we are losing until it is too late and the effects start compounding in ways that are evident in the larger rivers t hat are routinely gaged. Many kinds of stress phenomena in fluvial geom orphology have long lag times followed by periods of intense change when the gradual alterations eventually r each a critical threshold. For example, sudden and rapid periods of channel widening unfold after decades of gradual channel deepening over-steepens the banks to a point where they can no longer support their own mass. This is a common example of l ags and thresholds in channel evolution in eroding urban streams. In our site selection process, more than 75% of streams randomly selected were rejected from inclus ion in the study because of substantial human impacts in their watershed or due to direct modification of the channel. Establishing long-term gaging stations on more of the remaining inta ct small streams in Florida is a pressing need that could form th e hydrologic basis for a lot of applied
73 research related to natural resources, water supply, and fisheries management of Floridas stream networks. The amount of flow data from t he most common and perhaps most vulnerable streams are arrestingly small. Small streams are in more direct intimate contact with their watersheds t han large rivers and can serve as faster harbingers of undesirable changes in hydr ology, habitat, or water quality.
74 Table 2-1. Discharge calcul ation methods by location Site name Phys. DA (sq.mi)Gage I.D. Bankfull method Bankfull Manning's n Flood method Flood Mannings n Bell Creek UT FW0.2None SAM 0.13SAM 0.13 Lower Myakka River UT 3FW0.4None VAM 0.05SAM 0.05 East Fork Manatee UT 2 FW0.4None VAM 0.21SAM 0.21 Wekiva Forest UT FW0.5None SAM 0.10SAM 0.18 Coons Bay Branch FW0.5None SAM 0.13SAM 0.13 Grassy Creek UT FW0.8None VAM 0.14SAM 0.14 East Fork Manatee UT 1 FW0.9None VAM 0.10SAM 0.10 Hillsborough River UT FW1.0None SAM 0.12SAM 0.12 Lower Myakka River UT 2FW2.7None VAM 0.05SAM 0.08 Blues Creek near GainesvilleFW3.2None SAM 0.06SAM 0.06 Cow Creek FW5.6None SAM 0.07SAM 0.07 Moses Creek near MoultrieFW7.8USGS 02247027LTR 0.08LTR 0.07 Grasshopper Slough RunFW8.7None VAM 0.07VAM 0.08 Morgan Hole Creek FW11.0None VAM 0.06VAM 0.08 Tenmile Creek FW16.8None SAM 0.07SAM 0.11 Tyson Creek FW20.7None VAM 0.06VAM 0.13 Rice Creek near SpringsideFW45.8USGS 02244473LTR 0.08LTR 0.17 Bowlegs Creek near Ft MeadeFW50.9USGS 02295013LTR, VAM0.07LTR 0.35 Manatee River near Myakka HeadFW65.7USGS 02299950LTR 0.04LTR 0.06 Santa Fe River near GrahamFW94.1USGS 02320700LTR 0.05LTR 0.03 Little Haw Creek near SevilleFW106.2USGS 02244420LTR 0.03LTR 0.23 Horse Creek near ArcadiaFW219.0USGS 02297310LTR 0.06LTR 0.08 Fisheating Creek at PalmdaleFW313.0USGS 02256500LTR, VAM0.05LTR 0.20 Manatee River UT HL0.3None SAM 0.27SAM 0.27 Lowry Lake UT HL0.3SJR 72051622SAM 0.25SAM 0.25 Tuscawilla Lake UT HL0.3None SAM 0.27SAM 0.27 Shiloh Run near Alachua HL0.4None SAM 0.05SAM 0.05 Cypress Slash UT HL0.4None VAM 0.17SAM 0.17 Lake June-In-Winter UT HL0.6None VAM 0.34SAM 0.34 Tiger Creek UT HL0.9None VAM 0.08SAM 0.08 Snell Creek HL1.7None SAM 0.09SAM 0.09 Bell Creek HL1.9None SAM 0.08SAM 0.08 Alexander UT 2 HL2.3None SAM 0.10SAM 0.10 Jack Creek HL2.7None VAM 0.08VAM 0.09 Gold Head Branch HL2.8None SAM 0.27SAM 0.27 Hammock Branch HL3.0None SAM 0.07SAM 0.07 Jumping Gully HL4.2None SAM 0.12SAM 0.12 Ninemile Creek HL6.8None SAM 0.30SAM 0.30 South Fork Black Creek HL26.5None SAM 0.06SAM 0.15 Carter Creek near SebringHL36.0USGS 02270000SAM 0.04SAM 0.16 Tiger Creek near Babson ParkHL53.2USGS 02268390LTR, VAM0.11LTR 0.10 Catfish Creek near Lake WalesHL57.5USGS 02267000LTR, VAM0.20LTR 0.16 Blackwater Creek near CassiaHL118.4USGS 02235200LTR 0.03LTR 0.04 Livingston Creek near FrostproofHL119.8USGS 02269520LTR 0.05LTR 0.24 Morman Branch UT Spring RunK0.5None VAM 0.10SAM 0.10 Silver Glen UT Spring RunK1.0None VAM 0.16SAM 0.16 Forest Spring Run K1.7None VAM 0.26SAM 0.26 Little Levy Blue Spring RunK2.1None SAM 0.19SAM 0.23 Kittridge Spring Run K3.1None VAM 0.08SAM 0.08 Cedar Head Spring Run K5.2None VAM 0.07SAM 0.07 Alligator Spring Run K8.7None VAM 0.25SAM 0.25 Gum Slough Spring Run K27.0USGS 02312764VAM 0.15SAM 0.15 Juniper Spring Run K33.7None VAM 0.10SAM 0.15 Weeki Wachee River K85.9USGS 02310525LTR, VAM0.09LTR 0.09 Rock Spring Run K100.0USGS 02234610LTR, VAM0.04LTR 0.04 Alexander Spring Run K110.0SJR 18523784LTR, VAM0.21LTR 0.21 Phys. = basin physiography: FW = flatwoods, HL = highlands, K = karst. DA = drainage basin area. LTR = long term discharge record coupled with field indicators of stage. VAM = direct velocity-area measurement. SAM = slope-area method using field indicators of slope & Manning's equation. Manning's n from sites using VAM or LTR were calculated, all others were estimated from observed channel conditions.
75 Table 2-2. Bankfull and flood channel discharge summaries Site name Ph y s. Drainage basin area ( s q mi. ) Bankfull channel flow ( cfs ) Average number of bankfull flow exceedances per y ear* Percent of time bankfull flow exceeded for the p eriod of record Flood channel flow ( cfs ) Average number of flood flow exceedances per y ear* Percent of time flood flow exceeded for the p eriod of record Bowlegs Creek near Ft Meade FW 50.959.1 13 14234.1 3.25 2.0 Fisheating Creek at Palmdale FW 313.081.9 28 401,018.5 8.20 6.2 Horse Creek near Arcadia FW 219.0230.0 19 211,330.8 3.90 2.4 Little Haw Creek near Seville FW 106.2109.2 17 25580.5 1.40 1.5 Manatee River near Myakka Head FW 65.7139.9 17 121,246.6 1.65 0.5 Moses Creek near Moultrie FW 7.820.9 8 7138.4 1.10 0.8 Rice Creek near Springside FW 45.823.2 32 34521.9 1.50 0.5 Santa Fe River near Graham FW 94.1109.6 8 13516.4 0.53 0.7 Blackwater Creek near Cassia HL 118.4128.7 10 13885.1 0.03 0.0 Carter Creek near Sebring HL 36.031.5 16 2394.8 1.93 2.5 Catfish Creek near Lake Wales HL 57.545.1 22 35162.8 0.05 0.4 Livingston Creek near Frostproof HL 119.858.8 26 34335.1 1.10 0.6 Lowry Lake UT HL 0.30.6 34 481.9 0.06 0.0 Tiger Creek near Babson Park HL 53.260.9 16 17189.7 1.50 0.8 South Fork Black HL 26.552.3 29 2689.0 14.40 9.2 Alexander Spring Run K 110.0121.9 34 38247.3 1.43 1.0 Cedar Head Spring Run K 5.27.4 42 4320.4 0.10 0.0 Gum Slough Spring Run K 27.036.4 26 3556.0 9.60 10.6 Rock Spring Run K 100.048.0 32 5468.3 0.18 0.1 Weeki Wachee River K 164.0163.6 30 36183.5 18.40 19.2 Phys. = basin physiography. FW = flatwoods, HL = highlands, K = karst. *Based on partial duration series with minimum 7 days between indpendant flow peaks.
76 Table 2-3. ANOVA summaries VariablePhys.NMeanSESig.ANOVA test, pairwise procedure Bankfull eventsFW719.003.08AOne-way ANOVA, Holm-Sidak HL620.503.44A K532.882.73B Bankfull durationFW722.644.04AOne-way ANOVA, Holm-Sidak HL628.085.34A K541.363.52B Flood eventsFW72.920.98AKruskal-Wallis ranks, Dunn HL60.780.34A K55.943.56A Flood durationFW71.970.76AKruskal-Wallis ranks, Dunn HL60.720.38A K56.183.18A SFS/70aFW70.100.01AOne-way ANOVA, Holm-Sidak HL60.030.01B K50.010.00C Flood/bkf poweraFW79.892.51AOne-way ANOVA, Holm-Sidak HL64.920.80B K51.780.28C Rc/W FW71.190.17AOne-way ANOVA, Holm-Sidak HL60.960.15A K52.600.74B LWD/100'FW71.870.47AOne-way ANOVA, Holm-Sidak HL62.880.93A K52.770.73A %DischargeFW721.600.03AKruskal-Wallis ranks, Dunn HL622.800.07A K527.800.04A %SAVbFW70.190.19AOne-way ANOVA, Holm-Sidak HL67.262.29A K530.6410.38B n (W < 10')GW50.230.04AT-test BW40.070.02B n (W > 30')GW60.140.03AT-test BW80.070.02B Total alluv.FW77.120.72AOne-way ANOVA, Holm-Sidak HL65.600.51A K51.600.68B BioBanksFW71.000.00AKruskal-Wallis ranks, Dunn HL61.670.33AB K53.600.25B Sig. = significant differences between physiogr aphies with different letters (p < 0.05). SE = standard error. FW = flatwoods, HL = highlands, K = karst.aLog-10 transformation was used to meet assumptions for normality & equal variance.bIgnored normality and variance assumptions. SFS/70 = seasonal flow slope, Rc = radius of curvature, W = channel width. %Discharge = amount of rain on catchment that becomes streamflow. LWD/100' = snags per 100 linear feet of channel, SAV = submerged aquatic vegetation. n = Manning's friction factor, Total Alluv = no. alluvial features in the stream and floodplain. BioBanks = dominance of biological banks (1 rare, 2 present, 3 common, 4 ubiquitous). GW = groundwater stream, BW = blackwater stream.
77 Table 2-4. Regression summaries IV DVFWHLKFW HLK HLK FWFWHLKFW HLK HLK FW Log(DA) ctrLog(Qbkf)1.0850.9490.7500.1540.0860.0040.6520.7181.0720.4770.0060.001 SE------->0.0940.0680.113NSNSSig0.0930.0700.119NSSigSig Log(DA) ctrLog(Qflood ) 1.6981.3551.0470.0000.0070.0000.8570.8060.8980.6090.7100.751 SE------->0.0630.0920.109SigSigSig0.0650.0990.127NSNSNS Log(Qbkf) ctrLog(W)1.1221.1141.4850.8900.0000.0000.3140.4700.4170.0580.5310.223 SE------->0.0390.0570.066NSSigSig0.0570.0800.084NSNSNS Log = log10 transform, ctr = variable centered, NS = p > 0.05, Sig = p < 0.05, SE = standard error. FW = flatwoods, HL = highlands, K = karst. DA = drainage area, Qbkf = bankfull flow, Qflood = flood flow, W = bankfull channel width. VariablesB constantB slopep > F p > F
78 Figure 2-1. Florida Department of Envir onmental Protection ecoregions in the study area (FGDL 2009).
79 Figure 2-2. Florida Geological Survey geolog ic regions in the study area (FGDL 2009).
80 Figure 2-3. Example of a karst spring r un at bankfull stage (A lligator Spring Run, September 7, 2008).
81 Figure 2-4. Example of a blackwater st ream at wet season flood stage (Little Haw Creek, September 8, 2008).
82 Figure 2-5. Example of a flatwoods stream near bankfull stage (Rice Creek, July 2, 2008).
83 Figure 2-6. Example of a highlands stream at bankfull stage (Tiger Creek, June 9, 2009).
84 Figure 2-7. Example of a hi ghlands stream at baseflow st age (South Fork Black Creek, June 19, 2008).
85 y = 12.77e-0.0338xR2 = 0.871 0 2 4 6 8 10 12 14 0102030405060708090100 Percent Xeric SoilsUnit Seasonal Flow Difference Figure 2-8. Seasonal flow flashiness versus xeric soils in the drainage area. Xeric soils are defined as NRCS hydrologic soil groups A + C. Unit seasonal flow difference is the range between the 15% and 85% flow exceedance divided by the median flow.
86 Figure 2-9. Karst spring run flow duration curves. Percent Exceedance 0.20.51251020305070809095989999.8 Mean Daily Discharge/Median Discharge 0.001 0.01 0.1 1 10 100 Alexander Springs Cedar Head Gum Slough Springs Rock Springs Weeki Wachee River
87 Figure 2-10. Highland stream flow duration curves. Percent Exceedance 0.20.51251020305070809095989999.8 Mean Daily Discharge/Median Discharge 0.001 0.01 0.1 1 10 100 Blackwater Creek near Cassia Carter Creek Catfish Creek Livingston Creek Tiger Creek Lowry Lake Tributary
88 Figure 2-11. Flatwoods stream flow duration curves. Percent Exceedance 12510203050708090959899 Mean Daily Discharge/Median Discharge 0.001 0.01 0.1 1 10 100 Bowlegs Creek Fisheating Creek at Palmdale Horse Creek at Arcadia Little Haw Creek near Seville Manatee River near Myakka Head Moses Creek near Moultrie Rice Creek Santa Fe River near Hildreth
89 Figure 2-12. Seasonal flow slope (SFS) of di fferent basin types. SFS is the difference between the 15% and 85% unit flow exceedance values divided by 70. It provides an approximation of the variabi lity of the flow regime between the wet and dry seasons.
90 Figure 2-13. Bankfull discharge versus t he dominant catchment area (springshed for karst streams or surface basin fo r highlands and flatwoods streams). Springsheds were derived from literature values and surface basins were delineated from topographic maps.
91 Figure 2-14. Flood discharge versus the dom inant catchment area (springshed for karst streams or surface basin for highlands and flatwoods streams).
92 Figure 2-15. Flood/bankfull discharge power rati os for perennial streams in different basin types.
93 Figure 2-16. Channel width versus bankfu ll discharge in different basin types.
94 Figure 2-17. Radius of curv ature/channel width ratio for pe rennial streams in different basin types.
95 Figure 2-18. Submerged aquat ic vegetation. Note the flow bending the plants.
96 Figure 2-19. Frequency percentage of in-s tream submerged aquatic vegetation for perennial streams in different basin types.
97 Figure 2-20. Channel resistance (n) com parisons for narrow and wide streams fed mainly by groundwater versus surface water runoff (blackwater).
98 Figure 2-21. Root step channel. Note the s hallow flow over t he step and the deep pools upstream and downstream of the living weir.
99 Figure 2-22. Alluvial feat ures of the channel and floodpla in for perennial streams in different basin types. Alluvial featur es are formed via sediment transport. Examples include natural levees, li near backswamps, point bars, oxbow lakes, stratified sediment layers, bend pools.
100 Figure 2-23. Biological banks. Note the live shrubs and trees are not only layered over the inorganic soil base but are growing over a hollow palm snag as well. This suggests long-term and aggressive self-organization of the living embankment.
101 Figure 2-24. Percent dominanc e of biological banks for perennial streams in different basin types.
102 Figure 2-25. Shell and detrital floc sediment under a thin veneer of sand. Most of the sediment yield in many spring runs is autochthonous and has a biological origin.
103 Figure 2-26. Sandy alluvium with thin organic layers from a flatw oods stream point bar. Most of the sediment yield in flatwoods and highlands streams is allochthonous and has an erosional origin.
104 Dendrogram using Ward Method Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Group +---------+---------+---------+---------+---------+ Carter Creek near Sebring 1 B5 BW Tiger Creek near Babson Park 1 C5 BW Catfish Creek near Lake Wales 1 C5 BW Blackwater Creek near Cassia 1 C5 BW Livingston Creek near Frostproof 1 C5 BW Little Haw Creek near Seville 1 C5 BW Bowlegs Creek near Ft Meade 2 C5 BW Rice Creek near Springside 2 C5 BW Manatee River near Myakka Head 2 E5 BW Santa Fe River near Graham 2 B5 BW Fisheating Creek at Palmdale 3 C5 BW Horse Creek near Arcadia 3 C5 BW Cedar Head Spring Run 4 C5 SR Lowry Lake UT 4 G5 SS Gum Slough Spring Run 4 C5 SR Alexander Spring Run 4 B5 SR Rock Spring Run 4 C5 SR Weeki Wachee River 4 C5 SR Figure 2-27. Dendogram of hydrologic clusters of streams. Cluster groups include; Group 1 = high baseflow with runoff spates, Group 2 = flashy intermediate discharge, Gro up 3 = flashy high discharge, Group 4 = steady groundwater flow. B5, C5, and E5 are Rosgen Level II c hannel classifications (Rosgen, 1996). FNAI (1990) stream classes include; BW = blackw ater streams, SR = spring runs, SS = seepage streams. Note that the Rosgen and FNAI classes are poorly asso ciated with the hydrologic clusters.
105 CHAPTER 3 ALLUVIAL AND GEOLOGICAL CONTROL T HRESHOLDS IN FLOR IDAS DERANGED STREAM VALLEYS Introduction Purpose Floridas drainage networks consist of co mpl ex valleys that offer highly varying degrees of lateral confinement, routinely have discontinuous open channels punctuated by in-line lakes and wetlands, and occur withi n three different hydrogeological settings that vary significantly in their surface water and groundwater discharge capacities. This all occurs within in a lowland, seasonally-wet sub-tropical landscape with potential for significant vegetative controls. The geomor phology of these deranged valley complexes has not been systematically descri bed, except for case studies for the larger rivers such as the Kissimmee, St. Johns, Suwannee, and Ocklawaha (Warne et al ., 2000; Interfluve, 1997). The main purpose of this investigation was to determine the following: How do valley form and dimensio n change along the drainage network? What associations of riparian sediment type and vegetation communities seem to occur with valley geomorphology? What physical indicators and floodplain hy draulic thresholds exist at the basin scale for alluvial control on floodplain form? What are the typical stream valley l engths and widths between in-line waterbodies and how might these vary spatially within the drainage network? How do valley patterns differ among the peninsulas three major hydrogeomorphic settings (sandy highlands, flatwoods, and kars t) in potential association with their runoff versus groundwater flow dominance? Answers to these questions are likely to provide managers of Floridas riparian corridors and watersheds with much-needed bas eline knowledge and should assist with
106 future restoration endeavors, especially those where it is important to restore functions related to the interaction of streams with their floodplains. General Classification of Draina ge Netw orks and Valley Forms Drainage networks tend to exist in patterns related to their history of interaction of climate with geology. Several qualitative mo rphologic patterns are widely described in modern textbooks with increasing emphasis on channel network evolut ion (for example Knighton, 1998). Common network morphologies include dendritic, rectangular, radial, centripetal, trellised, parallel, annular, and deranged configurations (Zernitz, 1932). In watersheds with rather uniform valley tilt and poorly sorted distri bution of geological exposures, dendritic networks are the norm. Dendritic networks consist of streams connected in a tree-like pattern (Figure 3-1). They could be considered the prototypical morphology (Zernitz, 1932) and it seems like mo st of the natural and laboratory stream network evolution studies in t he literature are prim arily dendritic in form, especially those summarized in textbooks (Knighton, 1998; Schumm, 1977; Leopold et al ., 1964; Gregory and Walling, 1973). Rectangular, radial, centri petal, trellised, parallel and annular networks could be viewed as dendritic networks where the underlying geology imposed some degree of repeated order on the pattern and dimension of the network. For example, a radial network consists of a series of other wise dendritic drainage complexes emanating outward from a point centered on a pronounced conical rise (for exam ple, from the cone of a volcano). Centripetal networks are the opposite, draining inward to a sinkhole, inland lake valley, or eroded dome. Rect angular, annular, and trellised networks follow rock fracture patterns existing on large scales. Parallel networks are series of long linear dendritic drainages that are conf ined by parallel interfluves in folded mountain ranges or
107 along linear dunes where the crests are largel y parallel. Deranged networks can also be ordered in a quasi-dendritic fash ion, but the stream valleys are frequently punctuated or interrupted by un-channelized features such as lakes and wetlands (Figure 3-1). This means that more than two low or der streams can join at a single node, a situation that is highly improbable in a dendritic network (or at any other network type except centripetal). While geology greatly affects and constrai ns drainage patterns, interactions of climate on soil and vegetation ap pear to be major driving forces behind the density and long-term dynamics of channel ne twork evolution. Drainage dens ity (total stream length per drainage area) appears to be non-linearly correlated with precipitation with intermediate amounts of annual rainfall or prec ipitation effectiveness (P-E) resulting in the lowest average drainage densities (M adduma Bandara, 1974) Although global drainage densities are quite variable as an associate of annual rainfall, the maximum drainage densities, as high as 32 miles per square mile (20 km/km2), occur in semi-arid climates with rainfall between six to 30 inc hes per year (150 to 800 mm/yr) (Gregory, 1976). Most of these areas are sparsely v egetated or are grasslands offering limited protection from erosion. Ignoring areas with virtually no rainfall, the lowest maximum drainage densities occur in regi ons with about 39 to 55 inches per year (1,000 to 1,400 mm/yr) at about five to eight miles/mi2 (3 to 5 km/km2). Most of the wo rlds tropical and sub-tropical savannas fall in that range of pr ecipitation (Bourliere, 1983). Gregory (1976) also showed that maximum drainage dens ity increases to about 10 miles/mi2 (six km/km2) in more humid climates with at least 59 inches per year (1,500 mm/yr). This perhaps over-generalized pattern suggests that the lowest drainage densities occur in
108 regions of intermediate rainfall. At lower leve ls of effective rainfall, the drier climate reduces stabilizing vegetation allowing for the most erosion while high levels of effective rain can overcome the effects of dense ve getation. Savannas occupy an interesting pivot point with the lowest capacity for ma ximum dissection, between the most highly dissected semi-arid regions and humid forest l andscapes. It should be pointed out that minimum drainage densities appear to be sim ilar among all climates, except in semiarid regions where they may be higher. Gregory (1976) reported minimum drainage densities typically less than two miles/mi2 worldwide. Peninsular Floridas Ge omorphology and Quaternary Climate Fluctuations Florida has a complex biogeographic and as sociated climactic history because it straddles the northern edge of the tropics and sea-level fluctuations have led to wide variation in exposure and relie f relative to marine base-levels during the last 25 million years (Webb, 1990). Marine forces shaped Floridas predominant land surface features as the Florida Platform exposure has chang ed repeatedly. Subaerial peninsular Florida comprises about one-third of the Platform. All three of the major hydrogeologic physiographies reflect different aspects of marine process associated with long-term fluctuations in global climate. Much of t he existing physiography greatly reflects genesis from the past 25 million years of variable exposures, and especially the repetitive sealevel fluctuations that occu rred during Pliocene and Pleistoc ene glacial and inter-glacial periods, during the last four or five million years. The establishment of Floridas carbonate lithology began duri ng the Jurassic Period some 200 million years ago when Florida was under a shallow sea (Webb, 1990). The extensive flatwoods ecoregions of the peninsula were once the shallow floors of ancient sea beds and severa l different marine terraces cr oss these plains along the
109 scarps of relict shorelines. At least six such shorelines formed during the last 2.5 million years are currently exposed at elevations ranging from roughly seven to 115 feet above existing mean sea level (MSL) (Webb, 1990). Doline features, lik ely associated with solution weathering of underly ing carbonate bedrock, are co mmon in the flatwoods, forming numerous round or oval wetland depr essions. Some of these depressions form in-line lakes and wetlands t hat interrupt the stream c hannel network. Most of the wetlands and lakes in Florida are less than several thousand years old (Webb, 1990). The spodosol catenas of the flat woods typically consist of a relatively thin veneer of leached fine sand, generally one to four feet thick, over a loamy clay layer or a sandyorganic layer partially cemented by aluminum or iron referred to as a fragipan or hardpan. The sub-layers have low hydraulic conductivity so this catena aids in maintaining groundwater tables at or near most of the land surface during the wet season in the flatwoods. Runoff coefficient s are accordingly high and wetlands abound. Subtle changes in grade, less than a foot can determine upland-wetland ecotones in the flatwoods. Organic soils are often welldeveloped in surface depressions ranging from a few inches to more than 10 feet in thickness. These histosols are often sapric, sometimes with fibric material Streams in the flatwoods typically have high color from dissolved organic compounds picked up from the organic wetland soils and decaying matter in the uplands and the water tends to be acidic and soft. Floridas sandy highlands consist of re lict aeolian and coastal dunes that formed and were re-worked not only as sea-levels rose and fell, but also as the climate fluctuated from moist to dr y. Dry phases allowed for aeo lian work and wet phases for pluvial work. These sequences formed catenas consisting of greater than five feet of
110 well-leached fine sand over clay or bedrock. The sand depths can exceed 20 feet. The term highlands is relative, as these areas are typically only 150 to 250 feet above sea level. Those forming the spine along the central part of the state owe a large fraction of their total elevation to isostatic r ebound that occurred after submergence and subsequent exposure and limestone weatheri ng created the Ocala Arch (Webb, 1990). The water table is generally several feet below the highlands land surface, allowing significant infiltration through the thick sands and subsequent seepage discharge to lowlying undulations in this landscape. Many wetlands and streams within the highlands are supported mainly from lateral seepage from the unconfined sandy aquifer. Ancient sinkhole lakes abound in many portions of the highlands, adding to the propensity toward internal drainage inherent to their th ick columns of sand. Although large areas of the highlands are internally drained, most hav e some inclusions of soil catenas similar to flatwoods that support higher groundwater tables and produce significant wet season runoff. Furthermore, low-lying depressions and valleys filled with organic soils are common and some of these punctuate and derange the drainage netwo rk as in-line waterbodies. Water quality in highlands stream s is typically acidic and soft. Water is often colorless in the dry season and highly tannic in the wet as contact with wetland soils increases with the rising water table. The peninsulas bedrock consists of ca rbonate rocks or ancient shell beds, some of which are near the land surface providing a milieu of paleoand ac tive karst features. Sinkholes, massive submerged karst c onduits, and artesian springs are common features in much of the state. Flor ida has more than 700 karst springs (Scott et al ., 2004). Thirty-three of them have median di scharge greater than 1 00 cfs, reportedly
111 forming the highest concentration of 1st magnitude springs in the world (Rosenau et al ., 1977). Most of the artesian springs emerge in the highlands or along scarps at the edge of the flatwoods, often formi ng perennial stream channels of clear, hard water. The importance of weathering and other erosion of Floridas karst have left an indelible stamp of active and paleokarst features on the landscape, associated with much of the present deranged drainage patterns. During the la st glacial (Wisconsonian, circa 20,000 years ago) sea level was about 330 feet below the present elevation. This means that maximum relief for erosion was roughly more than twice that present today. This is important because it gave an opp ortunity for very different valley erosion regimes than present. Some of those regimes have likely affected the alignment of present spring runs and other rivers. Lower sea-levels ma y have allowed the formation of deep valley cuts with attendant widely spaced interfluve crests. Therefore, some modern streams are likely flowing through thick accumulati ons of valley fill that has occurred as subsequent seas levels and associated base levels have risen. This may account for another aspect of apparent geologic cont rol on the modern drainage network concerning numerous ar eas with wide valleys that are over-dimensioned for the existing streams meander belt. Floridas existing drainage networks are influenced or even largely controlled by other aspects of their ancient marine history. For example, many of the rivers originating on the central peninsula (Peace, With lacoochee, Kissimmee, St. Johns, and Ocklawaha) have north-south alignments reflecti ng the long-axis of the various barrier islands, dunes and swales, and lagoons formed along former near-shore marine
112 environments. North-south alignments are not universal, however, with the Suwannee, Caloosahatchee, and Hillsboroug h Rivers providing examples of exceptions. All of the existing exposures have been repeatedly re-worked to varying degrees and are subject to being shaped by Holocene forces. The oldest c ontinuous exposures on the peninsula consist of the ancient dunes of the Lake Wales Ridge, portions of which have generally been above sea level during at least the last two million years. The Lake Wales Ridge supports numerous endem ic species of plants and animals uniquely adapted to the hot, wet climate wit h very droughty and seasonally dry sandy soils. Most of Floridas stream networks hav e likely been substantially altered during the last 20,000 years as sea levels have ri sen more than 300 feet and the climate has become increasingly wet. As a result, most of Floridas freshwater ecosystems are less than several thousand years old (Webb, 1990). Floridas complex climatogenetic hi story and resulting deranged drainage networks raise a compelling question, A re Florida streams predominantly under geological control and what, if any, Holocene alluvial forces are at work and where? General Longitudinal Concepts: Clinal versus Zonal Questions concerning the relative degree of importance of modern fluvial forces versus resistance to change by older geologi cal features in river valleys have been increasingly raised, with at l east three textbooks centered on the subject during the last 10 years or so (Thorp et al ., 2008; Miller and Gupta, 1999; and Schumm, 2005). These texts provide contrast to va lley process classifications that view drainage networ ks as longitudinally self-organizing systems at equilibrium for sediment transport and deposition (Leopold et al ., 1964). Such deterministic c oncepts for longitudinal and lateral alluvial channel and floodplain self -organization revolutionized and injected new
113 life into the disciplines of fluvial geomorphology and stre am ecology from the 1950s through the present. Since that time a classi c set of continuum principles have become textbook viewpoints concerning stream form and functi on along the valley network. Chief among these are that typical stream networks self-organize with gradual and predictable changes downgradient related to their hydrology and channel dimension (Leopold and Maddock, 1953; Wo lman, 1955), sediment tr ansport regimes (Wolman and Miller, 1960; Montgomery and Buffington, 1997), meander dimension (Williams 1986), floodplain dimension and thickness of alluvium (Wolman and Leopold, 1957), longitudinal gradient or valley slope (Mackin, 1948; Leopold and Langbein, 1962), and macroinvertebrate trophi c strategies (Vannote et al ., 1980). Montgomery and Buffingtons (1997) stream classification system was based on the underlying principle that process linkages along the drainage network would have systematic influence on any given stream re ach. They found that the common fluvial bedforms associated with mount ain stream channels (casc ades, step-pool, plane-bed, pool-riffle, and dune-ripple) were related to th resholds of sediment transport capacity relative to sediment supply and that the bedfo rms and their associated bed material size and organization was primarily a response of the system to offer greater frictional resistance in parts of the drainage network with the greatest transport capacity. They described their stream types as generally sorting along a conti nuum of drainage basin size and valley slope, but clearly illustrated that it was the processe s, not the positions that mattered most. They recognized t hat assessments of channels should also carefully consider disturbance history, local influences on channel morphology, and
114 local external constraints within the cont ext of the continuum of excess transport capacity and resistance forms they described. In fact, it is probably the norm that clinal processes along a continuum of form are in reality often disrupted or punctuated by local geological controls along many riverine valley systems. Anyone who has rafted down a river that alternates between multiple stretches of placid runs punctuated with wild rapids, with an occasional cascade portage has experienced this. Knighton (1998), usin g examples, describes how inputs from tributaries with differing geologic condition s and associated differences in sediment caliber and volumes can break up the norma l sediment transpor t continuum of the mainstem river and greatly affect its channel dimensions and planform in a manner that would cause a traveler to hardly view the river as having a gradual continuum of form progressing downstream. Many rivers appear to have sudden, rather than clinal, changes to their channel and valley form and dimension along their le ngth and these changes are often repeated as opposed to unfolding in a strictly progressi ve manner. Such syste ms are far from the exception and, as a result, Thorp et al. (2008) attempted to improve description, understanding, and management of riverine systems by recommending descretization into series of longitudinal functional proc ess zones (FPZ). FPZs are fluvial geomorphic units typically occupying valleys at a scale larger than the reach. The functions are related to fundamental hydrogeomorphic proc esses, especially those associated with differing channel and floodplain formations. Such formations are often the defining physical template for complex ecologic al gradients and community structure development and linkages within the terrestri al and aquatic portions of the riparian
115 corridor. The lateral sorting and linkages of different physical habit at patches repeat within FPZs, but differ among them. A valley can consist of more than one longitudinally linked FPZ. In fact, most Fl orida valleys appear to consis t of multiple sequences of different FPZs. Clinal or gradualistic processes certainly influence the development of FPZs, but they do not completely rely upon them and often repeat along the valley and are frequently defined not only by modern alluvial fact ors, but also by more chaotic relicts of their geological past or by some history of episodic events. The beauty of the FPZ concept is that it allows retention of c linal concepts related to modern alluvial and hydraulic processes along the drainage network without having to neglect the variety of fluvial forms and functions that are under alter nate geological or biolog ical controls that are largely independent of (or at least resistant to) such gradients. Florida drainage networks, deranged by numerous in-line wetlands and lakes and with many abrupt transitions in lateral valley confinement, may be among the most quintessential systems where FPZ concepts are necessary for properly characterizing and managing fluvial systems. Therefore, it seems important to explore reach data for patterns related to fluvial form with position in the drainage network and for any continua that may exist and also for patterns likely to be repeated or punctuat ed within the clinal progression that warrant description as FPZs. While it is important to tease out the zonal patterns intrinsic to gradients of fluvial adjustment intrinsic to the scale of the watershed or present magnitude of the flow regime, it is just as important to recognize the less predictably structured sp atial heterogeneity somewhat ex trinsic to the effects of the modern climate.
116 Methods All 56 streams selected for this study were utilized in this analysis. Field meth ods and at-a-station hydraulic calculations were conducted as described in Chapter 2 for bankfull and flood conditions. GIS layers were developed for LiDAR-derived topography where available to delineate watersheds and develop large-scale transects bigger than the reference reach surveys. Drainage networ ks were described for each reachs basin using the topographic data in the GIS, USGS digital 1:24,000 quad maps, and georeferenced 2004 true-color aerial photography available at one-meter resolution. Box plots, one-way analysis of variance (ANOVA), cross-tabulation comparisons of categorical data, and regression of continuous variables were used to explore the data. Results and Discussion Valleys and their streams can be measured and described from three twodimensional viewpoint s; longitudinal, planf orm, and lateral. Longitudinal patterns are those that occur along transec ts parallel to the centerline of a valley. Lateral patterns are those that occur along transects orient ed across the valley, perpendicular to the longitudinal axis. Planform pa tterns can be described as map views, looking straight down on the valley like a roadmap so one can determine where it exists in the landscape. All three viewpoints are related to each other in three-dimensional space, collectively providing a complete description of the fluvial system morphology. This section is organized to evaluate and describe Floridas fluvial systems in terms of each of these standard viewpoints. A wide range of valley widths and lengths were measured between the in-line waterbodies for this study. Variability in va lley patterns such as hillslope relief, longitudinal relief, meander belt confinement by hillslopes, occurrence of alluvial
117 features, and longitudinal concavity were observed and recorded between the in-line waterbodies during the extensive field reconnaissance conducted for this study. Various types of riparian, headwater, and in-line waterbody communi ty types were recorded. Numerous soil associations were observ ed and recorded along potential longitudinal and lateral gradients. These measurements and observations were sorted into their appropriate lateral, longitudinal and planf orm perspectives and were examined for patterns in association with increasing drai nage area size and increasing drainage order to determine potential associations with t heir position in the dr ainage network. Sites were segregated based on their landscape physiogr aphy to compare the associations of valley form and patterns among Florida l andscape types (flatwoods, highlands, and karst). Planview Valley Network Pattern s and Landscape Associations In general, stream drai nage area should increase with stream order but the magnitude may differ among various physiog raphic settings. Because a small number of 3rd through 5th Order streams occurred in the study compared with 1st and 2nd order systems, the three higher-order categories were lumped into a mid-order category to facilitate a more equitable comparison. Mean drainage basin size increased with Strahlers stream order for flatwoods and highlands landscapes with each successive order (Figure 3-2) and the results were stat istically significant for post-hoc pairwise comparisons of the log transformed drainag e area values among orders (Table 3-1). Headwater systems of highlands l andscapes may warrant additional considerations because internal drainage can lead to delineations of very high watershed areas that would be unlikely for flatwoods (which generally lack internal drainage). For example, of the seven 1st order flatwoods str eams in the study, the
118 largest drainage area measured was 2.7 square miles (for Lower Myakka UT 2). The two largest 1st Order drainages out of the 10 hi ghlands streams studied were 57.5 square miles (Catfish Creek) and 6.8 square miles (Ninemile Cree k). Catfish Creek drains a large headwater lake with no infl uent streams on the Lake Wales Ridge and Ninemile Creek drains seepage from a hi gh sandy scrub and sandhill complex with internally drained wetlands and ponds located on the Ocala Ridge. Neither of these areas have the capacity to develop surface water drainage because rainfall is quickly captured by a large lacustrine depression or a thick sandy surficial aquifer. Such areas are not exceptional in the hi ghlands and are rare to nonexis tent in the flatwoods. Drainage area was not strongly associated wit h Strahler order for karst landscapes (Figure 3-2). This is not surprising cons idering that the drainage area used in this comparison is often remote from the karst stream. Therefore, an alternate comparison was made substituting the local surface water basin for the recharge basin area for the karst systems. This also failed to produc e increases in mean drainage area in association with increasing order for the karst systems studied. The experimental design deliberately selected ka rst systems from a population lik ely to be independent of surface water controls (in areas located cl ose to the headspring). As some spring runs are joined by surface water streams along thei r length, it seems likely that long runs should increase their local drainage area alo ng their length and so will stream order. Whether this occurs to the same magnitude as in highla nds or flatwoods landscapes was not assessed by this study. Drainage network magnitude based on Shreves ordering system is a measure of drainage complexity. Unlike Strahler order s, Shreves magnitude cumulatively adds
119 each branch in a downstream progression (S hreve, 1966). Figure 3-3 illustrates that more streams entered the dr ainage system as basin size increases and that these trends were particularly strong for flat woods and highlands systems. Flatwoods appeared to support greater drainage network complexity than highlands streams with apparent increases in regression slope and cons tant versus drainage area (Table 3-2). Generally, karst systems differed at statistica lly significant levels (p < 0.05) for all pairwise comparisons of slope and regr ession constant wit h the other two physiographies, except that ka rst slope was statistically indistinguishable from that of highlands (Table 3-2). It appears that the sens itivity of the association of drainage magnitude with draina ge area increases with the surface water influence in the hydrologic regime versus groundwater dominance. Drainage density is the total stream l ength divided by drainage area. For this study, it was computed using the perennial and intermittent streams delineated in the National Hydrographic Database, expressed as linear feet per square mile. No substantial differences were apparent between flatwoods and highlands physiography or the highlands and karst sites based on Dunn post-hoc tests of Kruskal-Wallace ANOVA on ranks, but karst and flatwoods we re different with the flatwoods averaging twice the drainage density of karst basins (Table 3-1, Figure 3-4). This suggests that as surface water processes increasingly dominate over groundwater processes, drainage density tends to increase. Floridas drai nage densities are among the lowest in the world for humid climates, given that densities mapped at the 1:24,000 to 1:50,000 scales are typically in excess of one mile per square mile (Gregory, 1976). This may be due to a combination of factors in addition to groundwater capture of rainfall, including
120 the simple fact that much of the drainag e network is encumbered by in-line lakes and wetlands which directly reduce the total stream length. In-line waterbodies types located immediately downstream of the stream segments studied differed in their distribut ion by physiography (Pearson Chi-Square, p = 0.005). For example, most flatwoods dow nstream junctions consisted of streams followed by various forms of in-line su rface water wetlands (depressional marshes, swamps and quasi-depressional sloughs) (Figure 3-5). Highlands downstream waterbodies consisted primarily of stream junctions, in-line lakes, depressional swamps and seepage swamps. Comparing flatwoods and highlands regions, lakes and seepage swamps appeared to be more common in th e highlands while stream junctions appeared to be more common in the flatwoods. Various forms of in-line surface water wetlands (sloughs, marshes, and swamps) appeared to be in overall similar proportion. Karst streams mainly differed from the ot her landscapes by joining more springs downstream and by having prop ortionally fewer in-line depr essional wetlands. Karst regions appeared to support the lowest over all proportion of inline waterbodies and were the least deranged, while highlands ha d the greatest proportion. This suggests fundamentally different geology/genesis of highlands and karst valley structure. Upstream waterbody types also differed significantly by physiography (Pearson Chi-Square, p = 0.002). Karst systems were not included in the cross-tabs comparisons because the experimental design called for all of their upstream junctions to occur as springs or spring runs and they clearly diffe r on that respect. Most flatwoods upstream junctions consisted of various forms of su rface water wetlands (depressional marshes, swamps and quasi-depressional sloughs) follow ed by influent streams (Figure 3-6).
121 Waterbodies in the highlands upstream of the studied channels consisted primarily of seepage swamps, followed by in-line lakes, depressional swamps, and stream junctions which were found in nearly equal proportions to each other. Comparing flatwoods and highlands regions, lakes and seepage swamps appeared to be more common in the highlands while stream junctions, depr essional marshes, and sloughs appeared to be more common in the flatwoods. Much of these differences may exist based on the relative occurrences of different headwater wetlands in each landscape. Marshes are more common in the flatwoods, while lake s and seepage swamps are more common in the highlands (Myers and Ewel, 1990). The distribution of dominant riparian community types within stream meander belt also varied by physiography (Pearson ChiSquare, p = 0.003) (Figure 3-6). The meander belt is the generally flat part of t he valley that the st ream meanders across. Streams in the flatwoods coursed mainly through valleys occupied by cypress bottomland swamps, hydric hammocks and me sic hammocks. Streams in the highlands were predominantly flanked by seepage swamps, bottomland hardwoods and bottomland cypress swamps. Mo st spring runs coursed through valleys consisting of seepage swamps or mixed swam ps (with hardwoods, pines, palms, and some cypress). By definition, mixed swamps have less propensity for overbank flooding than bottomland swamps. In addition to karst systems which generally lacked bottomland swamps, the biggest differences among the landscapes were that bottomland cypress was the largest single category in the fl atwoods while the riparian zones of the highlands and karst systems were most lik ely to consist of lateral seepage swamps. This suggests that the land scape groundwater regime not only interacts with the fluvial
122 geomorphology of the streams, but also has pronounced association with the riparian zone plant communities. The relative distribution of riparian communities also appears to be associated with Strahlers stream order (Pear son Chi-Square, p = 0.039) (Fi gure 3-7). First and second order streams meandered in contact with a rich array of upland and wetland plant communities ranging from narrow valleys of xeric sandhills to wide bottomland cypress swamps. Mid-order systems (3rd through 5th order) rarely were in much direct contact with uplands and generally flowed through wetland valleys. These comparative differences likely reflect the fa ct that mid-order and higher order stream valleys tend to be formed and maintained by fluvial forces that operate at much greater magnitude and frequency than those found in the headwater portions of the landscape. The comparative reduction in the sheer volume of water available in low order systems likely allows a wider variety of upland and mesic communities to persist within the meander belt. Blanton (2008) reported that cypress trees were most common on flat, floodprone floodplains. Systems with that kind of hydr omorphology tend to be located in mid-order and higher positions along the drainage network in Florida. Meander belt width increased significantly in association with drainage area for all landscape classes (Figure 3-9). This is co mmon in humid regions worldwide (Williams, 1986). Basically, as stream discharge volumes increase, meander geometry increases. Therefore, streams draini ng larger watersheds require more lateral space to accommodate their stable meander pattern. Streams of the flatwoods exhibited statistically significantly higher intercept s and than those of the highlands or karst regions, while highlands and karst streams di ffered little in that regard (Table 3-2).
123 Regression slopes for highlands streams did not differ in a statistically significant fashion from those of karst or flatwoods, but karst streams differed from flatwoods. The differences did not appear to have a very lar ge practical effect, with significant overlap between all three landscapes. However, it did appear that surface water systems exhibited greater meander widths than the groundwater dependent systems for small streams and that the differ ence diminished with increasing basin size. Medium and larger systems appeared to meander more similarly among the landscape types. This may indicate that somewhat geographically universal fluvial forces in the larger basins consistently overcome colluvial controls that can resist such forces more effectively in the headwaters. In other word s, meander geometry is influenced more by biological and geological controls that appear to be sorted differently among physiographic settings in the headwaters, but that the physics of wa ter and sediment transport overcome these differential controls irrespective of physi ography at some threshold of basin scale represented by the higher-or der systems. Inspection of the data scatter suggests convergence of the dominance of alluvial control of meander pattern occurred at drainage area equal to or greater t han 10 square miles (Figure 3-9). Stream meander belts can be confined or constrained by geology. In such cases where the hillslope materials are erodible, the stream c hannel will cut into and flatten the slope edges over time, leading to a meander belt that is rather uniform in width and well-adjusted to its valley. In cases where t he flow regime is greatly resisted by the valley slopes, the stream cannot cut a valley flat that ma tches its meander belt width and it is said to be laterally confined. This can occur in Florida in areas where dense vegetation provides shear strength that endures even the most severe of floods,
124 perhaps typically closer to the headwaters. Unconfined streams c ourse through valleys that are wider than their meander belt. A ll three arrangements, unconfined, welladjusted, and confined stream valleys occur in Florida and were routinely encountered in this study. Figure 3-10 depicts an alternat ing sequence of two types (unconfined and well-adjusted). Valley confinement and its landscape associations are discussed in more detail in the Lateral Valley Pattern section, but the conc epts were introduced here because they need to be illustrated in plan view as well as cross-section to be fully understood. Longitudinal Valley Patterns and Landscape Associations When viewed on a sufficiently lar ge scale drainage networks tend to exhibit a generally concave longitudinal profile (Ma ckin, 1948; Montgomery and Buffington, 1997). This means that the streams drai ning the small watersheds in headwater positions of the longitudina l profile tend to occur withi n valleys exhibiting steeper longitudinal slopes than those st reams draining larger watersheds at lower positions in the landscape. This pattern results from differential effects of sediment transport regimes and energy efficiency that are altered by the ever increasing discharge of water and sediment as one moves down the valley. A well-organized concave profile is referred to as a graded profile Graded profiles are consist ent with sustained differences in sediment supply versus transport capac ity whereby headwater streams have more capacity than supply and supply progressively increases downstream, eventually overcoming capacity. Where that occurs, se diment fills the valle y, reducing its grade (Montgomery and Buffington 1997). Systems can be characterized as existing in three zones along the graded profiles; export, tr ansitional, and depositio nal (Schumm, 1977). Export zones occur in the colluvially c ontrolled valleys of the headwaters, while
125 depositional zones occur in higher order systems with alluvially controlled floodplains. Therefore, transitional areas c an exist with a variety of alluvial and colluvial influences. Florida, in a very general sense, tends toward graded profiles within all three physiographies as evidenced by the fact that valley slope decreases in association with increased drainage area (Figure 3-11). T he most notable difference among the landscape types occurred between the intercept s of the highlands streams versus those of the karst and flatwoods regions. This is due to the fact that headwater streams in the highlands had the steepest stable slopes me asured in the study. These seepage and sapping streams are the previously ment ioned root-step channels that seem to maintain their steep profiles by substantial vegetative controls. The higher valley relief of low-order highlands streams probably also occurs due to the fact that these regions have greater overall available relief than flatwoods in g eneral and also because spring runs are more likely to emerge in comparat ively low spots in the landscape (Walker, 2006). Streams further down the valley and draining larger watersheds appeared to differ little by physiography once drainage area reaches about 10 square miles. Regression slopes were statistically similar among all comparisons ex cept for highlands and flatwoods (Table 3-2). Although Florida exhibits a tendency to develop graded prof iles in a general way, lots of local exceptions occur, consist ent with the wide scatter in valley slope versus drainage area. Grade inflections were meas ured along valley profiles for each study reach from the reach upstream to the headwaters of that valley. Four classes of inflections were observed. Concave prof iles bow downward, convex profiles bow
126 upward, flat or linear profiles represent relatively constant gradient and exhibit no obvious inflection, while mixed profile s have convex and concave segments. All four types of profile inflection s commonly occurred in each physiographic region, without any clear differences in their distribution am ong the landscape types (Pearson Chi Square, p = 0.558) Statistically significant differences occurred among Strahler stream orders (Pearson Chi Square p = 0.041). All four types occurred for each order, but flat profiles were most co mmon at headwater streams, concave profiles at second order systems, and mixed profiles along mid-order valleys (Figure 3-12). So, even though on average the valle y profiles tend toward a graded (concave) profile in Florida as evidenced by the negative regression of valley slope versus drainage area (Figure 3-11), site-specific profiles can be highly variable and may actually have a slight overall bias towards mixed mid-order shapes that include relatively flat headwater reaches followed by concave second order segments. This probably st ems from the fact that the vast majority of headwater stream s drain either seepage wetlands or depressional wetlands, which to remain saturated require flat or depressed lands. The system picks up more energy downstream and the profile begins to grade toward concavity in many 2nd order segments. Since this process is usually driven by headward erosion of the bed, it obviously must be resisted in the headwater reaches to some degree to maintain their predominantly flat or convex profiles. This means that grade controls in 1st order streams and at their upstr eam junction with their headwater waterbodies are critical to maintaini ng their valley grade. Therefore, headwater waterbody to stream channel transitions are part of an ongoing study. Preliminary
127 results show that most of these transitions unfold over distances of a few hundred feet with poorly defined or anastomosed channels that serve to dissipate hydraulic forces. It is important not to overstate these gener al patterns in valley grade morphology because virtually every combination can be found at all orders. The di versity of Floridas valley profile shapes likely reflect the effects of intense vegetativ e controls that can resist grading in a low-relief landscape and the complex clim atogenetics of the peninsula which have left behind a deranged network with lots of old marine scarps and dune lines to cross. Valley segment length was defined as the distance along the va lley centerline with an uninterrupted alluvial stream channel between two in-line waterbodies and/or stream junctions for each study reach. This variable represents the stream li nkage length of the valley for chains-of-waterbodies formed by Floridas deranged stream networks. Valley segment length increased in association wi th drainage area for all three physiographies (Figure 3-13). This pattern is analogous to that of dendritic net works where stream segment lengths generally increase with drainage area as well (S trahler, 1957). In Florida, the frequency (and length) of punctuation by in-line waterbodies appeared to be inherently scale dependant on drainage basin area, perhaps because large-deep depressions, which are presumably less frequent than small-shallow depressions, are necessary to interrupt the continuity of larger stream cha nnels. For example, derangement of headwater reaches was often provided by shallow seepage swamps and marshes a few acres in size, while deran gement of Floridas ma jor rivers was not caused by such wetlands, which the riverine hydraulic and sediment transport regimes
128 can simply overwhelm. Therefore, rive rine derangement was usually caused by large lakes a few thousand acres in size and several feet deep. Valley segment length regressions vers us drainage area did not differ in a statistically significant manner between flatwoods and highlands landscapes suggesting that their stream lengths are somewhat simi larly organized in association with drainage area (Table 3-2). Conversely, karst systems exhi bited statistically significant differences in slope from flatwoods systems and in inte rcept from highlands systems, suggesting that the artesian stream valley le ngths may be organized differently. The number of transitions within a valley per unit valley length (number per mile) was calculated for each reference reach. A transition was inventoried wherever a stream junction was formed, at in-line waterbodies, and at breaks between welladjusted and unconfined valleys. T herefore, this variable could be viewed as an index of longitudinal valley complexity per unit lengt h. The number of transitions per mile declined in association with drainage area for all three physiographies, but was not nearly as sensitive in high lands landscapes (Figure 3-14) This scale dependency is consistent with observations t hat streams draining larger watersheds receive sufficient quantities of water and sediment to re-wor k and grade their valleys more significantly than headwater systems which receive lower i nputs of water and sediment. This means that colluvial factors remain more pronounced in the headwater positions. This suggests that the complex climat ogenetic history of the landscape may remain less altered by modern fluvia l systems near their headwaters leading to longitudinally less graded and more complex valley forms. The regression slope for highlands valley transitions per mile versus drainage area was significantly different
129 from those of karst and flat woods landscapes (Table 3-2). Flatwoods and karst regions appeared to have similar regression slopes bu t statistically significant different intercepts. The consistently gr eater longitudinal complexity of spring run valleys implies that they are subject to more pronounced influences from colluvial geomorphology versus streams in the flatwoods. The very different and more gradual regr ession slope for highland stream valleys, and its low R2 of 0.14, suggests that colluvial fa ctors may wield a heavier influence on their valley structure than fl uvial and alluvial processes normally associated with increasing drainage area. Part this likely to be due to varying degrees of valley confinement caused by the relict dunescapes common in the highlands, as evidenced at several sites like Catfish Creek (illustrat ed on Figure 3-10). However, it appeared that the regression slope difference was influenced mo st heavily by the low order streams in the highlands having less longitudinal comple xity than their counterparts in other landscapes. Most of these headwater highla nds streams were greatly influenced by groundwater sapping, a powerful land-forming pr ocess that was absent from the karst and flatwoods headwater stream s studied. Sapping leads to relatively straight, deep, and typically narrow seepage valleys that are confined to a narrow set of hydrogeologic conditions (including thick columns of sand in areas of high relief and copious groundwater seepage) (Schumm et al ., 1995). They simply rarely, if ever, occur in flatter areas associated with complex in-line depressions. Highlands and karst streams draining larger watersheds seem to co-exi st with more longitudinal valley complexity than their flatwoods counterparts, suggesting that colluvial influences may persist further along their drainage networks.
130 Lateral Valley Patterns and Landscape Associations Valley bottom width generally inc reases with drainage area because larger streams require wider meander belts to accommodate their bigger migrating bends (Williams, 1986). Florida stream systems weakly comported with this general pattern, exhibiting much scatter across a regression of mean va lley width versus drainage area for all three physiographies (Figure 3-15). This is consistent with t he fact that deranged networks frequently create wide depressed valleys that sometimes streams can maintain their continuity through, dependi ng on the relative depth of the deranging feature versus the magnitude of sediment and stream power av ailable. The geologically mediated scatter is so great t hat no statistically significa nt differences in regression slope or intercept were detected among the three landscape classes for valley width versus drainage area (Table 3-2). Four primary types of lateral valley conf igurations were observed among the sites studied and the dominant form was inventoried for each reach. The valley forms included seepage ravines, confined, well-adjus ted and unconfined forms (Figure 3-16). Seepage ravines consist of relatively narro w sapping valleys. They were typically Vshaped and the meander belt was confined by ei ther sandy upland hillslopes or mucky seepage swamp slopes. Overbank flooding is s eemingly too rare to create a floodprone bench or floodplain. Upland confined streams exhibited upland co mmunities within a large fraction of the meander belt width. Much of the banklin e and virtually every outer bend was in contact with or very close proximity to upland hillslopes. These systems exhibited limited signs of overbank fl ooding and often consisted of streams meandering through dense palmettos, with some wetland species occupying sporadic low-lying benches
131 within the meander belt. Although Figure 3-16 illustrates an example with upland bluffs several feet high, the confining uplands o ften consisted of much lower hillslopes, especially in the flatwoods. Even a couple of f eet increase in elevation can make for an upland confined channel in Florida. In well-adjusted valley systems the majority of the meander belt was occupied by wetland communities generally subject to seasonal overbank floods that at least partially structure the valley floor. Many but not all outer bends contacted or approached upland hillslopes, but most of the total bank length was bordered by wetlands. Essentially, well-adjusted va lleys had meander belts coursing through wetland valley-flats that were typically bounded by upland hillslopes, although in some cases the hillslopes consisted of s eepage wetlands. Well-adjusted streams often included textbook examples of fluvial systems predominantly under alluvial control as opposed to colluvial or geologic factors. Unconfined meander belts occupied very wi de flat valley flats that were much wider than the belt width. They tended to r epresent systems under si gnificant geologic control or paleo-valleys where perhaps fluvia l systems previously had much greater flow and sedimentation regimes than present. One type of unconfined str eam valley included systems that were largely encompassed by lowlying colluvial wetlands that flood, not so much in response to overbank stream fl ow, but due to seasonally fluctuating local groundwater tables. The other type of unconfined valley included systems encompassed by alluvial wetlands with co mparatively routine overbank flow and associated floodplain sedimentati on from the str eam discharge.
132 Significant differences in the distribution of valley confinement classes were observed among different Strahler stream orders (Pearson Chi-Square, p = 0.069; Likelihood Ratio, p = 0.025) (F igure 3-17). All four types of confinement were present along 1st and 2nd order streams, but onl y those with wetland flats subject to overbank flooding (well-adjusted and uncon fined) were present in 3rd order and higher systems. Seepage ravines were most common in 1st order systems. Significant differences in the distribution of valley confinement classes were observed among the different physiographic regions (Pearson Chi-Square, p = 0.062; Likelihood Ratio, p = 0.010) (Figure 3-18). Flatwoods systems lacked seepage regimes which were common in highlands and kars t systems. Karst systems lacked upland confined streams, rather ubiquitously being flanked by extensive wetlands. This suggests that the karst valleys are more lik ely to have a history as infilled paleodepressions as opposed to scoured colluvium Highlands landscapes were the only physiographic division that ex hibited all four types of valley confinement. This adds to the impression that highlands valley forms reflect a complex intersection of modern alluvial and relict geologic controls. Significant differences in the distribution of dominant meander belt sediment or soil classes were observed among Strahler stre am orders (Pearson Chi-Square, p = 0.016) (Figure 3-19). First order syst ems had the greatest overall di versity of sediment types reflecting their common contact with a variety of colluvial soils. Alluvial soil layers such as those consisting of finely stratified organi c and inorganic layers were only present in the mid-order stream s, implying that 1st and 2nd order systems have lower overall alluvial characteristics than higher order systems.
133 Significant differences in the distributi on of dominant meander belt sediment or soil classes were observed among the different physiographies (Pearson Chi-Square, p = 0.164; Likelihood Ratio, p = 0.029) (Figure 3-20) Stratified layers were only present in flatwoods streams, suggesting that the less flashy groundwater fed systems less commonly generate sufficient power to depos it sand in their floodplains. Peat and mucky peat were largely absent from flat woods valleys but were quite common for highlands and karst systems. This sugges ts that peat development requires rather constant seepage in Floridas riparian corridor s with limited overall hy drologic flood and drawdown pulses. Muck (cohesive sapric hist osols) and mucky sand were the only two classes found in all three physiographies, reflec ting the rather widespread distribution of non-perennial wetlands in the ri parian corridors of Florida. Channel and Floodplain Hydrau lics and Alluvial Fe atures In Floridas humid sub-tropical climat e, year-round bioturbation, dry season oxidation of organic layers, a landscape dom inance of fine sandy soils, and a lack of Fall leaf litter pulses can combine to obscure alluvial-organic soil layers that are commonly developed in temperate regions and that can serve as excellent verification of alluvial floodplain construc tion. Therefore, in addition to looking for such sediment lamellae, a variety of other a lluvial features were inventor ied within the stream channels and their floodplains to improve understanding of landscape characteristics associated with active alluvial processes. Features inventoried included sand bed ripples, induced scour pools, bend pools, point bars, sand shoal s or riffles, natural bank levees, linear backswamps with fine textured sediments, floodplain chutes and secondary channels indicative of past avulsions, a ubiquitous va lley flat with fine textured soils, sandy benches between bends, and oxbow lake s or ponds in the floodplain.
134 The number of alluvial features incr eased with drainage area substantially for flatwoods and highlands areas and rather modestly for karst sys tems (Figure 3-21). Differences among the regression constants were statistically significant among all pairwise comparisons of physiography (Table 3-2). Flatwoods and highlands regression slopes could not be statistically segregated, but karst differed significantly from both. The regression comparison suggests that al luvial features increase steadily with increased drainage area (perhaps in response to associated increases in water and sediment yields). The regression compar isons further suggest that the number of alluvial features were consistently higher for systems dominated by surface water flows versus those under the influence of groundwater flow regimes. The karst systems, clearly dominated by steady groundwater fl ow regimes, have comparatively limited alluvial features. Flood and bankfull channels were determined at each reach using the best available and most reliable field indicato rs. The non-karst perennial streams studied were routinely overbank, often in excess of 25% of the year and generally fluctuated above bankfull stage at least several times duri ng the year (Table 2-2). This situation is similar to many areas in the seasonal tr opics which exhibit a channel-within-a-channel configuration and the wet-seas on or flood channel is typically heavily vegetated (Junk, et al ., 1989). Flood channels were delineated in the field using a combination of biological and physical indicators including pe rsistent stain lines, lichen lines on mature trees, moss collars on trees close to t he bank, sharp palmetto lines at wetland boundaries, and the horizontal limits of finel y textured soils on a valley flat. The flood channels identified in this manner generally flowed ever y year and the upper stage of
135 the channel was reached typically once every 1.5 to 5 years (based on annual maximum series calculated by Blanton, 2008). The upper stage of the flood channels showed a lot more variability among sites w hen a partial duration series was used to calculate the exceedance frequency, but t he most typical exceedance frequencies were right around once per year (Table 2-2). Basically, the flood channel represents the routine wet season channel with hydropattern thresholds associated with at least some of the sorting of the ecological communities in the floodscape. The flood channel hydraulics are expected to serve as a good indi cation of the capacity of the system to conduct relatively routine geomorphic work in the floodplain. The ratio of flood channel to bankfull channel stream power provides a dimensionless index of the capacity for work that can be conducted in the floodplain versus that which the system more routinel y provides within the main channel. Karst systems exhibited no trend in association with drainage area on this index, but highlands and flatwoods str eams did and were accordingl y depicted on Figure 3-22. The regression constant was statistically different but the regression slope was not. This implies that flatwoods systems produce consistently larger flood flow work compared to highlands streams draining si milarly dimensioned watersheds. Flatwoods landscapes were also associ ated with proportionally wider floodplains versus those draining the highlands in a regression comparing the width of the flood channel to the width of the bankfull channel versus draina ge area (Figure 3-23). The regression constant was statistically signif icantly different but the regression slope was not (Table 3-2). This association does not necessarily demonstrate cause and effect in a deranged network, but when viewed together wit h other factors such as the increased
136 number of alluvial features for flatw oods systems over highlands and the increased flood to bankfull power ratio, it seems to add credence to the concept that flatwoods systems generate more routine floods that c onduct more work in their floodplains than their highlands counterparts draining watersheds of similar size. The flatwoods sites exhibit disproportionately large flood channels compared to their bankfull channels versus those of the highlands. This is because bankfull discharges are similar in both types of watersheds, but that the larger spates of the flatwoods are necessarily accommodated by larger (wider) flood channels. Montgomery and Buffington (1997) characte rized mountain streams as selfadjusting systems that achieved channel di mensions and roughness conditions necessary to balance sediment transport c apacity with supply under a variety of valley slope conditions. To achieve this balance, channel resistance (roughness) was necessarily higher in areas with steeper valley slopes and low sediment supply. In the mountainous regions studied, roughness coefficients were associated with the size of rocky bed materials. Even in comparatively fl at, sandy Florida, convergent principles seem to apply. The roughness mechanisms diffe r as they are largely induced by living vegetation and logs in Florida in lieu of rocks, but nevertheless, increased roughness occurs in association with increased va lley slope (Figure 3-24). No statistically significant differences were detected on the regression constant or slope between flatwoods and highlands str eams (Table 3-2). Mannings n in karst streams exhibited no association with valley slope.
137 Conclusions Application of Clinal and Func tional Process Zone Concepts Floridas deranged stream networks appeared to have an underlying self-adjusting and clinal s tructure similar to that of many dendritic and alluvial watersheds around the world with tendencies toward development of graded profiles, increasing stream order and magnitude with drainage ar ea, increasing channel and fl oodplain dimensions with drainage area, increased meander belt widths wit h drainage area, increasing alluviation with drainage area, greater co lluvial contact in the headwat ers, and the development of more channel resistance with increasing vall ey slope. It is important to be aware of these patterns. Some forms of floodplains simply cannot be supported in the headwater reaches, especially those dependent on alluvial deposition. However, these general patterns often exhibi ted many local exceptions and lots of scatter due to Floridas intense sub-tropical vegetative controls and how they interact with groundwater flow regimes (see Chapter 2). Complexities also arose due to a long history of differential solution weathering t hat has formed many doline depressions in the landscape, some of which interrupt the continuity of channel systems leading to description of the network as being deranged Furthermore, the multiple partial inundations of the peninsula by sea water have created a co mplex array of relict marine terraces and dune lines that collectively br eak up clinal patterns toward concavely graded profiles and increasingly wider floodplains with increas ed drainage size. Numerous punctuations in the drainage net work occurred due to in-line depressions and sudden and repeated transitions in valley width and slope inflections occurred frequently. The geologic controls were not comp letely chaotic as evidenced by the fact
138 that channeled valley lengths between interr upting waterbodies increased with drainage size. Any useful characterization of Floridas stream systems must take into account fluvial and vegetation controls operating under the modern climate which are nominally clinal processes and must also consider the geologically-oriented punctuations that add seemingly chaotic elements to the valley stru cture. To ignore either kind of control would lead to oversimplified solutions for conserving, managing, or restoring small streams in the Florida. For that reason, use of FPZ concepts are strongly encouraged, because these readily and naturally accomm odate repeated and punc tuated conditions without abandoning important clinal considerations. Which dominates is a matter of spatial scale. Clinal patterns are unlikely to be obvious except if one were to rapidly travel long distances along any given drainage network. Sudden changes in grade, valley width, and in-line waterbodies form ec otonal boundaries that are rather obvious when traversing even a short distance along the network. Under such short distances any overall graded pattern along the valley is ob scured. It seems likely that most stream restoration practitioners will end up working on local scales. To prescribe appropriate earthwork and vegetation, they will want to know what palette of valley and channel associations to draw from and to do so will need to know their position along the fluvial systems clinal gradient. Even though Flori das complex stream system genesis allows for a fair amount of abrupt change, so me combinations of geomorphology and vegetation just do not make much sense and are unlikely to be self-sustaining. The position of the stream in the drainage network is associated with its likelihood to be in a zone of excess sediment transport capacity and net export (most headwater streams),
139 mixed transport/deposition zones (most mi d-order well-adjust ed streams), or a predominantly depositional floodscape (most mi dto higher order well-adjusted or unconfined streams). Descriptions of Valley Types and Their Landscap e Associations Several combinations of valley processes and form associations can be inferred from the data. The relative amount of groundwater and surface water dominance appeared to greatly associate with valley pr ocess and related form. Although there was overlap in valley types among flatwoods, highlands, and karst landscapes, some types were less common or even absent from par ticular physiographies. Furthermore, the scale dependencies of common processes and associated valley forms differed among these three physiographies. It is probably a good idea to view these hydrogeomorphic landscapes as the first hier archy of consideration. The second consideration is a matter of position along the drai nage network as it relates to sediment and water yields that are sensitive to drai nage area. These factors directly affected the scale and form of the st ream channel and its floodplain. Different processes dominated along this gradient as well. Riparian soil and vegetation community patches were associ ated with the different hydrol ogy zones that these scaledependant processes formed, such as sandy bank levees, mucky linear backswamps, sandy chutes or secondary channels with detritus, oxbow lakes, sandy islands, and silty mucky valley flats. Each of these alluvial features tends to support niche requirements of different groups of vegetat ion and, presumably, different meta-populations of aquatic and terrestrial fauna (Thorpe et al ., 2008). For example, Blanton (2008) observed that cypress dominated bottomlands occupied valleys wi th extensive alluvial flats or linear backswamps and cypress trees were largely absent from the more entrenched
140 (colluvial) stream valleys in the landscape. Palmettos and live oaks were generally only encountered on systems with conf ined upland meander belts or on natural sandy levees or islands. The third consideration is local lateral valley confinement. Confinement can influence local hydraulics and allows for spatially variable contact with colluvial inputs of sediment and chemicals with t he stream. Some types of valley confinement are also scale dependant. The various apparent scale dependencies and their interactions with physiography led to several common types of valley Functional Process Zones that were observed during this study and that became even more apparent after evaluation of these data. These types of observations revealed several basic types of colluvial versus alluvial valleys occupied by Florida streams. The positions of these systems in the drainage network (in association with drai nage area) seemed to differ among the physiographic regions (Figure 3-25). For example, Tiger Cr eek drained a 53 square mile highlands watershed and had created an alluvial valley flat about 150 feet wide, while Tenmile Creek drained a flatwoods basin three times smaller and had created a similarly dimensioned alluvial valley fl at. The Manatee River drained a flatwoods watershed more similar in size to that of Tiger Creek and had a substantially more complex, wider and deeper floodscape. Note t hat even the 86 square mile watershed of the Weeki Wachee River spring run failed to produce an alluvial valley rivaling that of the 17 square mile Tenmile Cr eek of the flatwoods. These examples illustrate the normal propensity of runoff dominated watersheds to produce more alluvial work and complexity in bigger flood channels for a given basin size versus those of the less flashy groundwater systems. Note also the comparat ively high bluffs present in all three
141 highlands valley examples. These did not occu r for all highlands stream segments, but most highlands valleys included at leas t portions of their shoreline with such geomorphic features, while such bluffs were comparatively rare in the flatwoods, generally only occurring where larger st reams cross old marine terrace lines. Valleys where alluvial proc esses and forms were almost completely limited to the stream channel bed and their meander belt were dominated by soils and landscape features not created by modern alluviation were deemed to be colluvial valleys. Colluvial valleys included seepage ravines, upland-c onfined channels, and wetland-confined channels. Seepage ravines are V-shaped or U-shaped valley cross-sections that promote lateral seepage to the stream channel and the groundwater discharge is sufficient to support sloped wetland communities such as bay swamps (Figure 3-26). No alluvial floodplain is present. In some ca ses, the lateral extent of the seepage slope wetland can be several hundred feet wide, but in many cases it is much smaller, as little as 20 feet. Upland-confined channels meander th rough upland valleys where the wetland boundary closely corresponds to the channel banks. A common setting for this arrangement includes the headw ater and low-order positi ons of streams of the flatwoods that form chains of wetlands (Figure 3-27). These systems are bordered by either pine and palmetto savannas or by me sic hardwood gallery forests that lack a floodplain, but sometimes have small bank full benches along the inner portions of bends with shrubby or forested wetland species inclusions. Wetland-confined channels meander through shallow depressed areas subject to flooding or prolonged saturation where it occurs long enough to support a variety of
142 wetland types, usually hardwood swamps or hydric palm/pine hammocks and less commonly freshwater marshes, wet prairies, or cutthroat grass swales (Figure 3-27). These wetlands do not include alluvial features or soils and therefore appear likely to be receiving most of their water from non-fluvial sources. In other words, these colluvial areas would be wetlands irrespective of t he presence of the stre am and the stream network serves primarily as a downhill exporter of water from the we tland rather than an overbank source to it. Valleys where alluvial processes and fo rms appeared to directly influence soils and landscape features within the meander belt were deemed to be alluvial. These valleys included well-adjusted floodplains and unconfined floodplains. Well-adjusted floodplain valleys have a channel meander belt that is very close in typical width to the width of the valley flat, and the meander bel t is confined by upland hillslopes, or sometimes by seepage slopes (Figure 3-28). These streams are well-adjusted to their valleys, generally meandering across the enti re valley floor. As a result of channel migration and overbank deposition of sediments, the valley floor is populated by alluvial features. The outer channel bends frequently are bordered by uplands on the valley slope and wetlands border most of the channel elsewhere. The floodplain is almost always a wetland. Some systems have large portions of their outer bends flanked by upland bluffs rather than ju st the apex of t he bend. This represents a condition intermediate between upland confined and welladjusted systems that may warrant its own designation, but for now these systems we re categorized as well-adjusted. Most well-adjusted alluvial botto mlands present more than one al luvial feature type and can be vegetated by a variety of plant communi ties, mostly hardwood or cypress bottomland
143 swamps, with inclusions of hydric or me sic palm, pine or oak hammocks. Sediments can consist of various combinations of s andy alluvium, fine-textured alluvium, and cohesive black muck. These sediments can sometimes occur in layers, often with detrital inclusions, but they generally sort in to features roughly parallel to the valleys long axis such as channel levees, linear backswamps, and oxbow lakes. Unconfined channels meander through very wide valley flats compared to their meander belt width (Figure 3-29). These are ess entially portions of streams unconfined by the geologic history of the segment. Unconfined valleys can be alluvial or non-alluvial depending on their position in the landscape and its associated sediment yield. Where they were colluvial, they were referred to as the wetland confined channels described earlier and where they were alluvial, t hey were called unconfined floodplains. Unconfined floodplains can be dominated by a single alluvial feature such as a flat valley fill canopied by mixed cypress and bottomland hardwood swamp species growing on a fine-textured (silty) and mucky alluvial so il, or they can be occupied by a diverse array of sandy versus mucky alluvial feat ures forming a comparatively rough bottomland that presents a variety of rela tively dry and deep water habitats. These five valley types (seepage ravines upland-confined channels with colluvial valleys, wetland-confined channels with colluvial valleys, welladjusted alluvial valleys, and unconfined alluvial valleys) represent land scape level sorting of sediment transport regimes and resultant geomorphi c features. Cluster analysi s and principal components analysis were used to further interpret the valley variables to determine how to best use them in a stream classification system in Chapter 4. Although some valley types alternated with each other in various combin ations along the drainage network, they
144 appeared to have strong associations with partic ular positions in the drainage network. For example, the V-shaped seep age valleys of most root-st ep streams were confined to the colluvial hillslopes of headwater s eepage areas in highlands physiography. The alluvial floodplain characteristics increased with drainage area for blackwater streams, seemingly because more sediment is availa ble for transport and there is more water available to carry and deposit it in a downstream directi on along the drainage network. Research Needed Very little systematic a nd detailed studies of the fluvial geomorphology of lowto mid-order components of warm-climate deranged drainage systems have been made. As a result, preliminary studies of tr opical deranged networks ar e underway using highresolution aerial photography. Initial results suggest a relatively high presence of derangement of savanna drainage networks compared to those in tropical arid zones and rainforests. The fluvial geomorphology and related hydroecology of warm-climate deranged networks likely warrants systematic re search to determine if any common processes are involved or if this is me rely an example of convergence of form. Comparative hydrobiological studies should be made to determine the ecological relevance of various valley forms, if any, to the aquatic fauna and flora of Floridas riparian corridors. Studies emphasizing fi sh and phytoplankton are especially needed given the paucity of data on the occurrence, seasonality, and s patial distribution of such biota along Florida riparian corridor s. The FDEP has extensively studied macroinvertebrates in Flori da streams, going to great lengt hs to develop what they believe is a scale-independent index of biological integrity (Fore et al ., 2007). Further research is needed in the opposite vein to det ermine what, if any, factors related to macroinvertebrate species composition and productivity differ am ong FPZs. It seems
145 that differences in the m agnitude and frequency of longitudi nal and lateral hydraulic connections among different FPZs should affect the aquatic fauna. Related nutrient fluxes or spiraling also warrant further resear ch to help identify potential differences in water quality and trop hic functions among FPZs. Such fluxes may provide clues related to the natural buffering capac ity of groundwater versus surface water dominated systems and the wi dely varying organic content of their floodscape soils. For example, it could be hy pothesized that in t he headwaters, organicrich seepage valleys would process nitrogen compounds differently from flatwoods valleys with sandy soils right up to the channel banks. If such differences in nutrient assimilative capacity exist, agricultural and dev elopment buffers woul d necessarily differ as a function of which type of headwater stre am corridor is present to assure similar levels of protection for stream wate r quality and associated trophic status.
146 Table 3-1. ANOVA summaries VariableFactorNMeanSESig.ANOVA test, pairwise procedure Flatwoods DA*1st order70.817.8ATwo-way ANOVA, Holm-Sidak 2nd order917.915.7B Mid-order7115.617.8C Highlands DA*1st order107.014.9ATwo-way ANOVA, Holm-Sidak 2nd order813.216.6B Mid-order388.227.1C DA*FW2344.89.9ATwo-way ANOVA, Holm-Sidak HL2136.111.7A K1254.519.9A Drainage densityFW232863.1313.8AKruskal-Wallis ranks, Dunn HL212459.7418.5AB K121381.8511.5B Sig. = significant differences between physiographies with different letters (p < 0.05). SE = standard error. FW = flatwoods, HL = highlands, K = karst. *Log-10 transformation was used to meet assumptions for normality & equal variance. DA = drainage area (square miles). Drainage density = feet of stream per square mile. Orders based on Strahler method (Mid-order is 3rd, 4th and 5th orders).
147 Table 3-2. Regression summaries IV DVFWHLKFW HLK HLK FWFWHLKFW HLK HLK FW Log(DA) ctrLog(Magn)0.5970.4180.0960.0540.0050.0000.5530.3730.1890.0710.1660.006 SE------->0.0620.0910.108NSSIGSIG0.0640.0980.125NSNSSIG Log(DA) ctrLog(MBW)1.9521.8441.7900.0450.3940.0120.2800.3540.4930.1970.0700.005 SE------->0.0360.0520.062SIGNSSIG0.0370.0560.072NSNSSIG Log(DA) ctrLog(VSS)-0.754-0.546-0.8840.0050.0000.131-0.364-0.536-0.4440.0290.3710.421 SE------->0.0710.0520.086SIGSIGNS0.0760.0580.102SIGNSNS Log(DA) ctrLog(LVS)3.5243.6613.2720.2070.0040.0530.3220.4640.7010.2250.1300.014 SE------->0.0730.1070.127NSSIGNS0.0750.1150.148NSNSSIG Log(DA) ctrLog(Trans)0.1540.1940.5500.7130.0100.004-0.569-0.153-0.4990.0010.0330.647 SE------->0.1090.0800.133NSSIGSIG0.1180.0890.158SIGSIGNS Log(DA) ctrLog(VW)2.5832.4852.3600.4290.8600.3990.3310.3620.5630.0850.2620.856 SE------->0.0840.1230.146NSNSNS0.0860.1700.132NSNSNS Log(DA) ctr(TAlluv)4.8053.6641.0230.0060.0000.0002.1011.9540.7180.7350.0380.016 SE------->0.4010.2930.488SIGSIGSIG0.4320.3270.579NSSIGSIG Log(DA) ctrLog(RPower)0.6480.439--0.007----0.2200.117--0.197---SE------->0.0500.073--SIG----0.0510.078--NS---Log(DA) ctrLog(RWidth)0.9500.436--0.000----0.3590.300--0.617---SE------->0.0740.108--SIG----0.0760.116--NS---Log(VS) ctrLog(n)-1.080-1.013--0.322----0.3900.352--0.795---SE------->0.0470.067--NS----0.1230.147--NS---Log = log10 transform, ctr = variable centered, NS = p > 0.05, Sig = p < 0.05, SE = standard error. FW = flatwoods, HL = highlands, K = karst. DA = drainage area, Magn = Shreve's order, MBW = meander belt width, VSS = valley segment slope%. LVS = length of the valley segment (ft), Trans = no. of transitions per valley mile, VW = valley width (ft). TAlluv = total alluvial features, RPower = ratio of flood/bankfull stream power. RWidth = ratio of flood/bankfull channel width, n = Manning's friction factor, VS = reach valley slope%. Variables B constant B slope p > F p > F
148 Figure 3-1. Dendritic and deranged drainage netwo rks with example of Strahlers (1957) ordering system. Stream Channel Lake or Wetland, without Channel 1 1 1 1 1 1 4 2 2 3 4 DENDRITIC NETWORK 1 1 1 1 1 1 4 2 2 3 4 DERANGED NETWORK
149 Figure 3-2. Drainage area associated with stream order for three physiographic regions.
150 Figure 3-3. Shreve (1966) cumulative network magnitude versus drainage area for three physiographic regions.
151 Figure 3-4. Drainage density associated with stream order for three physiographic regions. Drainage density calculated from the National Hydrographic Database of perennial and in termittent streams.
152 Figure 3-5. Proportions of waterbody type occurring downstream of the channel reach for three physiographic regions.
153 Figure 3-6. Proportions of waterbody type occurring upstream of the channel reach for three physiographic regions.
154 Figure 3-7. Proportions of riparian wetland type dominant in t he channel meander belt for three physiographic regions.
155 Figure 3-8. Proportions of riparian plant co mmunities dominant in the channel meander belt by Strahler stream order.
156 Figure 3-9. Meander belt width versus catc hment area for three physiographic regions.
157 Figure 3-10. Catfish Creek stream channel with alternating unconfined and welladjusted meander belts.
158 Figure 3-11. Valley slope versus drai nage area for three physiographic regions.
159 Figure 3-12. Longitudinal valley shape di stribution by Strahler stream order.
160 Figure 3-13. Valley segment lengths between in-line waterbodies or stream junctions versus drainage area for three physiographic regions.
161 Figure 3-14. Number of valley segment transitions per valley mile versus drainage area for three physiographic regions.
162 Figure 3-15. Valley width versus catchm ent area for three physiographic regions.
163 Distance (ft) 0 50 100 150 200 250 300 Elevation (ft) 96 98 100 102 104 106 0 50 100 150 200 250 300 Elevation (ft) 96 98 100 102 104 106 0 50 100 150 200 250 300 Elevation (ft) 96 98 100 102 104 106 0 50 100 150 200 250 300 Elevation (ft) 96 98 100 102 104 106 MBW MBW MBW MBW Seepage Ravine Upland Confined Stream Well-Adjusted Stream Unconfined Stream Figure 3-16. Types of valley confinem ent. MBW = meander bel t. Confinement depends on the relative width of the meander bel t to the seasonal flood width line. The flood width corresponds to the uppermost of the two thin horizontal lines. The lower line is the bankfull stage.
164 Figure 3-17. Valley confinement distri bution by Strahler stream order.
165 Figure 3-18. Valley confinement distribution by physiography.
166 Figure 3-19. Dominant meander belt sediment distribution by Strahler stream order.
167 Figure 3-20. Valley confinement distribution by physiography.
168 Figure 3-21. Total alluvial features ve rsus catchment area fo r three physiographic regions. Alluvial features are formed via sediment transport. Examples include natural levees, linear backswamps, point bars, oxbow lakes, stratified sediment layers, bend pools. S ee Appendix A for full listing.
169 Figure 3-22. Ratio of flood channel to bankfu ll channel stream power versus catchment area for two physiographic regions.
170 Figure 3-23. Ratio of flood channel to bankfu ll channel width versus catchment area for two physiographic regions.
171 Figure 3-24. Bankfull channel friction fact or versus local valley slope for two physiographic regions.
172 050100150200250300350400 85 90 95 100 105 110 115 Distance (ft) 050100150200250300350400 Elev. (ft) 85 90 95 100 105 110 115 Distance (ft) 050100150200250300350400 85 90 95 100 105 110 115 Distance (ft) 050100150200250300350400 85 90 95 100 105 110 115 050100150200250300350400 Elev. (ft) 85 90 95 100 105 110 115 050100150200250300350400 85 90 95 100 105 110 115 050100150200250300350400 Elev. (ft) 85 90 95 100 105 110 115 050100150200250300350400 85 90 95 100 105 110 115 050100150200250300350400 85 90 95 100 105 110 115 Flatwoods Highlands KarstDA = 0.2 Colluvial FP DA = 0.3 Colluvial FP DA = 1.0 Colluvial FP DA = 17 Alluvial FP DA = 53 Alluvial FP DA = 27 Colluvial FP DA = 65 Alluvial FP DA = 120 Alluvial FP DA = 86 Colluvial FPBell UT Tuscawilla UT Silver Glen UT Tenmile Tiger Gum Slough Weeki Wachee Livingston Manatee Figure 3-25. Valley bankfull and floodscape channel comparisons by drainage area (DA, sq. miles) and physiography Dotted vertical lines delineate fl ood channel and solid lines mark the bank full. Vertical datum normalized.
173 Scale is approximately 1 inch = 2,000 feet. Flow direction is toward the lake. Figure 3-26. Sapping valleys with seepage ravines. Lake Lowry Unnamed Tributary (UT) (USDA 1943a)
174 Scale is approximately 1 inch = 1,000 feet. Flow direction is to the northwest. Figure 3-27. Chain-of-wetlands with upland and wetland confined channels. Lower Myakka Unnamed Tributar y (UT) 2 (USDA 1948).
175 Scale is approximately 1 inch = 1,000 feet. Flow direction is to the south. Figure 3-28. Well-adj usted channel within a high-gradient alluvial bottomland forest. Horse Creek near Arcadia (USDA 1943b).
176 Scale is approximately 1 inch = 2,000 feet. Flow direction is to the southeast. Figure 3-29. Unconfined channel within an immense bottomland forest. Blackwater Creek near Cassia (USDA 1941).
177 CHAPTER 4 A CLASSIFICATION SYSTEM FOR THE CONSERVATION AND RESTORATION OF FLORIDAS FLUVIAL SYSTEMS Introduction About $10 billion has been spent on 30,000 rive r restoration projects in the United States and the industry is growing rapidly (Malakoff, 2004). Florida has been behind the national trend in awareness of protecting stream s from disruptions to fluvial geomorphic processes, but this is expected to change. In fa ct, it is possible that the findings of this proposed research topic will help to promote awareness in the state regarding stream protection and restoration. During the site selection for this study, 75 of the first 100 randomly-selected stream sites were reject ed because they were likely to be impacted by their basin-scale land use alterations, drainage ditches, land clearing, filling or other human activities. The prioritization of stream restoration projects and the design approaches to fix damaged streams (or arrest further damage) often starts with a regionally applicable fluvial geomorphic classificati on for intact, properly functi oning stream systems. Streams with measurements departing from the desired classification are sometimes identified as those in need of restoration. Furthe rmore, the awareness, conservation, and management of intact stream segments are also often based on how well a system fits natural channel classification schemes. Florida currently lacks a systematic fluvial geomorphic classificati on for freshwater streams useful for management and restoration. This is unf ortunate, because Florida has unique fluvial forms that likely depart from national norms. This distinction is likely because the classification norms being used to gui de restoration activities in the United States are derived largely fr om studies of perennial streams in temperate climates
178 under alluvial control. Alluvial control means the stream shape is controlled largely by sediment transport. In contrast to the rest of the U.S., Flor ida has a mostly sub-tropical climate with a major stochastic presence of pow erful tropical storms, most of Floridas streams flow intermittently (s easonally) rather than perennially, and the stream corridors appear to be only partially under alluvial control. While existing alluvial-based stream classifications are likely to apply to streams in Florida originati ng from the temperate continental land mass (such as the Apalachicola River), they could be more limited or even incorrectly applied to the population of streams originating in the unique climate and physiography of the Florida peninsula. Fluvial geomorphologists working in nontemperate, non-perennia l, or non-alluvial systems, especially in deserts and the seasonal tropics, are finding streams in such settings do not fit prevailing reach-scale shape-based classification approaches very well. Miller and Gupta (1999) provide a compilation of case studies of unique fluvial fo rms that do not fit alluvial control norms developed from north, te mperate regions. Thorp et al (2008) are also questioning some of the fundamental clinal conc epts of stream self-organizati on even for the regions in which they were first derived, suggesting that patch dynamics are the norm for most systems worldwide. Purpose The seasonally wet Florida peninsula, poised between the seasonal tropics and a humid temperate landmass, offers an intriguing possibility to te st concepts related to the limits of alluvial and clinal classification systems based on humid temperate norms. From a practical standpoint, applied stream morphologists working in Florida should want to know, Can we be comfortable re lying on classifications dev eloped under
179 potentially different circumstances than thos e in Florida? and If not, then what should we be using? Therefore, the main objective is to derive at least a t entative classification scheme tailored to facilitate improved under standing, management, and restoration of freshwater streams on the Florida peninsula that ar e unique or otherwise poorly classified through the lens of norms developed for streams elsewhere. General Approaches to Stream Classification Most modern stream classifications depend, at least in part, on regime theory. Under regime theory, stream morphology can be viewe d as a product of a generally constant set of long-term environmental forci ng functions of climate, physiography, and alluvial sediment characteristics. This set of relatively constant forcing functions is the systems regime. Streams that react to these forcing functions on a time scale that is short enough to prevent a confounding series of lag effects from previous environmental regimes are said to be in-regime for their region. Lag is best reduced to the point of favoring equilibrium concepts when there is a lot of water delivered to the channel at high frequencies which provides energy result ing in work that routinely transports readily available sediments. Perhaps regime theory is therefore best applied to streams under routine alluvial control rather than those under more stochastically determined features related to bedrock controls or colluvial control. Regi me theory presumes t hat streams enter a relatively predictable equilibrium of channel form as an associate of basin characteristics within a relatively homogeno us region. Regions must be sufficiently homogenous and correctly delineated to proper ly apply regime theory. Examples of streams fitting such conditions have been de scribed in the humid northeast, humid mid-
180 west, and various non-desert areas of the western United States, in humid New Zealand, in humid Great Britain and Europe. Knight on (1998) provides a good summary. Regime-based classification and restoration practices are commonly applied to gravel and sand bed streams in humid temperate climates around the world. For systems where regime theory is applicable, one can often apply regression equations to carefully defined regions relati ng independent form variables (such as drainage basin area) to dependent form variables in the channel (such as bankfull channel cross-section area). Be cause these regressions are limited by region, they are referred to as regional curves. Region al curves are encountered often in applied stream restoration practices. Regions and stream classificati ons within regions are often segregated based on visual inspections of slope and intercept differences in the regression line among samples drawn from a priori populations. Rosgen (1994) developed what is perhaps the most prevalent general classification method using a regime theory framework. T he Rosgen stream classification focuses primarily on stream channel shape, cla ssifying streams by measurements taken at a reac h scale typically a few hundr ed feet long (Rosgen, 1996). Rosgen based his physical form-based classifi cation largely on the works of fluvial geomorphologists working in perennial al luvially-controlled channels who were interested in predicting the associations between channel form and processes (Leopold and Maddock, 1953; Leopold et al. 1964; Williams, 1986). One of the central tenants of Rosgens shape-based classification is that changing any one of the dimensional variables in his classification at the reach scale will cause shifts in the others for the stream to regain eq uilibrium status.
181 Rosgen picked relatively easy to meas ure forms that had been identified as sensitive indicators of channel process in alluvial streams. For this reason, it is often assumed to be sufficiently process-based to be used to guide stream restoration designs, sometimes including major riparian engi neering works. Such use of Rosgens approach has been the topic of several peer-review journal articles and even more conference proceedings debating the merits of widespread application of its technology. Critics or cautionaries include Montgom ery and Buffington (1997), Juracek and Fitzpatrick (2003), Harmel et al (1999), and Caratti et al 2004. Some have found Rosgens system was readily adaptable to their region of interest (Epstein, 2002; Doll et al ., 2003; Savery et al ., 2001; Hey, 2006). An earlier regime-theory based classifica tion was offered by Leopold and Wolman (1957). That system also relied on observati ons of channel shape at the reach scale, with less standardization of measurements and a more vis ual approach to define channel shape as opposed to Rosgens rather quantitative methods. Channels were classified as a continuum of forms includ ing braiding, meandering, and straight. This classification was largely conceptual. If streams under alluvial control best fit cl assifications systems developed under a regime theory framework, t hen streams under varying degrees of non-alluvial control could be expected to be outliers to such a cl assification system or they could fit the classification by mere coincidence and si mply have similar shapes as a matter of unrelated convergence of form. Streams with significant non-alluvial controls likely belong to a different population of str eams than alluvial syst ems and it becomes
182 important to understand how and why they differ if one is interested in managing, restoring, or otherwise prot ecting such riparian systems. Systems with low-frequency flow events t hat do the most work moving channel materials, systems with low availability of transportable sedim ents, systems with nonhydraulic controls imposed on sediment mo vement, and systems with rapidly changing climate or physiography are less likely to fit regime t heory classifications. Desert streams, streams of the seasonal tropics with monsoons, streams with bedrock (nonalluvial) controls, and streams fo rming on newly volcanic soils or areas of recent glacial retreat do not seem to fit r egime theory very neatly (Mill er and Gupta, 1999; Gupta, 1995; McCarthy et al ., 1992; Sidle and Milner, 1989). The dimensions of non-regime channel systems are sometimes controlled largely by rare, somewhat unpredictable events (f or example, colluvial processes like landslides, or unusual hydraulic events such as megafloods). Non-regime streams may also be controlled by non-alluvial processes related to valley geology or biology that greatly restrict or preclude the movement of transportable alluvi um such as exposed bedrock, subsidence/collapse features, massive log jams, or incredibly dense vegetative controls. The basic difference is that regime channels are best viewed as a product of existing climate and physiographic conditions in a region and non-regime channels reflect relict or heavily constrai ned physical conditions resistant to change under the existing climate. O ne responds and one resists. Most workers noting exceptions to the regime-theory model probably assume they are dealing with unique cases, and many are perhaps correct, so no universal classification system for non-alluvial, nonequilibrium channels has emerged. Workers
183 in regions with non-regime channels proba bly must develop special geographicallylimited classifications, although potential exc eptions are emerging. For example, Gupta (1995), based on observations in South Americ a, the Caribbean, and India, has offered that streams in the seasonal wet tropics exhibit a channel-withi n-a-channel geometry. Evidence suggests that rare, extremely high rainfall events form the mega-channel within a valley. The mega-channel, or a portion of it, also conveys the wet season flows, but is not necessarily formed or maintained by these. A dr y-season channel cuts into the mega-channel, formed under locally varying degrees of alluvial and bedrock control. The mega-channel is probably not a regime syst em, getting reset every so often by rare storms, while the dry season channel is likely to be under sufficient alluvial control to be in-regime with its watersheds routine delivery of water and sediment. This dual channel concept for the s easonal tropics extends beyond fluvial geomorphology into ecological-based stream classification, further enhancing its utility. Ecologists now recognize one key differenc e between temperate st reams and those of the seasonal tropics is that tropical stream flora and fauna are more closely adapted to seasonal flood pulses. A heavily vegetated outer channel (part of the mega-channel) receives a wet-season flood pulse that is sustained for months, then the water levels retreat during the dry season (sometimes dropping more than 40 feet in elevation) where flow is confined to a much smaller interior channel. The seasonal flood pulse, coupled with the dual channel struct ure is a major force of nature with some tropical tree species so in tune with it that their seeds only germinate after dispersal through the guts of fishes which are adapted to eat their s eeds. The trees only drop seeds when the wet season channel is flooded and the fish are likely to be present.
184 Approaches not presuming applicability of regime theory require process-based classification with knowledge of the system at more than one spatia l dimension. They may also require recognition of the temporal history and trajectory of the system if it is not in a period of relative stasis since t he last threshold-shifting pulsed disturbance. Some literature has emerged openly questioning the regimes that are assumed even in temperate humid climates. Gi ven the pervasive degree of logging, farming, grazing, mining, and development one ma y prefer to use classifica tions that are strengthened by investigations into the processes behind channel dimension as opposed to simple measurement of seemingly associated forms. This outlook is often referred to as a classification of natural kinds or process-based classification. One of the best-described and oft-cited examples of such a process-based classification is that of Montgomery and Buffington (1997). They classified streams in mountainous terrain of the Pacific Northwes t of the United States. They found some cause to invoke regime theory for that setti ng, but could not find cause to simply adopt shape-based reach-scale classifications such as that of Rosgen. They coupled reach level processes to reach shapes and also found justification to link these to hillslope processes, valley shapes, vegetation, and woody debris to achieve a useful classification system. Montgomery and Buffington (1997) based t heir classification on the differing relationships between sediment transport capacity and sediment supply along the channel network, which in mountainous regions typicall y leads to a graded profile exhibiting steeper slopes at the highest el evations and more gentle slopes at lower elevations. The differences also manifest themselves with rather distinct segregation
185 among stream classes in their associati ons between channel slope and grain size relative to channel depth, between dr ainage area and bankfull shear stress, and between channel slope and drainage area. Convergence of form can exist among functionally differing streams types in this type of setting, perhaps rendering shapebased classification insufficiently diagnostic. Fluvial geomorphologists and st ream ecologists working in Australia have devised River Styles concepts using a hierarchy of scale starting with t he catchment and its associated valley settings based on their degree of confinement and then incorporating distinctions related to different process-fo rm associations within the riparian corridor. After determining the position in the drainage network and the type of valley confinement, which in Australia are generally associated with the degree of floodplain alluviation, the delineative cr iteria then segregate the river styles based on hierarchical combinations of geomorphic units located within the valley, including the valley bed materials, channel planform type, channel bedforms, and floodplain alluvial forms present (Brierley and Fryirs, 2000). Which set of riparian delineators is utilized is nested within the valley confinement class. This hierarchical classification approach was developed to improve underst anding of processes and form associations and to describe streams more holistically as latera lly and longitudinally organized floodscapes, as opposed to merely linear channel syst ems, to guide better management decisions regarding the protection and rest oration of Australian riparian corridors. A total of 18 river styles were proposed. Erskine et al (2005) adopted a similar approach for Australias tropical rivers, originally identifying ni ne river types. Saynor et al (2008) later expanded this to 12
186 classes including certain fluvial forms wit h discontinuous channels. They called for additional research concerning two of the par tially channelized systems to first make distinctions among various chains-of-ponds, which included a diverse array of spatially extensive in-line wetlands down to large in-l ine pools that remain wet well into the dry season long after the river links have ceased flowing. Second, they encouraged further exploration of conditions leading to non-channelized valley floor s associated with seepage percolines, alluvial fans, and hillslope hollows. The authors also described floodouts as channel discontin uities derived from differential bedload deposits and lakes, swamps, and billabongs as includ ing backflow bill abongs and channel billabongs which seem to be similar to deep in-line sloughs us ing North American terminology. This classification is important as it was the only classification system encountered for streams that explicitly re cognized discontinuities in the channelized drainage network and some of the forms described appear to have Florida analogues. Streams are very much place-based ecosystems, and those in settings not particularly consistent with regime t heory will warrant unique, rather than generic approaches to classification. Conversely, some generic classification approaches appear to be well conceived, broadly applicable and quite useful to stream managers in a variety of settings. It woul d be foolhardy to misapply a generic classification to an inappropriate setting and it would be a waste of resources to derive new classification approaches for each area where previously developed broad or generic approaches apply. Which of these two approaches is warranted for Florida, especially in the states non-continental watersheds?
187 Florida Fluvial Geomorpholog y and Stream Classification Goodwin (1999) recommends that fluvial clas sifications be based on natural kinds of streams as opposed to nominal kinds. Natural kind classes are based on a desire to understand complex ph enomena and are ideally based on the relationships between processes and form. Nominal kind cl assifications are based on very specific purpose or convenience and do not necessarily relate to natural laws. The only published fluvial classifications for Florida a ppear to be closer to nominal rather than natural kinds. The purpose of this proposed re search is to move closer to a natural kinds classification, while retaining the pr actical advantages of a nominal (useful) system. Although not technically a classificati on, some workers have derived stream regions in the state. This could be important, because regime theory relies on correct delineation of a region. T he Florida Department of Environmental Protection defined three stream regions outside of the Ever glades/South Florida region, based on an extensive database of macroinvertebrat e species and related metrics (Barbour et al 1996). The purpose of their work was to dev elop biological criteria as a means of understanding stream water qualit y and for defining the ecological health or degree of ecological integrity or impairment of a stream. The USGS delineated three stream regions in the state ou tside of the Everglades based on flood-flow regressions relating annual peak flows with various return intervals between 2 and 100 years to basin characterist ics including basin size, lake area, and basin relief (Bridges, 1982). These regions were empirically derived to establish a basis for providing a parsimonious set of flood-prediction regression equations for ungaged stream segments throughout the state. The regression differences are likely due to the
188 states north to south climactic gr adient superimposed on areas with broad physiographic differences. These regressions have been refined and additional subregions have been mapped in west-central Flor ida, one of the st ates most abundant stream regions (Hammett and DelCharco, 2005). The sub-regions, while also empirically derived, correspond reasonab ly well to Whites physiographies. Kelly (2004) examined the daily median fl ow records of Florida streams with longterm gage records and noted that the seasonal flow patterns differ rather distinctly across the state. He ident ified three geographic stream regions based largely on the relative influence of continental versus tropical weather patterns and the associated seasonal distribution of fl ow. Panhandle streams, infl uenced heavily by continental weather patterns, receive much rainfall from winter and spring frontal storms resulting in a pulse of increased flow in the winter and spring. Fronts push south less effectively down the peninsula while the humid sub-trop ical climate provides increased summer convective storms. Summer and fall tropical st orms provide ample rain as well on the peninsula. These factors combine to create a distinct flow pulse during the summer-fall wet season. This pattern is generally more pronounced as one progresses south. Therefore, a transitional ar ea exists with streams exhibiting bimodal wet seasons between the panhandle in an area roughly between Tallahassee in the panhandle and peninsular Florida north of Gainesville. An examination of Kellys data also suggests differences in wet season unit flow (stream discharge per basin area) among the hy drologic regions. This is probably not only related to climate, but to basin soils and relief. In fact, Kelly (2004) also notes that streams with substantial groundw ater inputs from springs and seeps have very limited
189 seasonal pulses compared to streams receiving most of their water from overland flow (runoff). This means that str eam hydrology in Florida is ve ry much a function of regional climate and of geomorphology. The ques tion remains, Do these fundamental differences in hydrology translate to differences in fluvial fo rm in Florida streams, and if so, how much and in what manner? Some examination of Florida fluvial geomorphology has occurred. Gross (1987) described two shape-based classes founded on her measurements of reach scale channel and floodplain cross-sections of palustr ine streams in peninsular Florida. She described one type as narrow channels deeply in cised in small floodplains and the other as wide-shallow channels meandering through broad floodp lains. Tighe (1988) described selected geomorphic characteristics of Florida drainage net works at the basin scale, but made no attempt to classify streams or map stre am regions based on geographic differences. Metcalf (2009) applied Rosgens shape-bas ed classification to streams largely confined to extreme north Florida and the panhandle, identifying two major physical classes of streams (C5broad and shallo w versus E5deep and narrow). Distinct regional differences were noted with panhandle streams exhibiting la rger channel crosssections and higher bankfull flow versus basin size when compared to those of northcentral Florida and south-centra l Georgia. This is not surprising given that the panhandle averages about 10 more inches of ra in per year than nor th-central Florida. Blanton (2008) measured bank full channel dimensions in blackwater streams on peninsular Florida as part of this Dissert ations project and comp ared regressions of bankfull channel dimension versus drainage area for the northern and southern half of
190 the study area. She found that bankfull dimension was not sensit ive to latitude within the peninsula. This suggests that the climactic variation of the peninsula is not significant enough to do more or less work on maintain ing open channel dimensions that vary more than the combined other sources of vari ation in channel size. Peninsular Florida streams have regional curves distinctly di fferent from the continentally influenced regions of Florida measured by Metcalf (2009). However, work on the peninsula has been c onsistent with Metcalfs inventory of streams dominated by Rosgen C5 and E5 cla sses. Kiefer and Durbin (2004) determined that all 14 headwater st reams they measured in north-weste rn Hardee County classified as Rosgen C5 and E5 types. Kiefer and Moss a (2004) noted statistically significant differences in valley slope for two Rosgen channel shape types (C5 versus E5) of small headwater streams in we st-central Florida. Streams with cross-sect ions of low width-todepth ratios occurred in steeper valleys th an those with high width/depth ratios. Anecdotal evidence suggests that the occu rrence of sloughs and strands (very broad, shallow streams with largely or ganic sediments and almost fully vegetated beds) is also related to valley slope, with these systems occ upying valleys with the lowest gradients. Valley slope appears to be associated with stream channel shape in Florida. The low topographic gradient of many Florida valleys, coupled with high water tables and numerous wet depressions and lake s sometimes means that the receiving waterbody establishes seasonally variable ba ckwater or embayment effects that change the effective base level of t he stream outlet, keeping it high and shifting it upstream during the wet season when most flow is ava ilable to work on the stream. This effect
191 was rather well-documented as occurring on the pre-channelized Kissimmee River as a result of interactions between the river and Lake Okeechobee (Warne et al ., 2000). Vegetation also probably exerts signific ant confinement on channel cross-section morphology and planform patterns in Florid a compared to other regions due to low relief, mild humid climate, and nearly yea r-round growing season. For example, the Ocklawaha River did not c onform to normal planfo rm associations and patterns established by Williams (1986) for more t han 400 temperate climat e alluvial streams (Inter-Fluve, 1997). This was attributed to substantial vegetative controls exerted by the trees along its bank and in its floodplain. Many Florida headwater streams appear to take rather random walks through their heavily canopied valleys, exhi biting little of the predictable planform and profile periodicities found in regions without nearly continuous growing seasons. Other researchers have described vegetation-im posed pool-riffle and planform morphologies in headwater streams among a variety of climates that disrupt or trump alluvial controls, but this is less commonly reported for ri vers (Montgomery and Buffington, 1997; McCarthy et al ., 1992). Beck (1965) and Kelly (2004) suggest classifi cations that also distinguish between streams dominated by groundwater versus surf ace water inputs. Florida has among the worlds greatest occurrences of streams f ed mainly by artesian springs (vents that discharge flow to the land surface from a confined aquifer) (Meinzer, 1927). No systematic comparisons are curr ently available between palus trine (runoff) and artesian (spring run) stream morphol ogies or potential process-a ssociations in Florida. Comparisons have been made in spring runs and runoff streams on volcanic regions of the Pacific Northwest, noting substantia l differences in channel and floodplain
192 morphology, soils, sediment transport capac ities, large woody debris, and vegetation between these two basic types of stream valleys in that region (Whiting and Moog, 2001; Whiting and Stamm, 1995). Sapping (or piping) has also been sugges ted to be an important process for stream network formation in parts of Fl orida, especially in the panhandle (Schumm et al ., 1995). This is a relatively rare form of stream network. S apping is the gradual movement of non-cohesive soils by groundwate r flow. Sapping valle ys appear to form in Florida sites with rather high hydraulic groundwater gradients and deep sand layers. This process can lead to a relatively stra ight valley that abruptly terminates at its upstream end at a steep hillslope shaped like an amphitheatre. A seep feeding the stream channel typically emanates from clos e to the base of the amphitheatre. A seep differs from a spring as it is sourced from the surrounding surficial (unconfined) aquifer versus a confined aquifer. Seep flow is gener ally laminar emerging diffusely through an unconsolidated porous media as opposed to the concentrated turbulent flow of a spring which gushes through a macroporous rock medium. The FNAIs steepheads are a type of sapping stream. Steepheads often create microclimactic conditions which support vegetation unique to their region, incl uding some of the rare st plant species in Florida. Sapping valleys may have been more preval ent in Florida than they are today given that groundwater gradient s are currently suppressed by the higher sea levels of the Holocene compared to the Pleistocene. Sporadic occurrences of sapping streams occur on the peninsula. Examples include Gold Head Branch in Clay County and Hidden Waters Ravine in Lake County. T he highland sand-scrubs and sandhills of the
193 Lake Wales Ridge, the Ocala Ridge, and Br ooksville Ridge and even some localized inclusions of seeps in flatwoods physiography elsewhere in the peninsula, especially in areas where stream valleys cros s terraces (relict marine, la custrine, or floodplain) may also have conditions conducive for sapping or at least exhibit sapping as one of the processes important to thei r channel and valley morphology. Florida has an assemblage of apparent stream types including some unusual fluvial forms, but no one has assessed the boundaries of association between basin and reach scale forms and processes that lead to distinctions between sloughs and alluvial channels, between steepheads and spring runs, between spring runs and alluvial channels, etc. No systematic classificati on of Florida freshwater streams based on principals of fluvial geomorphology exists. This is necessary to remedy because the ex isting nominal classifications of Florida streams largely ignore physics in perhaps the most physically-driven of aquatic ecosystem types, fluvial channels. Furt hermore, the existing physically-based classifications used elsewhere in North Am erica should be used with caution in Florida given that their underlying theory was devel oped in climates and physiographies that differ from seasonally humid sub-tropical, sandy-soil, low-gradient peninsulas on limestone. It is possible that fundamentally different stream types in the state are likely to have convergent shape factors when applying shape-based classification schemes. However, these streams may require consi deration of their unique source of water (groundwater versus runoff), valley shape (s lope and width), position within a basin and basin size, basin soil drainage classificati on (and depth to groundwater), lithology, and
194 other factors to predict their stable c hannel and floodplain morphologies and to be properly managed or restored. If so, a regionally-specific, process-based, and multiscale classification may be warranted and shape-based reach-scale classifications, such as the internationally popular Rosgen technique, may be limited to use in only a subset of Florida stream types. A better classification approach then we currently have is likely to be essential to moving the pr actice of stream restoration and management forward in Florida. Methods Site Inclusion, Fiel d and Deskt op Measures All 56 sites selected by the methods descr ibed in Chapter 1 are included in the classification analysis. Field measures ta ken at the reach scale are summarized in Chapter 1 and Blanton (2008) provides very detailed descriptions. Valley scale metrics were measured as part of a desktop GIS analysis. This analysis used the best available topographic data for each study site location surrounding its reference reach. Data ranged in quality from one-f oot LiDAR-derived contours to five-foot USGS quads. All measurements were made using ESRI ArcGIS 9.3 software. Appendix A provides descriptions of all measured and derived variables. Exploratory Statistics The variables fall into classes based on their derivation including: measured continuous data, dimensionless variables de rived from the raw data by dividing one measured variable by another of the same units of measure, factor variables d erived by dividing two variables of different units of measure (u sually, these were metrics commonly used by fluvial geomorphologists to differentiate shapes independent of scale), and categorical data derived from simp le measurements parsed into classes or
195 from observational data. Some of the ca tegorical data was ordinal and was used in statistical tests requiring numerical as opposed to strictly categorical data. The primary statistical tests were explor atory. Hierarchical cluster analyses (CA) was used to examine how sites grouped on vari ous combinations of these variables. The clusters were made using Wards method to calculate distance measures and agglomerate the sites. All variables were centered by clustering on their z-scores to eliminate the scale effects among va riables with different units. CA was invoked in a systematic approach. First, all sites were clustered based on all 123 non-categorical variables. Then, each site was assigned a group variable based on the first two clusters and each group of si tes was separately clustered on the 123 variable set. This was done because the first split sometimes hides meaningful clusters. Given the results from Chapter 2, which suggest that groupings of stream sites based on three watershed types are useful, s eparate clusters were examined on based on group categories (flatwoods, highlands, and ka rst). Separate factors using PCA were also derived from all 123 variables for each of these three groups. Because one of the major hypotheses of this study is that Florida stream classification may work best if it is based on variables at multiple scales (watershed, valley, reach, and habitat patch ), separate clusterings were produced for all sites based on groups of variables for each scale. S eparate factors were derived using PCA for each of these variable groupings to aid in understanding why sites grouped the way they did. Clusters were also ran on just the 45 dime nsionless variables for all sites and then also for the dimensionless and shape-factor variables (56 total). These two analyses
196 remove the direct effects of scale, but not necessarily its indirect effects. This can lead to more interesting interpretations than just observing that somethi ng clusters as big because it is large. Some shapes and dimensionless ratios are almost undoubtedly correlated with scale variables such as drainage area. Valley slope for example is a well known inverse associate of basin size Comparing clusters derived when scale variables are not directly included with those that are can provide clues concerning the nature of scale effects. The CA dendograms from all assessments are provided in Appendix D. Examination for latent variables wa s performed using PCA to simplify the description of how sites differ concerning the 123 non-categorical variables in the study. PCA was performed on the same combinations of sites and variables used in the suite of CA assessments. For each evaluation, an in itial extraction was made of five factors from the correlation matrix Variable communalities scoring less than 0.4 were winnowed. The analysis was re-run on the re duced variable set with varimax rotation. Coefficients were sorted by size and display of scores less than 0.5 were suppressed to aid in the visual examination of the resu lts. Tabulations from each of the rotated component matrices are included in Appendix E. The results from the various CA groupings and some of their PCA factors were assessed and interpreted to form a concept ual basis for a classification system. The explorations enabled judgment concerning the value of including certain types of variables for Florida stream classification as well as suggesting ways that Florida streams naturally are grouped, at least bas ed on the variables included in the study.
197 PCA and CA calculations were made us ing SPSS 16.0 Graduate Pack statistical software. Results and Discussion A spectrum of watershed sizes and slopes were represented in the study for each physiographic class. Table 4-1 provides the roster of study sites and information on their dominant physiography, drainage area, basin soils, basin wetlands, basin lakes, and local valley longitudinal slope. Florida str eam channels and their valleys also present various combinations of valley and channel form related to their degree of confinement and flood channel dimension. Ta ble 4-2 provides data rela ted to the bankfull channel and Table 4-3 provides information compar ing the flood channel and bankfull channel dimensions for each site. Florida drainage networks can best be described as deranged rather than dendritic. This mean s that the stream c hannels are often interrupted by in-line lakes and wetlands. Table 4-4 provides descriptions of the valley segment configuration for each reference reach. Metrics include the meander belt vegetative community, its form of valley confinement, the types of waterbodies brooked by the stream segment, ratio of the riparian wetlands total width versus t he stream channels m eander belt width, and the number of alluvial floodplain features present. For the purposes of this study, a valley segment was defined as a length of valley between the two waterbody junctions encompassing the reference reach. Keep in mind that a reach is a small-scale detailed survey area, typically 20 times the bankfull width. While it is meant to repr esent typical conditions within a somewhat uniform, but typically much longer valley segment, the rapid and fr equent transitions of
198 valley confinement in many of Floridas str eams complicate claims that a reach survey represents anything than perhaps a subset of the valley conditions within a segment. Clusters of Streams in Tw o Size Classes The initial cluster was perfo rmed using all non-categorica l variables on all sites. This resulted in primary branches clearly re lated to channel flow capacity and drainage basin size. Alexander Spring Run had the biggest and widest channel in the study, (cross-section of about 560 square feet and bankfull width of 250 feet) and one of the largest bankfull discharges (122 cfs). It split off first. T he next two major branches split the sites into large and small capacity systems. The division occurred for watersheds of several square miles in size. Big Capacit y systems ranged from drainage areas of approximately three to more than 300 s quare miles and Small Capacity systems typically drained less than three square miles. The next hierarchy of branches split the Big Capac ity sites into those with the highest capacity floodplains versus those with lower floodplain capacity. Divisions beyond that are largely uninterpretable, including various seemingly jumbled combinations of spring runs and blackwater streams. The Small Capacity branch split into groups that seemed to cluster based primarily on valley slope, with a group of eight sites including the highest slopes in the study splitting off from the res t. After that, no obvious co mmon themes were readily interpretable from the smaller branches in ei ther of the two size capacity groups. In other words, branches splitting at less than five distance units on the rescaled cluster combine line were deemed lar gely uninterpretable or of limit ed utility. These lower-level groupings variably represented quite a wide variety of channel shapes, valley categories, and physiography.
199 The main interpretation of this initial cluste r is that it suggests variables related to stream magnitude such as basin size and ba nkfull discharge are of primary importance. The floodplain capacity, groundwater physi ography, and reach valley slope area also are likely to be essential and primary com ponents of any peninsular Florida stream classification. PCA was conducted to explore potential latent variables. The five factors potentially explained 71.1% of the va riance in all 123 variables. The 1st component accounted for 30.6% of the total variance alone. Measures of channel depth, bankfull discharge, flood channel discharge, alluvial features in the floodplain and in the channel, channel and floodplain stream power, drai nage area, and drainage network magnitude all loaded high on that component. It seems to be a measure of the scale-dependant capacity to deliver powerful flow regime s capable of maintaining deep channels and alluvial floodplains. This component is the B ig, Powerful, and Alluvial Basin variable. The 2nd component accounted for 17.4% of the variance and loaded positively on measures of channel width, wetted perimeter, wid th to depth ratio, radius of curvature, channel cross-section area, percent substr ate as submerged aquatic vegetation (SAV), meander belt width, and distance between bends It appears to be a measure of wide channels with large gradual bends and substantial presence of SAV on the bed that do not correlate with major flood pulses. Such systems generally are spring runs that provide steady flow and usually lack major flood pulses. This component could be called the Wide and Steady Flow variable. The 3rd component explained 8.4% of the variance, loading positively on the percentage of D soils in the watershed, ratio of flood to bankfull power, width ratio of the flood to bankfull channels, valley width at th e flood limits, and percent wetlands in the
200 watershed. It loaded negatively on percent A soils. This component describes an association between watershed soil and wetland conditions sufficient to generate seasonal overbank flood pulses to t he stream corridor. While the 1st component also deals in part with flood pulses it seems to be oriented on the sheer size of the watershed and valley system at thresholds necessary for alluvial work, and this 3rd component is oriented on the qualities of the watershed soils and vegetation that typically support seasonal flood pulses without c onsideration of alluvial work. It could be called the Flatwoods Flood-Pu lse variable because it positively associates with characteristics common in that kind of ecoregion. The 4th component accounted for 7.8% of the overall variance. It was positively associated with longitudinal slopes down the valley and along the stream channel, channel shear stress, overbank and in-c hannel unit power, thalweg depth, and presence of root steps in the channel. This component could be called the Steep Slope variable. The 5th component explained 6.0% of t he variance and had solely to do with the overall width of t he riparian wetland and its relative width compared to the bankfull channel and its meander belt. It is e ssentially a measure of a lack of valley confinement. Systems with related characteri stics were referred to as unconfined streams because geological cont rols on the valley led to a width greater than what is necessary to accommodate the stream meander corridor. Therefore, this component serves as the Geologic Valley Control variable. As hypothesized, it is clearly not su fficient to describe sites based only their limnological characteristics without directly considering scale. The clusters were clearly split based on system scale and the five prin cipal components explai ning 71.1% of the
201 variance appeared to be associated with processe s related to forces sufficient to shape alluvial floodplains, maintain wide channels produce wet season floods, or with physical controls on valley shape (slope and width). Notably, channel shape at the reach scale did not emerge as an important latent variable in this most fundamental phase of the analysis. It may turn out to be an important re fining variable within ce rtain categories of physiography and scale, but it was not the pr imary classifier for peninsular Florida streams. To explore potential cluster masking from init ial effects, the sites were subdivided into two groups based on the first three br anches. Alexander Run split out on its own and was added to the rest of Big Capacity gr oup. That cluster was also checked without inclusion of Alexander, and with the exception of Alexander itself, the same clusters appeared. The rest of the sites were separatel y clustered as the Small Capacity group. The Big Capacity group cluster provided br anching patterns di fferent from the smaller branches of the same sites in the All Sites cluster. The biggest difference is that most of the fine branches in the Big Capacity group (less than five units on the rescaled distance cluster combine) were readily interp retable. Nine interpretable clusters were apparent for the 27 sites included in this group, plus two site s that seemed to be miscellaneous outliers. These two sites, Al exander UT 2 and Blues Creek drain basins on the cusp of large and small thresholds 2.3 and 3.2 square miles respectively. Subgroup 1 consisted of a single site, Alexa nder Spring Run that was a very wide, high capacity spring run without an alluvial fl oodplain and with a low va lley slope. It was the only such site in the study, but other similar streams occur in Florida including Rainbow Spring Run and the Chassohowitzka River, for example. Subgroup 2
202 consisted of the Weeki Wac hee River, the only other 1st Magnitude spring run in the study but one with a deep and sinuous channel. Subgroup 3 consisted of three deeply entrenched channels draining large flatwoods basins that produced routine overb ank floods with sufficient power to create some of the most alluvially complex floodp lains in the study, namely Horse Creek, the Little Manatee River and the Santa Fe River. Subgroup 4 consisted of the two largest highlands drainages in the study, both of which had modest alluvial floodplain features, Blackwater Creek near Cassia and Livings ton Creek. Subgroup 5 consisted of two unconfined channels coursing through wide alluvial cypress bottomlands, Fisheating Creek and Little Haw Creek. Both drained large watersheds. Subgroups 3 through 5 comprised the largest and most powerful stream s in the study, all with significant alluvial controls in their floodplains. Their drainage ar eas ranged from 65.7 to 313 square miles. Subgroup 6 consisted of a miscellaneous a ssortment of mid-si zed streams from both highlands and flatwoods areas, all wit h floodprone valley flats and at least one alluvial floodplain feature. These comp rised the smallest group of streams with recognizable alluvial floodplain controls in the study. The smallest site in this subgroup was Hammock Branch which drained three s quare miles and the largest was Carter Creek draining 36. 0 square miles. Subgroups 7 and 8 consisted of streams which drained watersheds ranging from 20.7 to 50.9 square miles, placing this subgroup generally intermediate in size between most systems in either Subgroup 6 or S ubgroups 3 through 5. All four streams in Subgroups 7 and 8 had valley flats with finely textured organic-rich alluvium. Subgroups 7 and 8 differed mainly in their degree of valley confinement and longitudinal valley
203 slope. Subgroup 7 included two well-adjust ed streams with moderat e slopes, Bowlegs Creek and the South Fork Black Creek. Subgroup 8 consisted of two unconfined streams, Tyson Creek and Rice Creek, in areas where they meandered through very low gradient and wide valley segments. Subgroup 9 consisted of an assortment of perennial streams fed by copious groundwater discharge, none with alluvial floodplai n features. Five of the seven sites in this group were artesian spring runs and t he other two drained highlands landscapes. A potential deficiency of this group is that spring runs which from Chapter 2 we learned have some fundamental differences from the other st ream physiographic settings, especially the flatwoods streams, did not consistently form any independent group. This may be because the flood and bankfu ll flow metrics are a poor substitute for other metrics such as the seasonal flow slope and the partial duration series flood frequencies, that require a long term daily flow record to develop. Neither did highlands and flatwoods streams segregate very well, which was unexpected given their rather systematic differences in sensitivity of allu vial processes with basin area (see Chapter 3). PCA results for this group of Large sites produced five components that cumulatively explained 73. 0% of the variance. The components suggested latent variables representing stream power and depth (20.3%), stream width (19.7%), alluvial floodplain processes (15.2%), valley sl ope and shear stresses (9.1%), and channel roughness or riffle-pool heterogen eity (8.7%). These variables seemed to collectively represent hydraulic processes and associated hydraulic geometry, which is understandable for a collection of mostly perennial mid-order streams. This set of latent
204 variables and clusters failed to make important distinctions related to source of water and its medium of delivery, but did prov ide evidence of the general importance of gradients related to scale of the deliver y system and magnitude of hydraulic forces. The Small Capacity streams when asse ssed without the Big Capacity sites clustered into four groups at about 10 to 20 re scaled distance cluster units. The clusters were not interpretable beyond that. Subgroup 1 consisted a single site, Shiloh Branch, which was a small intermittent channel with hi gh clay content in its banks and clay a few inches below the sand on it s bed. It drained a V-shaped va lley among a landscape of gently rolling hills in a region with Hawt horne formation (clay) outcroppings. The only other site in the study t hat had a similar setting was Bl ues Creek, which clustered independently of all of the other sites in the Large Capacity group. Subgroup 2 consisted of six of the seven root -step sites in the study, plus one site, Jumping Gully, which exhibited sparse root-s teps immediately down stream of the study reach. These sites occupied the steepest valley slopes in the study. Subgroup 3 consisted of the smallest spring runs studi ed plus a small sapping stream, Lowry Lake UT, with copious seepage. Lowry Lake UT has root steps and was the only such site not to be split into Subgroup 2. Subgroup 4 forms a group of 15 sites at a cluster distance of about 16 units that consisted of an uninterpretabl e mix of seepage streams, in termittent runoff sites, and a couple of spring runs of various channel sha pes and valley slopes. The most to be said is that these sites generally consisted of those generic low-order streams that are neither among the smallest spring r uns nor root-step sapping ravines.
205 PCA results for this group of Small sites produced five components that cumulatively explained 67. 7% of the variance. The components suggested latent variables representing channel depth features (19.6%), str eam width (13.5%), seepage potential of the watershed (12.5%), channel uniformity (12.3%), and channel sediment transport capacity (9.9%). These variables seem to collectively represent in-channel hydraulic processes and associated hydraul ic geometry, with one representing the seepage flow delivery system of the watershed. This set of latent variables and clusters failed to distinguish many dissimilar low-order streams, but did rather cleanly delineate steep-sloped sapping streams with root-step morphology and very small artesian spring runs. The drainage area threshold between the fi rst split among all sites into Large and Small clusters was a bit blurred at somew here between three to seven square miles. Large and Small clusters appeared to differ rat her sharply concerning the presence of alluvial floodplain features. Twenty-six of the 29 Large sites had at least one alluvial floodplain feature, while only tw o of 27 Small sites did. The two smallest sites in the Large group were clearly mis-assigned and neither had an alluvial floodplain. The remaining Large site with a non-allu vial floodplain was Grasshopper Slough which drained an 8.7 square mile catchment. This site was unique and warrants some discussion because it consisted of a chain of five in-line sloughs alternating with four deep and sinuous sand-bed channels in quick succession over a valley length of 4.4 miles. The sloughs occurred on more gradual longitudinal valley slopes versus the channel segments. The sloughs immediately upstream and downstream of the study reach were carefully inspected from the ground and had multi-threaded (anastomosing)
206 channels with discontinuous sandy or mucky beds and collections of small bars often with roughly two-inch bands of alternating white sand and muck. In effect, alluviation was occurring extensively in this system in zones located between the single-thread channels. Since the materials were being depos ited in broad flats al ong the valley, it seems that they were not r outinely available for lateral overbank deposition along the steeper channel stream linkages. The steeper segments formed deep hydraulically efficient channels with sand beds that can mainta in continuity of sediment transport, but that had limited material available for over bank work because it was more readily trapped by the sloughs. This is an interesting outcome of a deranged network. Similar arrangements are described for streams in the seasonally wet-dry tropics of Australia and South Africa where they are re ferred to as floodouts (Erskine et al ., 2005). Two Small sites were ascribed with one alluvial floodplain f eature. Wekiva UT drained a small (0.5 square mile) basin with a varied input of runoff and seepage from its watershed. It was unconfined through a very wide and flat valley floor vegetated with cabbage palms and bottomland hardwood species with sandy organic soils. The striking flatness of the valley led to its assignment as a valley flat but it appears this may be erroneous, especially since t he sediments were not dominantly fine-textured, and the system was more likely a colluvial wetland. Jack Creek was the remaining site ascribed as having an alluvial floodplain feature in this group. It drai ned a 2.7 square mile watershed of sandy scrub and some large bay swamps and appeared to have perennial seepage flow. During the study, the system also experienced at least two large spates, one of which completely blew out the culver ted dirt road crossing located about 100 feet downstream of the study reac h. The site had sporadic bankfull benches consisting of
207 sandy-organic lamellae situated between sections of moss-covered biological banks. This site seems to be a transitional one, existing between gentle seepage sites lacking alluvial floodplains and those with more rout ine spate-dominated cont rols that transport and deposit sand in floodplains. Based on the overall cluster divisions and attri butes of alluvial floodplains, it would appear that a scale-dependent threshold for floodplain alluviation occurred at approximately six square miles, with an indefinite range occu rring from about 2.5 to nine square miles. The indeterminate range suggests that the potential for alluviation is not strictly dependent on basin size and can be m oderated by a variety of factors. The cluster and PCA results suggested that these modifiers could include variations in longitudinal valley slope and valley width, and the watersheds capacity for groundwater infiltration versus runoff generation from ra infall. Streams drai ning watersheds ranging from 2.5 to 9 square miles should be carefully examined for these modifiers before assuming their proper alluvial floodplain c ondition. True floodpla in alluviation was absent from all 22 streams studied with wate rsheds less than 2.5 square miles in any peninsular Florida landscape setting, while all 17 non-karst streams draining watersheds in excess of nine square miles included alluvial flood plain features. The spring runs studied rarely had alluvial floodpl ain features, the only exception being the Weeki Wachee River which had built some bankfull benches with alternating sand and organic layers. This may not be a natural condi tion, as for many years the run was fed an artificial sediment load in terms of beach building at the mermaid attraction at the headspring. However, it does point out that areas of la rge spring runs receiving
208 allochthonous sand yields have the capacity to develop at least modest alluvial features in their floodscapes. Clusters of Streams Am ong Phy siographic Settings Sites were split into groups based on their physiography and then separately clustered using all non-categorical variables. Clustering of the 23 si tes in the Flatwoods Group resulted in seven subgroup s, readily interpretable at splits below five distance cluster units. Subgroup 1 included Fis heating and Little Haw Creeks, both with seasonally flashy, very large capacity fl oodscapes with sandy bed shoals in the channel and large, wide alluvial cypress bottomland floodplains with mixed organic and sandy sediments rich in alluvial features. The meander belts were well-adjusted to unconfined versus the valley flat. Subgroup 2 was closel y related, but the streams were more entrenched with higher banks in association with larger valle y slopes for their drainage area. They also occupied extensive flashy alluvial valleys, usually with some cypress trees mixed in with hardwood bottoml and species on topographically complex floodplains rich in alluvial features. Ho wever, their floodplains were cut through otherwise confining upland blu ffs, generally well-adjusted to the meander belt. This group included Horse Creek, the Manatee River, and th e upper Santa Fe River. Subgroups 1 and 2 consisted of high-pow er, large-capacity systems draining watersheds in excess of 65 square miles. Subgroup 3 also included syst ems with large alluvial bottomlands, but these systems were less flashy, less confined than Subgroup 2 and their floodplains were very flat and featureless with finely-textured mucky sediments when compared with Subgroups 1 or 2. Two of the three sites in this subgroup, Rice Creek and Tyson Creek, had bottomlands dominated by cypress trees, while Bowlegs Creek had an emergent
209 marsh floodscape. These streams drained watersheds ranging from 20 to 50 square miles. Subgroups 4 and 5 included sites draining sm aller watersheds than the first three subgroups (5 to 17 square miles), with smaller alluvial meander belts that were variably confined and unconfined along the valley. Subgroup 4 consisted of Cow, Tenmile and Moses Creeks, all of which have sma ll linear backswamps of mixed cypress and hardwoods with lenses of finely textured mucky sediments or sand and muck layers. Subgroup 5 included two sites, Morgan Ho le and Grasshopper Slough that were transitional between alluvial and non-allu vial floodscapes. Grasshopper Slough, as previously discussed, had in-line slough segment s receiving alluvial deposition. Morgan Hole has a flat valley cross-section with an occasional avulsion pool in the floodplain and fairly well-developed natural sandy levees along the banks. This places it barely into the alluvial floodplain category. Subgroup 6 included four lo w-order streams without alluvial floodplains with drainage basins ranging from 0.5 to 3.2 squar e miles. Subgroup 6 included a single site, Blues Creek, that was fundamentally different from the rest of the sites in at least two key respects. It was bordered by high upland bluffs that extend to the bankfull stage on both banks and it was a disappearing stream that discharged into a sinkhole. The stream had cut down to a resistant clay and rock layer and, although it had some sandy alluvium on the bed with point bars, the site had obvious and abundant geologic controls too. Subgroup 7 also included six lo w-order streams with colluvial corridors draining small watersheds ranging from 0. 2 to 2.7 square mile s. Subgroups 6 and 7 were distinguishable based on channel shape (bankfull width-to-depth ratio as defined
210 by Rosgen (1996)). Subgroup 6 W/D ratios ranged from 3.6 to 10.3 compared to Subgroup 7 which ranged from 10.4 to 86.0. Rosgen uses a W/D cut-off of 12 to distinguish his C (wide) versus E (narrow) channel forms. On this basis, all but one of the Subgroup 7 sites classified as Cs and all of the Subgroup 6 sites as Es. The streams partitioned into these two Subgroups occurred across a wide array of valley confinement and associated riparian vegetat ion communities, including uplands and wetlands. PCA results for this group of Flatwoods sites produced four interpretable components that cumulatively explained 65. 5% of the variance. The components suggested latent variables representing channel and floodscape power and alluviation (38.3%), valley confinement (9.7%), dr ainage aspects of flatly-sloped wetland dominated riparian corridors (9 .1%), and drainage aspects of the landscape associated with large lakes (8.3%). These variables se em to collectively represent hydraulic processes, potential for sedi ment transport, and their a ssociation with landscape conditions. The latent variables and clusters sugges ted the dimension of the flow delivery system (watershed) and its capacity to produce flood flows that can transport and deposit alluvium in the floodplai n was the main point of segregation, followed by the valley form with respect to stream entr enchment and lateral confinement. Smaller headwater channels with non-allu vial floodplains clustered separately from those with alluvial features. Colluvial stream systems appeared to furt her segregate based on their channel morphology.
211 None of the streams in the flatwoods group appeared to be erroneously clustered. However, one potential short-comi ng of this clustering reflects the fact that the riparian vegetative metrics in the study are categor ical and therefore were excluded. This resulted in some systems with very diffe rent riparian comm unities being lumped together in Subgroups 6 and 7, the headwater channels. For exam ple, 6 of the 10 small colluvial sites had much if not most of their embankments bor dered by palmetto and other upland species of the flatwoods. Thes e steeply banked, but shallow streams drain depressional wetland systems, providing we t season flow linkages across the upland plain. The other four sites were flanked by colluvial wetlands. At least for ecological purposes, these two types of bank condi tions should probably be distinguished. Clustering of sites restrict ed to those of the Highlan ds Group resulted in three interpretable subgroups of the 21 sites included. These clusters appeared to primarily split into three main groups based primarily on the inverse association of valley slope with basin size. Subgroup 1 included lowgradient streams draining the largest highlands basins, which ranged from 26 to 120 square miles. All six of these sites have at least one alluvial component in thei r floodplain. Subgroup 1 systems reflected different degrees of geologic confinement on their alluvial floodplains with the confined meander belts tending to develop slightly more roughness in the floodplain. Welladjusted and unconfined forms frequently alternated al ong highlands valleys. Subgroup 2 consisted of eight streams with comparatively smaller drainage systems (one to seven square miles) than the first subgroup and with generally steeper valley profiles. Most of these system s received copious, perennial groundwater seepage, but did not appear to exhibit runoff spates sufficient to develop alluvial
212 floodplains although they had sandy shoals and other alluvial bed features. Most were flanked by lateral seepage wetlands of varying widths. Subgroup 2 also included three streams that appeared to receive occasion al wet-season spates. Two of these, Hammock Branch (3.0 square miles) and Jack Creek (2.7 square miles), exhibited some floodscape alluviation. Subgroup 3 consisted of six streams drai ning relatively steep headwater valleys with root-step channel morphology. Watersheds ranged from 0.3 to almost 3.0 square miles. Most of these systems t ended to receive water rather directly from their adjacent uplands or sloped wetlands as well as their headwater bay swamps. The copious lateral drainage supported virtually ubiquitous biol ogical banks and the longitudinal drainage usually commenced from a sudden, amphi theatre-like seepage escarpment in the uplands at the head of the stream. Groundwater sapping is the dominant mechanism that forms and maintains these types of va lleys. One root-step variant, found only at Cypress Slash UT, differed from the others in that it had limited signs of lateral seepage and its root-steps were formed from pal mettos as opposed to the more typical formations from seepage swamp hardwoods (for example, bay trees and dahoon holly). This site sat high on a ridge complex and appeared to receive its water mainly from a small headwater lake ringed by bay sw amp during the wet season only. Subgroup 3 also contained a seventh site that was incongruent with the others, Shiloh Creek, that occurred in a valley sl ope and landscape position similar to that of the root-step systems. Shiloh, however, lacked root-steps and was not flanked by sandy seepage slopes either longitudinally or laterally. In fact, it was flanked by upland soils with a clay sub-layer and had cut to bed clay, with a thin layer of sand up to a few
213 inches thick above the clay. This site may be under some degree of geologic control and the high clay content in the near surf ace soil layers probably precluded sapping effects and groundwater seepage necessa ry to develop root-step morphology. PCA results for these Highlands sites produc ed five components that cumulatively explained 75.0% of the variance. The components suggested latent variables representing floodplain dimension and alluviat ion (30.5%), stream width and associated light-loving habitats (18.2%), channel uniformity (10.6%), runoff producing soils in the watershed (8.4%), and associations of st eep valley slopes and channel hydraulics (7.4%). These variables seemed to collectivel y represent hydraulic processes, potential for sediment transport, and their a ssociation with landscape conditions. Much like their counterparts in the flatw oods, the dimension of the flow delivery system (watershed) and its capacity to produce flood flows that can transport and deposit alluvium in the floodplain appeared to be the main point of segregation, followed by the valley form with respect to longitu dinal slope. Smaller h eadwater channels with non-alluvial floodplains clustered separately from those with alluvial features. The Highlands cluster revealed potential differences among steep-sloped headwater streams with root-step morphol ogy that the cluster with a ll the streams from other physiographic groups failed to illicit. Clust ering appeared to be rather clean, with only two sites out of 21 seemingly misplaced. In addition to the previously mentioned Shiloh Run, Ninemile Creek was a root-step seepage channel that failed to cluster with the other six root-step systems. Its watershed, at six square miles, was twice the size of the next largest root-step channels basin. Perh aps the biggest deficiency of this Highland cluster was that lateral confinement ( and the different vegetation communities
214 associated with higher hillsl opes) alternate frequently and over comparatively short distances in many highlands valleys and the clusters generally failed to distinguish streams on that basis. Clustering of sites restri cted to those of the Kars t Group resulted in four interpretable subgroups of t he 12 sites included. Subgroup 1A included a very wide and shallow 1st magnitude run in a low-gradient va lley with dense meadows of submerged aquatic vegetation (SAV) carpeting the st reambed, represented by a single site Alexander Run. Subgroup 1B also included a single site, the Weeki Wachee River, which was deep with strong current, patchy SAV and a firm sandy bed at the thalweg with detrital floc patches along the channel margins. Alexander Spring Run and the Weeki Wachee River were the only 1st Magnitude runs in the study, providing a dominant (bankfull) discharge of 122 cfs and 164 cfs respectively. Subgroup 2 included three 2nd magnitude runs, Gum Slough, Rock, and Juniper, with deep sandy channel thalwegs of moder ate resistance alternating with shallow patches of SAV meadows offering higher resistance. Light gaps were generally available and the SAV meadows o ften grew on lateral accumula tions of detrital floc near the channel margins. Two sites, Alligat or Run and Cedar Head Run, comprised Subgroup 3. These sites were closed canopied with detrital floc providing the dominant sediment substrate and very limited SAV. Subgroup 4 consisted of the five sm allest runs in the study, of 3rd or 4th magnitude. These sites were fully canopied and all but one completely lacked SAV. They generally had relatively uniform flat, broad, and shallo w sandy beds with steady but gentle flow. One 3rd magnitude run in Subgroup 4, Little Levy Bl ue Run, differed in that it had a peat
215 bed reflecting the fact that the run had cut through a qua si-depressional peat-filled swamp basin. The swamp trees had water stain lines indicating fairly routine drowning of the run by surface waters. This system was generally non-alluvial. None of the spring runs had alluvial floodplains, except for the previously discussed Weeki Wachee River. PCA results for this group of Karst sites produced five components that cumulatively explained 83. 0% of the variance. The components suggested latent variables representing channel width and associated SAV (28.2%), channel depth and related hydraulics (25.2%), potential for loca l allochthonous input of sand to the channel (11.5%), channel bed comple xity and roughness (10.3%), and associations of steep valley slopes, channel hydraulics, and in-stream habitats (7.8%). These variables seem to collectively represent hydraulic proce sses, potential for sedi ment transport, and associations with in-stream habitats. Splitting the Karst systems away from ot her stream physiograph ic categories was quite useful as it revealed several cluste rs masked by the comprehensive inventory of streams. In a common thread with the other physiographies, the spring runs clustered primarily based on the magnitude of their fl ow delivery system. The interactions of channel width and discharge hydraulics, s ediment type, and shade appeared to be the most important considerations for classifying spring runs. Meinzers (1927) spring magnitude categories (1st magnitude greater than 100 cfs, 2nd magnitude between 10 and 100 cfs, 3rd magnitude between 1 and 10 cfs, and 4th magnitude less than 1 cfs) did not appear to be directly repres enting flow thresholds of geomorphic significance in spring runs. The dominant discharge data and cluster analysis from this study suggested approxim ate alternate thresholds of greater
216 association with run geomorphology. For exampl e runs in the largest capacity groups (1A and 1B) had bankfull discharge from 122 to 164 cfs, while the Subgroup 2 sites ranged from 27 to 73 cfs, Subgroup 3 in cluded sites with 7.4 and 11.3 cfs, and Subgroup 4 ranged from 0.4 to 1. 9 cfs. These data cannot be used to set very precise divisions, but it is clear that most would straddle Meinzers. The division between very large and large runs is likely to be somewh ere between 73 and 122 cfs, nominally 100 cfs (plus or minus 20 cfs). The division betwe en large and medium runs is likely to fall somewhere between 11 and 27 cfs, nominally 20 cf s (plus or minus six cfs) which falls well within the 2nd Magnitude range. The division betwe en medium and small runs is likely to occur between 1.9 to 7.4 cfs, nominally five cfs (plus or minus two cfs). Clusters of Streams Based on Variables from Four Scales In the approaches dis cussed to this point, sites were segregated into a series of logical groups and then clustered on all variable s to explore the sensitivity of the types of clusters developed without potential interference from fu ndamentally different sites diluting the analyses. The approach in this se ction differs in that all study sites are simultaneously considered, but logical subs ets of variables are used to determine the clusters. This was done for variables associat ed with four different scales, in declining order; Watershed, Valley, Reach, Patch. Watershed variables offered initial branchi ng that segregated sites into big delivery systems versus other systems. Beyond that, t hese variables failed to consistently segregate sites into their alluvial floodplain c haracteristics, failed to distinguish root-step systems from other headwater streams, and generally lumped and split a wide variety of the small streams in no compelling fashi on. Three Watershed classes were apparent. Subgroup 1 included 12 large scale systems fr om all three physiographies. Subgroup 2
217 included 19 mid-sized to sma ll systems, all from either ka rst or highlands landscapes. Subgroup 3 included 25 mid-sized to small sites, mostly flatwoods systems (16), but also included four root-step systems plus f our other highlands streams, and one spring run. Watershed variables provided important stru cture to classification data, but are by no means complete and they failed to consistently partition streams by their physiographic settings. This hierarchy of data failed to stand alone. PCA results for the Watershed variables produced four components that cumulatively explained 74. 3% of the variance. The components suggested latent variables representing watershed size (31. 2%), watershed groundwater infiltration capacity (21.4%), basin slopes and magnitude of drainage dissection (10.9%), and wetland influence in the landscape (10.8%). These variables seemed to collectively represent common landscape processes impor tant to stream sediment and water budgets. The PCA and the fundamental importance of hydrology and sediment processes suggests that Watershed variables should be included in any Florida stream classification and the CA suggests that they are far from being the only important class of variables. Valley scale variables provided a consist ently interpretable set of nine clusters. The last cluster consisted of Alexander Run. The first multi-site branch split off based on its characteristics related to large, powerfu l flood channels with strong alluvial floodplain features forming Subgroup 1. These valleys were typically in the higher order, downstream portions of the drainage network. All nine sites in this subgroup were either unconfined or well-adjusted wit hin broad wetland floodscapes. Subgroup 2 consisted of
218 two large, unconfined spring runs (Gum Slough and Juniper Run) within very wide wetlands (without alluvial floodplains). Subgroup 3 was comprised entirely of midorder channels with alluvial floodplains and unconfined meanders includ ing Bowlegs Creek, South Fork of Black Creek and Tenmile Creek. Subgroup 4 consisted entirely of eight mid-order channels, seven with well-adjusted meanders in alluvial floodplai ns. This suggests confinement categories should be considered as a fundam entally important classifying variable for mid-order stream valleys. This makes sense because we ll-adjusted alluvial channels imply a high level of fluvial work was necessary to form and maintain the valley flat, while in unconfined systems less such work was required by the fluvial system to structure the valley floor. Subgroup 5 consisted of four spring runs with little in common among their valley form other than being non-alluvial. Subgroup 6 properly captured al l six groundwaterdependant root-step systems located in seepage ravines, plus one spring run in a similar ravine, Forest Spring Run. Forest Run had a single pronounced root step about 200 feet upstream of the study reach in an unusually steep part of t he valley. The study reach did not have any such features as it was located in a less steeply sloped part of the valley. Subgroup 7 consisted of two stream gullies with high clay content in their bed and banks, Shiloh Run and Blues Creek. Neither had a floodplain. Twenty low-order sites comprised Subgroup 8, only one of which (J ack Creek) had any alluvial floodplain features. As previously mentioned, Jack Cree k was barely alluvial in that regard. A variety of confinement classes were repr esented by the 19 colluvial systems. This
219 suggests that valley confinement should be view ed as a modifier, ra ther than a primary classifier for low-order streams. PCA results for the Valley variables produc ed five components that cumulatively explained 70.1% of the variance. The components suggested latent variables representing floodscape flow and power and it s alluviation potentia l (20.9%), valley dimension and its geologically-i nfluenced complexity (19.8% ), degree of dominance by wetlands in the riparian zone (13.3%), va lley slope and related floodscape hydraulics (8.6%), and degree of valley confinement (7.5%). These variables seemed to represent key characteristics at the interface betw een stream valley bottoms and their hillslopes very well. Dimension and form associated with alluviation appeared to be wellrepresented too. The PCA and CA results imply that the valley variables offer a lot of useful information for classifying str eams. However, valley scale variables sometimes failed to distinguish spring runs from non-artesian systems and failed to satisfactorily distinguish sites within a large group of 20 loworder streams beyond recognizing their fundamentally colluvial valley slopes. Reach scale variables produced seven in terpretable subgroups. The clusters formed on major branches dependant mainly on channel size. The large capacity channels branch provided four subgroups. S ubgroup 1 consisted of Alexander Run. Subgroup 2 consisted of the six largest blackw ater streams in the study plus the Weeki Wachee River. All have deep powerful main channels with large cross-sectional areas. Subgroup 3 consisted of six wide channels drai ning mostly mid-sized basins including four spring runs and two high lands streams. Nine streams draining mostly mid-sized
220 basins with comparatively narrow channel dimension comprised Subgroup 4. Three highlands streams and six flatwoods stream s comprised this subgroup. The mid-sized channels seemed to mainly segregate based on channel width, with about 30 feet being the threshold. The small capacity channels branch provided three subgroups. Subgroup 5 included five of the steepest sloped headwater streams, including four root-step systems. Subgroup 6 included four small lowgradient streams with very high width-todepth ratios in excess of 35. Twenty-four lo w-order streams were lumped in Subgroup 7 with generally unremarkable depths, widths, or slopes. The reach scale variables provided a good general framework for segregating sites based on their channel capacity and dim ension. Channel conditions add value for stream classification, but no pattern emerged giving confidence that variables at this scale alone offered a complete picture. Cla ssification schemes relying solely on reach scale variables are apt to miss key consider ations of fluvial process that occur at different hierarchies of scale. Channel condit ion was not fully associated with important conditions occurring in the floodscape or watershed. PCA results for the Reach variables produ ced five components that cumulatively explained 82.8% of the variance. The components suggested latent variables representing stream depth and associated concentrations of bankfull discharge, stream power and velocity (30.8%), channel widt h and its association with bend curvature (28.2%), reach valley slope and shear stress (9.5%), amount of channel complexity (horizontal and vertical channel roughness) (9.1%), and planform geometry (5.2%). These variables seemed to represent key asso ciations in hydraulic geometry quite well.
221 Habitat Patch variables included mostly aquatic features such as pools and substrates deemed important for various assemblages of aquatic fauna (submerged vegetation, rocks, logs, pools, leaf packs, undercut roots, etc.) within the channel. Canopy closure was also included as it can affect in-stream habitat. Pools were divided into three categories; deep (greater than f our feet deep at bankfull condition), medium (two to four feet deep), and shallow (one to two feet). Habitat variable clusters suggested eight Subgroups. Subgroups 1 and 2 had the lowest c anopy densities among the clusters. Subgroup1 consisted of spring runs with deep and medium pools that were also wide enough to reduce canopy cover to less t han 39% and allow for SAV growth. Subgroup 2 consisted of a wide array of small to lar ge blackwater streams with low canopy cover (less than 47%), a dominance of medium pools, and generally high diversity of alluvial bed features (typically four to five). Eight of the largest channels in the st udy comprised Subgroup 3. These sites featured a dominance by deep pools and had abundant alluvial bed features. This subgroup included representatives from a ll three landscape types. A wide range of canopy cover occurred (nine to 88%). Subgroup 4 consisted of a combination of medium sized spring runs and blackwater streams with inte rmediate to dense canopy closure (56% to 94%) and was mainly distinguished from other groups by hav ing the highest large woody debris load (2.5 to 8.8 logs per 100 linear feet of c hannel) among the clusters. Interestingly these sites also had low to modest alluvial bed feat ure counts (zero to three), suggesting that the debris loads were not resulting in high levels of induced bed morphology.
222 Subgroup 5 was comprised of 17 sites with intermediate levels of canopy closure (most typically 65% to 85%). These sites al so had a generally even distribution of pools among shallow, medium, and deep ca tegories. They consistently presented the highest range of root habitats (19% to 63% of the total bed habit at) among groups. All other groups had less than 26% roots. This subgr oup included a highly diverse array of streams ranging from small seepage-fed root-step chan nels to the large, deep and flashy Santa Fe River. Most of these chann els were from well-adjusted or confined valleys, suggesting that confi nement may promote root scour and development of root habitats. Subgroups 6, 7, and 8 may be representing a cline of progressive canopy cover within 16 of the smallest streams in the study. These three subgroups averaged canopy cover of 74%, 85%, and 95% respectively. T he subgroups also showed a potential cline of their average large woody debris loads, perhaps in direct relation to the canopy trend, of 1.6, 3.2, and 4.3 logs per 100 linear feet. The number of alluvial bed features averaged 2.7, 2.7, and 1.2 respectively. S hallow pools dominated within Subgroups 6 and 8, with medium pools dominant in Subgr oup 7. Large woody debris can induce morphologic complexity in the bed, but it r equires interaction with water at sufficiently high velocity to do so. The greatest bed comple xity in this potential cline occurred within the intermediate Subgroup 7. The smallest streams occurred in Subgroup 8, and almost all of them were dominated by gentle groundwater flow regi mes. Therefore, it seems plausible that the optimum combination of wood availability and flow capacity for inducing alluvial bed forms and creating medium pools occurred in the middle subgroup.
223 Habitat patches alone were poor predict ors of channel type. Habitat patch variables were important for segregating spring runs and root-step systems when used in concert with variables from other scale categories. PCA results for the Habitat variables produced five components that cumu latively explained 76.3 % of the variance. The components suggested latent variabl es representing canopy closure and suppression of SAV (21.5%), woody debris and detritus (15.8%), varied bed forms and the presence of deep pools (15. 3%), root habitats and a ssociated pools (12.5%), and simple systems with shallow pool dominance (11.1%). These variables seemed to represent key associations between bank and bed habitat components important to stream fauna. Thresholds of interaction between tree canopy an d light availability in the water column, water scour and pruning of r oot interfaces along the banks and bed, and woody debris loads from the tree canopy to t he stream bed are all ex amples covered by this suite of latent variables. Each hierarchy of scale seemed to offe r something unique to classification and each fell short of providing a sufficient classification alone. One important and consistent thread among all four scale groups of variables is that, in different ways, they sorted sites based on dimension. Sites formed groups related to big, medium, and small dimensionality irrespective of whether it was watershed, valley, reach, or patch variables being used. Of all the sets, valley variables provided the most consistent and complete predictions of stream classes, while reach variables offered the least consistency. Watershed scale clusters were not very interpretable beyond the earliest clusters.
224 Clusters of Streams on Dimensionless Variables Size drove the development of major clus ter groups in all analyses using the entire continuous variable set Because of the impo rtant influence of dimension, it would be interesting to assess metrics where the di rect affects of scale have been removed by using dimensionless variables. Such variables in fluvial geomorphology often describe shapes or forms that in some cases imply pr ocess. For example, one of the key metrics in the Rosgen classification system and other descriptive schemes for open channels is the width to depth ratio (W/D). Narrow and deep channels have low W/D ratios and broad, shallow channels have high W/D ratios This metric does not directly correlate with the size of the channel It is dimensionless. All sites were clustered on the dimens ionless variables, resulting in eight interpretable groupings. Interpretation was aided by examination of PCA results from the same variable set, which produced five components that cumulatively explained 62.9% of the total variance. The components suggested latent variables representing landscape infiltration potential (14.3%), flood fo rces relative to bankfull forces (13.9%), valley slope and associated channel shape factors (11.9%), channel canopy closure and associated bend ratios and aquatic plant distributions (11.5%), and channel roughness factors (11.3%). All of the latent variables seem ed to relate to important processes and process-form associations commonly described in fluvial systems. The Landscape Infiltration variable pos itively loaded on percent A+C soils, percent A soils, percent uplands, basin gradient, and valley hillslope gradient and negatively on percent D soil and percent wetl ands in the watershed (Table 4-5). This clearly reflected the capacity of the catchment to allow for groundwater infiltration versus direct runoff. The positive associ ation with basin and valley grades simply
225 reflects the fact the Floridas sandy xeric uplands that allow for high infiltration rates consist of rolling relict dune complexes. Th is component also loaded positively on a ratio of top-of-bank height to bankfull stage. High numbers on that ratio indicate stream entrenchment or confinement. This implie s that some landscape factors leading to seepage streams can also favor or associate with some forms of stream entrenchment or confinement. Root-step s apping streams are one example. The Relative Flood Forces variable positively loaded on the watershed bifurcation ratio, flood/bankfull discharge ratio, flood/bankfull depth ratio, flood/bank height depth ratio, flood/bankfull power ratio, floodplain/bankfull channel width ratio, and percent pools greater than f our feet deep. It loaded negat ively on the flood/bankfull velocity ratio. The bifurcation ratio is a measure of how finely dissected the watershed is by its stream network. In this study, the highest bifurcation ratios generally, but not universally, occurred in the flatwoods landscapes. Finely dissected landscapes are associated with high runoff pot ential. That high runoff pot ential accentuates flow differences for the wet and dry seasons and it also suggests an overall flashier flow regime. This runoff characteristic leads to more pronounced flood flows for a given volume of rainfall and the fluvial system must be able to accommodate these flood pulses. It does so by building a floodplain. The floodplain serves to dissipate energy during flows, leading to a negative associat ion of basin flashiness with flood/bankfull velocity ratios. The flashiness brings jet pulse s to the channel leading to the formation of deep pools. Systems operati ng under the dominant influence of this latent variable are in direct contrast to those that tend to be buffered by watersheds favoring infiltration which is represented by the Landscape Infiltration variable.
226 The Valley Slope Association variable loaded positively with valley segment slope, reach valley slope, bankfull channel slope, the ratio of maximum/minimum channel depth in the study r each, the mean reach pool/riffl e thalweg depth ratio, the meander belt to channel width ratio, and percent C-soil. The last two associations are hard to interpret and may be random associations but the rest are mo re straightforward to discuss concerning process-form associat ions known to operate in fluvial systems. The component also loaded negatively with the bankfull channel wi dth/depth ratio. Steeply sloped valleys tend to favor channels that downcut ra ther than widen, hence the negative association of this slope-oriented va riable with the W/D ratio. Steeply sloped channels also tend to produce high levels of resistance, without which they would be planed flat by channel grading forces. That resistance was offered by root-steps and woody debris in Florida channels and these features created pronounced vertical roughness on the bed, leading to high pool/riffle depth ratios. The Channel Openness variable is the inverse of the more commonly phrased canopy closure concept. Most streams in humid climates, but by no means all, are lined by trees. Wide channels in forested riparian zones are less fully shaded than narrow ones, permitting more light to penetrate the water surface. This latent variable loaded negatively on percent canopy closure along the stream cent erline and on total closure (which is measured facing not onl y upstream and downstream, but also facing both banks). The variable also loaded positively on the percent aquatic substrate with SAV and on percent substrate with emergent aquatic vegetation. These two forms of aquatic herbaceous plants require ample lig ht and are shaded out by tree canopy. The variable loaded negatively on shallow pool s and positively on the mean radius-of-
227 curvature/channel width ratio (Rc/W). The Rc/W ratio provides a sense of how tight the channel bends are compared to c hannel width. Rc/W ratios of 2 to 3 are considered to be the modal value that is inherently stable in alluvial channels with limited vegetative or geologic controls (Williams, 1986). Florida streams tended to support lower ratios in association with their intense strengthening of the bank with very dense sub-tropical vegetation. The negative associ ation with shallow pools is al so probably an artifact of channel dimension. Channel width is associated with discharge and higher discharge generally is also associated with increased channel depth, so wider streams are simply less likely to have shallow pools. In this case, Channel Openess provides processform associations with channel dimension and pattern setting threshol ds that shift the competitive balance between canopy and in-stream aquatic plants for light. The final latent variable assessed, C hannel Roughness loaded positively with the ratio of maximum/minimum channel cross-section area in the bankfull channel, a similar ratio comparing maximum and minimum bankfull dept hs in the reach, the ratio of mean pool depths versus mean riffle depths in the reach, and the ratio of the maximum to minimum channel widths measured in the reac h. Channels scoring high on this variable are physically complex with high vertical and horizontal roughness. Such roughness appears to be associated with hydraulic inte ractions with large woody debris and live vegetation in the channel and on the banks. When vegetation and debris interact with water forces in this manner the resultant bed and bank forms are said to be induced morphology. With that understanding of the latent variables, better informed discussion of the cluster analysis can proceed. The clusters appear ed to divide primarily based on either
228 basin infiltration capacity or on valley sl ope, with various refinements thereafter concerning channel form, canopy closur e, aquatic vegetation, bend geometry, and channel complexity. Subgroup 1-A consisted of six sites with high percentages of infiltration soils (mean of 72% A+C soils ) (Table 4-6). These sites had the steepest valley slopes of any group, averaging 1.4% and the lowest W/D ratios, averaging 6.6. They also had the roughest channels, aver aging 3.0 on the cross-sectional area minimum/maximum ratio. All six sites had root-step channel morphology and drained small watersheds in the highlands. Subgroup 1-B also had high watershed inf iltration capacity, averaging 75% A+C soils. However, this subgroup had subst antially lower average valley slopes than Subgroup 1-A at 0.2% (a factor of seven times less). The four streams in Subgroup 1-B all consisted of intermediate to large siz ed basins draining the highlands. They all had copious groundwater discharge wit h perennial flow. W/D ratios were high, averaging 26. Canopy closure was generally moderate, averaging 50% and this appeared to allow occasional patches of SAV or emergent vegetation in the channels (less than 10% of the bed). Rc/W ratios were low (mean = 1.1), mainly due to the wide channels. Channel complexity was generally low, with the min-ma x cross-section area ratio averaging 1.9. Subgroup 2-A consisted of five of the six steepest sloped spring runs in the study (mean valley slope = 0.44%). These sites occurred within areas dominated by high infiltration capacity soils (mean = 95% A+C soils). Cano py closure was virtually complete, averaging 95%. SAV and emergent veget ation cover was low, both averaged less than 4%. The mean Rc/W ratio was the lo west among all subgroups at 0.9. These were the smallest spring runs in the study Width to depth ratios were variable, and
229 some of the bends of the more narrow channel s were sometimes so tight that they simply wrapped part way around a single trees root disk along the bank edge. Subgroup 2-B consisted of f our intermediate magnitude spring runs. These sites averaged valley slopes of 0.096%, more than four times less than that of subgroup 2-A and W/D ratios were consistently greater than 17 (mean = 27.8). Canopy closure was highly variable among the sites, averagi ng 63% with an associated average of 7.8% SAV and 18.6% emergent vegetation. Subgroup 2-C had valley slopes that were about half those of Subgroup 2-B, averaging 0.043%. W/D ratios were corresp ondingly high, averaging 65.8, the highest among any subgroup. All three sites in this cluster were high magnitude spring runs. The wide channels allowed for sparse canopy (mean = 12%) that allowed for very high SAV (mean = 44.8%) and high em ergent vegetation cover (me an = 12.1%). The 2-B and 2-C spring runs both averaged Rc/W ratios of a bit more than three, making them the highest scoring subgroups on that metric. Subgroup 3-A consisted of six sites t hat averaged the lowest percentage of infiltration prone soils (6%). All were headw ater streams draini ng wetlands in the Flatwoods, except a seeming out lier, Little Levy Spring Run. Valley slopes were variable ranging from 0.1 to almost 0.8% (mean 0.39%). Canopy closure was generally high (mean = 83%) and SAV was completely absent. Em ergent vegetation, especially ferns, lizards tail or other shade-tolerant wetland species, was present (mean bed coverage = 9%). These sites generally exhibited hi gh bed roughness (mean channel cross-section ratio = 2.8).
230 Subgroup 3-B also consisted of sites with a wide range of valley slopes (range 0.11 to 0.88%, mean 0.41%). The 13 sites in this sub-group represented a catchall of large and small systems draining flatwoods and highlands basins. Percent A+C soils were variable, ranging from four to 73% (average = 38% ). Some were headwater streams and others were mid-order. Gullie s, perennial seepage st reams, and one rootstep sapping stream were in this group. These systems seemed to have small W/D ratios (mean = 9.4) and high canopy closur e in common (mean = 74%). They could best be described as blackwater streams that ar e not wide enough to allow significant light penetration to the channel. SAV was completely absent and emergent vegetation only averaged 0.8% bed cover. Subgroup 3-C differed from 3A and 3-C primarily with cons istently more gradual valley slopes, averaging less than 0.1%. Low slopes tended to be associated with wider and shallower channels and these sites acco rdingly averaged W/D of 18.5, although considerable scatter occurred. Canopy closure was quite variable, ranging from three to 91% with a mean of 50%. These were all blackwater streams and SAV was low to absent because the dark water attenuates light (mean SAV bed coverage = 1.3%), but the mix of channel widths in this subgroup apparently allowed for substantial light penetration that emergent plants could ta ke advantage of (mean bed cover = 13.9%). Another distinguishing factor of these sites was that they averaged the greatest flood/bankfull depth ratio of among all the clus ters (mean = 2.2). That suggests that the sites routinely received seasonal flood pulses with overbank water levels more than twice as high above the bed as the bankfull levels. Since this happens in most midorder and larger streams draining flatwoods and highlands streams and such larger
231 streams tended to occupy positions in t he drainage network with gradual valley slopes, it is no surprise that this group of 15 si tes consisted of 11 of the largest drainage systems in the study. However, it also incl uded streams draining watersheds less than a few square miles. The dimensionless variables provided clus ters partially interpretable based on basin physiography, channel shape, and valley slope but did not follow this sequence along all cluster branches. Dimensionless rati os served quite well to expose some potentially important process-form associatio ns and these kinds of variables would form an important component of any classifications system in terested in representing process. However, they served as incomplete predict ors of factors relat ed to system scale, sometimes lumping very small streams wit h very large ones. For example, Subgroup 3C contained Jack Creek and Horse Creek which were spectacularly different kinds of streams that happened to have very similar flood/bankfull depth ratios (2.7 and 2.6 respectively). Jack Creek was predominantly a seepage fed stream which drained a 2.7 square mile basin in the highlands. It wa s eight feet wide and one foot deep at bankfull. Horse Creek drained a 219 square mile flat woods watershed, was 38 feet wide and 4.5 feet deep under bankfull conditions. Jack Creeks bankfull discharge was five cfs and its wet-season flood channel carried 18 cfs, while Horse Creeks bankfull discharge was 230 cfs and its wet-season flood channel carri ed 1,330 cfs. During the wet season, one could stand in Jacks 2.7 feet of water in the channel and expect to live, but woe onto those who stand in Horse Creeks channel duri ng the same time of year, when it would be almost 12 feet deep. So size does matter. Shape factors provided important insight
232 concerning form-to-process considerations fo r stream classification, but convergence of form among different physiographic settings and frequently between streams of vastly different magnitude and alluvial processes means that other kinds of variables must also be considered. Descriptions of Natural Kinds of Flor ida Streams with Delineative Criteria The collective interpretations of the va rious cluster analyses strongly suggested that classification of peninsular Florida streams required variabl es from all four hierarchies of scale. However, perfect and seamless classification cannot be extracted from simply throwing a bunch of variables into a bin and expecting them to stratify on their own. Therefore, the cl assification is based on a strategic progression that starts with the physiographic setting at the waters hed scale, then incorporates drainage area and valley slope in a concerted fashion, optio nally followed by consideration of valley confinement, and completed using reach and pat ch variables as dependant variables in association with the larger hierarchies of watershed and valley scale. This approach not only takes the best of what wa s learned from the exploratory cluster analyses, it also allows for additional profe ssional judgment to be incorporat ed based on categorical data and the some key concepts from the exis ting limnology-based classification schemes for Florida streams. Highlands and flatwoods stream types ar e described starting with their largest riparian systems and moving upgradient. Spri ng runs start with those in the highest discharge magnitude categories. Thresholds were derived from the range of the apparent delineative variables within vari ous reliable and interpretable cluster groupings. This study has identif ied general thresholds of alluvial controls in Florida floodplains, dependant on landscape-derived hydr ology and drainage area. Based on
233 this approach, there appears to be 15 natural ki nds of lowto mid-order, alluvial-bed, single-thread stream system s in peninsular Florida. Most nat ural kinds were identified in the clusters conducted by assessing cases split into logical groups based on physiography and then running the analyse s on all non-categorical variables. Refinements concerning the types of str eams dominated by gr oundwater-biological interactions, such as seepage ravines with r oot-step morphology and larger spring runs became more apparent upon analysis usin g dimensionless variables. Basin size and valley slope appear to be fundamentally important variables for understanding fluvial forms and so me of the associated alluvial processes in Florida streams. They also provide easily measured or observed metrics, often with fairly clear thresholds for delineating classes of str eams. Valley slope versus basin size and bankfull channel W/D ratio versus valley slope provide useful zones of confidence for determining the likely presence or absence of a single-thread alluvial channel in the landscape. Similar associations apply for flatwoods and highlands physiographies, so the cases from these two physiographies were combined to create a blackwater stream confidence chart applicable to str eams in both physiographies (Figure 4-1). Karst systems were statistically different in those associations and so warranted separate considerat ion (Figure 4-2). The basin size at which streams star t to develop persistent and continuous (as opposed to small and patchy) allu vial floodplain features di ffers for all three basin physiographies (Table 4-4). Such features seemed to consistently appear in basins larger than five square miles in the flatw oods, while widespread alluvial floodplain features appear to typically require drai nage areas of at least 20 square miles in
234 highlands basins (Figure 4-3). Smaller loca lized exceptions can occur in both settings and were reliably observed in sites draining as little as 2.5 square m iles. The fact that these floodplain process-form thresholds wo uld differ between these two landscapes is consistent with findings related to statistically significant differences regarding floodplain hydraulics and floodplain dimensions of t hese two physiographies in association with sensitivity of regressions versus drainage ar ea. However, the stated thresholds should be treated as tentative or nominal because no highlands basins between seven and 26 square miles were measured, so the alluvial floodplain threshold for highlands streams could be as low as seven square miles. Li kewise, no flatwoods basins were measured between 3.5 and 5.5 square miles, so the threshold may be as low as 3.5 square miles for such landscape settings. I rrespective of the specific thresholds, the general comparative differences strongly suggest that flatwoods are more prone to develop alluvial floodplains at lower drainage area thresholds than their highlands counterparts, largely in association with higher wet-season flood pulse s and associated capacity to transport sediments. These functional differences appear to be important, so the tentative drainage area thresholds are offer ed for consideration and use until such time as they can be refined. The largest local basin and largest springshed basin in the spring runs studied were 50 and 110 square mile s respectively, but none supported an alluvial floodplain, providing further evidence that as landscapes shift from runoff to groundwater dominated flow delivery regimes, the drainage area thresholds and overall potential for alluvial controls in the floodplain is diminished. Some stream types required further consi deration of valley confinement or channel shape as supplementary measures, but typica lly those variables were not independently
235 diagnostic. Valley confinem ent is highly variable across the landscape and should generally be considered as a modifier to more intrinsic classes of streams based on the three principal classifiers (physiography, valley slope, and drainage area). Valley confinement classes have been found to be of primary importance in some regions, especially Australia where asso ciations of confinement we re identified with in-stream habitats and fisheries utilization (Erskine et al., 2005). We found no analogous formform associations and the fisheries of low-or der Florida streams are largely unstudied. Until evidence emerges that valley confinem ent should be used as a primary classifier in Florida, its use is suggested as a lower-hierarchy modifier instead. Root-steps and biological banks are important in-stream habitat patches helpful to properly characterize some of the smallest headwater streams in highlands areas. Deep pools are associates of certain larger stream types. Dense SAV meadows also associate with particular stream settings and channel widths. However, these diagnostic in-stream habitats should probably be viewed as dependant variables rather than direct classifiers because they are associated with par ticular combinations of more universally determinable factors including basin physiog raphy, valley slope, bankfull discharge, and seasonal flood discharge. Those latter fa ctors can be determined even in altered landscapes, whereas if a stream has been cl eared of its bank ve getation, channelized, or overgrazed, the habitat patches may be de stroyed or unrecognizable. Habitat patch variables may therefore serve better as moni toring items to determi ne stream integrity or restoration success. The first step in this delineation is to determine if the basin is draining a flatwoods, highlands, or karst physiography. The vast ma jority of karst spring runs and their
236 headsprings are inventoried and mapped. Che ck Florida Department of Environmental Protection records if you suspect the site is a spring run. These systems have very clear water with high hardness and neutral to slightly alkaline pH. The water is typically a constant 72 degrees F. Flatwoods and highlands ecoregions can produce darkly stained water during the wet-season, usually soft wit h low to neutral pH. Flatwoods ecoregions generally consist of low-gradient landscapes with numerous wetlands depressions scattered within savanna-like grasslands with patches of variably dense shrubs and palmettos and usually with a scattered-open canopy of pines. Dry prairies are included in this definition. Xeric or scrubby flatwoods are not. For our purposes, a flatwoods is a system that delivers most stream flow by rainfall runoff generating wet-season pulses and extensive shallow flooding in the we tlands and riparian corridors. Highlands ecoregions generally consist of rolling sandy hills dotted with a variety of deep and shallow lakes, seepage wetlands, and some depr essional wetlands. The uplands are very well-drained, resulting in a dominance of dense scrubby schlerophytic vegetation adapted to water stress. Highlands include longleaf pine wiregrass sandhills, sand pine scrub, scrubby flatwoods, xeric oak communi ties and a variety of other xeric upland communities growing on thick sand layers wit h groundwater tables ro utinely several feet below the land surface. Flatwoods hydrology is associated with the poorly drained NRC S Hydrologic Soil Group (HSG) D and not with a dominance of higher infiltration soils categorized as A and C. The delineative threshold occurs when HSG soils A+C collectively sum to less than 45% of the total soil cover in the catchment (Figure 2-8). If that is the case, then proceed to the Streams draining the flatwoods section. If the HSG A+C cover sums to
237 greater than 45%, then the site should be classified in accor dance with the Streams draining the sandy highlands section. Al though an inflection in a seasonal flow flashiness index occurs near 45%, the reality is that st reams draining HSG A+C soil cover close to that inflection (ranging from 40 to 50%) should be carefully considered from the perspectives of both flatwoods and highlands physiographies because they exist in a tension zone or transitional area. Low-order streams are probably less likely to differ much across that tension zones with respect to their floodplain forms and processes than the higher-order systems. Therefore, wh ile prediction of flood-flow magnitude and discharge should be made to guide decisions related to what kind of floodplain restoration is necessary for all streams (NRCS, 2007b), this is especially important for streams draining five to 25 square mile watersheds with 40 to 50% A+C soils because that combination represents the zone of greatest uncertainty concerning the alluvial characterist ics of the floodplains betw een highlands and flatwoods. It is also important to consider al terations to the landscape. The apparent thresholds reported in this study were obser ved from data collected from some of the least altered watersheds remaining in Fl orida. Ditching, farming, and residential development can change the water deliv ery and must be considered. Altered watersheds will likely require some form of modeling to establish if their hydrologic performance has remained within the range of natural conditions. It is just as important to assess common bankfull flows, which in Florida can be equal ed or exceeded frequently and for extended periods (up to 40% of the total re cord in perennial streams) as it is to assess basin response to co mparatively uncommon storm events (with oneyear, two-year and 25-year return interval s). When numerical hydrology studies would
238 be required is a matter of site-specific engineering judgment and is beyond the scope of this research. The further a site differs fr om the conditions observed in this empirical study, the less applicable it becomes and the need for hydrology modeling increases. This research should not be applied to urban or suburban areas with substantial amounts of directly connected impervious area. Urban stream restoration and management simply has too many potent ially confounding factors limiting the application of empiricallyderived data from unpaved and un-sewered lands (Riley, 1998). This research is most applicable for rural sites or special conditions where altered watersheds can be manipulated or re stored to function analogously to natural rural landscapes. A shorthand nomenclature is provided to assist with an efficient understanding and communication of the basis for each stream cl ass. These are basically acronyms that start with the physiography (FW = flatwoods HL = highlands, K = karst), next add the valley type for flatwoods or highlands streams based on its degree of alluvial characteristics (for example, AFS = alluvi al floodscape, CV = colluvial valley, MM = medium magnitude) or on the discharge cl ass for karst systems, and closes with an optional channel modifier (for example, HG = high-gradien t, WC = wide channel). So a FW-AFS-HG channel drains a flatwoods (FW) watershed through a highly alluvial floodscape (AFS) and the channel is a compar atively deep system associated with its high energy gradient (HG). Some useful recurring terms have been adopted with specific definitions for this classification. First, an orig inal term suggested by Thorpe et al (2008) is the floodscape. The floodscape is comprised of the aquatic and terrestrial components of
239 the riparian corridor located at elevations gr eater than the limits of the main channels bankfull threshold and that are connected to the main channel only when it is flowing overbank. The flood channel described in th is dissertation provides one way to conceive of a useful kind of floodscape. Floodscapes can exist across colluvial or alluvial formations. For this study, the alluvial floodscape is a zone lateral to the stream channel with sufficiently routine and powerful flooding an d sedimentation to create alluvial features including anabranches, lev ees, linear backswamps, etc. Thorpe et al (2008) also refer to the bankfu ll channel and all its internal components as the riverscape, which can be used synonymously with bankfull channel or alluvially-act ive open channel. Riverscape provides a convenient alternative terminology, as some riparian sp ecialists refer to all open, active, bankfull channels as rivers with no implication of magnitude. Typically, small channels attributed with place names often include the terms Brook, Creek, Run, Branch, etc. while larger streams are often designated as Rivers. The term riverscape does not imply scale and means any active bankfull channel The riverscape and floodscape form a riverine landscape which for the purposes of this research is used rather synonymously with riparian corridor. Nomographs are provided for each land scape class to aid in riparian system classification (for example, Figure 4-4). It should also be recognized that dashed lines were used to delineate the apparent thresholds among stream classes to symbolize the probabilistic or fuzzy nature of classification. The closer the system is to the line, the more likely it is to have shared or intermedi ate characteristics wit h the adjacent group. Furthermore, systems close to the line may occa sionally be more properly classified in
240 the adjacent group. These classes should be viewed as central tendencies more so than as absolute or rigid thresholds. They were derived to prom ote thought concerning common associations of fluvial form and proce ss in Florida landscapes, not to stop it. Streams draining flatwoods The delineative threshold for applying th is section occurs when HSG soils A+C collectiv ely sum to less than 45% of the total soil cover in the catchment (Figure 2-8). Five of the six main classes proposed for flat woods landscapes sort well along a plot of reach valley slope versus drainage area (Figur e 4-4). While most of the classes sort neatly in association along this gradient, the two colluvial valley stream classes sort based on factors that do not st rongly segregate within the range of these variables under which these stream types exist. The details are discussed under the appropriate category below, but channel shape (W/D) and drainage network positions seem to be associated with these two classes. High-gradient alluvial floodscapes (FW-AFS-HG) FW-AFS-HG systems consist of stream corridors in comparatively high-gr adient floodplains drai ning larger flatwoods basins. Their most notable features includ e a complex array of alluvial floodscape features and deep, strong-flowing blackwater riverscapes with numerous bends and deep pools (Figure 4-5). These systems typi cally drain watersheds in excess of 50 square miles, which evidently are large enou gh to routinely generate discharge volumes sufficient to transport, deposit, and otherwise rework alluvium in the vegetated floodscape. Recalling that flood power is a product of the discharge volume times the water surface slope, the comparatively high gradient of the valley slopes of these systems of at least 0.08% (or 4.2 ft/mile) hel ps to generate a lot of floodscape power. It is important to refer to the nomograph because the aforem entioned thresholds are not
241 as linear as a simple narrative description may imply (Figure 4-4). This is true of all of the riparian system classes among all landscape settings. Riparian corridors with this combinati on of drainage area size and valley slope appear to be associated with mid-order system s crossing old marine terraces or other scarps and their valley flats are typically less than 1,000 feet wi de, flanked by steep upland hillslopes. This combination of fl oodplain confinement and longitudinal slope promotes the deepest routine flood depths among the sites studied, in excess of nine feet. Examples from this study included Ho rse Creek near Arcadia, the Manatee River near Myakka Head, and the Santa Fe River near Gresham. The combination of big floods generated from these mid-order watersheds through comparatively steep valley grades assures t hat the floodscapes of these systems are populated with a diverse array of alluvial fl oodplain features which sort into areas dominated by deposition or scour. As a resul t, the floodplain usually includes at least three of the following featur es; sandy natural levees, vegetated islands on mixed sand and detritus, anabranching channels with sandy or layered sandy and organic beds, linear backswamps with finely-textured organic soils, and oxbow pools/lakes. Most of these features run roughly paral lel with the valleys main axis, so their lateral roughness does little to impede flood flows and consequently Mannings n is almost as low during flood discharge as during bankfull flow (about 0.05). Thalweg flood depths are nearly double the bankfull depths, of ten exceeding nine feet. The riparian vegetation partially sorts in a ssociation with these alluvial features, increasing the plant community diversity wit hin the riparian corridor. Common inclusions are hydric or mesic oak hammocks on isla nds or sandy bank levees, often with
242 palmetto. Cypress, blackgum or popash va riably occupy the linear backswamps. Valley flats can be occupied by virtually any wetl and bottomland species common in Florida. The oxbow lakes sometimes have floatingleaf emergent communities. Anabranches can be vegetated by sedges or other em ergent wetland plants but are usually unvegetated depending on depths and shade. The crest of the bankfull channel is typically entrenched below the valley flat by at least half a foot and is often bordered by a pronounced sandy levee. The riverscape is several feet deep with mobile sandy shoals a nd a dominance of pools at least four feet deep at bankfull conditions. The channels are e fficient with relatively low Mannings n values (approximately 0.05) and low W/D ratios. Depending on the amount of entrenchment below the floodplai n, these riverscapes should typically classify as Rosgen E5, and sometimes B5 channels. T he high stream power, ubiquitous sandy alluvium, and darkly stained waters generally preclude submerged aquatic vegetation. Habitat diversity is good and most systems o ffer an assortment of sandy riffles, deep pools, large woody debris, fine woody debris, leaf packs, and overhanging roots. Emergent aquatic vegetation can occur along the shallow channel margins and on point bars. Most of the channel length is bor dered by wetland bottomland species (often including cypress or water hickory) or by palmettos and oaks on some of the higher sand levees. These valley segments are typically joined by lateral stream junctions at their upstream and downstream ends, providing direct channel c onnections to other streams in the drainage network. Obviously, routine lateral connections between the floodscape and riverscape occur. Fauna benefitting from such combinations of lateral and
243 longitudinal hydraulic connecti ons would almost definitely include a wide variety of freshwater fish species from differing trophic guilds, includi ng various aspects of their life cycles. Therefore, these systems should support diverse fisheries. Where the reach has been directly alter ed, the probable occurrence of an FWAFS-HG could be inferred from watersheds draining flatwoods landscapes within the valley slope-drainage area zone of confidence depicted on Fi gure 4-4. Valley flats less than 1,000 feet wide should be loca ted between sandy bluffs at least several feet higher than the base of the floodplai n. Intact reaches draining watershed-valley slope combinations in this range can be diagnosed or confirmed in the field by observation of bankfull channels with low W/D ratios (tentatively less than 15) and floodscapes with at least three kinds of alluvial floodscape f eatures, creating a rough valley floor. Bankfull delineations in these systems require care as most appear to be variably entrenched at least a half-foot below the valley flat, which is ra rely actually flat itself. This requires use of a bankfull inflection as the channel field in dicator (Blanton, 2008). Banks are typically steep and more than one such inflection may be apparent. The lowest consistent inflection line at or above the tops of point bars is most likely to be correct. To reliably establish a bankfull profile using fi eld indicators at these kinds of sites it is prudent to set and survey lots of pin flags and confirm bankfu ll stage with the lower limits of alluvial deposition at multiple points along the fl oodplain. Due to dense vegetation and rough topography it would be extremely tedious to properly conduct a bankfull assessment in this type of channel without use of a total station. Low-gradient alluvial floodscapes (FW-AFS-LG) FW-AFS-LG systems are similar to FW-AFS-HG systems in terms of dr aining larger flatwoods basins. The main
244 difference is that they consis t of stream corridors in co mparatively low-gradient valleys that are less confined by their flatter upland hillslopes, allowing for shallower flood depths. Their most notable features include a complex array of alluvial floodscape features with non-entrenched and wide meandering blackwater riverscapes with deep pools. These systems typically drain waters heds in excess of 50 square miles which routinely generate discharge volumes sufficient to transport, deposit, and otherwise rework alluvium in the vegetated floodscape. The comparatively low gradient of the valley slopes of these systems of between 0.03% to 0.07% is nevertheless sufficient to generate floodscape power necessary for alluvial sorting, but is gradual enough to promote relatively high W/D riverscapes and to retard channel entrenchment below the valley flat (Figure 4-6). These floodscapes c an occur in wide valleys either under welladjusted or unconfined conditions. Examples from this study included portions of Fisheating Creek near Palmdale and Little Haw Creek near Seville. The big floods generated from these mi d-order watersheds create floodscapes populated with a diverse and rough a rray of alluvial floodplain features which sort into areas dominated by deposition or scour. Friction factors are high in the floodplain (n is typically greater than 0.20) and the flood channel s are much wider (typically more than 1,000 feet) and shallower than those of the FW-AFS-HG systems. The floodplain usually includes at least three of the followi ng features; sandy natural levees, vegetated islands on mixed sand and detritus, anabranching channels with sandy, layered sandy or finely-textured organic beds, linear ba ckswamps with finely-textured organic soils, and oxbow pools/lakes.
245 The riparian vegetation partially sorts in a ssociation with these alluvial features, increasing the plant community diversity wit hin the riparian corridor. Common inclusions are hydric oak and cabbage palm hammocks on islands or sandy bank levees, sometimes with palmetto. Cypress, black gum or popash variably occupy the linear backswamps. Valley flats can be occupied by virtually any wetland bottomland species common in Florida. The oxbow lakes often have floating-leaf emergent communities. Anabranches can be vegetated by sedges or other emergent wetland plants or unvegetated depending on depths and shade. The bankfull channel is usually not entr enched and typically grades smoothly to the valley flat. Natural levees tend to be less pronounced and more sporadic than those of the FW-AFS-HG systems. Riverscapes ar e generally less than three feet deep with mobile sandy shoals and a dominance of pool s at least four feet deep at bankfull conditions. The riverscape channels are much more efficient than the floodscape with relatively low Mannings n values (approxim ately 0.05 or less). The riverscape typically is greater than 50 feet wide with high W/D ratios (typica lly greater than 15). These riverscapes should classify as Rosgen C5s. Submerged aquatic vegetation can occur but will be rare or patchy and is unlikely to cons ist of long-lived species. Habitat diversity is good and most systems offer an assortment of sandy riffles, deep pools, large woody debris, fine woody debris, leaf packs, and overhanging roots. Emergent aquatic vegetation usually occurs along the shallo w channel margins and on some point bars. Most of the channel length is bordered by wetland bottomland species, usually cypress. Some trees extend onto the active channel bed.
246 These low-gradient valley segments typically connect non-riverscape waterbodies such as in-line sloughs or lakes at their upstream and downstream ends, providing direct channel connections to other types of large waterbodies in the drainage network. Even lower gradient valleys in this range of drainage basin size will often take on anastomosing planforms or transition to deep sloughs with organic beds Routine lateral connections between the floodsca pe and riverscape occur. Fauna benefitting from such combinations of lateral and l ongitudinal hydraulic connecti ons would almost definitely include a wide variety of freshwater fish s pecies from differing trophic guilds, including various aspects of their life cycles. Theref ore, these systems should support diverse fisheries. Fauna also benefitting from combi nations of lotic, paralotic, and lentic waterbodies would also benefit tremendously by these systems. Perhaps it is no coincidence that Fisheating Creek is one of the best riverine system s to observe dense aggregations of alligators and colonial wading birds in the state. Where the reach has been directly alte red, the probable occurrence of an FWAFS-LG could be inferred from watersheds dr aining flatwoods landscapes in the valley slope-drainage area zone of confidence delineated on Figure 4-4. Valley flats should be well in excess of 1,000 feet wide, some times approaching 4,000 f eet. Intact reaches draining watershed-valley slope combinatio ns in this range can be diagnosed or confirmed in the field by observation of bankfull channels with high W/D ratios (tentatively greater than 15) that rather seamlessly gr ade into valley flats with floodscapes containing at least three kinds of alluvial floodscape features, creating some roughness on an otherwise flat valley floor. Unlike the FW-AFS-HG systems,
247 bankfull field survey is uncomplicated, rely ing on delineation of the valley flat which occurs at the top-of-bank co incident with the bankfull stage. Wide alluvial valley flats (FW-AF-WF). FW-AF-WF systems drain smaller flatwoods basins than the two FW-AFS classes. Their most notable features include a simple alluvial floodscape with nonentrenched and wide meander ing blackwater riverscapes. These systems typically drain wa tersheds ranging roughly from 20 to 50 square miles which routinely generate di scharge volumes sufficient to transport and deposit fine alluvium in the vegetated flood scape at valley slopes greater than 0.05%. These floodscapes can occur in wide valleys either under well-adjusted or unconfined conditions. Examples from this study included portions of Rice Creek near Springside, Tyson Creek, and Bowlegs Creek near Fort Meade. The big floods generated from these midorder watersheds create comparatively flat floodscapes dominated by depositional features usua lly several hundred feet wide (Figure 4-7). As a result, the floodplain typica lly is dominated by layered sandy or finelytextured organic beds and/or linear backswam ps with finely-textured organic soils. Floodplain friction factors tend to be high (n greater than 0.15), with up to three feet of flooding above the bankfull stage. The riparian vegetation can be virtually any wetland bottomland species common in Florida. Cypress is common, but not ubi quitous. Most sites are densely forested, but natural or unnatural catastrophi c disturbances such as hurricanes or clear-cut logging can lead to areas vegetated by herbaceous emergent wetland plants. The bankfull channel is usually not entrenched and typically grades smoothly to the valley flat. Natural levees tend to be less pronounced and more sporadic than those
248 of the FW-AFS systems. Riverscapes are approximately two to three feet deep with mobile sandy shoals and a mixture of medium and deep pools. The channels are efficient with relatively low Mannings n valu es (approximately 0.07) and high W/D ratios (typically greater than 15). T hese riverscapes should classify as Rosgen C5s. Habitat diversity is good and most syste ms offer an assortment of sandy riffles, deep pools, large woody debris, fine woody debris, l eaf packs, and overhanging roots. Emergent aquatic vegetation is present in light gaps, usually along the shallow channel margins and on some point bars. Most of the channel length is bordered by wetland bottomland species, often cypress. These valley segments connected non-ri verscape and riverscape waterbodies, providing direct channel connections to vari ous types of flowing waterbodies in the drainage network. Lower gradient valleys in th is range of drainage basin size will take on anastomosing planforms or transition to sloughs with organic beds. Routine lateral connections between the floodsca pe and riverscape occur. Fauna benefitting from such combinations of lateral and l ongitudinal hydraulic connecti ons would almost definitely include a wide variety of freshwater fish s pecies from differing trophic guilds, including various aspects of their life cycles. Theref ore, these systems should support diverse fisheries. Where the reach has been directly alter ed, the probable occurrence of an FW-AFWF could be inferred from watersheds draining flatwoods landscapes in association with valley slope-drainage ar ea zone of confidence depict ed on Figure 4-4. Intact reaches draining watershed-valley slope comb inations in this range can be diagnosed or confirmed in the field by observation of bankfull channels with high W/D ratios
249 (tentatively greater than 15) that rather seamlessly gr ade into valley flats with floodscapes containing at least one ki nd of alluvial floodscape feature with predominantly depositional genesis. Bankfull fiel d survey is uncomplicated, relying on delineation of the valley flat which occurs at the top-of-bank coinci dent with the bankfull stage. Compact complex alluvial corridors (FW-AF-CC). FW-AF-CC systems drain smaller flatwoods basins than the FW-AF-WF class. They have alluvial floodplain features, but these may be more sporadica lly formed than those of the previously discussed stream types as this particular cla ss is transitional betwe en those rather fullyformed alluvial floodscapes and systems clear ly dominated by colluvial floodscapes. FW-AF-CC systems include a variety of channel forms and dimensions meandering through partially alluvial valleys. This is a co mplex of small, variably alluvial systems. These systems typically drain watersheds r anging from three to 20 square miles which routinely generate discharge volumes sufficient to transport and deposit fine alluvium in the vegetated floodscape at valley slopes ranging from 0.05% to 0.5%. These floodscapes can occur in moderately wide va lleys, typically less than 500 feet across, either under well-adjusted or unc onfined conditions. Examples from this study included portions of Cow Creek, Moses Creek near Moultrie, Tenmile Creek, Grasshopper Slough, and Morgan Hole Creek (Figure 4-8). The floods generated from these most ly mid-order watersheds create comparatively flat floodscapes dominated by depositional features. As a result, the floodplain usually is dominated by sandy or mixed sandy and organic soils. Floodplain friction factors tend to be low (n less than 0. 10), with about one to tw o feet of flooding
250 above bankfull. The most common alluvial features include small sandy levees and linear backswamps filled with either layered sandy and organic sedi ments or finely textured silty organic sediments. The riparian vegetation can consist of virtually any wetland bottomland species common in Florida. Cypress is common in the backswamps, but not ubiquitous and hardwoods dominate most of the riparian corridor. Most sites are densely forested, but areas with high fire frequencies can have areas vegetated by herbaceous emergent wetland plants and pines. The bankfull channel can be entrenched by up to a few inches, but also often grades smoothly to the valley flat. Natura l levees tend to be less pronounced and more sporadic than those of the FW-AFS systems. Riverscapes are nominally two feet deep with mobile sandy shoals and a typical domin ance of medium pools. The channels are efficient with relatively low Mannings n values (approximately 0.06) and variable W/D ratios. These riverscapes should typically cla ssify as either Rosgen C5 or E5 types. Habitat diversity is good and most systems offe r an assortment of sandy riffles, medium pools, large woody debris, fine woody debris, leaf packs, and overhanging roots. Emergent aquatic vegetation is present in light gaps, usually along the shallow channel margins and on some point bars. Most of the channel length is bordered by wetland bottomland species, often hardwoods. These valley segments connected non-ri verscape and riverscape waterbodies, providing direct channel connections to vari ous types of flowing waterbodies in the drainage network. Lower gradient valleys in th is range of drainage basin size will take on anastomosing planforms or transition to sloughs with organic beds. Routine lateral
251 connections between the floodsca pe and riverscape occur. Fauna benefitting from such combinations of lateral and l ongitudinal hydraulic connecti ons would almost definitely include a wide variety of freshwater fish s pecies from differing trophic guilds, including various aspects of their life cycles. Theref ore, these systems should support diverse fisheries. Where the reach has been directly alter ed, the probable occurrence of an FW-AFCC could be inferred from watersheds draini ng flatwoods landscapes in the appropriate zone of confidence depicted on Figure 4-4. In tact reaches draining watershed-valley slope combinations in this range can be di agnosed or confirmed in the field by observation of alluvial valley flats with wetland floodscapes variably and approximately between 100 and 500 feet wide c ontaining natural levees or backswamps. Bankfull field survey is uncomplicated, relying on delineati on of the valley flat or easily read bank inflections. Narrow channels of colluvial valleys (FW-CV-NC) FW-CV-NC systems are characterized by low W/D channels that drai n small flatwoods basins through colluvial floodscapes (Figure 4-9). Wate rsheds ranging from 0.1 to 3.0 square miles are typically large enough to create alluvial riverscapes, but rarely generate discharge volumes sufficient to transport and deposit fine alluvium in the vegetated floodscape at valley slopes ranging from 0.07% to 2%. These fl oodscapes can occur in a range of valley conditions, but are usually located in 2nd order positions with concave or convex profiles approaching downstream junctions with larger streams. Examples from this study included portions of Coons Bay Branch, Ea st Fork Manatee UT 1, and Wekiva Forest UT.
252 The colluvial floodscapes can consist of either sand or mucky sand soils. Floodscape friction factors tend to be high (n greater than 0.10), with typically less than one foot of flooding above bankfull. The ripari an vegetation usually consists of mesic or hydric hammocks or hardwood swamps. Pines and palmettos often flank most of the narrow unconfined or well-adjusted meander corridor, which is typically less than 100 feet wide and may only be a few feet wide. Mo st sites are densely forested, but areas with high fire frequencies can have areas vegetated by herbaceous plants and pines. The bankfull channel is usually entrenched by up to a few inches, but also can grade smoothly to the colluvial valley flat. Riverscapes are nomina lly 1.5 feet deep with mobile sandy shoals often mixed with detritu s. Pools tend to be a mix of shallow and medium depths. The channels ha ve moderately high Mannings n values (typically close to 0.10) and narrow W/D ratios, typically less than 11. These riverscapes should typically classify as Rosgen E5 types. Habita t diversity varies and mo st systems offer an assortment of sandy riffles, shallow to m edium pools, large woody debris, fine woody debris, leaf packs, and overhanging roots. Spor adic root steps or undercut large trunk roots can occur, but are usually not presen t. Emergent aquatic vegetation is present in light gaps, usually along the shallow channel margins. Most of the channel length is bordered by wetland bottomland species, often hardwoods and occasionally pines, cabbage palms, and palmettos. Cypress is typically absent. These valley segments appear to provi de seasonal connections among a variety of shallow non-riverscape and riverscape wa terbodies upstream, providing direct channel connections to various wetlands types and streams in the upper parts of the drainage network. Downstream connections are more routinel y made with larger
253 streams as opposed to in-line waterbodies. Routine lateral connections between the floodscape and riverscape are modest. Fauna benef itting from such combinations of lateral and longitudinal hydraulic connecti ons should include a variety of small freshwater fish species from differing trophic guilds, includi ng various aspects of their life cycles, but the fisheries of th ese systems have been poorly studied. Where the reach has been directly alter ed, the probable occurrence of an FW-CVNC could be only partially inferred from wa tersheds draining flatwoods landscapes in the valley and drainage area z one of confidence depicted in Figure 4-4. It also is necessary to know if the stream occupi es a convex or concave valley profile approaching a larger tributary. This is im portant because streams draining similar sized watersheds and valley slopes, but that drain headwater wetlands or that connect two wetland depressions with flat valley profiles (instead of crossing convex or concave valleys to join another stream), are inherent ly more likely to be FW-CV-WC channels instead of FW-CV-NC types. Intact FW-CVNC reaches can be diagnosed or confirmed in the field by observation of narrow non-allu vial floodscapes typically much less than 100 wide, drained by tightly meandering ri verscapes with W/D ratios less than 12 (Figure 4-10). Bankfull field survey is unc omplicated, relying on delineation of easily read bank inflections. To more fully underst and the FW-CV-NC channels it is necessary to also understand the somewhat closely aligned FW-CV-WC channel s described next. Wide channels of colluvial valleys (FW-CV-WC) FW-CV-WC systems represent the fluvial forms most likely to be draining headwater wetlands or to be chaining together two wetland depressions along a low-order valley. They are characterized by high W/D channels that drain small flatwoods basins through colluvial
254 floodscapes (Figure 4-11). Watersheds are similar to those of FW-VC-NC systems ranging from 0.1 to 3.0 square miles with va lley slopes ranging from 0.07% to 2%. These floodscapes usually occupy 1st order positions with fl at longitudinal valley profiles. Examples of FW-CVWC systems from this study in cluded portions of Bell UT, Lower Myakka UT 2, Lower Myakka UT 3, East Fork Manatee UT 2, Grassy UT, and Hillsborough UT. While FW-CV-WC and FW-CV-NC riparian corridors cannot be distinguished solely on the basis of their valley slopes and basin areas, they appear to generally occupy different landscape positions along the colluvial valley portions of the watershed. The WC systems typically drain headwater wetlands in generally low gradient valleys exiting the wetland depression or they of ten occur between two wetland depressions in 1st order chains-of-wetlands. In contrast the NC systems are typically further downstream, often picking up additional infl ow from other small tributaries and becoming 2nd order systems. Furthermore, the NC systems tend to occupy convex or concave valleys because they of ten are the streams connecting chains of wetlands to a larger stream across its floodplain inflecti on (Figure 4-12). This means that they terminate at the relatively low base levels of larger magnitude stream channels and can therefore head cut more deeply up from the connecting junction. This head cutting process is evidently greatly resisted as t he valley flattens closer to a depressional headwater or in-line wetland along a 1st order chain. Without such head cutting, the channels ne ar these kinds of wetlands tend to develop a wide and shallow form. It is common to probe shallow woody root disks extending all the way across the channel bed in the WC channels with dense mats of
255 fine roots in the upper two to three inches of sandy sediment (Figure 4-13). Roots extending across the NC channels are unlik ely to exhibit such shallow planar characteristics and generally lack shallow me shes of ubiquitous fine root mats across the entire bed. So in this case, bankfull W/D appears to be a functionally relevant associate of head cutting resistance in low-order colluvial valleys of the flatwoods, that functionally segregates the WC and NC channel types. That resistance appears to lose its dominance further downstream as at least one of three things occur; 1) additional 1st order streams join the network (adding flow volume energy), 2) the channel begins to cross the valley hillslope of a larger channel system and picks up slope (adding momentum energy), or 3) the channel enters the floodscape of a larger stream as it approaches its downstream junc tion and the larger channel systems lower base level allows or promotes headcutting (by allowin g greater sediment export capacity). The colluvial floodscapes of FW-CV-WC systems can consist of either sand or mucky sand soils with hillslopes that may or may not confine the meander belt. Floodscape friction factors tend to be high (n greater than 0.10), with typically less than one foot of flooding above bankfull. The ripari an vegetation usually consists of mesic or hydric hammocks or shallow hardwood swamps (for example, those dominated by laurel oaks). Pines and palmettos often flank most of the narrow meander corridor, which is typically less than 150 feet wide and may only be a few feet wide. Most sites are densely forested, but na rrow sites with high fire fr equencies can be vegetated by herbaceous plants like Fakahatchee grass or sand cordgrass with copses of cabbage palms, slash pines, and often with dense wax myrtle thickets.
256 The bankfull channel can be entrenched by up to a few inches, but also often grades smoothly to the valley flat. Riversc apes are nominally one foot deep or less with well-rooted sandy beds often mixed with detri tus. Pools tend to be shallow (less than two feet deep at bankfull). The channels hav e moderately high Mannings n values (typically close to 0.10) and large W/D ratios, typically greater than 11. These riverscapes should typically classify as Rosgen C5 types. Habitat diversity varies and most systems offer an assortment of sandy riffles, shallow pools, large woody debris, fine woody debris, leaf packs, and shallow r oot exposures. Emergent aquatic vegetation is present in light gaps, usually along the sha llow channel margins. Most of the channel length is bordered by wetland bottomland s pecies, often hardwoods and occasionally pines, cabbage palms, and palmettos. Cypress is typically absent. These valley segments appear to provi de seasonal connections between shallow depressional waterbodies, forming chains-ofwetlands in the upper par ts of the drainage network. Routine lateral connections bet ween the floodscape and riverscape are modest. Vertebrate fauna benefitting from such combinations of lateral and longitudinal hydraulic connections should include a variety of generalist freshwater fish or amphibian species from differing trophic guilds, including various aspects of t heir life cycles, but the aquatic fauna of these systems hav e been poorly studied. It is also possible that the mostly aquatic round-tailed muskrat would use such systems as travel corridors between denning populations in herbaceous wetlands. Where the reach has been directly alter ed, the probable occurrence of an FW-CVWC could be partially inferred from watersh eds draining flatwoods landscapes in the range depicted on Figure 4-4. It is also necessary to ve rify that the valley slope is
257 generally flat or perhaps slightly convex and that it is close to a wetland depression or is an interior link in a chain-of-wetlands. In tact reaches in the appropriate landscape and valley settings can be diagnosed or confirmed in the field by observation of narrow nonalluvial floodscapes typically less than 150 wide, drained by meandering riverscapes with W/D ratios greater than 11 (Figure 4-10). Bankfull field survey is uncomplicated, relying on delineation of the valley flat or easily read bank inflections. Streams draining areas of sandy highlands The delineative threshold for applying th is section occurs when HSG soils A+C collectiv ely sum to greater than 45% of the to tal soil cover in the catchment (Figure 2-8). All three of the main classes proposed for hi ghlands landscapes sorted well along a plot of reach valley slope versus drainage area (Figure 4-14). Sand ridge alluvial floodscapes (HL-AFS) HL-AFS systems drain large highlands watersheds. They have alluvial floodplain features, but these may be more sporadically formed than those of similarly large flatwoods drainage areas. HL-AFS systems include a variety of channel forms and dimensions meand ering through highly varied hillslope morphologies that can r apidly and repeatedly alternate among large unconfined wetland flats, seepage slopes, and welladjusted to partially confining sandy upland bluffs. Of all the str eam systems described from this study, these seem to have the greatest overall longitudinal diversity in their valley hillslope morphology. These systems typically drain watersheds at leas t 15 square miles and probably more than 20, which routinely generate discharge volumes sufficient to transport and deposit fine alluvium in the vegetated floodscape at valley slopes ranging from 0.06% to 0.6%. Examples from this study included portions of Blackwater Creek near Cassia, Carter
258 Creek near Sebring, Catfish Creek near Lake Wales, Livingston Creek near Frostproof, the South Fork of Black Creek, and Tiger Creek near Babson Park (Figure 4-15). The floods generated from these large watersheds create narrow floodplains which can be discontinuous and hi ghly variable in width ranging from 50 to 500 feet wide. The floodplain usually is dominated by muck or mixed sandy and organic soils. Floodplain friction factors tend to be high (mostly greater t han 0.15), with about two to three feet of flooding above bankfull stage. The most common alluvial features include small sandy benches and short backswamps filled with either layered sandy and organic sediments or finely text ured silty organic sediments. The riparian vegetation can consist of virtually any wetland bottomland species common in Florida. Cypress is common in the backswamps, but not ubiquitous and hardwoods dominate some of these riparian co rridors. Most sites are densely forested, but areas with hurricane damage can have areas vegetated by herbaceous emergent wetland plants. The bankfull channel can be entrenched by up to a few inches, but also often grades smoothly to the valley flat where it occurs. Natural levees tend to be sporadic where present. Riverscapes are variable, typica lly ranging from 1.5 to four feet deep with mobile sandy shoals and a typical dom inance of deep pools, with some medium pools too. The channels are efficient with relatively low Mannings n values usually less than 0.06, but patches of s ubmerged aquatic vegetation or dense debris fields are not uncommon, leading to friction factors up to 0.20. These channels tend to be at least 20 feet wide and with W/D ratios gr eater than 12. The riverscapes should typically classify as Rosgen C5 types, with occasional areas as B5s in highly conf ined valleys where the
259 stream has created sporadic or narrow a lluvial benches. Submerged aquatic vegetation was routinely encountered, covering up to 13% of the channel bed, but rarely at the densities found in karst systems of similar width. Habitat diversity is good and most systems offer an assortment of sandy riffl es, large and medium pools, large woody debris, fine woody debris, and overhanging roots. Emergent aquatic vegetation is present in light gaps, usually along the shallow channel margins and on some point bars. Most of the channel length is bor dered by wetland bottomland species, often hardwoods or cypress. These valley segments connected non-ri verscape and riverscape waterbodies, providing direct channel connections to vari ous types of flowing waterbodies in the drainage network. Lakes and stream junctions were the most common. Some of these systems are best characterized as forming chains of lakes. Lateral hillslopes consist of a wide variety of vegetation zones including xeric uplands (scrub or sandhill) that meet the outer channel bends frequently, seepage swamps, or mesic oak hammocks. Routine lateral connections between t he variably dimensioned floodscapes and riverscape occur. Fauna benefitting from such combinations of lateral and longitudinal hydraulic connections would almo st definitely include a wide variety of freshwater fish species from differing trophic guilds, includi ng various aspects of their life cycles. Therefore, these systems s hould support diverse fisherie s. It appears that these riverscapes have the highest in-stream habitat diversity of any of the stream types studied along with the la rger karst streams. Where the reach has been directly altered, the probable occurrence of an HL-AFS system could be inferred from watersheds drai ning highlands landscapes in the zone of
260 confidence depicted on Figure 4-14. Intact reaches draining watershed-valley slope combinations in this range can be diagnosed or confirmed in the field by observation of at least one alluvial valley feature withi n wetland floodscapes that vary between 50 and 500 feet wide. Bankfull field survey can be complicated, relying on delineation of the valley flat or bank inflections and requiring multiple moves to negotiate the variable and very densely vegetated bluffs constricting the narrow floodplain. Baseflow corridors (HL-BFC) HL-BFC systems drain mid-sized highlands watersheds. They generally lack alluvial floo dplain features and these systems include a variety of channel forms and dimensions meandering through highly varied hillslope morphologies that can rapi dly and repeatedly alternate among large unconfined wetland flats, seepage slopes, and well-adjusted to pa rtially confining sandy upland bluffs. These systems can be found draining a very wide range of watersheds ranging from 0.5 to perhaps 20 square miles which rarely generate discharge volumes sufficient to transport and deposit fine alluvium in the vegetated floodscape at valley slopes ranging from 0.1% to 0.7%. Examples from this study included portions of Alexander UT, Bell Creek, Hammock Branch, Jack Creek, Jumping Gully, Snell Creek, and Tiger UT. It should be noted that the study lacked sites bet ween 10 to 20 square miles. All but the largest streams in the HL-AFS category barely exhibited cons istent alluviation in their floodplains with few alluvial features. Th is suggests that the divide between those systems and HL-BFC without consistent floodplain alluviation is likely to be closer to 20 square miles than 10. These systems are intermediate in form between systems which routinely receive alluvial flood pulses and those that practically never receive them. Systems within this
261 category that drain the highest levels of A+ C soils are clearly dom inated by groundwater seepage, usually without any signs of floodplai n alluviation. Examples include Snell Creek and Tiger UT (Figure 4-16). Howeve r, as increasing amounts of D soils and wetlands occur in the watershed, these system s can begin to pick up occasional spates that form sporadic alluvial benches at the bankfull stage. Good examples include Jack Creek and Hammock Branch (Figure 4-17). Syst ems with increasing influence from D soils begin to take on discontinuous floodscape forms akin to those more continuously present in the flatwoods AF -CC systems, while systems more completely dominated by baseflow regimes begin to take on wider channel forms with less alluvial floodplain work more akin to those of medium sized spri ng runs. The HL-BFC systems therefore seem to occupy an interesting transition that intersects important process thresholds concerning flow-regime and sediment transport gradients that exist along the groundwater versus surface water conti nuum and the continuum of basin scale. The floods generated from these intermediat e watersheds tend to course through narrow floodscapes less than 100 feet wide. The floodscape usually is dominated by muck, mucky sand, or mu cky peat, reflecting the steady groundwater seepage and long-term saturation. Floodplain friction factor s tend to be moderate (most around 0.10), with about 0.5 to one foot of flooding above bankfull stage. Alluvial features are generally absent and where present typically c onsist of discontinuous sandy benches or anabranches or backswamps filled with muck or mucky sands. The riparian vegetation can consist of a wide array of wetland or upland communities including pine forests, seepage swamps, mesic and hydric hammocks, and bottomland cypress. Most sites are densely forested.
262 The bankfull channel is usually entrenched by up to a few inches. Riverscapes are shallow, typically less than 1.5 feet deep at ri ffles with mobile sandy shoals and a typical dominance of medium and shallow pools. The channels have relatively high Mannings n values usually around 0.10. These channels tend to be less than 25 feet wide and the W/D ratios vary widely causing the riverscapes to typically classify as Rosgen C5 or E5 types. Submerged aquatic vegetation was absent. Habitat diversity is good and most systems offer an assortment of sandy riffl es, large and medium pools, large woody debris, fine woody debris, leaf packs, and overhanging roots. Emergent aquatic vegetation is present in light gaps, usually along the shallow channel margins. Most of the channel length is bordered by wetland bot tomland species, typically hardwoods or cabbage palm. These valley segments connected non-ri verscape and riverscape waterbodies, providing direct channel connections to vari ous types of flowing waterbodies in the drainage network. Wetland and str eam junctions were the most common. Almost all inline wetlands were forested consisting of seepage slopes, depressional hardwood swamps, and cypress or hardwoods strands. Later al hillslopes consist of a wide variety of vegetation zones including xeric uplands (scrub or sandhill) t hat meet the outer channel bends frequently, seepage swamps, or mesic oak hammocks. Routine to sporadic lateral connections between t he variably dimensioned floodscapes and riverscape occur. Fauna benefitting from t hese systems probably take advantage of the perennial or nearly perennial longitudinal flow connections between waterbodies. Where the reach has been directly altered, the probable occurrence of an HL-BFC system could be inferred from watersheds draining highlands l andscapes within the
263 zone of confidence depicted on Figure 4-14. Intact reac hes draining watershed-valley slope combinations in this range can be di agnosed or confirmed in the field by observation of no more than one discontinuo us alluvial valley feature within wetland floodscapes that vary between a few feet and 100 feet wide. Bankfull field survey relies on delineation of the bank inflections and is pretty straightforward. Root-step channels (HL-RSC) HL-RSC systems drain small highlands watersheds. They lack alluvial floodplain f eatures and are characterized by root-step morphology in valleys often formed by groundwater sapping. These systems typically drain very sandy watersheds ranging from 0. 2 to 10 square miles which rarely generate discharge volumes sufficient to transport and deposit fine alluvium in the vegetated floodscape at valley slopes rangi ng from 0.6% to almost 3.0%. Examples from this study included portions of Cypress Slash UT, Gold Head Branch, Lake-June-In-Winter UT, Lowry Lake UT, Manatee River UT, Ni nemile Creek UT, and Tuscawilla Lake UT (Figure 4-18). These systems practically never receive allu vial spates and as a result their banks are typically constructed by biologically -mediated processes and include moss-covered live root masses growing in peat or peaty mu ck (Figure 4-19). These biological banks can be continuous or sporadic along the flood scape margins. The floodscape usually is dominated by narrow sapping valleys with mu ck, mucky sand, or mucky peat, reflecting the steady groundwater seepage and long-term saturation. Fl oodplain friction factors tend to be high (most around 0. 25), with less than 0.5 feet of flooding above bankfull stage. Alluvial features are absent. The riparian vegetation community usually consists
264 of seepage swamps and most sites are very densely forested thickets of vine-tied bay trees and their associates. The bankfull channel is usually entrenched by up to a few inches. Riverscapes are shallow, typically less than 1.5 feet deep at ri ffles with some mobile sandy shoals mixed with detritus and a typical dominance of medium and shallow pools. The channels have very high Mannings n values usually around 0.25 caused by the pres ence of living root weirs that span the channel. These live weir s organize the channel into a series of irregularly spaced steps and pools. The c hannels tend to be less than 10 feet wide and with narrow W/D ratios usually less than 13. Rosgen C5, E5, B5, a nd G5.types could be encountered depending on how narrow the v-shaped sapping valley is at the surveyed cross-section. Rosgen classes are not particularly enlightening for these systems because they are not formed from alluvial processes, but rather from groundwater sapping. Habitat diversity is good and most systems offer an assortment of large and medium pools, fine woody debris, leaf pa cks, and overhanging roots. Most of the channel length is bordered by seepage species (t ypically sweet bay, with loblolly bays, dahoon, and blackgum) and sometimes palmetto. These valley segments generally connect ed headwater seepage swamps to other kinds of waterbodies, providing seepage condui ts to them. Lakes and or large stream junctions were the most common downstream connections. Lateral hillslopes usually consist of seepage swamps, sometimes with mesic oak hammocks, and usually topped by scrub or sandhill communities. Very lim ited lateral connections occur between the riverscape and floodscape. Fauna benefitti ng from these systems probably take
265 advantage of the perennial or nearly perennial longitudinal flow connections between waterbodies. Where the reach has been directly altered, the probable occurrence of an HL-RSC system could be inferred from watersheds draining highlands l andscapes within the zone of confidence depicted on Figure 4-14. Intact reac hes draining watershed-valley slope combinations in this range can be verified by the presence of root-step morphology. Bankfull field survey relies on de lineation of the bank inflections or root scour lines at the bottom of moss collars and is pretty stra ightforward for these small, steeply sloped sites. Streams draining karst aquifers The delineative threshold for applying this section occurs when the stream receives the majority of its normal annual discharge from an artesi an karst aquifer. Spring runs not only receive water from t he artesian aquifer, but that volume can be supplemented from runoff or phreatic seepag e from local surface watersheds remote from the springshed. This study focused on si tes likely to be dominated by their artesian discharge. Copeland (2003) describes a spring run as a stream whose primary (>50%) source of water is from a spring, or sp ring group. The geomorphic relevance of this definition has not been thoroughly te sted or reported in the ava ilable literature. Most of the streams in this study are likely to be re ceiving at least 65% of their water from springs based on the location and comparative size of their local watersheds versus their springsheds. Four of the five main classes of spring runs can be determined almost solely based on their dominant ( bankfull) discharge (Figure 4-20). The only exception occurs for certain types of the largest runs.
266 Great magnitude, wide spring runs (K-GM-WC) K-GM-WC systems receive copious flow from large springsheds. They lack alluvial floodplain features. These systems include very wide, high capacity ri verscapes that gradually meander through varied hillslope morphologies that can r apidly and repeatedly alternate among large unconfined wetland flats, seepage slopes, and welladjusted to partially confining sandy upland bluffs. These systems typically dr ain springsheds delivering bankfull discharge greater than 40 cfs. The lone example from th is study included part of Alexander Spring Run (Figure 4-21). Similar sites are known fr om other locations such as the Rainbow River and Chassahowitzka River. The active floodscape is generally confined to a narrow band of vertical fluctuation below the top-of-bank, rarely resulting in overbank discharge to the valley floor. Flood stage is typically less than a foot above ban kfull stage and the riverscape is generally entrenched by greater than a foot into its valley floor. Ther efore, this run, like most other runs studied, could essentially be charac terized as a special type of permanently inundated gully. The floodscape is narrow, about 20 feet wider than the riverscape, and the soils located near the surface water interface consist almost entirely of those constructed by biologically-mediated proce sses. These include moss-covered live root masses growing in peat or peaty muck. These biological banks tend to be rather continuous along the floodscape margins, sometimes forming hanging root-shelves protruding up to a few feet over the water su rface. The floodscape usually is bordered by valley sediments with muck, mucky sand, or mucky peat, reflecting the steady groundwater seepage and long-term saturation of the riparian corridor. The riparian vegetation can consist of virtually any we tland bottomland species common in Florida.
267 Cypress is common along the banks, but is not ubiquitous and hardwoods dominate much of these riparian corridors. Most si tes are densely forested hardwood swamps or hydric hammocks. The bankfull channel is entrenched and is best recognized by water pruning that occurs at the vertical inflection of the root s and moss collars along the biological banks. Riverscapes typically average ab out two to three feet deep with mixed sand and shell beds on most of the bed and thick soft organic a ccumulations referred to as detrital floc along the channel margins. The channels are inefficient with high Mannings n values usually around 0.20, largely due to dense co ver of submerged aquatic vegetation and emergent aquatic vegetation. T hese channels tend to be at least 200 feet wide with W/D ratios greater than 60, even exceeding 100. T he riverscapes should typically classify as Rosgen C5 types, with occasional areas as B5 s in portions of the stream valley with high sandhill or scrub bluffs. Submerged aquatic vegetation (SAV) was routinely encountered, covering approximately 60% of the channel bed, largely because canopy closure was close to zero. In addition to the SAV, habitat types include medium pools, large woody debris, fine woody debris and overhanging roots. Emergent aquatic vegetation is present, usually along the shallow channel margins on about 20% of the bed. Most of the channel length is border ed by wetland bottomland species, often hardwoods, cypress, or cabbage palm. These valley segments connect headwater springs to non-riverscape and riverscape waterbodies, providing direct channel connections to various types of flowing waterbodies in the drainage network. Lakes (o r saltwater bays), stream junctions, or other spring clusters were the most common downstream connections. Lateral
268 hillslopes consist of a wide variety of veget ation zones including xe ric uplands (scrub or sandhill) that meet the outer channel bends occasion ally, seepage swamps, or mesic oak hammocks. The fish and mollusk fauna benef itting from such runs have been wellstudied and these systems support dive rse fisheries an d snail fauna. The probable occurrence of a K-GM-WC system can only be partially inferred from spring runs with mean annual discharge in excess of 40 cfs (F igure 4-20). These systems differ from the other type of great magnitude system, K-GM-DC, based largely on geologic controls that are not well under stood from this study. Presently, reaches draining watershed-valley slope combinations in the zone of confidence depicted on the nomograph must be confirmed in the field by observation of riverscapes with W/D ratios greater than 50 and channels at least 100 feet wide. Fortunately, not many of these stream types occur and they are all well-known Bankfull field survey is straightforward and relies on root scour lines at bank inflections. Great magnitude, deep spring runs (K-GM-DC) K-GM-DC systems receive copious flow from large springsheds. They generally lack alluvial floodplain features. These systems include deep, high capacity ri verscapes that gradually meander through varied hillslope morphologies that can r apidly and repeatedly alternate among large unconfined wetland flats, seepage slopes, and welladjusted to partially confining sandy upland bluffs. These systems typically drai n springsheds at least 40 cfs of bankfull discharge. Examples from this study included portions of Rock Spring Run and the Weeki Wachee River (Figure 4-22). Similar si tes are known from other locations such as the lower Silver River and por tions of the Ichetucknee River.
269 The active floodscape is generally confined to a narrow band of vertical fluctuation below the top-of-bank, rarely resulting in overbank discharge to the valley floor, except at sporadic bankfull benches. Flood stage is typically less than a foot above bankfull stage and the riverscape is generally entrenched by greater than a f oot into its valley floor. Therefore, these runs could essentially be characterized as a special type of permanently inundated gully. The floodscape is na rrow, typically less than 20 feet wider than the riverscape except at the sporadic bankfull benches which can be as wide as 100 feet. The soils located near the surface wa ter interface consist almost entirely of moss-covered live root masses growing in peat or peaty muck. These biological banks tend to be rather continuous along the floodscape margins, sometimes forming hanging root-shelves protruding slightly over the water surface. Bankfull benches, where they occur, usually consist of sediments with alternating bands of sand and muck, each a few inches thick. The floodscape usually is bordered by valley sediments with muck or peat, reflecting the steady groundwater seepage and long-term saturation of the riparian corridor. The riparian vegetation can consist of virtually any wetland bottomland species common in Florida. Cypress is common along the banks, but is not ubiquitous and hardwoods dominate much of these riparian corridors. Most sites are densely forested hardwood swamps or hydric hammocks. The bankfull channel is entrenched and is best recognized by water pruning that occurs at the vertical inflection of the r oots and moss collars along the biological banks. Riverscapes typically average about 2.5 to five feet deep with mixed sand and detritus on most of the bed and thick soft organic accumu lations referred to as detrital floc along the channel margins. The c hannels are deep and efficient with Mannings n values
270 usually less than 0.09. These channels tend to be on the order of about 50 feet wide with W/D ratios less than 60. The riverscapes should typically classify as Rosgen C5 types, with occasional areas as E5s or even B5s in portions of the stream valley with high sandhill or scrub bluffs. Pa tches of SAV were routinely encountered, covering 30 to 40% of the channel bed. Canopy closure wa s less than 30%. In addition to the SAV, habitat types include deep pools, large woody debris, fine woody debris, overhanging roots, and sporadic limestone exposures. Emergent aquatic vegetation is sporadically present, usually along the shallow bankfull benc hes where they occur. Typical emergent vegetation includes sawgrass. Most of the channel length is bordered by wetland bottomland species, often hardwoods, cypress, or cabbage palm. These valley segments connect headwater springs to non-riverscape and riverscape waterbodies, providing direct channel connections to various types of flowing waterbodies in the drainage network. Large sw amps, stream junctions, or other spring clusters were the most common downstream connections. Lateral hillslopes consist of a wide variety of vegetation zones including xeric uplands (scrub or sandhill) that meet the outer channel bends occasionally, seepage swam ps, or mesic oak hammocks. The fish and mollusk fauna benefitting from such runs have been well-studied and these systems support diverse fisheries and snail fauna. The probable occurrence of a K-GM-DC syst em could be partially inferred from spring runs with mean annual discharge in exce ss of 40 cfs, but they differ from the other type of great magnitude system, K-GM-WC, based largely on geologic controls that are not well understood from this study. Presently, r eaches draining watershedvalley slope combinations in the range depicted in Figure 420 must be confirmed in the
271 field by observation of riverscapes with W/ D ratios less than 60 and channels typically less than 100 feet wide (usually closer to 50 feet). Fortunately, not many of these stream types occur and they are all well -known and have large areas with apparent geomorphic integrity among local areas impacted by recreation activities, and in the case of the Weeki Wachee and Ichetucknee Rivers, by residentia l frontage. Bankfull field survey is straightforward and relies on root scour lines and/or bank inflections. High magnitude spring runs (K-HM) K-HM systems receive copious flow from their springsheds, but less than the Great Magnitude sites. T hey generally lack alluvial floodplain features. These systems include a mix of deep and shallow, high capacity riverscapes that gradually meander thr ough varied hillslope morphologies that can alternate among large unconfined wetland flats, seepage slopes, and well-adjusted to partially confining sandy upland bluffs. These systems typically drain springsheds delivering 20 to 40 cfs. Examples from th is study included portions of Gum Slough Run and Juniper Springs Run (Figure 4-23). The active floodscape is generally confined to a narrow band of vertical fluctuation below the top-of-bank, rarely resulting in overbank discharge to the valley floor, except at sporadic non-alluvial anabranches. Flood stage is typically less than two feet above bankfull stage and the riverscape is generally entrenched by greater than two feet into its valley floor. Therefore, these runs coul d essentially be characterized as a special type of permanently inundated gu lly. The floodscape is narrow, typically less than 20 feet wider than the riverscape except at the sporadic anabranc hes which can be as wide as 100 feet. The soils located near t he surface water interface consist almost entirely of moss-covered live root masses growing in peat or peaty muck. These
272 biological banks tend to be rather continuous along the floodscape margins. Anabranches, where they occur, usually consist of soft black sapric muck with very high water content. These are treeless areas not co vered by the biologic al banks. If they are vegetated, a variety of emer gent marsh vegetation is pr esent, sometimes including sawgrass. The floodscape usually is border ed by valley sediments with muck or peat, reflecting the steady groundwater seepage and long-term saturation of the riparian corridor. The riparian vegetation can consist of virtually any wetland bottomland species common in Florida. Cypress is common along the banks, but is not ubiquitous and hardwoods dominate much of these riparian co rridors. Most sites are densely forested hardwood swamps or hydric hammocks. Some of these swamps or hammocks can be spectacularly broad, measuring close to a mile wide. The bankfull channel is entrenched and is best recognized by water pruning that occurs at the vertical inflection of the r oots and moss collars along the biological banks. Riverscapes typically average about 1.5 to two feet deep with mixed sand and shell beds on most of the bed and thick soft organic a ccumulations referred to as detrital floc along the channel margins. The channels typically alternate repeatedly between deep and efficient zones with bare beds and shallow zones with denser SAV meadows. Mannings n values are greater than 0.10. These channels are on the order of about 30 to 70 feet wide with W/D ratios from 20 to 50. The riversc apes should typically classify as Rosgen C5 types. Patches of SAV were r outinely encountered, covering 10% to 20% of the channel bed. Canopy closure was less than 50%. In addition to the SAV, habitat types include mostly medium pools with some deep pools, large woody debris, fine woody debris, overhanging roots, some exposed limestone, and leaf packs. Emergent
273 aquatic vegetation is sporadically present, usually along shallow bankfull benches where they occur. Typical em ergent vegetation includes sawg rass. Most of the channel length is bordered by wetland bottomland s pecies, often hardwoods, cypress, or cabbage palm. These channels exist just above the discharge threshold that tends to support runs with substantial amounts of SAV providing a clear functional distinction from systems with slightly lowe r discharge regimes (Figure 4-24). These valley segments can connect headwater springs to non-riverscape and riverscape waterbodies, providing direct channel connections to various types of flowing waterbodies in the drainage network. Other spring clusters were the most common downstream connections for the sites in the study. Lateral hillslopes consist of a wide variety of vegetation zones including xeric uplands (scrub or sandhill) that meet the outer channel bends occasionally, seepage swam ps, or mesic oak hammock. The fish and mollusk fauna benefitting from such runs have been well-studied and these systems support diverse fisheries and snail fauna. The probable occurrence of a K-HM system could be inferred from spring runs within the zone of confidence depicted on Figure 4-20. Where intact, systems within this discharge regime can be confirmed in the field by observation of riverscapes with channels at least 30 feet wide, typically wit h at least 10% of their bed covered by SAV and a dominance of biological ba nks. Bankfull field survey is straightforward and relies on root scour lines and/or bank inflections. Medium magnitude spring runs (K-MM) K-MM systems receive moderate flow from their springsheds. They lack alluvial floodplain features. These systems include closed canopy riverscapes that gradually meander through hillslope morphologies that
274 can consist of large unconfined wetland fl ats, seepage slopes, or well-adjusted to partially confining upland sand or limestone bluffs. These systems typically drain springsheds delivering bankfull discharge ranging from five to 20 cf s. Examples from this study included portions of Alligat or Run and Cedar Head Run (Figure 4-24). The active floodscape is generally confined to a narrow band of vertical fluctuation below the top-of-bank, rarely resulting in overbank discharge to the valley floor. Flood stage is typically less than one foot above bankfull stage and the riverscape is generally entrenched by greater than a foot into its valley floor Therefore, these runs could essentially be characterized as a specia l type of permanently inundated gully. The floodscape is narrow, typically 10 to 40 feet wider than the riverscape. The soils located near the surface water interface routinely consist of moss-covered live root masses growing in peat or peaty muck. These biolog ical banks tend to be less continuous along the floodscape margins than the previously discussed spring run classes, alternating with areas of dense, cohesive sapric muck or mucky sand that lack the peat-filled root disks covered in moss. The floodscape usually is bordered by valley sediments with muck or peat, reflecting the steady groundw ater seepage and long-term saturation of the riparian corridor. The riparian vegetati on can consist of virtually any wetland bottomland species common in Florida. Cypress is uncommon along the banks, and hardwoods dominate much of these riparian corridors. Most sites are densely forested hardwood swamps or hydric hammocks.. The bankfull channel is entrenched and is best recognized by water pruning that occurs at the roots and moss collars along t he biological banks and by an inflection at similar stage in the banks comprised of muck Riverscapes typically average about 1.5
275 to 2.5 feet deep with mi xed detrital floc and shell beds on most of the bed. Mannings n values can vary substantially (from 0.07 to 0.25) depending on the emergent aquatic vegetation and woody debris load in the channel. These c hannels are on the order of about 20 to 40 feet wide with W/D ratios les than 30. The riverscapes should typically classify as Rosgen C5 types. SAV was virtually absent, probably in response to canopy closures greater than 90%. Habitat types in clude medium pool, large woody debris, fine woody debris, overhanging roots, and leaf packs. Emergent aquatic vegetation is present, usually along the channel margins, so metimes in thick beds that comprise up to 40% of the riverscape bed. Typical em ergent vegetation includes shade tolerant wetland species such as lizards tail and nev er-wet. Most of the channel length is bordered by wetland bottomland species, often hardwoods, cypress, or cabbage palm. These channels exist just below the discharge threshold that tends to support runs with substantial amounts of SAV providing a clear functional distinction from systems with slightly higher discharge regimes (Figure 4-24). These valley segments can connect headwater springs to non-riverscape and riverscape waterbodies, providing direct channel connections to various types of flowing waterbodies in the drainage network. Other spring clusters were the most common downstream connections for the sites in the st udy. Lateral hillslopes consist of a variety of vegetation zones including seepage swamps, mesic oak hammocks or xeric uplands. The fish and mollusk fauna of these closed canopy systems lacking SAV is less studied than those of the larger wider runs with SAV. The probable occurrence of a K-MM system could be inferred from spring runs within the zone of confidence depicted on Figure 4-20. Where intact, systems within this
276 discharge regime can be confirmed in the field by observation of riverscapes with channels less than 40 feet wide, typically with less than 1.0% of their bed covered by SAV and a presence of biological banks. Bankfu ll field survey is straightforward and relies on root scour lines and/or bank inflections. Low magnitude spring runs (K-LM) K-LM systems receive low flow from their springsheds. They lack alluvial floodplai n features. These systems include closed canopy riverscapes that steadily trickle through seepage ravines in low-lying hammocks or swamps. These systems typically drai n springsheds providing dominant discharge ranging from 0.2 to five cfs. Examples from this study incl uded portions of Forest Spring Run, Kittridge Spring Run, Morman Branch UT, and Silver Glen UT (Figure 4-26). The active floodscape is generally confined to a narrow band of vertical fluctuation below the top-of-bank, rarely resulting in overbank discharge to the valley floor. Flood stage is typically a few inches above bankfull stage and the riverscape is generally entrenched by greater than a foot into its valley floor. Th e floodscape is narrow, typically less than 30 feet wider than the riverscape and usually le ss than 80 feet wide, most often located at the base of much la rger gradually-sloped seepage ravines. This suggests that most of these sites also receiv e flow input from the surficial aquifer. The soils located near the surface water interface routinely consist of moss-covered live root masses growing in peat or peaty muck. These biological banks tend to be less continuous along the floodscape margins than the previously discussed spring run classes, alternating with areas of dense, cohesive sapric muck or mucky sand that lack the peat-filled root disks covered in moss. The floodscape usually is bordered by valley sediments with muck or peat, reflecting t he steady groundwater seepage and long-term
277 saturation of the riparian corridor. The ripar ian vegetation usually consists of seepage slope hardwoods including bays, dahoon, and anise. The bankfull channel is typically quite s hallow, less than a f oot deep at sandy riffles, and it is best recognized by water pruning that occurs at the roots and moss collars along the biological banks and by an inflection at similar stage on the banks comprised of muck. Riverscape bed materials t end to be either mixed or layered sand and detritus. Mannings n values can vary s ubstantially but are ty pically greater than 0.10. These channels were generally less than 25 feet wide, with some approaching five feet. W/D ratios vary widely (seven to 50) as does the amount of confinement from the seepage ravine slopes leading to a wide arra y of probably rather meaningless Rosgen classifications including C5, E5, B5, G5, and F5 types. SAV was absent, probably in response to canopy closures greater than 90%. Habitat types include shallow pools, large woody debris, fine woody debris, overhangi ng roots, small patches of emergent vegetation, and leaf packs. Most of t he channel length is bordered by wetland hardwoods and cabbage palms. These valley segments can connect headwater springs to non-riverscape and riverscape waterbodies, providing direct channel connections to various types of flowing waterbodies in the drainage network. The fi sh and mollusk fauna of these low-flow closed canopy systems have been little studied. The probable occurrence of a K-LM system could be inferred from spring runs existing within the zone of confidence depi cted on Figure 4-20. Where intact, systems within this discharge regime can be confirmed in the field by observation of riverscapes with channels less than 25 feet wide, less than one foot deep, typi cally without SAV and
278 with at least occasional presence of biol ogical banks. Bankfull field survey is straightforward and relies on root sc our lines and/or bank inflections. Less common streams and unique situations Shiloh Run and Blues Creek are functi onallyconfined and entrenched channels within well-drained rolling landscapes with mix ed sand and clay outcroppings (Figure 427). These systems could be referred to as c lay gullies of colluvial valleys (CV-CG). However, the form may be convergent from di fferent landscape-level processes. In the case of Blues Creek, the system drains alon g 75 feet of relief from an in-line wetlandpond complex to an internally-drained sinkhole 2.7 miles downstream. That amount of raw valley relief was the greatest of any of the 56 sites studied. Blues Creeks entrenchment is probably related to a peri od of pronounced base level lowering at the sink. The system has entrenc hed within its meander and thus has a highly sinuous valley with v-shaped hillslopes. Shiloh Run drains a small headwater swamp across 57 feet of relief to a junction with a larger stream valley about mile downstream. That amount of raw valley relief was second only to that of Blues Creek among the sites studied. Both of these system s appear to intersect mixed sand and clay outcrops. In addition to having some clay associated with the channel bed and hillslopes, these two streams also share share the characteristic that they drain two of the highest overall relief valleys in the study. Little Levy Blue Spring Run created a sinuous channel with well-defined banks through an organic wetland sediment without inorganic alluvium. The channel is within the valley slope-drainage area r egime and has a W/D ratio for its valley slope within the ranges that can support alluvial channels, so the bed is likely to be erosional in its genesis even though no inorganic alluvium was present. The system is also routinely
279 drowned by the swamp it occupies, leading to water stain lines that have little to do with the spring flow. Another site intersec ting a larger wetland bottomland, Hillsborough UT, also had a water-stain line from anot her waterbody (an upper terrace of the floodplain of the Hillsborough River) that was independent of the study reachs flow regime. Hillsborough UT occupies an upland c onfined valley immediately upstream of the area where it enters t he river terrace. So even though the system appears to be unconfined, it probably functions as a confi ned system in a wetland at that location. These two examples show that the interpretation of field indicators of hydrology and geomorphology require care and a diligent look upstream and downs tream of the area of interest to more fully understand site conditions. What is learned from field assessments should be checked against the drainage area-valley slope regressions and other form-form factors associated with the presence or absence of alluvial channels for a give landscape class. Conclusions Using the thresholds and associations obs erved from this study, stream managers can make informed predictions of inherently self-sustaining channel and floodplain dimension and shape usually with little more than reliable knowledge concerning three site-specific variables; 1) the hydrogeologic r egion (or some measure of the capacity for rainfall infiltration versus runoff), 2) the st reams drainage area, and 3) its local valley slope. It is important to under stand the probabilistic nature of empirical process-form and form-form associations in fluvial systems. Na ture provides for si gnificant variability. The aim of this study was to identify re cognizable thresholds and provide guidance for where the important tr ansitions or tension zones are likely to occur. The study has identified several key threshold zones in the data including:
280 Landscape Hydrologic Soil Group conditions where systems shift the balance from runoff controls to groundwater Threshold ranges where systems begin to fo rm alluvial features in the floodplain associated with drainage basin area in different physiographic regions Channel width threshold ranges ne cessary to support submerged aquatic vegetation communities Combined valley slope and landscape char acteristics associated with root-step seepage streams Appropriate drainage area and valley slope combinations fo r channels of different width-to-depth ratios The lower and upper limits of valley slope and drainage area beyond which the occurrence of natural st able streams with sandy beds become very unlikely. While this classification appears to add va lue to our understandi ng of the fluvial forms found in peninsular Florida, it is not offered as the final word. It is hoped that it provides an excellent addition, building upo n and refining the works of earlier Florida limnologists and geomorphologists working with streams in the peninsula, and it is expected to be refined over time. General Benefits of Multi-Scal e, Hierarchical Classification The main benefit of a multi-scale approach is that it helped to delineate the scaledependant limits and conditions of alluvial ve rsus other kinds of stream channel and floodplain c ontrol processes operating in three different physiographic settings in Florida. It overcame issues related to t he convergence of form that sometimes occur using shape-based classification, adding proper context for the application of Rosgen Level II classification as part of a broader hierarchy of classifica tion metrics. It also built upon existing Florida stream classifications that are based mainly on limnological associations of water source water quality and aquatic biota, by retaining much of the basic structure of these associations while adding a much-needed fluvial
281 geomorphology component that takes scale s eamlessly and directly into account. Large streams simply function differently than small ones and we can now attach certain meaningful and measurable physical thre sholds for such scale dependencies. The multi-scale approach to classificati on provides a more complete and finelyresolved characterization of the fluvial forms of Florida, providing 15 types as opposed to assigning more than 90% of streams into just two categories based only on channel shape (Rosgen C5 or E5) (Kiefer and Mossa, 2004) or four kinds based on scaleindependent limnology (FNAI, 1990). This study has made it abundantly clear that stream channels and their floodplains belong to their watersheds. Stream classification in Florida is much more interesting and usef ul when floodscapes and their valley form are given as much emphasis as the open channels themselves. This is particularly true because certain floodscape types only occur in particular parts of the landscape. The multi-scale approach helped to discover and describe unique aspects of Florida streams, not solely as channels shaped or di mensioned in a particular way, but to identify them as whole fluvial systems wit h different water and sediment delivery systems, floodscapes, and channelscapes organi zed into self-sustaining functional process zones. The blackwater streams occur within two main types of landscapes, highlands and flatwoods, resulting in similar dependencies of scale for bankfull channel process-form associations, but resulting in quite different floodscape forms and process thresholds associated with basin size. Nevertheless these systems can be viewed in a summary fashion as existing along a gradient of colluvial versus alluvial controls on their morphology, some of which are more great ly influenced by the amount of the annual
282 discharge that is sourced via t he surficial aquifer versus as overland runoff (Table 4-7). Karst systems differ substantially from blackwater systems because their main water delivery system is from deep underground and is typically independent of their local surface basins. The steady flow and clear water of these systems is associated with riverscape and floodscape process-form associat ions that consistently differ from the blackwater streams. Karst streams are perhaps best consi dered based on their position along gradients related to dominant discharge and associated channel width as it relates to light availability (Table 4-8). Systems dominated by groundwater flow, with limited seasonal flood spates, allo w for biological controls that occur at thresholds simply not present in spate-driven systems. These biological controls lead to the formation of two of Floridas most interesting and unique fluv ial forms, 1) narrow rootstep sapping ravines of the highlands and 2) ultra-wide spring runs supporting SAV meadows growing on sediments created inte rnally by the spring system itself. Research Needed While this classification appears to add much needed understanding of the fl uvial systems and their forms found in peninsular Flori da, it is not offered as the final word. The study was more explorator y rather than confirmatory in its scientific design and associated statistical methods. An ideal foll ow up study would involve predicting fluvial classification and dimension using the recommended metrics and conducting confirmatory measurements on a set of site s independent from t he original sample. The delineative criteria include some types of habitat patch variables thought to be associated with fluvial forces and under stood to generally benefit fish and macroinvertebrates. However, it is not exp licitly known what group s of aquatic fauna or particular species may associate with the suggested classes of st reams or, as meta-
283 populations, rely on specific groupings of t hese classes of streams and what temporal dynamics may be involved with their use. Much more study is warranted on these types of relationships. In fact, hydrobiology data may help to resolve if some of the proposed 15 fluvial forms suggested by geomorpholog y and hydrology should be expanded or lumped. Some of the thresholds explored for sp ring runs in association with dominant discharge were necessarily fuzzy because only 12 runs were studied. These tolerance levels could likely be refined by studying si tes within the ranges where gaps occurred in the dominant discharge continuum of this st udy. Also, this study did not attempt to identify at what basin size thresholds spring runs receiving combined runoff or surficial aquifer seepage begin to function more like blackwater streams. This study focused on single-thread c hannels. It did not include multi-thread (anastomosed) channels which occur in Flor ida with some frequency, especially in lowgradient areas of long spring runs and in so me broad, flat valleys that are parts of blackwater stream systems. Such streams, although genera lly outnumbered by singlethread forms, can be found virtually anywhere on the peninsula and they appear to be rather common in south Florida countie s such as DeSoto, Glades, Highlands, and Okeechobee. Reference reach surveys and hier archical study of anastomosed streams conducted in a manner similar to this one woul d provide an even more complete picture of the states fluvial forms. That concept coul d, of course, be fully extended to virtually all flowing waterbodies in the state, incl uding non-alluvial channels such as sloughs, native swales, and strands. Anastomosed al luvial channels in Florida may be
284 intermediate forms situated between more power ful alluvial single-thread channels and less powerful slough/strand/ swale conveyances with fully non-alluvial beds. The transitions between wetlands or la kes and their connecting stream channels are important in deranged networks. Our team has commenced research on such transitions to better define their pr operties. Several upstream and downstream connections have been surveyed and are being analyze d, but it is apparent that the loworder streams often attain a multithreaded form for up to a few hundred feet before entering or exiting a wetland. Large streams warrant further study in this regard. This study only researched low to mid-or der streams up to 330 square miles. It could be usefully expanded with study of larger rivers and spring runs. Such work would take some equipment that di ffers substantially from that used on wadable streams. Large streams are well-represented in Flor ida with long-term discharge records, but finding unaltered channels in unditched or non-urbanized watersheds could be challenging. The best that could be hoped for would be to find large stable stream channels without systematic hydrology regime changes during the last 25 years of so. Unlike mid-order systems and higher, low-order stream gages are a relative rarity. Of the few gaged headwater stream s in Florida, a large fraction are not on natural, unditched watersheds but are in urban areas. Ou r team has instrumented eight natural streams and a tremendous knowledge gap would be filled if those gages could be maintained for at least eight more years to obtain a 10 year discharge record. That would be a good start, but even more, perhaps 20 such sites, should be established to fully determine the flow regimes of low-order Florida streams in association with their landscape attributes.
285 Florida streams may have much in common with streams of the seasonal tropics, particularly those draining savannas, and other wet coastal plains or lowlands in the sub-tropics. Preliminary and ongoing res earch suggests that deranged networks are fairly common in tropical savannas and are significantly more common in such landscapes than in rainforests or deserts fo und on the same continents. This suggests a global context for Florida as one of m any deranged landscapes found in strongly seasonal wet-dry, warm climates around the world. It is also possible that some lessons learned in Florida have application to tem perate zones areas with large groundwater flow dominance or spatially differential su rface water-groundwater interactions. Like Florida, such landscapes ar e often under intense agricultural or development pressure due to their moderate climate, abundance of water resources, and proximity to rivers or the coast. Areas worthy of comparative st udies may include northern Australia and New Guinea savannas, sub-Saharan African lowla nds, southern Brazil and adjacent areas, the Bolivian Moxos, the Venezuelan Llanos various other savannas in South and Central America, portions of the southeastern coastal plain of the U.S. (especially the coastal plains of South Carolina, Georgia, Alabama, and Lousiana), and environments rich in karst springs wherever they occur.
286 Table 4-1. Site physiography, drainage area, and valley slope Site name Ph y s. Drainage basin area ( s q mi. ) A+C soils ( % ) D soils ( % ) Wetlands ( % ) Lakes ( % ) Stream order Reach slope ( % ) Bell Creek UT FW 0.201003011.437 Lower Myakka River UT 3FW 0.4010029010.139 East Fork Manatee UT 2 FW 0.4158510010.250 Wekiva Forest UT FW 0.5445624020.183 Coons Bay Branch FW 0.5277314010.531 Grassy Creek UT FW 0.8148213410.350 East Fork Manatee UT 1 FW 0.9178311020.244 Hillsborough River UT FW 1.049626010.554 Lower Myakka River UT 2FW 2.709932010.154 Blues Creek near GainesvilleFW 3.234659030.282 Cow Creek FW 5.679344020.210 Moses Creek near MoultrieFW 7.829825040.279 Grasshopper Slough RunFW 8.7118912050.065 Morgan Hole Creek FW 11.08927030.169 Tenmile Creek FW 16.879330090.124 Tyson Creek FW 20.7128829060.084 Rice Creek near SpringsideFW 45.82277300190.160 Bowlegs Creek near Ft MeadeFW 50.93164195310.166 Manatee River near Myakka HeadFW 65.72376110610.092 Santa Fe River near GrahamFW 94.118702712190.084 Little Haw Creek near SevilleFW 106.2207133650.066 Horse Creek near ArcadiaFW 219.0891180460.072 Fisheating Creek at PalmdaleFW 313.0694220360.039 Manatee River UT HL 0.3564420012.390 Lowry Lake UT HL 0.39733010.735 Tuscawilla Lake UT HL 0.3514913011.039 Shiloh Run near Alachua HL 0.488113011.278 Cypress Slash UT HL 0.483128912.119 Lake June-In-Winter UT HL 0.6564416011.111 Tiger Creek UT HL 0.98787610.288 Snell Creek HL 1.7732620020.117 Bell Creek HL 1.941597030.403 Alexander UT 2 HL 2.3524715510.705 Jack Creek HL 2.7554520020.403 Gold Head Branch HL 2.89723131.671 Hammock Branch HL 3.0643540120.156 Jumping Gully HL 4.26323141620.799 Ninemile Creek HL 6.85522181811.010 South Fork Black Creek HL 26.57322154350.103 Carter Creek near SebringHL 36.0701551430.256 Tiger Creek near Babson ParkHL 53.2751913540.070 Catfish Creek near Lake WalesHL 57.57017111310.072 Blackwater Creek near CassiaHL 118.44846266270.019 Livingston Creek near FrostproofHL 119.849341715110.084 Morman Branch UT Spring RunK 0.510004010.465 Silver Glen UT Spring RunK 1.010002010.121 Forest Spring Run K 1.79092010.335 Little Levy Blue Spring RunK 2.189245010.094 Kittridge Spring Run K 3.1871313010.395 Cedar Head Spring Run K 5.29093010.077 Alligator Spring Run K 8.789106110.134 Gum Slough Spring Run K 27.0831710120.244 Juniper Spring Run K 33.79465020.135 Weeki Wachee River K 85.986135110.072 Rock Spring Run K 100.09533110.050 Alexander Spring Run K 110.07422134100.055 Phys. = Basin physiography. FW = flatwoods, HL = highlands K = karst.
287 Table 4-2. Bankfull channel dimensions Site name Ph y s. Drainage basin area ( s q mi. ) Width ( ft ) Bankfull flow ( cfs ) Cross section area ( s q ft ) Mean thalweg de p th ( ft ) W/D ratio Rc/W ratio Bell Creek UTFW0.26.22.33.31.010.41.7 Lower Myakka River UT 3FW0.411.81.03.90.785.61.7 East Fork Manatee UT 2FW0.410.72.09.21.212.31.2 Wekiva Forest UTFW0.58.85.69.184.108.40.206 Coons Bay BranchFW0.56.62.65.01.210.32.5 Grassy Creek UTFW0.8220.127.116.11.920.40.9 East Fork Manatee UT 1FW0.96.33.26.18.104.22.168 Hillsborough River UTFW1.010.66.110.21.612.61.5 Lower Myakka River UT 2FW22.214.171.124.01.020.01.3 Blues Creek near GainesvilleFW3.28.514.014.02.57.53.0 Cow CreekFW5.612.520.315.51.913.32.7 Moses Creek near MoultrieFW7.812.220.9126.96.36.199.4 Grasshopper Slough RunFW8.718.518.9188.8.131.52.8 Morgan Hole CreekFW11.011.519.8184.108.40.206.6 Tenmile CreekFW16.819.223.734.82.810.61.7 Tyson CreekFW20.723.310.728.01.824.21.0 Rice Creek near SpringsideFW45.822.6220.127.116.110.12.0 Bowlegs Creek near Ft MeadeFW50.931.718.104.22.1687.51.9 Manatee River near Myakka HeadFW65.726.9139.922.214.171.124.8 Santa Fe River near GrahamFW94.122.0109.6126.96.36.199.6 Little Haw Creek near SevilleFW106.236.6109.297.95.642.50.8 Horse Creek near ArcadiaFW219.038.3230.0113.84.513.12.6 Fisheating Creek at PalmdaleFW313.044.581.987.24.329.81.3 Manatee River UTHL0.35.12.56.188.8.131.52 Lowry Lake UTHL0.34.50.62.184.108.40.206 Tuscawilla Lake UTHL0.32.50.22.01.23.84.9 Shiloh Run near AlachuaHL0.46.59.24.21.09.11.2 Cypress Slash UTHL0.46.50.91.70.710.51.6 Lake June-In-Winter UTHL0.66.41.55.220.127.116.11 Tiger Creek UTHL0.918.104.22.168.216.81.1 Snell CreekHL1.718.63.721.71.823.91.0 Bell CreekHL22.214.171.124.126.96.36.199 Alexander UT 2HL188.8.131.52.62.08.71.2 Jack CreekHL2.78.15.05.41.016.51.8 Gold Head BranchHL2.87.04.46.61.66.02.5 Hammock BranchHL3.011.38.114.184.108.40.206 Jumping GullyHL220.127.116.11.18.104.22.168 Ninemile CreekHL22.214.171.1240.21.113.11.2 South Fork Black CreekHL26.521.052.344.43.412.90.9 Carter Creek near SebringHL36.019.031.526.72.031.31.2 Tiger Creek near Babson ParkHL53.247.260.995.43.824.30.7 Catfish Creek near Lake WalesHL57.559.045.166.92.132.41.3 Blackwater Creek near CassiaHL118.447.8128.7108.84.314.81.1 Livingston Creek near FrostproofHL119.833.358.864.13.623.32.8 Morman Branch UT Spring RunK0.57.30.41.40.335.00.8 Silver Glen UT Spring RunK1.027.20.810.10.650.00.6 Forest Spring RunK126.96.36.199.188.8.131.52 Little Levy Blue Spring RunK184.108.40.2065.80.833.01.2 Kittridge Spring RunK220.127.116.11.50.637.01.0 Cedar Head Spring RunK18.104.22.1685.61.817.03.1 Alligator Spring RunK8.743.811.361.02.530.24.4 Gum Slough Spring RunK27.054.536.4106.82.843.04.2 Juniper Spring RunK33.722.214.171.124.021.01.2 Weeki Wachee RiverK85.945.8163.6161.25.714.51.9 Rock Spring RunK100.053.648.073.23.552.01.6 Alexander Spring RunK110.0251.3121.9567.02.8131.05.8 Phys. = basin physiography: FW = flatwoods, HL = highlands, K = karst. W/D ratio based on reference reach width divided by the hydraulic depth. Rc/W ratio is the mean radius of curvature to bankfull width for all bends in the reference reach.
288 Table 4-3. Flood channel dimensi ons and bankfull comparison ratios Site name Ph y s. Drainage basin area ( s q mi. ) Flood width ( ft ) Flood flow ( cfs ) Flood/bkf de p th ratio Flood/bkf width ratio Flood/bkf flow ratio Flood/bkf p ower ratio Bell Creek UT FW 0.22126.96.36.199.02.02 Lower Myakka River UT 3FW 0.4755.01.36.45.35.44 East Fork Manatee UT 2 FW 0.41188.8.131.52.23.22 Wekiva Forest UT FW 0.59316.41.810.62.92.88 Coons Bay Branch FW 0.5184.108.40.206.32.31 Grassy Creek UT FW 0.81323.41.6220.127.116.11 East Fork Manatee UT 1 FW 0.918.104.22.168.41.46 Hillsborough River UT FW 1.022.214.171.124.51.51 Lower Myakka River UT 2FW 2.78718.21.8126.96.36.199 Blues Creek near GainesvilleFW 3.21188.8.131.52.12.08 Cow Creek FW 5.665184.108.40.206.33.33 Moses Creek near MoultrieFW 7.8418138.41.9220.127.116.11 Grasshopper Slough RunFW 8.716039.11.48.62.14.30 Morgan Hole Creek FW 11.010766.32.09.33.44.45 Tenmile Creek FW 16.817718.104.22.168.73.74 Tyson Creek FW 20.7246207.73.310.519.419.57 Rice Creek near SpringsideFW 45.8834521.92.436.922.522.53 Bowlegs Creek near Ft MeadeFW 50.9703234.11.822.24.03.96 Manatee River near Myakka HeadFW 65.78821246.63.132.88.913.19 Santa Fe River near GrahamFW 94.1141522.214.171.124.74.71 Little Haw Creek near SevilleFW 106.23127580.51.8126.96.36.199 Horse Creek near ArcadiaFW 219.07431330.82.6188.8.131.52 Fisheating Creek at PalmdaleFW 313.036411018.51.881.812.412.43 Manatee River UT HL 0.3184.108.40.206.22.21 Lowry Lake UT HL 0.3220.127.116.11.03.04 Tuscawilla Lake UT HL 0.331.01.31.24.84.50 Shiloh Run near Alachua HL 0.41020.91.61.62.32.26 Cypress Slash UT HL 0.418.104.22.168.02.99 Lake June-In-Winter UT HL 0.622.214.171.124.51.53 Tiger Creek UT HL 0.9126.96.36.199.61.55 Snell Creek HL 1.73188.8.131.52.51.50 Bell Creek HL 1.986.61.01.01.61.64 Alexander UT 2 HL 2.328184.108.40.206.02.96 Jack Creek HL 2.77818.02.79.73.64.78 Gold Head Branch HL 2.876.91.41.01.61.56 Hammock Branch HL 3.03416.01.33.02.01.98 Jumping Gully HL 4.243.01.00.91.31.29 Ninemile Creek HL 6.8220.127.116.11.51.55 South Fork Black Creek HL 26.521689.01.410.31.71.70 Carter Creek near SebringHL 36.05518.104.22.168.04.73 Tiger Creek near Babson ParkHL 53.217822.214.171.124.13.41 Catfish Creek near Lake WalesHL 57.5504126.96.36.199.63.61 Blackwater Creek near CassiaHL 118.44108188.8.131.52.97.23 Livingston Creek near FrostproofHL 119.82293184.108.40.206.77.47 Morman Branch UT Spring RunK 0.571.21.61.03.13.09 Silver Glen UT Spring RunK 1.0220.127.116.11.12.00 Forest Spring Run K 1.7672.71.618.104.22.168 Little Levy Blue Spring RunK 2.11139.92.05.45.15.40 Kittridge Spring Run K 3.122.214.171.124.12.10 Cedar Head Spring Run K 5.23020.41.21.32.72.72 Alligator Spring Run K 8.78818.11.32.01.61.62 Gum Slough Spring Run K 27.014556.01.42.71.51.55 Juniper Spring Run K 33.75126.96.36.199.41.39 Weeki Wachee River K 85.9127188.8.131.52.11.12 Rock Spring Run K 100.05468.31.11.01.41.42 Alexander Spring Run K 110.0272247.31.31.12.02.03 Phys. = basin physiography: FW = flatwoods, HL = highlands, K = karst.
289 Table 4-4. Valley descriptions Site name Phys. DA (sq.mi.)MBW communityUpstream community Downstream community Valley confinement Wetl. MBW ratioAFF Bell Creek UT FW0.2Mesic hammockDepressional marshStream junctionConfined 0.30 Lower Myakka River UT 3FW0.4Hydric hammockDepressional marshDepressional marshWell-adjusted1.10 East Fork Manatee UT 2 FW0.4Hydric hammockDepressional swampDepressional swampUnconfined 4.00 Wekiva Forest UT FW0.5Bottomland hardwoodsSeepage swampStream junctionUnconfined 4.41 Coons Bay Branch FW0.5Hydric hammockDepressional marshStream junctionWell-adjusted1.50 Grassy Creek UT FW0.8Cutthroat seepDepressional marshSeepage swampUnconfined 3.80 East Fork Manatee UT 1 FW0.9Hydric hammockDepressional marshStream junctionUnconfined 2.90 Hillsborough River UT FW1.0Mixed swamp Depressional swampSlough Unconfined 5.20 Lower Myakka River UT 2FW2.7Hydric hammockDepressional marshDepressional marshWell-adjusted0.80 Blues Creek near GainesvilleFW3.2Mesic hammockDepressional swampDepressional swampConfined 0.10 Cow Creek FW5.6Bottomland cypressStream junctionStream junctionWell-adjusted2.02 Moses Creek near MoultrieFW7.8Bottomland cypressStream junctionStream junctionWell-adjusted1.22 Grasshopper Slough RunFW8.7Mesic hammockSlough Slough Unconfined 0.40 Morgan Hole Creek FW11.0Herbaceous wetlandDepressional marshStream junctionWell-adjusted1.22 Tenmile Creek FW16.8Bottomland cypressStream junctionStream junctionUnconfined 1.73 Tyson Creek FW20.7Bottomland cypressSlough Stream junctionUnconfined 3.81 Rice Creek near SpringsideFW45.8Bottomland cypressSlough Stream junctionUnconfined 3.32 Bowlegs Creek near Ft MeadeFW50.9Herbaceous wetlandStream junctionStream junctionUnconfined 3.72 Manatee River near Myakka HeadFW65.7Bottomland hardwoodsStream junctionStream junctionWell-adjusted0.93 Santa Fe River near GrahamFW94.1Bottomland cypressStream junctionStream junctionWell-adjusted0.63 Little Haw Creek near SevilleFW106.2Bottomland cypressLake Depressional swampWell-adjusted1.33 Horse Creek near ArcadiaFW219.0Bottomland cypressStream junctionStream junctionWell-adjusted0.64 Fisheating Creek at PalmdaleFW313.0Bottomland cypressSlough Slough Unconfined 9.55 Manatee River UT HL0.3Seepage swampSeepage swampStream junctionSeepage ravine0.40 Lowry Lake UT HL0.3Seepage swampSeepage swampStream junctionSeepage ravine1.80 Tuscawilla Lake UT HL0.3Seepage swampSeepage swampStream junctionSeepage ravine0.20 Shiloh Run near Alachua HL0.4Hydric hammockDepressional swampStream junctionWell-adjusted0.70 Cypress Slash UT HL0.4Pine flatwoodsLake Seepage swampConfined 0.30 Lake June-In-Winter UT HL0.6Seepage swampSeepage swampLake Seepage ravine1.90 Tiger Creek UT HL0.9Seepage swampSeepage swampSlough Unconfined 2.60 Snell Creek HL1.7Hydric hammockSeepage swampSlough Unconfined 9.80 Bell Creek HL1.9Seepage swampStream junctionStream junctionUnconfined 4.10 Alexander UT 2 HL2.3Mesic hammockDepressional swampDepressional swampConfined 0.20 Jack Creek HL2.7Seepage swampDepressional swampSeepage swampUnconfined 1.61 Gold Head Branch HL2.8Seepage swampSeepage swampLake Seepage ravine4.00 Hammock Branch HL3.0Bottomland cypressDepressional swampDepressional swampWell-adjusted0.91 Jumping Gully HL4.2Xeric upland Depressional swampDepressional swampConfined 0.10 Ninemile Creek HL6.8Seepage swampSeepage swampDepressional swampSeepage ravine2.10 South Fork Black Creek HL26.5Bottomland hardwoodsStream junctionStream junctionUnconfined 2.02 Carter Creek near SebringHL36.0Bottomland hardwoodsLake Seepage swampWell-adjusted0.51 Tiger Creek near Babson ParkHL53.2Bottomland hardwoodsStream junctionLake Well-adjusted1.12 Catfish Creek near Lake WalesHL57.5Bottomland cypressLake Lake Well-adjusted0.61 Blackwater Creek near CassiaHL118.4Bottomland cypressLake Stream junctionUnconfined 2.41 Livingston Creek near FrostproofHL119.8Bottomland hardwoodsStream junctionStream junctionWell-adjusted0.81 Morman Branch UT Spring RunK0.5Seepage swampSpring Stream junctionSeepage ravine6.10 Silver Glen UT Spring RunK1.0Seepage swampSpring Slough Seepage ravine0.60 Forest Spring Run K1.7Seepage swampSpring Lake Seepage ravine7.10 Little Levy Blue Spring RunK2.1Bottomland hardwoodsSpring Spring Unconfined 2.90 Kittridge Spring Run K3.1Seepage swampSpring Stream junctionSeepage ravine11.20 Cedar Head Spring Run K5.2Hydric hammockSpring Spring Unconfined 2.40 Alligator Spring Run K8.7Mixed swamp Spring Stream junctionUnconfined 5.90 Gum Slough Spring Run K27.0Mixed swamp Spring Spring Unconfined31.20 Juniper Spring Run K33.7Mixed swamp Spring Spring Unconfined37.50 Weeki Wachee River K85.9Mixed swamp Spring Slough Well-adjusted0.91 Rock Spring Run K100.0Seepage swampSpring Stream junctionUnconfined 3.60 Alexander Spring Run K110.0Hydric hammockSpring Stream junctionWell-adjusted0.80 Phys. = basin physiography: FW = flatwoods, HL = highlands, K = karst. DA = drainage basin area. Wetl. MBW ratio = ratio of the riparian wetland width to the meander belt width. AFF = number of alluvial floodplain features.
290 Table 4-5. Principal components from dimensionless variables Component 12345 A+C soils .880 Percent A-soil .869 Percent D-soil -.866 Percent wetlands -.751 Percent upland .669 Basin grade (ft/ft) .599 Bank height ratio .550 Hillslope grade (ft/ft) .512 Flood/bankfull depth ratio .805 Flood/bank height depth ratio .779 Ratio of flood to bankfull power .776 Ratio of flood to bankfull flow .722 Width ratio of floodplain and bankfull channels.670 Ratio of flood to bankfull velocity -.653 Pools >4 ft deep (%) .626 Bifurcation ratio .534 MBW to W ratio .741 Valley segment slope (%) .732 Reach valley slope (%) .688 Bankfull slope (ft/ft) .666 Ratio of max./min. reach TW depths .642.631 W/D ratio -.637 Percent C-soil .605 Width ratio of bank height to bankfull Percent canopy closure US DS -.844 Percent canopy closure -.840 Percent substrate as SAV .681 Mean Rc/W ratio .657 Percent substrate as emergent vegetation .599 Pools 1-2 ft deep (%) -.539 Valley segment sinuosity ratio Tightest bend ratio Percent substrate as bare sand Bankfull area max./min. ratio .743 Bankfull mean depth max./min. ratio .722 Bankfull width max./min. ratio .692 Ratio of mean reach pool and riffle TW depths .513.681
291 Table 4-6. Selected variable compar isons among dimensionless clusters ClusterStatistic %A+C soils Flood/bankfull de p th ratio Valley segment slo p e ( % ) Bankfull W/D ratio Canopy closure%SAV%Ve g Reach Rc/W ratio Mn/Mx XSA* 1-AMean72 1.441.47767%0.04.32.093.0 Std Dev20 0.210.40332%0.010.01.480.9 1-BMean75 2.020.202650%4.83.01.141.9 Std Dev8 0.420.13723%184.108.40.206.6 2-AMean95 1.540.442895%0.53.90.932.4 Std Dev6 0.110.28193%220.127.116.11.8 2-BMean89 1.280.102863%7.818.104.22.168 Std Dev5 0.080.061238%8.915.01.550.4 2-CMean85 1.160.046612%44.822.214.171.124 Std Dev10 0.130.025915%15.810.72.331.6 3-AMean6 1.550.393083%0.09.01.342.8 Std Dev7 0.330.292817%0.07.20.320.9 3-BMean38 1.290.41974%0.00.81.792.0 Std Dev23 0.210.22317%0.01.80.690.7 3-CMean26 2.180.091850%1.313.91.611.9 Std Dev22 0.560.061030%3.517.00.580.4 *Ratio of minimum to maximum channel cross-section area meaured in the reach. %SAV = submerged aquatic vegetation. %Veg = emergent aquatic herbaceous vegetation.
292 Table 4-7. Summary of flatwoods and highlands ripar ian system types Name AcronymTypical landscape position Characteristic formsCharacteristic processes Root-step channelsHL-RSCHeadwaters draining thick sandy knolls in steep-sloped valleys. Root-step channels, often in seepage ravines. Groundwater sapping. Channel grade control & flow resistance by large root weirs. Wide channels of colluvial valleys FW-CV-WCHeadwaters draining chainsof-wetlands in linearly sloped valleys. Rosgen C5 channels with high W/D ratios. In-channel sediment transport continuity (net export). Downcutting resisted by shallow root masses in bed. Narrow channels of colluvial valleys FW-CV-NCHeadwaters connecting chains-of-wetlands to midorder streams across convex or concave valley slopes. Rosgen E5 channels with low W/D ratios. In-channel sediment transport continuity (net export). Friction resistance due to channel narrowing. Baseflow corridorsHL-BFCLarger headwaters and middle areas dominated by sandy knolls and large lakes. Can have varying amounts of flatwoods and wetland inclusions. Wide variety of small to medium capacity channel forms. Small to nonexistent alluvial floodplains. Extended baseflow through most of the year or perennially. Varying degrees of infrequent spates and associated alluviation. Compact complex alluvial corridors FW-AF-CCMiddle basins dominated by flatwoods and wetlands. Wide variety of small to medium capacity channel forms with sporadic to continuous simple alluvial floodplains. Highly variable seasonal flow with routine wet-season spates and associated alluviation. Wide alluvial valley flats FW-AF-WFWide, flatly sloped valleys in middle and lower basins dominated by flatwoods and wetlands. Generally wide and shallow channels within very broad and relatively featureless valley fills. Good continuity of alluvial features in the flood p lain. Floodplain deposition of fine textured materials. Sand-ridge alluvial floodscapes HL-AFSLower basins dominated by sandy knolls and large lakes. Variety of high-capacity channel forms with at least small, continuous alluvial floodplains. Complex alternations of confined and unconfined valleys. Copious perennial baseflow with sporadic wet season spates. High-gradient alluvial floodscapes FW-AFS-HGModerately sloped valleys in lower basins dominated by flatwoods and wetlands. Deep powerful channels with well-fit meanders in alluvially complex floodplains. Often Rosgen E5. Mixed floodscape deposition and scour during routine wet season floods. Large annual vertical flood fluctuations. Low-gradient alluvial floodscapes FW-AFS-LGLow-sloped valleys in basins dominated by flatwoods and wetlands. Wide powerful channels with well-fit or underfit meanders in wide alluvial floodplains. Often Rosgen C5. Floodscape deposition during routine wet-season floods. Large annual horizontal flood fluctuations. Colluvial valley clay gullies CV-CGSteeply sloped valleys with low-base levels intersecting Hawthorne (clay) or similar outcroppings. Streams with mixed sand, clay, and rubble beds generally entrenched in Vshaped valleys. Gullying due to high relief. Floodplain construction restricted by dense cohesive bank materials.Other TransitionAlluvial processes dominantRiparian system type Basic descriptionsColluvial processes dominant
293 Table 4-8. Summary of karst riparian system types Name AcronymTypical landscape position Characteristic formsCharacteristic processes Low-magnitude spring runs K-LMSeepage coves, seepage ravines, and the valleys of larger streams (yazoos). Often in association with other springheads. Closed canopy. Small, shallow, sandy beds flanked by sporadic to continuous biological banks. Low, steady, perennial discharge. Sand ripple bedforms common over shallow root systems in bed. No signs of autochthonous sedimentation. Light limitations prevent SAV establishment. Medium magnitude spring runs K-MMOften feeding larger runs downstream via simple valleys. Closed canopy. Medium, shallow, mixed sand and detrital floc beds flanked by sporadic to continuous biological banks. Steady perennial discharge. Some autochthonous sedimentation from snails and detritus. Light limitations prevent SAV establishment, but shadetolerant emergents present. High magnitude spring runs K-HMLong complex valleys with alternating bottomland swamps, seepage slopes, and/or high sandy bluffs. Variably open canopy. Complex alternating shallow and deep channel zones. Detrital floc sorted along channel margins in deep zones and across the bed in shallow zones. Sand common. Biological banks common. Copious perennial discharge. Internal and external sedimentation. Light gaps allow for some SAV establishment. Variability in SAV, deep pools, and bed material sorting probably reflects the fact that no one process dominates.TransitionGreat magnitude, deep spring runs K-GM-DCLow-lying complex valleys with alternating bottomland swamps, seepage slopes, and/or high sandy bluffs. Usually discharging to a large river, lake, or coast. Open canopy. Deep powerful channels, with deep pools and detrital floc sorted to channel margins. Biological banks largely continuous except at anabranches. Sporadic rock outcroppings. Very copious perennial discharge. Geologic controls may be allowing hydraulic establishment of deep efficient channels. Internal and external sedimentation. Great magnitude, wide spring runs K-GM-WLow-lying complex valleys with alternating bottomland swamps, seepage slopes, and/or high sandy bluffs. Usually discharging to a large river, lake, or coast. Very wide channels with relatively uniform crosssections and dominance of SAV on mixed sand, detritus, and detrital floc bed. Biological banks dominant. Very copious perennial discharge. Geologic factors may be allowing biological controls to occupy wide inefficient channels. Internal and external sedimentation. Light limited High light availabilityRiparian system type Basic descriptions
294 Primary Drainage Area (sq. miles) 0.1 1 10 100 1000 Valley Segment Slope (%) 0.001 0.01 0.1 1 10 S T R E AM S W I T H A L L U V I A L B E D SAN AST O M O S ED ST R EA M S ?U N S T A B L E G U L L I E S S L O U G H S S T R A N D S S W AL E S Valley Segment Slope (%) 0.01 0.1 1 10 W/D Ratio 1 10 100 S T R E A M S W I T H AL L U V I A L B E D SAN AS T O M O SED S T R EAM S ?U N S T AB L E G U L L I E S S L O U G H S S T R A N D S S W AL E S Figure 4-1. Single channel blackwater stream zone of confidence (95% prediction interval).
295 Primary Drainage Area (sq. miles) 0.1 1 10 100 1000 Valley Segment Slope (%) 0.001 0.01 0.1 1 10 S P R I N G R U N S W I T H AL L U V I AL B E D SA N A S T O M O S E D R U N S ?U N S T AB L E G U L L I E S ? ? ? Valley Segment Slope (%) 0.01 0.1 1 W/D Ratio 1 10 100 U N S T A B L E G U L L I E S? ? ?S P R I N G R U N S W I T H A L L U V I A L B E D SA N A S T O M O S E D R U N S ? Figure 4-2. Single-channel spri ng runs zone of confidence (95% prediction interval).
296 Surface Drainage Area (sq. miles) 0.1 1 10 100 1000 0.01 0.1 1 10 Alluvial Floodscape Colluvial Valley 0.1 1 10 100 1000 Valley Slope (%) 0.01 0.1 1 10 0.01 0.1 1 10 100 1000 0.01 0.1 1 10 Karst Highlands Flatwoods Figure 4-3. Continuous alluvial versus colluvial floodscapes associated with drainage area for three physiographies.
297 Primary Basin Area (sq. miles) 0.1 1 10 100 Reach Valley Slope (%) 0.1 1 CV-CG = Clay Gullies FW-AF-CC = Complex Compact Alluvial Floodplains FW-AF-WF = Wide Alluvial Valley Flats FW-AFS-HG = High Gradient Alluvial Floodscapes FW-AFS-LG = Low Gradient Alluvial Floodscapes FW-CV-NC = Narrow Channels of Colluvial Valleys FW-CV-WC = Wide Channels of Colluvial Valleys AFS-HG AFS-LG AF-WF AF-CC CV-NC CV-WC Figure 4-4. Distribution of flatwoods riparian system cla sses by drainage area and valley slope.
298 Figure 4-5. Example of riparian system type FW-AFS-HG, Manatee River (see Appendix C for legend). 35 40 45 50 55 60 65 2800282028402860288029002920294029602980300030203040306030803100 Distance (ft)Elevation (ft) Colluvial Sand Colluvial Sand Sand Shoals over Bed Clay Alluvial Sand & Detritus Alluvial Sand & Detritus MBW 511 615 427 434 434 615
299 Figure 4-6. Example of riparian system type FW-AFS-LG, Fisheating Creek (see Appendix C for legend). 25 30 35 40 45 886088808900892089408960898090009020904090609080 Distance (ft)Elevation (ft) MBW (350') 511 621 621 0 Alluvial Sand Alluvial Sand Muck Over Sand Layer Mucky Sand Stagnant at Bankfull Flow
300 Figure 4-7. Example of riparian system type FW-AF-WF, Rice Creek (see Appendix C for legend). 0 5 10 15 20 800820840860880900920940960980100010201040 Distance (ft)Elevation (ft) MBW 511 615 615 Alluvial Sand & Detritus A lluvial Silt & Sandy Silt Layers Alluvial Silt & Sandy Silt Layers
301 Figure 4-8. Example of riparian system ty pe FW-AF-CC, Tenmile Creek (see Appendix C for legend). 95 100 105 110 0 20 40 60 80 100 120 140 160 180 Distance (ft)Elevation (ft) Mucky Silt & Sandy Loam Layers Alluvial Sand & Detrital Layers Colluvial Sand Mucky Silt & Sand Layers Colluvial Loamy Sand MBW 615 434 511 615 411
302 Figure 4-9. Example of riparian system type FW-CV-NC, Wekiva Forest UT (see Appendix C for legend). 95 100 105 110 0102030405060708090100 Distance (ft)Elevation (ft) Colluvial Sand Mucky Sand Sand & Detritus MBW 617 617 511
303 Reach Valley Slope (%) 0.00.20.40.60.81.01.21.41.6 W/D Ratio 0 10 20 30 40 50 FW-AFS-LG FW-AFS-HG FW-CV-WC FW-CV-NC W/D > 12, Rosgen C W/D < 12, Rosgen E Figure 4-10. Distribution of large and small flatwoods riparian system classes by W/D and valley slope.
304 Figure 4-11. Example of ri parian system type FW-CV-WC, Lower Myakka UT 3 (see Appendix C for legend). 95 97 99 101 103 105 107 109 02 04 06 08 01 0 0 Distance (ft)Elevation (ft) MBW Alluvial Sand Colluvial Sand Colluvial Sand 511 624 321 411 624
305 Distance (ft) 0 1000 2000 3000 Elevation (ft) 80 90 100 110 Land Surface Headwater Marsh Mid-Order Stream Valley In-Line Swamp FW-CV-WC FW-CV-NC Figure 4-12. Typical landscape positions and valley profile distribution of flatwoods colluvial riparian systems.
306 Figure 4-13. Partially expos ed shallow root discs on a FW -CV-WC channel bed (Lower Myakka UT 2).
307 Primary Basin Area (sq. miles) 0.1 1 10 100 Reach Valley Slope (%) 0.1 1 CV-CG = Clay Gullies HL-AFS = Sand Ridge Alluvial Floodscapes HL-BFC = Baseflow Corridors HL-RSC = Root-Step Channels HL-AFS HL-BFC HL-RSC Figure 4-14. Distribution of flatwoods riparian system classes by drainage area and valley slope.
308 Figure 4-15. Example of ri parian system type HL-AFS, Catfish Creek (see Appendix C for legend). 65 70 75 80 85 90 95 100 105 110 115 120 125 0 1002003004005006007008009001000 Distance (ft)Elevation (ft) MBW Alluvial Sand & Detritus Colluvial Sand 6" Peat Over Sand Layer Colluvial Sand Colluvial Sand 511 621 434 434 413 413 617
309 Figure 4-16. Example of riparian system type HL-BFC domi nated by seepage, Tiger UT (see Appendix C for legend). 95 100 105 110 01 02 03 04 05 06 07 0 Distance (ft)Elevation (ft) Sapric Muck Sapric Muck Sand and Organic Layers Biological Bank (Peat) MBW 611 611 511
310 Figure 4-17. Example of ri parian system type HL-BFC with blackwater sources, Hammock Branch (see Appendix C for legend). 95 100 105 110 115 0 20 40 60 80 100 120 140 Distance (ft)Elevation (ft ) MBW 615 434 434 511 61 5 Alluvial Sand & Detritus Colluvial Sand Sapric Muck Colluvial Sand
311 Figure 4-18. Example of ri parian system type HL-RSC, Lowry Lake UT (see Appendix C for legend). 95 100 105 110 115 01 02 03 04 05 06 0 Distance (ft)Elevation (ft) MBW Colluvial Sand Colluvial Sand M ucky Sand Mucky Sand Root Steps & Sand Biological Banks (Peat) Biological Banks (Peat) 511 611 412 412 611
312 Figure 4-19. Root-step and biological bank detail, Tuscawilla Lake UT.
313 Bankfull Discharge (cfs) 0.1 1 10 100 Reach Valley Slope (%) 0.1 1 K-GM-DC = Great Magnitude, Deep Spring Runs K-GM-WC = Great Magnitude, Wide Spring Runs K-HM = High Magnitude Spring Runs K-LM = Low Magnitude Spring Runs K-MM = Medium Magnitude Spring Runs GM-DC GM-WC HM MM LM Figure 4-20. Distribution of karst riparian system classes by bankfull discharge and valley slope.
314 Figure 4-21. Example of ri parian system type K-GM-WC, Alexander Spring Run (see Appendix C for legend). 0 5 10 15 20 25 30 320340360380400420440460480500520540560580600620640660680 Distance (ft)Elevation (ft ) MBW (500') 511 630 630 Sand, Shell, & Gyttja Biological Banks (Peat) Biological Banks (Peat) Ubiquitous SAV Meadow Colluvial Sand
315 Figure 4-22. Example of ri parian system type K-GM-DC, Weeki Wachee River (see Appendix C for legend). -5 0 5 10 15 20 600 650 700 750 800 850 900 Distance (ft)Elevation (ft) MBW Mucky Sand Sand & Organic Layers Biological Ban k (Peaty Muck) Mucky Sand Alluvial Sand & Detritus Sporadic SAV Biological Ban k (Peaty Muck) 511 434 617 641 (615) 615
316 Figure 4-23. Example of ri parian system type K-HM, Juni per Creek Spring Run (see Appendix C for legend). 90 95 100 105 110 115 02 04 06 08 0 Distance (ft)Elevation (ft) 615 (641) 617 5 11 617 MBW (130') Peaty Muck Sand Center & Gyttja Flanks Biological Bank (Dominant) Sa p ric Muck SAV Patches Biological Bank (Dominant)
317 Bankfull Discharge (cfs) 0.1 1 10 100 1000 Percent Substrate as SAV 0 10 20 30 40 50 60 70 17 cfs K-GM-DC K-GM-WC K-HM K-LM K-MM Figure 4-24. Distribution of karst ripari an system classes by bankfull discharge and submerged aquatic vegetation.
318 Figure 4-25. Example of riparian system type K-MM, Cedar Head Spring Run (see Appendix C for legend). 90 95 100 105 110 115 0102030405060708090100110 Distance (ft)Elevation (ft) MBW C olluvial Sand Sapric Muck Gyttja & Shell Biological Banks (Muck) Biological Banks (Muck) Limestone Outcrop 511 617 434 434 617
319 Figure 4-26. Example of ripar ian system type K-LM, Kittridge Spring Run (see Appendix C for legend). 95 97 99 101 103 105 0 5 101520253035404550 Distance (ft)Elevation (ft) MBW 511 611 617 Sandy Muck Sapric Muck Sand & Detritus Biological Bank (Peaty Muck)
320 Figure 4-27. Example of ri parian system type CV-CG, Bl ues Creek (see Appendix C for legend). 90 95 100 105 110 01 02 03 04 05 06 0 Distance (ft)Elevation (ft) A lluvial Sand, Gravel, & Stif f Clay Colluvial Sand Colluvial Sand MBW (130' ) 511 414 414
321 CHAPTER 5 SUMMARY AND POTENTIAL APPLICATIONS Summary of Findings Peninsular Florida str eams change gradually along the drainage network in some ways akin to the typical dendritic and allu vial fluvial systems described around much of the world, but they are punctuated and deranged by in-line wetlands and lakes due to local geologic controls and differential w eathering of carbonate lithology. The strong wet-dry seasonality of the region also t ends to sort hydrobiological and geomorphic processes as a matter of landscape physiography and scale based on the relative infiltration versus runoff capacity of the wa tershed. Therefore, bot h large-scale clinal and local-scale zonal concepts are impor tant for understanding Florida stream processes and associated fluvial forms. This fa ct lends itself well to use of functional process zone concepts for charac terizing Floridas streams. Florida provides a rich environment of 15 types of stream systems under varying degrees of alluvial control and groundwater di scharge. The combination of controls on fluvial form depend on the scale and landscape position of the str eam, within three different types of physiography; karst, hi gh sandy ridges (highlands), and flatwoods. Consistent associations of channel type were identified and quantified, relating stream type and channel characteristics with waters hed size, soils, and valley slope. Floodplain morphology and process are every bit as impor tant for delineating and describing fluvial systems in Florida as are the open channel characteristics. In fact, Florida streams are best conceived as primarily existing along a gradient of differing flood pulse potential and associated fluvial forms in the flood scape, more so than as systems whose processes associate predominantly with bankfull channel form. Channel form is
322 convergent among some classes and can be an im portant delineator in others. It seems to be most important in t he smallest streams and the la rgest, but not for systems draining intermediate basins. Perhaps the main reason it is important to conceive of Florida streams based largely on the characteristics of their floodscapes is because many of them are routinely flowing in them. Overbank flow is common and sustained, often for more than 25% of the year in many perennial blackw ater streams. Portions of the floodplain should actually be viewed as a vegetated wet-season channel with trees. The open channel could be viewed as a specia l transport-dominated in clusion within the riparian system. In stream s draining smaller basins, the flood pulses decrease in importance and associated alluvi al floodplain features are di minished or non-existent. Reduction of flood-pulse influence also occu rs as a result of increased groundwater mediation of the annual discharge associat ed with highlands and karst landscapes and a concomitant decrease in r unoff spate potential versus that associated with the flatwoods. Some high-relief sandy highla nds develop small sapping valleys on the peninsula. These form seepage ravines fed by the unconfined aquifer. Hydrobiology plays a key role in geomorphology and that role increases with groundwater influence. Groundwater regimes lacking powerful flood pulses or spates allow for certain types of live vegetation communities to provide substantial and dominant bed stabilization and grade control. In the steep-sloped s apping streams this control takes the form of live root-weirs that form a stepped arrangement with pools between the steps. The root weir s are typically formed by tree species that thrive in saturated water regimes. By retarding c ontinued valley grading, these root-step systems prevent excessive dewatering of their s eepage valleys, allowing for their continued
323 competitive advantage. Dense meadows of s ubmerged aquatic vegetation can form in streams with copious artesian spring flow. These underwater meadows substantially increase flow resistance and stabilize potentia lly mobile sediments, keeping the channel wide and shallow and allowing continued light penetration to their bed. The spring runs also produce autochthonous sour ces of sediment via high pr oductivity of detritus and snail shells forming shelly-organic sediments (detrital floc) that are often laterally sorted by fluvial forces. The channel banks of both seepage streams and artesian streams typically have areas of biologically-medi ated levees that mound up over the mineral shoreline. These biological banks consist of thick layers of moss, peat and muck held tightly by dense live root syst ems of woody veget ation adapted to saturated conditions. This is not simply a matter of classic bank stabilization by root s. The trees and mosses appear to work synergistically to build land and increase direct contact with the steady supply of water at the light-rich channel boundary. The biological banks encroach upon the channel, sometimes forming overhanging ledges ultimately kept in check by water pruning of the roots and cantilever failures. Self-organization of Florida streams can be rather physically based as it is in streams with alluvial controls around the wo rld, but these controls require certain thresholds in basin size, valley slope, and landscape runoff characteristics. The low elevations and seasonally-wet sub-tropical landscape promot e flood-pulse regimes for larger streams associated with significant alluvial floodscape controls. Groundwater sorting also promotes some key biogeomor phic controls. Understanding these selforganizing principles helps to make sense of how Florida str eams belong to their watersheds, even when those watersheds are genetically deranged by relictual and
324 modern geological processes. This mix of fluvial, alluvial, biological and geologic controls makes Floridas lowand mid-order streams some of the most fascinating and complex in the world. With that u nderstanding, their protection, management, and restoration must be carefully consider ed and diligently implemented using the best available science. Implications for Stream Resource Management Florida streams are stressed indire ctly by agriculture, development and groundwater pumping. Because of intense veget ation controls, the streams are slow to change and are likely to be in a very significant state of decline by the time they display obvious physical responses such as bed degradation, bank erosion and widening, floodplain soil subsidence, or planform avulsions. Furthermore, many of the streams in the state appear to already be damaged or have watersheds with characteristics demonstrated to create long-term problems for streams elsewhere in North America. The proposed classification identifies str eam channels as part of a watershed and valley system. Knowing this system, and particu lar thresholds that may invoke channel changes, should help Floridas environm ental managers make prudent decisions concerning watershed protection and mitigati on that are not only related to water quality, but that also are protective of the fundamental associations of fluvial form and hydrologic process. In addition to indirect effects in the wa tershed or springshed, many Florida streams have been ditched, filled, clear ed, mined, culverted/buried, severely overgrazed or otherwise directly destroyed or largely dimi nished from their natur al level of geomorphic complexity and associated biological function s. This study assists with information
325 necessary to figure out what to put back when someone has an opportunity to do so in such radically disturbed landscapes. The rest of this chapter summarizes potent ial strategies or particular viewpoints concerning riparian system conservation and maintenance, restor ation, and scientific technology transfer in various land use setti ngs common in Florida. These perspectives are intended to provide guidance on how this information may be useful to private and corporate land owners, conservation organi zations, and regulatory programs. This guidance merely reflects the authors opinion and is not in tended to thoroughly summarize any particular regulatory programs approach to stream protection, which is beyond the scope of the study. Some of the term s, such as restoration, maintenance, or buffer, may have specific and different meanings among federal, state, and local regulatory programs, so no attempt has been made to standardize the use of these terms on any one programs use. Any such te rms, unless specifically noted otherwise, are applied based on their general scientific use, solely in the context of the scientific disciplines employed for this study. Conservation Conservation is the deliberat e protection of a natural or restorable riparian system corridor. Conservation often requires land purchases or management costs to be derived from among competing prio rities or projects. Theref ore stream conservation is most likely to be pursued in association with other forms of conservation initiatives. Streams could be viewed as the spines of the ecosystem. They control much of the movement of water across the landscape, ce rtainly providing hydr ologic connections among a wide array of water body types in Florida.
326 This research confirmed the presence of some unique fluvial forms in Florida relying on groundwater discharge. Groundwater dependent systems such as root-step channels, baseflow corridors, and all spring runs are unlikely to remain stable or unique if the groundwater recharge of their waters heds is compromised. The conservation of groundwater regime systems starts with protec tion of the infiltration capacity of their catchments. Groundwater pumping thre sholds are also important. Most headwater streams, particularly t hose forming chains-of-wetlands, have been destroyed by ditching and clearing. Headwater streams are in t he most direct and overall extensive contact with colluvial soils, meaning whatever biogeochemistry functions that contact promot es has probably been altered extensively in Florida. Intact chains-of-wetlands surrounded by extensive nat ive buffers are likely to be worthy of conservation consideration for a wide vari ety of reasons, including endangered species management, watershed protection, upland and we tland conservation, etc. Intact loworder streams, especially if and when they connect to largely intact mid-order systems downstream, should be high priorities for acquisition and conservation. Due to the downhill nature of stream systems, the ident ification and conservation of continuous undamaged riparian corridors is a worthy objec tive. To best prioritize stream corridor conservation, it is highly beneficial to conduct watershed inventories of the riparian resources and rate th eir stability, integrity, and diversity of fluvial forms. Seldom will completely whole corridors be found, but much-needed holistic conservation and restoration strategies wi ll emerge from such assessment s. To properly conserve Floridas streams it is likely that portions of damaged riverscapes must also be acquired and subsequently restored.
327 Water Resource Management Water resource managers include water suppliers using any combination of surface water or groundwater withdrawals and surface water storage (offline or in-line reservoirs) or aquifer storage systems. Wa ter resource managers also include the designated operators of control structures used to manage water levels and flow releases of interconnected lakes, wetlands and streams (typically the six Water Management Districts or special-purpose wate r authorities like the Lake County Water Authority). Florida law provides Water Management Districts with the author ity to determine stream minimum flows and levels (MFL ) based on several metrics. Fluvial geomorphology is not explicitly one of them. However, s edimentation is one that is included and it allows some consideration of fluvial geom orphology at least for systems with even modest alluvial control. It is sel dom prioritized. In fact, water level and flow regime changes appear to often be consider ed as if they will have no effect on geomorphology. The underlying a ssumption that streams and their floodplains are static systems that will not change their shape under a changi ng flow regime can be misguided and lead to unanticipated problems that are difficult or impossible to remedy once a source of water has become institutionalized. A good example involves the changes that have occurred in the upper Peac e Rivers riparian corridor since the 1950s as a result of groundwater allo cations. Our work provides Dist rict staff with the means to assess if proposed withdrawals could lead to geomorphic change at the flow thresholds otherwise deemed appropriate based on t he metrics that have more commonly been assessed such as in-stream habitat availability and suitability.
328 Total Maximum Daily Loads (TMDLs) are not a specific land use, but affect virtually all land users. They are required by the U.S. Clean Water Act and Florida Impaired Waterbodies Rule to maintain or im prove the ambient water quality of virtually all waterbodies, including freshwater str eams. The general concept is that nature provides a certain degree of assimilative capacity for pollutants, which can be expressed as the allowable total maximum load on a daily basis. If a waterbody has been demonstrated to be impai red beyond its TMDL, then watershed solutions must be devised and implemented as a Best Managem ent Action Plan (BMAP). Many states invoke sedimentation TMDLs, viewing exce ssive sediment transport as an impairment to water quality irrespective of its chemical contamination. Sediment is viewed as a pollutant if it is associated with adver se geomorphic change to the stream channel or floodplain. So far, Florida has rarely, if ev er, invoked the TMDL pr ogram to protect the geomorphic integrity of its streams. Since many stream types require some sediment yield to maintain their integrity, excessive sedimentation reducti ons can create problems too. This is often a problem for streams dow nstream of an in-line reservoir. Sediment problems typically occur in urbanizing watersheds, often taking decades to become noticeable. Land Development Most low-impact ordinances in Flori da are centered on st ormwater quality. However, treatment volumes and techniques suitable for reducing urban pollutants in stormwater may be inappropriate to protect fluvial geomorphic integr ity. For example, we are aware of streams in Pinellas County that are well-protect ed from stormwater pollution, but that are nev ertheless massively erodi ng and threatening homesites because their balance of groundwater versus su rface water flow was altered since the
329 1950s. Most areas with a history of int ensive development should consider conducting riparian corridor integrity assessments. It is much easier and less-expensive to fix or restore streams that are in the early stages of channel evolution, before serious bed degradation and channel widening phases commence. Our research should prove helpful for identifying streams that are not in regime or are likely to become out of regime with their watersheds. Sometimes flood protection ordinances are not sufficient to protect homes from being lost to stream flow due to channel avulsions that will eventually occur within the meander belt of streams with some alluvi al floodscape controls. The meander belt of each stream should be identifi ed and development should be re stricted from within the meander corridor, even if the meander belt includes hillslopes at elevations higher than the regulatory baseflood level. This situation is most likely to occur in areas with sandhills/scrubs bordering 2nd order or higher streams and near old marine terraces. Farming and Groves Tailwater from irrigation practices c an greatly increase baseflow to nearby streams. This could ultimately affect geom orphology in streams of the flatwoods areas by changing their hydrology to be more lik e highlands or karst physiography. This could conceivably alter the forested wetl ands of the fluvial corridor, perhaps in unpredictable ways. Floridas minimum required 25 foot buffers along wetlands, including those of riparian corridors, is probably not adequate for pr otecting the biological integrity of headwater channels given that st reams in such situations often have uplands right up to the banks and their meander belt widths are o ften well in excess of 50 feet. In other words, a narrow 25 foot buffer would allow farming operations to directly encroach
330 within the meander corridor of the stream, perhaps altering its long-term capacity for self-organization and stability. Buffers in agr icultural settings should be set using the outermost limits of either the riparian wetland boundary or the ri parian meander corridor, whichever is wider. Cow-Calf Operations Clearing stream banks to promote cattl e access and overgrazing of riparian corridors can break down the banks and lead to significant erosion that not only impairs the system locally, but can create sediment smot hering downstream. Conversely, rural cow-calf properties offer tremendous opportunities to conduct stream conservation and restoration projects not feasible in urban settings. Ranchers may be able to use the riparian corridors on their property as a source of revenue, should the state ever make stream restoration an ex plicit type of mitigation activity Existing rules allow for stream impacts to be mitigated by any type of wetland, so incentives are virtually non-existent. Mining Phosphate miners are an exception to Florida stream mitigation rules, because the states mandatory reclamation rule does requi re explicit mitigation of stream length impacts on a type-for-type and linear foot-for-foot basis. In fa ct, such requirements were the main reason this study was funded by the Florida Institute of Phosphate Research. The mining companies are actively promot ing new technologies to restore Florida streams that will also be us eful in other settings. Some forms of mining that simply leave big pits in the gr ound have comparatively limited options for on-site stream reclamation, but would benefit from our research if tasked with creating offsite mitigation. C onversely, mineral sands miners working on high sandy ridges create post-reclamation la ndforms that may be the closest among all
331 Florida mining operations to putting back a landscape similar to the pre-mining condition topography. This study provides them with t ools to be able to carefully restore streams on their extensive landholdings, especially usi ng the data collected fr om highlands sites. Some titanium mines operate in areas with rare sapping, root-step streams. It is important to protect t hem from direct and indirect hydrologic impacts. Restoration Perhaps the primary use of this research will be as guidance for what to restore on properties where on-site str eams have been obliterat ed or so ubiquitously damaged that few could serve as analogues for restoratio n design. This study could be viewed as a library of reference reaches, properly placed in their landscape context for inspiring wellconceived stream creation and restoration projects. It can be used for hindcasting historical pre-disturbance conditions and for forecasting restoration outcomes. Scientific Exchange and Technology Transfer Florida streams are certai nly among the most unique in North America. However, some types of common Florida blackwater streams have clear overlap in form and process with other blackwater streams in the southeastern coastal plain of the United States, particularly those with long-durat ion overbank flooding. The biggest differences arise with considerations related to t he complicating factors related to derangement. Care must be taken when interpreting hydr obiological or geomorphic studies conducted on the riparian systems of the continental landmass versus the peninsula. There is much to be gained by comparative analyses between Florida and other southern states, but transferability should not be blindly pursued. In addition to the geologic differences arising from carbonate geology and associat ed derangement, peninsular Florida simply
332 has a much more distinct wet and dry season than most of the rest of the southeastern coastal plain. In fact, peninsular Floridas overall clim ate, especially the annual rainfall volumes and seasonality are generally more similar to that of some tropical savannas in South/Central America and nort hern Australia than to that of the neighboring states of Alabama and Georgia. It is not coincidental that Florida s least-altered pine flatwoods communities take on a more savanna-like tr ee distribution than si milar longleaf pine forest communities north of the peninsula. It is probably also not coincidental that Florida has a greater overall abundance of common vertebrate associates of tropical savannas, especially crocodilians and colonial wading birds, than most elsewhere in the southeast. It is probably just as import ant that Florida st ream ecologists and geomorphologists seek to shar e knowledge with peers worki ng in nearby coastal plain states as it is for us to do the same with those working in large sections of tropical savannas elsewhere in the Amer icas, Africa, and Australia.
333 APPENDIX A FLUVIAL GEOMORPHIC VARIABLE DESCRIPTIONS Distance dimensions are in linear feet unless otherwise st ated. Channel area measures are in square feet unless other wise stated. B asin area measures are in square miles. Volumetric flow rates ar e reported in cubic feet per second. = dimensionless variable SiteName The USGS name of the site or, if not named, our designation. UT means unnamed tributary. For exam ple, Lower Myakka UT 2 is an unnamed tributary to Lower Myakka Lake. Basin Scale Categorical Physiog : Physiographic regions. 0 = flatwoods (FW) basins have at least 50% D soils 1 = highlands (xeric, HL) have at least 45% A and C soils in combination 2 = Spring runs from karst aquifers (artesian or K). Geography : North or south peninsula (generally usi ng U.S. Interstate 4 as the divide). Gaged : If Gaged (1), the site has a long term daily discharge record meeting the study purposes. Basin Scale Continuous Drain_Area : Topographic surface drainage area in square miles. For the non-karst streams, this is close to the total surf ace water and groundwater catchment. For karst runs, this area is the local surface water basin only and it usually does not correspond to the major recharge ca tchment for the run.
334 DA_Infilt : Drainage area in square miles. This is identical to Drain_Area for non-karst streams. For karst runs, this is based on t he recharge area of the runs main spring(s). This basin therefore represents the dominant catchment for all streams in the study. A_Soil *: NRCS hydrologic soil group (HSG). Percent of DA. C_Soil *: HSG. Percent of DA. D_Soil *: HSG. Percent of DA. Wetlands *: Percent of DA. Lakes *: Percent of DA. Upland *: Percent of DA. Strah_Order : Strahler network position. Magn_Order : Cumulative number of segments upgr adient of the refe rence reach (RR). Drainage Density : Watershed longitudinal length in a straight line (L) divided by basin area (ft/sq. mile). Bifurcation Ratio *. This is average of the ratios of the number of st reams of a given order to the number of streams of the next higher order, using Strahlers ordering system. DA_L_Rel : Relief from the reach drainage areas longitudinal apex to its mouth along the DA_L line. HS_Rel : Highest relief along the reach DAs transversal apex to the valley flats elevation near the reference reach. DA_L : Longitudinal length of the drainage area from its upper divide to its mouth. Straight line.
335 DA_W : Widest part of the drainage area transverse to the longitudinal axis. This often occurs above the head of the drainage network. DA_Shape : Ratio of drainage area in square miles to basin length (DA_L) in miles (sq. miles/mile). Hillslope *: Overall valley hillslope grade, in perc ent, on either the left or right hillslope with the highest relief near the RR. Long_Slope *: Watershed gradient, in percent, from the drainage apex to the valley mouth along the DA_L line. Valley Scale Continuous Val_Seg_Rel : Valley bottom along the stream segment from the USGS quads or SWFWMD LiDAR. Val_Seg_L : Length of the valley segment with an uninterrupted open channel, between the channels US and DS waterbody junctions. Seg_Val_Slope *: Longitudinal slope of the valley segment. W_Wetland : Width of the wetland at the reference cross-section (ft). W_Wtld_W *: Width of wetland /bankfull width. MBW_W *: Ratio of meander belt width to bankfull width. WtldW_MBW *: Ratio of the wetland widt h to the meander belt width. Valley_SR *: Valley segment sinuosity ratio. This is the sinuosity of the valley segment as the valley centerline meanders across t he landscape. Some valleys appear to be very straight when compared to others, which essentially leads to a hierarchical meander of the channel/valley complex. The c hannel thalweg sinuosity is relative to the valley centerline length as calculated in this study.
336 Valley_L : Total length of the valley that is occupi ed by the reference r each, from the first transition boundary downstr eam of XS1 up to the valleys ul timate headwaters. This is at least as large, and frequently much larger than the RRs valley segment. Valley_Trans : Number of transitions along the valley. A transition is defined if a zone in the valley switches from lotic (511) to paralent ic (in line depressions) or paralotic (in line sloughs or island segments) and every time the valley switches from confined to unconfined forms. Valley_T_L : Number of valley transitions divided by the total valley length, expressed as number per linear valley mile. Zone_L : Average length of valley zones betw een their delineated b oundaries. Equals Valley_L/Valley_Trans. Zone_L_mn : Minimum zone length in the valley (ft). Zone_L_mx : Maximum zone length in the valley. Zone_L_R *: Min/Max ratio of zone lengths in the valley. Zone_W : Average flat wetland width of each zone at its typi cal midpoint among the valleys zones. Zone_W_mn : Minimum zone width in the valley Zone_W_mx : Maximum zone width in the valley Zone_W_R *: Min/Max ratio of zone widths in the valley Valley Scale Categorical Valley_Con : Categorical data classifying the shape of the valley profile, measured from the reference reach upstream to the headwaters, as 1 = concave,
337 2 = flat 3 = mixed concave/convex 4 = convex Reach Scale Continuous RR_Val_Slope *: Longitudinal slope of the reference reach. RR_HGL_Slope multiplied by Sinuousity. WClass : Reference sections bankfull width. W_Max : Maximum measured cross-section bankfull width in the RR. W_Min : Minimum measured cross-sect ion bankfull width in the RR. Wx_Wn *: Ratio of maximum to minimum width in the RR. Wstd : Standard deviation of the RR channel widths. W_RR_Mean : Average among section widths within the RR. DClass : Reference sections mean depth at bankfull stage (ft). MD_Max : Maximum mean cross-section bankfull depth in the RR. MD_Min : Minimum mean cross-secti on bankfull depth in the RR. MDx_MDn *: Ratio of maximum to minimum mean depth in the RR. MDstd : Standard deviation of t he RR channel mean depths. MD_RR_Mean : Average among section mean depths within the RR. XSAClass : Reference sections bankfull cro ss-sectional area in square feet. XSA_Max : Maximum cross-section area in the RR. XSA_Min : Minimum mean cross-se ction area in the RR. XSAx_XSAn *: Ratio of maximum to minimum area in the RR. XSAstd : Standard deviation of the RR channel cross section areas in the RR.
338 XSA_M : Mean area of all RR cross-sections. TWD : Bankfull thalweg depth of the reference section. POOLD : Maximum thalweg depth in the RR. TOB_W : Width of channel at bank height (top-o f-bank) at the classification section. RIFD : Minimum thalweg depth in the RR. POOL_RIF *: Ratio of max pool to minimum riffle thalweg depths. TWDstd : Standard deviation of the RR channel thalweg depths. TWD_Mean : Average RR thalweg depth. POOL_TWD_Mean : Average pool thalweg d epths within the RR. RIF_TWD_Mean : Average riffle thalweg depths within the RR. POOL_RIF_Mean *: Ratio of mean pool TW depth to mean riffle TW depth in the RR. BkHt : Obvious top-of-bank inflection at or above the alluvial tr ansport bankfull stage, reported as a depth above thalweg elevation. EntrRatio *: Rosgen entrenchment ratio fo r the classification section. BHW_BKFW *: Ratio of bank height width to bankfull width. WDRatio *: Ratio of bankfull width divided by mean bankfull depth at the reference section. Sinuosity : RR sinuosity ratio (thalweg length divided by valley length). MBW : Meander beltwidth for the RR (ft). Bends_L : Average distance between bends. Bend_No : No. of bends per 100 length stream. Bend_12W : Average number of bends /12*bankfull widths. RC_Min : Radius of curvature of the tightest bend.
339 RC_Mean : Mean radius of cu rvature of the RR. Pool_L : Average distance between pools (a pool must be >1.0 feet deep at TW & at least 1.5x mean classifica tion sections average depth). Pool_12W : Average number of poolss/12*bankfull widths. WP : Wetted perimeter at bankfull. HR : Hydraulic radius at bankfull. HGL_S *: Water surface slope within the refer ence reach, using the best available data (1st a measured slope within 75% of bankfull stage, 2nd a slope derived from fitting a line to reliable bankfull indicators, 3rd a slope derived from fitting a line tangential to the riffle crests). Man_n : Mannings friction factor. Back-calcul ated from measured discharges within 75% of bankfull stage. If such data are unavaila ble, mean values derived from similar stream conditions were used. Vel_BKF : Mean channel velocity at bankfull. 1st from measured values. 2nd from calculated. Q_BKF : Best calculation of bankfull discharge (1st from direct velocity-area measurement, 2nd from slope-velocity equation). Shear_BKF : Max bankfull shear stress calculated at bankfull discharge. Pow_BKF : Stream power as calculated at bankfull discharge. Pow_BKF_W : Unit power per bankfull bed width. FLOOD_D : Thalweg depth at the lichen line or best available flood field indicator (e.g. living bank inflection in seepage systems).
340 FLOOD_W : Width of floodplain at the flood depth indicated by a lichen line or moss collar if no lichen line. Taken at the classification section. n_FLOOD : Mannings n for the flood section. Vel_FLOOD : Mean conveyance velocity at flood discharge (fps). Q_FLOOD : Calculated discharge at the FLOOD stage, using the valley segment slope. Pow_FLOOD : Stream power calculated for flood depth discharge. Pow_FLOOD_W : Power per unit width of the floodplain. FLOOD_TWD *: Ratio of FLOOD depth to bankfull depth at the thalweg. FLOOD_BkHt *: Ratio of the FLOOD depth to the top of bank height at the thalweg. FLOODW_BKFW *: Ratio of floodplain (e.g. lichen) width to bankfull width. Q_FLOOD_BKF *: Ratio of flood to bankfull discharge. Pow_FLOOD_BKF *: Ratio of flood to bankfull stream power. Vel_FLOOD_BKF *: Ratio of mean flood to bankfull cross-section velocity. RcW *: Mean RR radius of curvature divided by mean RR bankfull width. RcWTight *: Tightest bend in RR. Minimum Rc/average RR W. BHRatio *: Ratio of thalweg bank height to thalweg bankfull depths. Reach Scale Categorical CLASS_ROS : Rosgen Level II channel classification. Valley_Conf : Categorical (ordinal, so it can be us ed classification clusters if desired): 0 = seepage ravine (lateral seepage slope flanks the top of bank) 1 = confined valley (upland FLUCCS within most of the MBW) 2 = well-adjusted valley (MBW is dominated by wetland FLUCCS, but is confined on both sides by an upland hillslope. Most outer bends are within 2 bankfull widths of an upland)
341 3 = unconfined valley (stream meander s through a broad valley flat with outer bends fully contained by wetlands at least 2 bankfull widths beyond the outer bends) Reach Scale Riparian Ecol ogy and Soils Categorical MBW_FLUCCS : Dominant FDOT (1999) FLUCCS within the meander belt. HS_FLUCCS : Dominant FDOT (1999) FLUCCS on the hillslope or other adjacent geomorphic feature adjacent to the meander belt (could simp ly be an extension of the valley flat in an unconfined system). Seg_US_BND : Waterbody FLUCCS upstream of the stream segment (511, 6xx). Seg_DS_BND : Waterbody FLUCCS downstream of the stream segment (511, 6xx). BKF_IND : Dominant, most reliable bankfull field indicator. Bed_upper_sed : Dominant sediment texture on the channel bed. Bank_sed_LB : Dominant sediment texture on the LB. Bank_sed_RB : Dominant sediment texture on the RB. MBW_sed : Dominant sediment texture in the meander belt. HS_sed : Dominant sediment texture in the co rridor just outside the meander beltwidth. Bio_Banks (ordinal, can be used in some numerical tests): Categorical: 4 = Ubiquitous (>90%) 3 = Dominant (>50%) 2 = Present (<50%) 1 = Rare (<10%) Reach Scale Riparian Ecology and Soils Continuous No_Bed_Alluv : Number of alluvial c hannel features in the RR. No_FP_Alluv : Number of alluvial floodpl ain features in the RR. No_Tot_Alluv : Total number of alluvial featur es in the RR channel and floodplain
342 Canopy_CL *: Canopy closure at the c hannel center facing US and DS. Canopy_Ttl *: Canopy closure at the reference se ction facing US, DS, LB, RB at the channel center. In-Stream Habitat Pa tch Scale Continuous LWD_Count : Logs per 100 feet of stream length. Sand *: % of total frequency encountered on t he RR substrate. Not percent area. Mud *: % of total frequency encountered on t he RR substrate. Not percent area. Leaf *: % of total frequency encountered on t he RR substrate. Not percent area. FWD *: % of total frequency encountered on t he RR substrate. Not percent area. Aveg *: % of total frequency encountered on t he RR substrate. Not percent area. Rock *: % of total frequency encountered on t he RR substrate. Not percent area. SAV *: % of total frequency encountered on t he RR substrate. Not percent area. Root *: % of total frequency encountered on t he RR substrate. Not percent area. Root_Steps : No. per 100 channel length. Pool_No : No. of pools per 100 length stream. Shallow_Pools *: %No. of pools 1 to 2 feet deep at TW. Medium_Pools *: %No. 2 to 4 feet deep at TW. Deep_Pools *: %No. >4 feet deep at TW. WP : Wetted perimeter at bankfull.
343 APPENDIX B HYDROLOGIC VARIABLE DESCRIPTIONS Distance dimensions are in linear feet unless otherwise stat ed. Area measures are in square feet unless other wise stated. V olumetric flow rates are reported in cubic feet per second. XerSoil %A+C soils in the watershed. DA_Main Primary drainage area. Surface area watershed for blackwater streams and springshed for karst systems. DA_Surf Surface area watershed for spring runs. QBKF Bankfull discharge. QFLOOD Flood channel discharge (a s defined in Appendix A). QBKF_PDS Average annual bankfull flow frequency calculated by partial duration series. QFLOOD_PDS Average annual flood channel flow frequency calculated by partial duration series. QBKF_Exc Percent of time bankfull discharge is equaled or exceeded. QFLOOD_Exc Percent of time flood channel di scharge is equaled or exceeded. SFSlope Seasonal flow slope of the dimensionl ess flow exceedance curve between the 15th and 85th percentiles. RO % rainfall that becomes stream discharge. Jan_Ma12 Mean January flow. CV_Jan_Ma24 Standard deviation of January flow divided by the mean January flow.
344 Feb_Ma13 Mean February flow. CV_Feb_Ma25 Standard deviation of January flow divided by the mean February flow. Mar_Ma14 Mean March flow. CV_Mar_Ma26 Standard deviation of January flow divided by the mean March flow. Apr_Ma15 Mean April flow CV_Apr_Ma27 Standard deviation of January flow divided by the mean April flow. May_Ma16 Mean May flow. CV_May_Ma28 Standard deviation of January flow divided by the mean May flow. Jun_Ma17 Mean June flow. CV_Jun_Ma29 Standard deviation of January flow divided by the mean June flow. Jul_Ma18 Mean July flow. CV_Jul_Ma30 Standard deviation of January flow divided by the mean July flow. Aug_Ma19 Mean August flow. CV_Aug_Ma31 Standard deviation of January flow divided by the mean August flow. Sep_Ma20 Mean September flow. CV_Sep_Ma32 Standard deviation of January flow divided by the mean September flow. Oct_Ma21 Mean October flow. CV_Oct_Ma33 Standard deviation of January flow divided by the mean October flow. Nov_Ma22 Mean November flow. CV_Nov_Ma34 Standard deviation of January flow divided by the mean November flow. Dec_Ma23 Mean December flow.
345 CV_Dec_Ma35 Standard deviation of January flow divided by the mean December flow. d1Min_DL1 Mean of the series of minimum 1-day moving average flow for each year divided by the drainage area. CV_1dMin_DL6 Coefficient of variation of the se ries of minimum 1-day moving average flow for each year divided by the drainage area. d3Min_DL2 Mean of the series of minimum 3-day moving average flow for each year divided by the drainage area. CV_3dMin_DL7 Coefficient of variation of the se ries of minimum 3-day moving average flow for each year divided by the drainage area. d7Min_DL3 Mean of the series of minimum 7-day moving average flow for each year divided by the drainage area. CV_7dMin_DL8 Coefficient of variation of the se ries of minimum 7-day moving average flow for each year divided by the drainage area. d30Min_DL4 Mean of the series of minimum 30day moving average flow for each year divided by the drainage area. CV_30dMin_DL9 Coefficient of variation of t he series of minimum 30-day moving average flow for each year di vided by the drainage area. d90Min_DL5 Mean of the series of minimum 90day moving average flow for each year divided by the drainage area. CV_90dMin_DL10 Coefficient of variation of t he series of minimum 90-day moving average flow for each year di vided by the drainage area.
346 d1Max_DH1 Mean of the series of maximum 1-day moving average flow for each year divided by the drainage area. CV_1dMax_DH6 Coefficient of variation of the series of maximum 1-day moving average flow for each year di vided by the drainage area. d3Max_DH2 Mean of the series of maximum 3-day moving average flow for each year divided by the drainage area. CV_3dMax_DH7 Coefficient of variation of the series of maximum 3-day moving average flow for each year di vided by the drainage area. d7Max_DH3 Mean of the series of maximum 7-day moving average flow for each year divided by the drainage area. CV_7dMax_DH8 Coefficient of variation of the series of maximum 7-day moving average flow for each year di vided by the drainage area. d30Max_DH4 Mean of the series of maximum 30-day moving average flow for each year divided by the drainage area. CV_30dMax_DH9 Coefficient of variation of t he series of maximum 30-day moving average flow for each year di vided by the drainage area. d90Max_DH5 Mean of the series of maximum 90-day moving average flow for each year divided by the drainage area. CV_90dMax_DH10 Coefficient of variation of t he series of maximum 90-day moving average flow for each year di vided by the drainage area. ZeroDays_DL18 Mean number of days with zero flow per year. CV_ZeroDays_DL19 Coefficient of variation of num ber of days per year with zero flow.times 100.
347 Baseflow_ML17 Baseflow calculated as mean of t he series of minimum 7-day moving average flows for each year divided by the mean annual flow for that year. CV_BaseFlow_ML18 Coefficient of variability for Baseflow_ML17. DateMin_TL1 Mean of the series of Julian dates on which the minimum flow occurred for each year. CV_DateMin_TL2 Coefficient of variation for Date Min_TL1. In Julian date units, but not to be interpreted as an actual day. DateMax_TH1 Mean of the series of Julian dates on which the maximum flow occurred for each year. CV_DateMax_TH2 Coefficient of variation for Date Max_TH1. In Julian date units, but not to be interpreted as an actual day. NumLoPulse__FL1 Mean of the number of flow events per year below the 25th percentile. CV_NumLoPulse__FL2 Coefficient of variation for NumLoPulse_FL1 times 100. DurLoPulse_DL16 Median of the series of average pulse durations for flow events below the 25th percentile (calculated for entire record) of each year. CV_DurLoPulse_DL17 Coefficient of variation of the yearly average low pulse durations multiplied by 100. NumHiPulse__FH1 Mean of the number of flow events per year above the 75th percentile. CV_NumHiPulse__FH2 Coefficient of variation fo r NumHiPulse_FH1 times 100. DurHiPulse_DH15 Median of the series of average pulse durations for flow events above the 75th percentile (calculated for entire record) of each year.
348 CV_DurHiPulse_DH16 Coefficient of variation of the yearly average high pulse durations multiplied by 100. RiseRate_RA1 Mean of the series of change in flow values for days in which the change is positive for the entire record. CV_RiseRate_RA2 Coefficient of variation for RiseRate_RA1 times 100. FallRate_RA3 Mean of the series of change in flow values for days in which the change is negative for the entire record. CVFallRate_RA4 Coefficient of variation for FallRate_RA3 times 100. Reversals_RA8 Mean of the series of the num ber of days each year when the change in flow from one day to the next changes direction. CV_Reversals_RA9 Coefficient of variation of Reversals_RA8 tiimes 100. Oct_PMAR The monthly average flow for October multiplied by the number of days in the month, all divided by the total runoff volume for the year. Nov_PMAR The monthly average flow for Novem ber multiplied by the number of days in the month, all divided by the total runoff volume for the year. Dec_PMAR The monthly average flow for Decem ber multiplied by the number of days in the month, all divided by the total runoff volume for the year. Jan_PMAR The monthly average flow for January multiplied by the number of days in the month, all divided by the total runoff volume for the year. Feb_PMAR The monthly average flow for February multiplied by the number of days in the month, all divided by the to tal runoff volume for the year. Mar_PMAR The monthly average flow for March multiplied by the number of days in the month, all divided by the total runoff volume for the year.
349 Apr_PMAR The monthly average flow for April mu ltiplied by the number of days in the month, all divided by the tota l runoff volume for the year. May_PMAR The monthly average flow for May multiplied by the number of days in the month, all divided by the tota l runoff volume for the year. Jun_PMAR The monthly average flow for June mu ltiplied by the number of days in the month, all divided by the total runoff volume for the year. Jul_PMAR The monthly average flow for July mult iplied by the number of days in the month, all divided by the tota l runoff volume for the year. Aug_PMAR The monthly average flow for August multiplied by the number of days in the month, all divided by the total runoff volume for the year. Sep_PMAR The monthly average flow for September multiplied by the number of days in the month, all divided by the total runoff volume for the year. Drainage_Area Square miles. MAR Mean annual runoff (average daily flow times 365.24). Flash_# RA10 Mean of the series of maximum fl ows for each year divided by the mean discharge value for the entire record. Skew MA59 Total skewness. The mean of the to tal record minus the median of the total record all divided by t he mean of the total record. CV_of_Daily_Flows_Ma3 Mean of the coefficients of variation for each year. Monthly_Skew_Ma40 The mean of the monthly flows minus the median of the monthly flows, all divided by medi an of the monthly flows. Ann_Runoff_Ma41 The mean of the mean annual flows for each year divided by drainage area.
350 Variability of Annual Flows Ma44 The 90th percentile flow minus the 10th all divided by the median of t he annual mean flows. CV_Monthly_Min_ML13 Standard deviation for the minimu m monthly flows of the entire flow record divided by the mean, times 100. Mn_Ann_Qmin_ML14 The mean of the series of mini mum flow ratios divided by the median flow for each year. Mn_Ann_Qmin_ML22 The mean of the series of mini mum flows for each year divided by drainage area. Oct_Mn_Qmax_Mh1 Mean of the series of maximum flows in October for each year. CV_Oct_Mh1 Coefficient of variation for Oct_Mn_Qmax_Mh1 for each year. May_Mn_Qmax_Mh8 Mean of the series of maximum flows in May for each year. CV_May_Mh8 Coefficient of variation for May_Mn_Qmax_Mh8 for each year. Mn_25_XCD_MH17 The 25% exceedance value for the entire record divided by the median flow for the entire record. Mn_Ann_Qmax_MH20 Mean of the series of maximum flows for each year divided by drainage area. LoPulse_Freq_Fl3 Num_Floods_FH11 Flood frequency of the average num ber of flow events above the 1.67 year annual return interval per year. The index is the mean of this series. Mn_Ann_30d_min_DL13 Annual minimum 30 day flow di vided by the median flow for period of record. Mn_Ann_7d_max_DH12 Annual maximum 7-day flow di vided by the median flow for the entire record.
351 Mn_Ann_30d_Max_DH13 Annual maximum 30-day flow divided by the median flow for the entire record. Nonflood_Predict_TH3 Maximum number of days in a row during which no flood (Q1.67 ) has ever occurred throughout the record di vided by the number of days pr year. BS1_Flash_# RA11 Bledsoe/Sanborn flash index. Sum of the absolute differences between the flow of each day and the next day divided by the total number of days in the record minus one, all divided by mean flow of the entire record. Colwell_Pred_TA2 Colwells predictability index. Tqmean Total number of days in t he flow record that are above the mean of the record divided by the total number of days in the record. P100_Q1.67 DH26 Total number of days in the reco rd that are at least at the Q1.67 value. P75_Q1.67 DH27 Total number of days in the record that are at least 75% of the Q1.67 value. P50_Q1.67 DH28 Total number of days in the record that are at least 50% of the Q1.67 value. Q_Mean Daily mean flow for the record. Q_Median Median daily flow for the record.
352 APPENDIX C STREAM CROSS SECTIONS LEGEND MBW is meander belt width. All elevations and distances are on an ar bitrary vertical and horizontal datum. The 3-digit numerical codes are Level III Florida Land Use and Cover Codes (FLUCCS) from FDOT (1999) as follows: 321Palmetto Prairies 411Pine Flatwoods 412Longleaf Pine-Xeric Oak 413Sand Pine 414PineMesic Oak 415Mixed Pine (combined xeric and mesic pines and hardwoods) 421Xeric Oak 425Temperate Hardwood 427Live Oak 432Sand Live Oak 434-Hardwood-Conifer Mixed 511Stream Channels (with alluvial beds) 611Bay Swamps 615Stream and Lake Swamps (Bottomland) 616Inland Ponds and Sloughs 617Mixed Wetland Hardwoods 621-Cypress 624-Cypress-PineCabbage Palm (may lack cypress) 625Hydric Pine Flatwoods 626Hydric Pine Savanna (this was used for Cutthroat Grass Seeps) 630Wetland Forest Mixed (eve n mix of cypress and hardwoods) 641Freshwater Marsh 643Wet Prairie
353 SPRING RUNS Figure C-1. Alexander Spring Run valley. Figure C-2. Alexander Spring Run channel. 0 5 10 15 20 25 30 35 40 45 50 55 60 0200400600800100012001400160018002000 Distance (ft)Elevation (ft) MBW Colluvial Sand Colluvial Sand Sand, Shell, & Gyttja Biological Banks (Peat) Biological Banks (Peat) 511 434 630 412 412 0 5 10 15 20 25 30 320340360380400420440460480500520540560580600620640660680 Distance (ft)Elevation (ft) MBW (500') 511 630 630 Sand, Shell, & Gyttja Biological Banks (Peat) Biological Banks (Peat) Ubiquitous SAV Meadow Colluvial Sand
354 Figure C-3. Alligator Spring Run valley. Figure C-4. Alligator Spring Run channel. 30 35 40 45 50 55 60 65 70 75 80 85 90 0100200300400500600700800 Distance (ft)Elevation (ft) Colluvial Sand Sand, Shell, & Gyttja Biological Banks (Peat) Biological Banks (Peat) Muck Mucky Sand Colluvial Sand MBW 511 615 434 434 615 35 40 45 50 55 60 450 470 490 510 530 550 570 590 Distance (ft)Elevation (ft) MBW 511 615 617 Sand, Shell, & Gyttja Biological Banks (Peat) Biological Banks (Peat) Muck Mucky Sand Mucky Sand Sporadic SAV
355 Figure C-5. Cedar Head Run channel and valley. Figure C-6. Forest Run channel and valley. 90 95 100 105 110 115 0102030405060708090100110 Distance (ft)Elevation (ft) MBW Colluvial Sand Sapric Muck Gyttja & Shell Biological Banks (Muck) Biological Banks (Muck) Limestone Outcrop 511 617 434 434 617 95 100 105 110 230240250260270280290300310320330 Distance (ft)Elevation (ft) Mucky Sand Sand with Mucky Inclusions A lluvial Sand Sand with Mucky Inclusions MBW 611 611 511
356 Figure C-7. Gum Slough Run valley. Figure C-8. Gum Slough Run channel. 30 35 40 45 50 55 60 65 70 75 80 85 90 40090014001900240029003400390044004900 Distance (ft)Elevation (ft) MBW Sand & Mucky Sand Sand, Shell, & Gyttja Biological Bank Muck Muck 615 434 434 511 615 35 40 45 50 55 60 3900392039403960398040004020404040604080410041204140416041804200 Distance (ft)Elevation (ft) MBW 615 617 511 617 Sand & Mucky Sand Sand, Shell, & Gyttja Biological Bank (Common) Muck SAV Patches
357 Figure C-9. Juniper Run channel. Figure C-10. Kittridge Run channel. 90 95 100 105 110 115 02 04 06 08 0 Distance (ft)Elevation (ft) 615 (641) 617 511 617 MBW (130') Peaty Muck Sand Center & Gyttja Flanks Biological Bank (Dominant) Sa p ric Muck SAV Patches Biological Bank (Dominant) 95 97 99 101 103 105 05101520253035404550 Distance (ft)Elevation (ft) MBW 511 611 617 Sandy Muck Sapric Muck Sand & Detritus Biological Bank (Peaty Muck)
358 Figure C-11. Little Levy Blue Run channel. Figure C-12. Morman Branch UT channel. 90 95 100 105 110 115 0102030405060708090100110 Distance (ft)Elevation (ft) MBW Colluvial Sand Sapric Muck Mucky Peat Biological Banks (Muck) Biological Banks (Peat) 617 434 434 511 617 97 99 101 103 105 107 051015202530 Distance (ft)Elevation (ft) MBW Peat & Sapric Muck Sapric Muck Sand & Detritus Biological Bank (Peaty Muck) Biological Bank (Peaty Muck) 511 611 611
359 Figure C-13. Rock Spring Run channel. Figure C-14. Silver Glen UT valley. 90 95 100 105 110 115 0102030405060708090100110120130140 Distance (ft)Elevation (ft) MBW (180') 617 434 511 617 Mucky Sand Sapric Muck Sand Biological Banks (Peat) Biological Banks (Peat & Muck) Peat SAV Patches 95 100 105 110 115 120 01 02 03 04 05 06 07 08 09 0 Distance (ft)Elevation (ft) MBW Colluvial Sand Alluvial Sand Biological Banks (Peat) Biological Banks (Peat) Colluvial Sand 511 425 425 432
360 Figure C-15. Weeki Wachee River valley. Figure C-16. Weeki Wachee River channel. -10 -5 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 020040060080010001200140016001800200022002400260028003000 Distance (ft)Elevation (ft) MBW Mucky Sand Alluvial Sand & Organic Layers Biological Bank (peaty muck) Colluvial Sand Mucky Sand Colluvial Sand 511 434 434 412 412 615 (641) -5 0 5 10 15 20 600 650 700 750 800 850 900 Distance (ft)Elevation (ft) MBW Mucky Sand Sand & Organic Layers Biological Bank (Peaty Muck) Mucky Sand Alluvial Sand & Detritus Sporadic SAV Biological Bank (Peaty Muck) 511 434 617 641 (615) 615
361 FLATWOODS AND HIGHLANDS STREAMS Figure C-17. Alexander UT2 channel and valley. Figure C-18. Bell Creek channel. 90 95 100 105 110 0510152025303540455055 Distance (ft)Elevation (ft) MBW Colluvial Sand Alluvial Sand & Detrital Layers Colluvial Sand 411 (617) 411 411 511 95 100 105 110 05101520253035404550556065 Distance (ft)Elevation (ft) Muck Alluvial Sand & Detritus Biological Bank (Muck) Muck MBW (70') 611 511 611
362 Figure C-19. Bell Creek UT channel and valley. Figure C-20. Blackwater Creek valley. 95 100 105 110 020406080100120140 Distance (ft)Elevation (ft) MBW Mucky Sand Colluvial Sand Alluvial Sand Colluvial Sand 617 (411) 411 411 511 10 15 20 25 30 35 40 45 50 55 60 65 70 105011501250135014501550165017501850195020502150 Distance (ft)Elevation (ft) MBW 511 615 434 434 615 Colluvial Sand Muck & Sand Layers Muck & Sand Layers Alluvial Sand & Detritus Colluvial Sand
363 Figure C-21. Blackwater Creek channel. Figure C-22. Blues Creek channel and valley. 15 20 25 30 35 40 150015201540156015801600162016401660168017001720 Distance (ft)Elevation (ft) 615 511 615 MBW (250') Alluvial Sand & Detritus 6" Muck Over Sand Layer 6" Muck Over Sand Layer 90 95 100 105 110 0102030405060 Distance (ft)Elevation (ft) Alluvial Sand, Gravel, & Stif f Clay Colluvial Sand Colluvial Sand MBW (130') 511 414 414
364 Figure C-23. Bowlegs Creek valley. Figure C-24. Bowlegs Creek channel. 90 95 100 105 110 115 120 125 130 135 140 145 150 5006007008009001000110012001300140015001600170018001900200021002200230024002500 Distance (ft)Elevation (ft) MBW Alluvial Sand & Detritus Colluvial Sand Muck & Sand Layers Colluvial Sand Muck & Sand Layers 511 641 (615) 434 434 411 641 (615) 95 100 105 110 115 120 15001520154015601580160016201640166016801700 Distance (ft)Elevation (ft) Alluvial Sand & Detritus 6" Muck Over Sand Layer 6" Muck Over Sand Layer 615 511 615 MBW
365 Figure C-25. Carter Creek channel and valley. Figure C-26. Catfish Creek valley. 95 100 105 110 115 120 0102030405060708090100 Distance (ft)Elevation (ft) 511 413 413 617 617 Alluvial Sand & Detritus Colluvial Sand Muck Colluvial Sand MBW (120') 65 70 75 80 85 90 95 100 105 110 115 120 125 01002003004005006007008009001000 Distance (ft)Elevation (ft) MBW Alluvial Sand & Detritus Colluvial Sand 6" Peat Over Sand Layer Colluvial Sand Colluvial Sand 511 621 434 434 413 413 617
366 Figure C-27. Catfish Creek channel. Figure C-28. Coons Bay channel. 70 75 80 85 90 95 300320340360380400420 Distance (ft)Elevation (ft) 511 621 617 /61 MBW (240') Alluvial Sand & Detritus 6" Peat Over Sand Layer Sand & Muck Layers 95 100 105 110 051015202530354045505560 Distance (ft)Elevation (ft) Sand & Detritus Colluvial Sand Colluvial Sand MBW 511 617 (411) 411 411
367 Figure C-29. Cow Creek channel. Figure C-30. Cypress Slash UT valley. 95 100 105 110 0102030405060708090100110120130140 Distance (ft)Elevation (ft) Sand & Detritus Soft Mucky Loam Colluvial Sand MBW 511 615 425 95 100 105 0102030405060708090 Distance (ft)Elevation (ft) MBW 511 321 421 421 321 Alluvial Sand & Detritus Colluvial Sand Colluvial Sand
368 Figure C-31. Cypress Slash UT channel. Figure C-32. East Fork M anatee UT1 valley and channel. 95 100 105 110 05101520253035404550 Distance (ft)Elevation (ft) Colluvial Sand Alluvial Sand & Detritus Colluvial Sand Colluvial Sand MBW 0 511 421 321 321 421 95 100 105 110 050100150200250 Distance (ft)Elevation (ft) MBW Alluvial Sand & Loam Biological Bank (Muck) Colluvial Sand Colluvial Sand Colluvial Sand Mucky Sand 617 411 411 511 617
369 Figure C-33. East Fork M anatee UT2 channel and valley. Figure C-34. Fisheating Creek valley. 95 100 105 110 050100150200250 Distance (ft)Elevation (ft) MBW 617 625 411 511 617 Alluvial Sand & Detritus Mucky Sand Mucky Sand Mucky Sand Colluvial Sand 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 55006000650070007500800085009000950010000105001100011500 Distance (ft)Elevation (ft) MBW 511 621 411 411 0 Alluvial Sand Muck Over Sand Layer Mucky Sand, Sand Islands, Muck Oxbow Colluvial Sand Colluvial Sand
370 Figure C-35. Fisheat ing Creek channel. Figure C-36. Goldhead Branc h channel and valley. 25 30 35 40 45 886088808900892089408960898090009020904090609080 Distance (ft)Elevation (ft) MBW (350') 511 621 621 0 Alluvial Sand Alluvial Sand Muck Over Sand Layer Mucky Sand Stagnant at Bankfull Flow 95 100 105 110 0102030405060708090100110120 Distance (ft)Elevation (ft) MBW 0 511 421 611 611 421 6" Peat Layer over Sand Root Steps & Sand Colluvial Sand Colluvial Sand Biological Bank (Peat) Biological Bank (Peat)
371 Figure C-37. Grasshopper Slough channel. Figure C-38. Grassy Creek UT valley. 95 100 105 110 050100150 Distance (ft)Elevation (ft) Mucky Sand Colluvial Sand Alluvial Sand & Detritus Alluvial Sand & Muck Layers MBW 511 624 625 434 434 95 100 105 110 020406080100120140160180200 Distance (ft)Elevation (ft) MBW Sandy Muck Mucky Sand Alluvial Sand & Detritus 630 626 626 511 630
372 Figure C-39. Grassy Creek UT channel. Figure C-40. Hammock Branch channel and valley. 95 100 105 110 60708090100110120 Distance (ft)Elevation (ft) MBW 630 630 511 Sandy Muck Mucky Sand Alluvial Sand & Detritus 95 100 105 110 115 020406080100120140 Distance (ft)Elevation (ft) MBW 615 434 434 511 615 Alluvial Sand & Detritus Colluvial Sand Sapric Muck Colluvial Sand
373 Figure C-41. Hillsborough UT channel. Figure C-42. Horse Creek valley. 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 0102030405060 Distance (ft)Elevation (ft) MBW 615 511 615 5" Alluvial Sand over Stiff Clay Muck Floodline is from Hillsborough River Floodplain Muck 0 5 10 15 20 25 30 35 40 45 50 55 60 020040060080010001200140016001800200022002400 Distance (ft)Elevation (ft) MBW 511 615 411 411 421 616 427 Colluvial Sand Colluvial Sand Alluvial Sand
374 Figure C-43. Horse Creek channel. Figure C-44. Jack Creek channel and valley. 5 10 15 20 25 30 35 1250 1300 1350 1400 1450 1500 1550 1600 Distance (ft)Elevation (ft) MBW (360') 615 511 427 Alluvial Sand Alluvial Sand Levee Alluvial Sand Colluvial Sand 10" Alluvial Sand over Soft Loam 95 100 105 110 020406080100120140160180 Distance (ft)Elevation (ft) MBW Alluvial Sand & Detritus Muck Colluvial Sand Muck Colluvial Sand 511 617 413 611 413
375 Figure C-45. Jumping Gully channel and valley. Figure C-46. Lake June-In-Winter UT channel and valley. 95 100 105 110 115 01020304050 Distance (ft)Elevation (ft) MBW 511 415 415 Alluvial Sand & Detritus Colluvial Sand Colluvial Sand 95 100 105 110 115 051015202530354045 Distance (ft)Elevation (ft) MBW 511 611 611 Root Steps & Sand Mucky Sand Mucky Sand Biological Bank (Peat) Biological Bank (Peat)
376 Figure C-47. Little Haw Creek channel. Figure C-48. Livingston Creek valley. 0 5 10 15 20 25 30 3500 3550 3600 3650 3700 Distance (ft)Elevation (ft) MBW 615 511 615 Alluvial Sand Alluvial Sand Alluvial Sand 55 60 65 70 75 80 85 90 95 100 105 110 115 100012001400160018002000220024002600 Distance (ft)Elevation (ft) MBW 511 615 413 413 427 427 Alluvial Sand Colluvial Sand Muck Over Sand Layer Colluvial Sand
377 Figure C-49. Livingston Creek channel. Figure C-50. Lower Myakka UT2 channel and valley. 55 60 65 70 75 80 85 204020602080210021202140216021802200222022402260 Distance (ft)Elevation (ft) Alluvial Sand Muck Over Sand Layer Colluvial Sand MBW (260') 511 615 427 427 95 100 105 110 020406080100 Distance (ft)Elevation (ft) MBW 511 617 425 425 617 Alluvial Sand Colluvial Sand Colluvial Sand
378 Figure C-51. Lower Myakka UT3 channel and valley. Figure C-52. Lowry Lake UT channel and valley. 95 97 99 101 103 105 107 109 02 04 06 08 01 0 0 Distance (ft)Elevation (ft) MBW Alluvial Sand Colluvial Sand Colluvial Sand 511 624 321 411 624 95 100 105 110 115 0102030405060 Distance (ft)Elevation (ft) MBW Colluvial Sand Colluvial Sand Mucky Sand Mucky Sand Root Steps & Sand Biological Banks (Peat) Biological Banks (Peat) 511 611 412 412 611
379 Figure C-53. Manatee River valley. Figure C-54. Manatee River channel. 30 35 40 45 50 55 60 65 70 75 80 85 90 50010001500200025003000350040004500 Distance (ft)Elevation (ft) Colluvial Sand Colluvial Sand Sand Shoals over Bed Clay Alluvial Sand & Detritus Colluvial Sand MBW 511 615 434 411 411 434 427 35 40 45 50 55 60 65 2800282028402860288029002920294029602980300030203040306030803100 Distance (ft)Elevation (ft) Colluvial Sand Colluvial Sand Sand Shoals over Bed Clay Alluvial Sand & Detritus Alluvial Sand & Detritus MBW 511 615 427 434 434 615
380 Figure C-55. Manatee UT channel and valley. Figure C-56. Morgan Hole Creek channel. 90 95 100 105 110 6065707580859095100 Distance (ft)Elevation (ft) MBW 511 414 414 Colluvial Sand Colluvial Sand Root Steps & Sand Sporadic Biological Banks (Peat) Sporadic Biological Banks (Peat) 95 100 105 110 050100150200250 Distance (ft)Elevation (ft) Colluvial Sand Colluvial Sand Alluvial Sand A lluvial Sand MBW 643 321 411 511 643
381 Figure C-57. Moses Creek valley. Figure C-58. Moses Creek channel. 0 5 10 15 20 25 30 35 40 45 50 55 60 01002003004005006007008009001000 Distance (ft)Elevation (ft) MBW 511 615 427 411 411 615 434 434 Colluvial Sand Colluvial Sand Alluvial Sand & Detritus Soft Loamy Muck Colluvial Sand 5 10 15 20 25 30 650 670 690 710 730 750 770 790 Distance (ft)Elevation (ft) MBW Alluvial Sand & Detritus Soft Loamy Muck Colluvial Sand Alluvial Sand Alluvial Sand 511 615 615 434
382 Figure C-59. Ninemile Creek channel and valley. Figure C-60. Rice Creek valley. 90 95 100 105 110 051015202530354045 Distance (ft)Elevation (ft) 511 611 611 MBW (75') Muck Muck Root Steps & Sand Biological Banks (Peat) Biological Banks (Peat) -10 -5 0 5 10 15 20 25 30 35 40 45 50 010020030040050060070080090010001100120013001400 Distance (ft)Elevation (ft) MBW 511 615 411 411 615 Alluvial Sand & Detritus Colluvial Sand Colluvial Sand A lluvial Silt & Sandy Silt Layers A lluvial Silt & Sandy Silt Layers
383 Figure C-61. Rice Creek channel. Figure C-62. Santa Fe River valley. 0 5 10 15 20 800820840860880900920940960980100010201040 Distance (ft)Elevation (ft) MBW 511 615 615 Alluvial Sand & Detritus A lluvial Silt & Sandy Silt Layers A lluvial Silt & Sandy Silt Layers 90 95 100 105 110 115 120 125 130 135 140 145 150 050100150200250300350400450500550600650700750800850900 Distance (ft)Elevation (ft) Colluvial Sand Sand Shoals over Limestone Alluvial Sand & Detrital Layers Colluvial Sand Alluvial Sand MBW 511 615 434 434 427 621
384 Figure C-63. Santa Fe River channel. Figure C-64. Shiloh Creek channel and valley. 95 100 105 110 115 120 125 120 140 160 180 200 220 Distance (ft)Elevation (ft) Sand Shoals over Limestone Alluvial Sand Alluvial Sand 511 615 615 427 MBW (150') 95 100 105 110 115 0102030405060 Distance (ft)Elevation (ft) 511 414 414 MBW Colluvial Sand 6" Sand Layer over Stiff Loam Colluvial Sand
385 Figure C-65. Snell Creek channel and valley. Figure C-66. South Fork Black Creek channel. 95 100 105 110 0102030405060708090100 Distance (ft)Elevation (ft) Sapric Muck Sapric Muck 6" Alluvial Sand over Peat and Sand Layers Biological Bank (Peat) MBW 611 611 511 95 100 105 110 020406080100120140160180200220 Distance (ft)Elevation (ft) Soft Loamy Muck Alluvial Sand & Organic Layers Alluvial Sand A lluvial Sand & Organic Layers Soft Loamy Muck MBW 615 615 511
386 Figure C-67. Ten Mile channel and valley. Figure C-68. Tiger Creek valley. 95 100 105 110 020406080100120140160180 Distance (ft)Elevation (ft) Mucky Silt & Sandy Loam Layers Alluvial Sand & Detrital Layers Colluvial Sand Mucky Silt & Sand Layers Colluvial Loamy Sand MBW 615 434 511 615 411 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125 130 135 140 145 150 0100200300400500600700 Distance (ft)Elevation (ft) MBW 511 615 413 413 611 434 Colluvial Sand A lluvial Sand Sapric Muck Colluvial Sand Colluvial Sand over Hardpan
387 Figure C-69. Tiger Creek channel. Figure C-70. Tiger UT channel. 60 65 70 75 80 85 90 300320340360380400420440460480500520540 Distance (ft)Elevation (ft) MBW A lluvial Sand & Detritus Sapric Muck Colluvial Sand Colluvial Sand over Hardpan 511 615 413 434 611 615 434 95 100 105 110 010203040506070 Distance (ft)Elevation (ft) Sapric Muck Sapric Muck Sand and Organic Layers Biological Bank (Peat) MBW 611 611 511
388 Figure C-71. Tuscawilla UT channel and valley. Figure C-72. Tyson Creek channel and valley. 90 95 100 105 110 115 0510152025303540 Distance (ft)Elevation (ft) MBW Colluvial Sand Colluvial Sand Root Steps & Sand Biological Banks (Peat) Biological Banks (Peat) 511 611 413 413 611 95 100 105 110 020406080100120140160180200220240 Distance (ft)Elevation (ft) Sapric Muck Alluvial Sand & Detritus Sapric Muck MBW 621 621 511
389 Figure C-73. Wekiva Forest UT channel and valley. 95 100 105 110 0102030405060708090100 Distance (ft)Elevation (ft) Colluvial Sand Mucky Sand Sand & Detritus MBW 617 617 511
390 APPENDIX D CLUSTER ANALYSES DENDOGRAMS C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ East Fork Manatee UT 1 6 Bell Creek 25 Wekiva Forest UT 23 Hillsborough River UT 11 Coons Bay Branch 4 Jack Creek 32 Bell Creek UT 1 Snell Creek 40 Tiger Creek UT 43 East Fork Manatee UT 2 7 Grassy Creek UT 10 Lower Myakka River UT 2 14 Lower Myakka River UT 3 15 Little Levy Blue Spring Run 52 Lowry Lake UT 36 Forest Spring Run 48 Kittridge Spring Run 51 Morman Branch UT Spring Run 53 Silver Glen UT Spring Run 55 Cypress Slash UT 29 Tuscawilla Lake UT 44 Jumping Gully 33 Ninemile Creek 38 Lake June-In-Winter UT 34 Manatee River UT 37 Gold Head Branch 30 Shiloh Run near Alachua 39 Fisheating Creek at Palmdale 8 Little Haw Creek near Seville 13 Santa Fe River near Graham 20 Weeki Wachee River 56 Horse Creek near Arcadia 12 Manatee River near Myakka Head 16 Blackwater Creek near Cassia 26 Livingston Creek near Frostproof 35 Gum Slough Spring Run 49 Juniper Spring Run 50 Alligator Spring Run 46 Cedar Head Spring Run 47 Bowlegs Creek near Ft Meade 3 South Fork Black Creek 41 Carter Creek near Sebring 27 Catfish Creek near Lake Wales 28 Tiger Creek near Babson Park 42 Rock Spring Run 54 Grasshopper Slough Run 9 Morgan Hole Creek 17 Blues Creek near Gainesville 2 Alexander UT 2 24 Hammock Branch 31 Cow Creek 5 Moses Creek near Moultrie 18 Tenmile Creek 21 Rice Creek near Springside 19 Tyson Creek 22 Alexander Spring Run 45 Figure D-1. Dendogram for all sites on all variables.
391 Dendrogram using Ward Method Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ Alligator Spring Run 24 Cedar Head Spring Run 25 Gum Slough Spring Run 26 Catfish Creek near Lake Wales 18 Tiger Creek near Babson Park 22 Rock Spring Run 28 Juniper Spring Run 27 Rice Creek near Springside 11 Tyson Creek 14 Bowlegs Creek near Ft Meade 2 South Fork Black Creek 21 Cow Creek 3 Hammock Branch 19 Moses Creek near Moultrie 10 Tenmile Creek 13 Grasshopper Slough Run 5 Morgan Hole Creek 9 Carter Creek near Sebring 17 Blues Creek near Gainesville 1 Alexander UT 2 15 Fisheating Creek at Palmdale 4 Little Haw Creek near Seville 7 Blackwater Creek near Cassia 16 Livingston Creek near Frostproof 20 Horse Creek near Arcadia 6 Manatee River near Myakka Head 8 Santa Fe River near Graham 12 Weeki Wachee River 29 Alexander Spring Run 23 Figure D-2. Dendogram for large sites on all variables.
392 Dendrogram using Ward Method Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ East Fork Manatee UT 1 3 Bell Creek 10 Wekiva Forest UT 9 Hillsborough River UT 6 Tiger Creek UT 21 Coons Bay Branch 2 Jack Creek 13 Snell Creek 20 Bell Creek UT 1 Grassy Creek UT 5 Lower Myakka River UT 2 7 Forest Spring Run 23 East Fork Manatee UT 2 4 Lower Myakka River UT 3 8 Little Levy Blue Spring Run 25 Kittridge Spring Run 24 Morman Branch UT Spring Run 26 Lowry Lake UT 16 Silver Glen UT Spring Run 27 Cypress Slash UT 11 Tuscawilla Lake UT 22 Jumping Gully 14 Ninemile Creek 18 Lake June-In-Winter UT 15 Manatee River UT 17 Gold Head Branch 12 Shiloh Run near Alachua 19 Figure D-3. Dendogram for small sites on all variables.
393 Dendrogram using Ward Method Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ East Fork Manatee UT 2 7 Grassy Creek UT 10 Hillsborough River UT 11 Lower Myakka River UT 2 14 Lower Myakka River UT 3 15 Bell Creek UT 1 Rice Creek near Springside 19 Tyson Creek 22 Bowlegs Creek near Ft Meade 3 Grasshopper Slough Run 9 Morgan Hole Creek 17 Cow Creek 5 Moses Creek near Moultrie 18 Tenmile Creek 21 Coons Bay Branch 4 Wekiva Forest UT 23 East Fork Manatee UT 1 6 Blues Creek near Gainesville 2 Horse Creek near Arcadia 12 Manatee River near Myakka Head 16 Santa Fe River near Graham 20 Fisheating Creek at Palmdale 8 Little Haw Creek near Seville 13 Figure D-4. Dendogram for flatwoods sites on all variables.
394 Dendrogram using Ward Method Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ Alexander UT 2 1 Hammock Branch 8 Jumping Gully 10 Ninemile Creek 15 Bell Creek 2 Jack Creek 9 Snell Creek 17 Tiger Creek UT 20 Gold Head Branch 7 Lowry Lake UT 13 Shiloh Run near Alachua 16 Lake June-In-Winter UT 11 Manatee River UT 14 Cypress Slash UT 6 Tuscawilla Lake UT 21 Carter Creek near Sebring 4 Catfish Creek near Lake Wales 5 South Fork Black Creek 18 Tiger Creek near Babson Park 19 Blackwater Creek near Cassia 3 Livingston Creek near Frostproof 12 Figure D-5. Dendogram for highlands sites on all variables.
395 Dendrogram using Ward Method Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ Kittridge Spring Run 7 Morman Branch UT Spring Run 9 Silver Glen UT Spring Run 11 Forest Spring Run 4 Little Levy Blue Spring Run 8 Alligator Spring Run 2 Cedar Head Spring Run 3 Gum Slough Spring Run 5 Rock Spring Run 10 Juniper Spring Run 6 Weeki Wachee River 12 Alexander Spring Run 1 Figure D-6. Dendogram for ka rst sites on all variables.
396 Dendrogram using Ward Method Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ East Fork Manatee UT 2 7 Grassy Creek UT 10 Coons Bay Branch 4 East Fork Manatee UT 1 6 Lake June-In-Winter UT 34 Manatee River UT 37 Cypress Slash UT 29 Wekiva Forest UT 23 Jack Creek 32 Alexander UT 2 24 Bell Creek 25 Blues Creek near Gainesville 2 Morgan Hole Creek 17 Bell Creek UT 1 Tuscawilla Lake UT 44 Moses Creek near Moultrie 18 Tenmile Creek 21 Grasshopper Slough Run 9 Tyson Creek 22 Hillsborough River UT 11 Lower Myakka River UT 3 15 Lower Myakka River UT 2 14 Cow Creek 5 Little Levy Blue Spring Run 52 Hammock Branch 31 Lowry Lake UT 36 Morman Branch UT Spring Run 53 Snell Creek 40 Kittridge Spring Run 51 Gold Head Branch 30 Shiloh Run near Alachua 39 Silver Glen UT Spring Run 55 Alligator Spring Run 46 Forest Spring Run 48 Weeki Wachee River 56 Tiger Creek UT 43 Gum Slough Spring Run 49 Juniper Spring Run 50 Cedar Head Spring Run 47 Rock Spring Run 54 Jumping Gully 33 Ninemile Creek 38 Carter Creek near Sebring 27 Catfish Creek near Lake Wales 28 Fisheating Creek at Palmdale 8 Horse Creek near Arcadia 12 Bowlegs Creek near Ft Meade 3 Manatee River near Myakka Head 16 South Fork Black Creek 41 Santa Fe River near Graham 20 Livingston Creek near Frostproof 35 Blackwater Creek near Cassia 26 Little Haw Creek near Seville 13 Tiger Creek near Babson Park 42 Alexander Spring Run 45 Rice Creek near Springside 19 Figure D-7. Dendogram for all sites on watershed variables.
397 Dendrogram using Ward Method Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ East Fork Manatee UT 1 6 Hillsborough River UT 11 Bell Creek 25 Lower Myakka River UT 3 15 Cedar Head Spring Run 47 Tiger Creek UT 43 Bell Creek UT 1 Jumping Gully 33 Coons Bay Branch 4 Alexander UT 2 24 Cypress Slash UT 29 Lower Myakka River UT 2 14 Jack Creek 32 Grassy Creek UT 10 Little Levy Blue Spring Run 52 Grasshopper Slough Run 9 Wekiva Forest UT 23 Morman Branch UT Spring Run 53 Silver Glen UT Spring Run 55 East Fork Manatee UT 2 7 Lake June-In-Winter UT 34 Ninemile Creek 38 Lowry Lake UT 36 Forest Spring Run 48 Gold Head Branch 30 Manatee River UT 37 Tuscawilla Lake UT 44 Blues Creek near Gainesville 2 Shiloh Run near Alachua 39 Bowlegs Creek near Ft Meade 3 South Fork Black Creek 41 Tenmile Creek 21 Rock Spring Run 54 Weeki Wachee River 56 Alligator Spring Run 46 Kittridge Spring Run 51 Cow Creek 5 Moses Creek near Moultrie 18 Carter Creek near Sebring 27 Catfish Creek near Lake Wales 28 Morgan Hole Creek 17 Hammock Branch 31 Snell Creek 40 Tiger Creek near Babson Park 42 Alexander Spring Run 45 Gum Slough Spring Run 49 Juniper Spring Run 50 Horse Creek near Arcadia 12 Manatee River near Myakka Head 16 Blackwater Creek near Cassia 26 Livingston Creek near Frostproof 35 Fisheating Creek at Palmdale 8 Little Haw Creek near Seville 13 Rice Creek near Springside 19 Tyson Creek 22 Santa Fe River near Graham 20 Figure D-8. Dendogram for all sites on valley variables.
398 Dendrogram using Ward Method Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ Wekiva Forest UT 23 Bell Creek 25 Hammock Branch 31 Alexander UT 2 24 Jumping Gully 33 Hillsborough River UT 11 East Fork Manatee UT 1 6 Morgan Hole Creek 17 Cow Creek 5 Cedar Head Spring Run 47 Tyson Creek 22 Coons Bay Branch 4 Lower Myakka River UT 2 14 Tiger Creek UT 43 Little Levy Blue Spring Run 52 Snell Creek 40 Lowry Lake UT 36 Forest Spring Run 48 Jack Creek 32 East Fork Manatee UT 2 7 Grassy Creek UT 10 Lake June-In-Winter UT 34 Ninemile Creek 38 Bell Creek UT 1 Kittridge Spring Run 51 Morman Branch UT Spring Run 53 Lower Myakka River UT 3 15 Silver Glen UT Spring Run 55 Gold Head Branch 30 Manatee River UT 37 Shiloh Run near Alachua 39 Cypress Slash UT 29 Tuscawilla Lake UT 44 Fisheating Creek at Palmdale 8 Little Haw Creek near Seville 13 Manatee River near Myakka Head 16 Santa Fe River near Graham 20 Horse Creek near Arcadia 12 Blackwater Creek near Cassia 26 Weeki Wachee River 56 Alligator Spring Run 46 Gum Slough Spring Run 49 Catfish Creek near Lake Wales 28 Tiger Creek near Babson Park 42 Juniper Spring Run 50 Rock Spring Run 54 Bowlegs Creek near Ft Meade 3 Tenmile Creek 21 Rice Creek near Springside 19 South Fork Black Creek 41 Moses Creek near Moultrie 18 Blues Creek near Gainesville 2 Grasshopper Slough Run 9 Carter Creek near Sebring 27 Livingston Creek near Frostproof 35 Alexander Spring Run 45 Figure D-9. Dendogram for all sites on reach variables.
399 Dendrogram using Ward Method Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ Jack Creek 32 Forest Spring Run 48 Lowry Lake UT 36 Morman Branch UT Spring Run 53 Silver Glen UT Spring Run 55 Kittridge Spring Run 51 Bell Creek 25 Snell Creek 40 Ninemile Creek 38 Grassy Creek UT 10 Lower Myakka River UT 3 15 Coons Bay Branch 4 Tiger Creek UT 43 Bell Creek UT 1 Wekiva Forest UT 23 Lower Myakka River UT 2 14 Manatee River UT 37 Shiloh Run near Alachua 39 Blues Creek near Gainesville 2 Santa Fe River near Graham 20 East Fork Manatee UT 1 6 Hillsborough River UT 11 Jumping Gully 33 Lake June-In-Winter UT 34 Tuscawilla Lake UT 44 Gold Head Branch 30 Tenmile Creek 21 Hammock Branch 31 Alexander UT 2 24 Cow Creek 5 Moses Creek near Moultrie 18 East Fork Manatee UT 2 7 Tyson Creek 22 Alligator Spring Run 46 Cedar Head Spring Run 47 Rice Creek near Springside 19 Blackwater Creek near Cassia 26 Little Levy Blue Spring Run 52 Rock Spring Run 54 Weeki Wachee River 56 Gum Slough Spring Run 49 Alexander Spring Run 45 Manatee River near Myakka Head 16 South Fork Black Creek 41 Horse Creek near Arcadia 12 Livingston Creek near Frostproof 35 Fisheating Creek at Palmdale 8 Tiger Creek near Babson Park 42 Juniper Spring Run 50 Little Haw Creek near Seville 13 Grasshopper Slough Run 9 Carter Creek near Sebring 27 Catfish Creek near Lake Wales 28 Morgan Hole Creek 17 Bowlegs Creek near Ft Meade 3 Cypress Slash UT 29 Figure D-10. Dendogram for all sites on habitat patch variables.
400 Dendrogram using Ward Method Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ East Fork Manatee UT 1 6 Bell Creek 25 Coons Bay Branch 4 Wekiva Forest UT 23 Jack Creek 32 Blues Creek near Gainesville 2 Grasshopper Slough Run 9 Morgan Hole Creek 17 Moses Creek near Moultrie 18 Santa Fe River near Graham 20 Cow Creek 5 Hillsborough River UT 11 Lower Myakka River UT 2 14 Alexander UT 2 24 Hammock Branch 31 South Fork Black Creek 41 Bell Creek UT 1 Grassy Creek UT 10 East Fork Manatee UT 2 7 Lower Myakka River UT 3 15 Little Levy Blue Spring Run 52 Snell Creek 40 Tiger Creek near Babson Park 42 Carter Creek near Sebring 27 Catfish Creek near Lake Wales 28 Tiger Creek UT 43 Rice Creek near Springside 19 Tyson Creek 22 Horse Creek near Arcadia 12 Manatee River near Myakka Head 16 Tenmile Creek 21 Blackwater Creek near Cassia 26 Fisheating Creek at Palmdale 8 Little Haw Creek near Seville 13 Bowlegs Creek near Ft Meade 3 Livingston Creek near Frostproof 35 Alligator Spring Run 46 Cedar Head Spring Run 47 Gum Slough Spring Run 49 Rock Spring Run 54 Weeki Wachee River 56 Juniper Spring Run 50 Alexander Spring Run 45 Lowry Lake UT 36 Kittridge Spring Run 51 Forest Spring Run 48 Morman Branch UT Spring Run 53 Silver Glen UT Spring Run 55 Cypress Slash UT 29 Tuscawilla Lake UT 44 Manatee River UT 37 Shiloh Run near Alachua 39 Jumping Gully 33 Ninemile Creek 38 Gold Head Branch 30 Lake June-In-Winter UT 34 Figure D-11. Dendogram for all sites on dimensionless and unit variables.
401 Dendrogram using Ward Method Rescaled Distance Cluster Combine C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ Lowry Lake UT 36 Kittridge Spring Run 51 Forest Spring Run 48 Morman Branch UT Spring Run 53 Silver Glen UT Spring Run 55 Gold Head Branch 30 Shiloh Run near Alachua 39 Lake June-In-Winter UT 34 Manatee River UT 37 Cypress Slash UT 29 Tuscawilla Lake UT 44 Rock Spring Run 54 Weeki Wachee River 56 Alexander Spring Run 45 Alligator Spring Run 46 Cedar Head Spring Run 47 Gum Slough Spring Run 49 Juniper Spring Run 50 East Fork Manatee UT 2 7 Grassy Creek UT 10 Bell Creek UT 1 Lower Myakka River UT 2 14 Lower Myakka River UT 3 15 Little Levy Blue Spring Run 52 Carter Creek near Sebring 27 Catfish Creek near Lake Wales 28 Snell Creek 40 Tiger Creek UT 43 Jumping Gully 33 Ninemile Creek 38 Blues Creek near Gainesville 2 Grasshopper Slough Run 9 Coons Bay Branch 4 East Fork Manatee UT 1 6 Wekiva Forest UT 23 Bell Creek 25 South Fork Black Creek 41 Alexander UT 2 24 Hammock Branch 31 Cow Creek 5 Hillsborough River UT 11 Rice Creek near Springside 19 Tyson Creek 22 Blackwater Creek near Cassia 26 Tiger Creek near Babson Park 42 Tenmile Creek 21 Little Haw Creek near Seville 13 Moses Creek near Moultrie 18 Fisheating Creek at Palmdale 8 Bowlegs Creek near Ft Meade 3 Morgan Hole Creek 17 Horse Creek near Arcadia 12 Manatee River near Myakka Head 16 Santa Fe River near Graham 20 Jack Creek 32 Livingston Creek near Frostproof 35 Figure D-12. Dendogram for all sites on dimensionless variables.
402 APPENDIX E PRINCIPAL COMPONENTS ANALYSIS TABLES Table E-1. All cases with all variables, rotated component matrix 1 2 3 4 5 Mean Reach Riffle TW Depth (ft) .924 Mean Reach TW D (ft) .921 Riffle TW Depth (ft) .919 Mean Reach Pool TW Depth (ft) .907 Max Reach Mean Depth (ft) .901 Mean Reach Average Depth (ft) .900 Min Reach TW Depth (ft) .899 Thalweg Flood Depth .896 Max Reach Pool TW Depth (ft) .896 Classification Bankfull Depth (ft) .892 Bankfull Hydraulic Radius .873 Min Reach Mean Depth (ft) .869 Low Bank Height (ft) .859 Pools >4 ft Deep (%) .835 Bankfull Discharge (cfs) .829 Flood Discharge (cfs) .762 Total Alluvial Features .757 Watershed Length (ft) .746 No. of Alluvial Valley Features .744 Stream Power (lb/s) .739 Bankfull Mean Velocity (ft/s) .722 Flood Stream Power (lb/s) .718 Total Valley Length (ft) .712 Pools 1-2 ft Deep (%) -.699 Primary Basin Area (sq. miles) .696 Watershed Width (ft) .689 Network Magnitude .687 Reach Standard Deviation of XS Area .679 Drainage Area (sq. mile) .657 No. of Alluvial Bed Features .643 Watershed Area to Length Ratio (sq. mi/mile) .642 Reach Standard Deviation of TW D .620 Bifurcation Ratio .614
403 Table E-1. Continued 1 2 3 4 5 Reach Standard Deviation of Mean D .581 Mean Valley Zone Length (ft) .535 No. Valley Transitions .531 Ratio of Flood to Bankfull Velocity Max-Min Ratio of Zone Lengths Watershed Relief on Longitudinal Axis (ft) Bends per 100 LF Maximum Valley Zone Width (ft) Minimum Reach Width (ft) .967 Mean Reach Width (ft) .963 Min Reach Radius of Curvature (ft) .962 Mean Reach RC (ft) .959 Classification Bank full Width (ft) .959 Minimum Reach XS Area (ft) .938 Maximum Reach Width (ft) .934 Mean Reach XS Area .930 Classification Cross-Section Area (sq. ft) .926 Maximum Reach XS Area (ft) .904 Bankfull Wetted Perimeter .904 Width at Bank Height .885 Mean Distance Between Pools (ft) .820 W/D Ratio .812 Percent Substrate as SAV .810 Mean Distance Between Bends (ft) .741 Meander Beltwidth (ft) .629 .674 Reach Standard Deviation of Width .618 Mean Rc/W Ratio .573 Percent Canopy Closure Percent Canopy Closure US DS A+C Soils -.725 Percent A-Soil -.721 Percent D-Soil .710 Ratio of Flood to Bankfull Power .652 Ratio of Flood to Bankfull Flow .641 Width Ratio of Floodplain and Bankfull Channels .627 Flood/Bank Height Depth Ratio .571
404 Table E-1. Continued 1 2 3 4 5 Percent Wetlands .563 Valley Width at Flood Line .562 Valley Segment Sinuousity Ratio -.540 Bends per 12 Bankfull Widths Bankfull Slope (ft/ft) .879 Reach Valley Slope (%) .871 Valley Segment Slope (%) .832 Root Steps per Stream Length (no./100ft) .822 Bankfull Shear Stress (psi) .779 Ratio of Max Min Reach TW Depths .779 Unit floodplain power .642 Ratio of Mean Reach Pool and Riffle TW Depths .627 Unit Stream Power .589 Manning's n Bankfull Mean Depth Max/Min Ratio Valley Relief in the Segment (ft) MBW to W Ratio Width of Riparian Wetland (ft) .808 Ratio of Wetland Width to Beltwidth .771 Wetland to Bankfull Width Ratio .770 Minimum Valley Zone Width (ft) .685 Mean Valley Zone Width (ft) .535 Flood Mean Velocity (fps) Bankfull Width Max/Min Ratio
405 Table E-2. Large sites with all variables, rotated component matrix 1 2 3 4 5 Riffle TW Depth (ft) .944 Mean Reach Riffle TW Depth (ft) .929 Mean Reach Average Depth (ft) .925 Min Reach TW Depth (ft) .919 Mean Reach TW D (ft) .908 Max Reach Mean Depth (ft) .901 Classification Bankfull Depth (ft) .888 Low Bank Height (ft) .871 Min Reach Mean Depth (ft) .865 Bankfull Discharge (cfs) .858 Mean Reach Pool TW Depth (ft) .841 Stream Power (lb/s) .831 Max Reach Pool TW Depth (ft) .805 Pools >4 ft Deep (%) .803 Pools 2-4 ft Deep (%) -.802 Bankfull Hydraulic Radius .797 Thalweg Flood Depth .768 Bankfull Mean Velocity (ft/s) .641 Flood Stream Power (lb/s) .578 .518 Primary Basin Area (sq. miles) .540 Watershed Length (ft) .537 Reach Standard Deviation of XS Area .508 Classification Bank full Width (ft) .979 Minimum Reach Width (ft) .979 Mean Reach Width (ft) .973 Min Reach Radius of Curvature (ft) .968 Mean Reach RC (ft) .964 Mean Distance Between Pools (ft) .961 Mean Reach XS Area .954 Minimum Reach XS Area (ft) .953 Bankfull Wetted Perimeter .950 Classification Cross-Section Area (sq. ft) .948 Maximum Reach Width (ft) .945 Maximum Reach XS Area (ft) .938 W/D Ratio .928 Width at Bank Height .892 Percent Substrate as SAV .763
406 Table E-2. Continued 1 2 3 4 5 Mean Distance Between Bends (ft) .734 Meander Beltwidth (ft) .718 Mean Rc/W Ratio .603 Reach Standard Deviation of Width .581 Manning's n .519 No. of Alluvial Bed Features Percent A-Soil -.836 A+C Soils -.814 Percent D-Soil .780 No. of Alluvial Valley Features .721 Ratio of Flood to Bankfull Power .704 Flood/Bank Height Depth Ratio .684 Total Valley Length (ft) .683 Valley Segment Sinuosity Ratio -.678 Ratio of Flood to Bankfull Flow .668 Bifurcation Ratio .654 Total Alluvial Features .643 Flood/Bankfull Depth Ratio .643 Watershed Area to Length Ratio (sq. mi/mile) .631 Width Ratio of Floodplain and Bankfull Channels .629 .593 Flood Discharge (cfs) .615 .625 Maximum Valley Zone Length (ft) .625 Network Magnitude .602 Watershed Width (ft) .600 Drainage Area (sq. mile) .584 Percent Wetlands .572 Bends per 12 Bankfull Widths .526 -.538 Ratio of Flood to Bankfull Velocity -.530 Basin Drainage Density (LF/SM) .509 No. Valley Transitions MBW to W Ratio Width Ratio of Bank Height to Bankfull Bankfull Slope (ft/ft) .866 Reach Valley Slope (%) .807 Bends per 100 LF .798 Bankfull Shear Stress (psi) .752 Pools 1-2 ft Deep (%) .731
407 Table E-2. Continued 1 2 3 4 5 Root Steps per Stream Length (no./100ft) .731 Valley Segment Slope (%) .675 Unit Stream Power .586 .622 Unit floodplain power .525 Percent Substrate as Root Mass Ratio of Max Min Reach TW Depths .774 Reach Standard Deviation of TW D .767 Reach Standard Deviation of Mean D .722 Ratio of Mean Reach Pool and Riffle TW Depths .680 Wetland to Bankfull Width Ratio .674 Bankfull Mean Depth Max/Min Ratio .673 Width of Riparian Wetland (ft) .655 Valley Width at Flood Line .561 .621 Minimum Valley Zone Width (ft) .603 Ratio of Wetland Width to Beltwidth .557 Bankfull Width Max/Min Ratio .525 Flood Mean Velocity (fps) Tightest Bend Ratio
408 Table E-3. Small sites with a ll variables, rotated component matrix 1 2 3 4 5 Mean Reach Pool TW Depth (ft) .947 Mean Reach Average Depth (ft) .939 Mean Reach TW D (ft) .934 Max Reach Mean Depth (ft) .927 Classification Bankfull Depth (ft) .882 Min Reach Mean Depth (ft) .873 Riffle TW Depth (ft) .848 Mean Reach Riffle TW Depth (ft) .843 Max Reach Pool TW Depth (ft) .828 Pools 1-2 ft Deep (%) -.825 Pools 2-4 ft Deep (%) .825 Bankfull Hydraulic Radius .823 Reach Standard Deviation of TW D .703 -.603 Thalweg Flood Depth .703 Low Bank Height (ft) .703 Min Reach TW Depth (ft) .677 Reach Standard Deviation of Mean D .674 Network Magnitude .600 W/D Ratio -.574 .514 Mean Distance Between Pools (ft) -.556 Bifurcation Ratio .545 Ratio of Flood to Bankfull Flow -.519 Ratio of Flood to Bankfull Power Percent Substrate as Emergent Veg Meander Beltwidth (ft) Max-Min Ratio of Zone Lengths Total Valley Length (ft) Pools per 12 Bankfull Width Max-Min Ratio of Zone Widths Sinuosity Ratio Mean Reach Width (ft) .926 Maximum Reach Width (ft) .864 Classification Bank full Width (ft) .849 Reach Standard Deviation of Width .828 Maximum Reach XS Area (ft) .822 Minimum Reach Width (ft) .807 Reach Standard Deviation of XS Area .777
409 Table E-3. Continued 1 2 3 4 5 Mean Reach RC (ft) .759 Mean Reach XS Area .523 .732 Width at Bank Height .690 Minimum Reach XS Area (ft) .550 .649 Classification Cross-Section Area (sq. ft) .523 .646 Min Reach Radius of Curvature (ft) .627 Percent Substrate as Bare Muck/Silt .614 Bends per 100 LF -.586 Percent Substrate as SAV .556 Mean Distance Between Bends (ft) .548 Bankfull Width Max/Min Ratio .544 -.522 Logs per Stream Length (no./100 ft) .530 No. of Alluvial Bed Features -.508 Total Alluvial Features A+C Soils .860 Percent A-Soil .853 Percent D-Soil -.851 Watershed Relief on Longitudinal Axis (ft) .804 Basin Grade (ft/ft) .751 Total Valley Relief on Wide Section (ft) .742 Flood/Bank Height Depth Ratio -.706 Valley Width at Flood Line -.684 Width Ratio of Floodplain and Bankfull Channels -.647 Percent Wetlands -.620 Hillslope Grade (ft/ft) .517 .610 Bank Height Ratio .600 Ratio of Flood to Bankfull Velocity .566 Entrenchment Ratio -.548 Percent Upland .532 Mean Valley Zone Length (ft) .507 Minimum Valley Zone Length (ft) .504 Maximum Valley Zone Length (ft) Ratio of Max Min Reach TW Depths -.851 Ratio of Mean Reach Pool and Riffle TW Depths -.754 Valley Segment Slope (%) -.713 Reach Valley Slope (%) -.660 Root Steps per Stream Length (no./100ft) -.654
410 Table E-3. Continued 1 2 3 4 5 Maximum Valley Zone Width (ft) .652 Ratio of Wetland Width to Beltwidth .646 Mean Valley Zone Width (ft) .626 Bankfull Slope (ft/ft) -.618 Tightest Bend Ratio -.605 Width of Riparian Wetland (ft) .605 Wetland to Bankfull Width Ratio .578 Bankfull Area Max/Min Ratio -.572 Bankfull Mean Depth Max/Min Ratio -.551 Manning's n -.543 MBW to W Ratio -.523 No. Valley Transitions Flood Stream Power (lb/s) .951 Stream Power (lb/s) .926 Unit Stream Power .922 Unit floodplain power .896 Bankfull Mean Velocity (ft/s) .828 Flood Mean Velocity (fps) .825 Percent Substrate as Bare Rock .713 Valley Relief in the Segment (ft) .709 Bankfull Discharge (cfs) .696 Flood Discharge (cfs) .625 Bankfull Shear Stress (psi) .587
411 Table E-4. Flatwoods sites with a ll variables, rotated component matrix 1 2 3 4 5 Classification Cross-Section Area (sq. ft) .962 Mean Reach XS Area .961 Maximum Reach XS Area (ft) .959 Watershed Length (ft) .943 Flood Discharge (cfs) .918 Reach Standard Deviation of XS Area .915 Minimum Reach Width (ft) .914 Minimum Reach XS Area (ft) .912 Mean Reach Pool TW Depth (ft) .910 Meander Beltwidth (ft) .903 Mean Reach Width (ft) .903 Max Reach Pool TW Depth (ft) .902 Bankfull Discharge (cfs) .900 Mean Reach TW D (ft) .891 Pools >4 ft Deep (%) .890 Riffle TW Depth (ft) .885 No. of Alluvial Valley Features .882 Mean Reach Riffle TW Depth (ft) .878 Primary Basin Area (sq. miles) .876 Drainage Area (sq. mile) .876 Maximum Reach Width (ft) .869 Total Alluvial Features .865 Min Reach TW Depth (ft) .862 Thalweg Flood Depth .856 Classification Bankfull Width (ft) .848 Total Valley Length (ft) .839 Max Reach Mean Depth (ft) .831 Network Magnitude .818 Mean Reach Average Depth (ft) .813 Mean Distance Between Bends (ft) .809 Watershed Width (ft) .806 Mean Reach RC (ft) .801 Stream Power (lb/s) .797 Min Reach Radius of Curvature (ft) .777 Classification Bankfull Depth (ft) .766 .501 Flood Stream Power (lb/s) .755 Width at Bank Height .750
412 Table E-4. Continued 1 2 3 4 5 Watershed Area to Length Ratio (sq. mi/mile) .740 .529 Low Bank Height (ft) .737 Bankfull Hydraulic Radius .734 .515 Valley Width at Flood Line .731 -.507 Reach Standard Deviation of TW D .724 Min Reach Mean Depth (ft) .715 Width Ratio of Floodplain and Bankfull Channels .709 Reach Standard Deviation of Width .709 Mean Distance Between Pools (ft) .706 Mean Valley Zone Width (ft) .704 Bankfull Wetted Perimeter .703 -.503 Reach Standard Deviation of Mean D .688 Maximum Valley Zone Width (ft) .662 No. of Alluvial Bed Features .643 No. Valley Transitions .632 -.581 Bifurcation Ratio .632 Maximum Valley Zone Length (ft) .626 Bankfull Mean Velocity (ft/s) .616 .603 Watershed Relief on Longitudinal Axis (ft) .593 Pools 1-2 ft Deep (%) -.578 Ratio of Flood to Bankfull Velocity -.543 Percent Canopy Closure US DS -.524 Percent Canopy Closure Max-Min Ratio of Zone Lengths Unit Stream Power .819 Flood Mean Velocity (fps) .797 Bank Height Ratio .637 Bankfull Shear Stress (psi) .612 Ratio of Wetland Width to Beltwidth -.608 Floodplain n -.600 Unit floodplain power .596 Width of Riparian Wetland (ft) .502 -.563 Minimum Valley Zone Length (ft) .706 Percent Wetlands .691 Percent Upland -.683 Valley Segment Slope (%) -.557 -.658 Bankfull Slope (ft/ft) -.656
413 Table E-4. Continued 1 2 3 4 5 Reach Valley Slope (%) -.650 Mean Valley Zone Length (ft) .649 Ratio of Flood to Bankfull Flow .623 Flood/Bank Height Depth Ratio .621 Ratio of Flood to Bankfull Power .615 Ratio of Max Min Reach TW Depths -.589 Bends per 100 LF -.557 -.569 Manning's n -.534 Flood/Bankfull Depth Ratio .526 Ratio of Mean Reach Pool and Riffle TW Depths -.502 Transitions per Valley Length (no./mile) Tightest Bend Ratio -.770 Mean Rc/W Ratio -.720 Bankfull Mean Depth Max/Min Ratio .661 Pools per 12 Bankfull Width .632 Basin Drainage Density (LF/SM) -.612 Percent Substrate as SAV .583 Width Ratio of Bank Height to Bankfull .540 Max-Min Ratio of Zone Widths -.535 Logs per Stream Length (no./100 ft) .520 Percent Lakes .503 Bends per 12 Bankfull Widths Bankfull Width Max/Min Ratio MBW to W Ratio Pools 2-4 ft Deep (%) Percent A-Soil .713 Percent Substrate as Bare Rock .663 Percent D-Soil -.634 Valley Relief in the Segment (ft) .610 A+C Soils .568 Bankfull Area Max/Min Ratio -.554 Length of the Valley Segment (ft) .512 Hillslope Grade (ft/ft) Percent Substrate as Leaf Packs Total Valley Relief on Wide Section (ft)
414 Table E-5. Highlands sites with a ll variables, rotated component matrix 1 2 3 4 5 Maximum Valley Zone Length (ft) .924 Classification Bankfull Depth (ft) .912 Max Reach Pool TW Depth (ft) .896 Riffle TW Depth (ft) .893 Mean Reach Pool TW Depth (ft) .892 Min Reach Mean Depth (ft) .891 Mean Reach TW D (ft) .886 Mean Reach Riffle TW Depth (ft) .876 Bankfull Discharge (cfs) .873 Total Valley Length (ft) .855 Mean Reach Average Depth (ft) .848 Min Reach TW Depth (ft) .848 Max-Min Ratio of Zone Lengths .846 Minimum Reach XS Area (ft) .842 Pools >4 ft Deep (%) .836 Flood Discharge (cfs) .824 Bankfull Hydraulic Radius .822 Low Bank Height (ft) .819 Mean Reach XS Area .816 .508 Classification Cross-Section Area (sq. ft) .808 Max Reach Mean Depth (ft) .804 Watershed Relief on Longitudinal Axis (ft) .789 Maximum Reach XS Area (ft) .783 .542 Percent Substrate as Bare Muck/Silt .768 Network Magnitude .765 Mean Distance Between Bends (ft) .749 Watershed Length (ft) .747 .539 Thalweg Flood Depth .739 .602 Primary Basin Area (sq. miles) .712 .618 Drainage Area (sq. mile) .712 .618 No. Valley Transitions .675 Mean Valley Zone Length (ft) .655 Mean Valley Zone Width (ft) .645 Reach Standard Deviation of XS Area .642 .628 Watershed Width (ft) .641 .574 Percent Substrate as Leaf Packs .610 Maximum Valley Zone Width (ft) .599
415 Table E-5. Continued 1 2 3 4 5 Reach Standard Deviation of TW D .580 Pools 1-2 ft Deep (%) -.563 No. of Alluvial Valley Features .555 Bifurcation Ratio .553 Ratio of Flood to Bankfull Flow .552 Width of Riparian Wetland (ft) .546 Max-Min Ratio of Zone Widths .525 Transitions per Valley Length (no./mile) Width Ratio of Floodplain and Bankfull Channels Percent Substrate as SAV .838 Percent Canopy Closure US DS -.803 Mean Reach RC (ft) .790 Flood/Bank Height Depth Ratio .783 Mean Distance Between Pools (ft) .751 W/D Ratio .748 Bankfull Wetted Perimeter .745 Width at Bank Height .738 Min Reach Radius of Curvature (ft) .732 Reach Standard Deviation of Width .725 Percent Canopy Closure -.724 Percent Substrate as Emergent Veg .718 Flood/Bankfull Depth Ratio .716 Maximum Reach Width (ft) .507 .703 Meander Beltwidth (ft) .609 .692 Mean Reach Width (ft) .600 .672 Classification Bankfull Width (ft) .615 .640 Watershed Area to Length Ratio (sq. mi/mile) .631 .635 Minimum Reach Width (ft) .603 .633 Length of the Valley S egment (ft) .570 .623 Valley Width at Flood Line .590 .606 Bends per 100 LF -.590 Ratio of Flood to Bankfull Power .579 Basin Drainage Density (LF/SM) -.572 Bankfull Width Max/Min Ratio -.720 Ratio of Max Min Reach TW Depths -.699 .560 Root Steps per Stream Length (no./100ft) -.673 Ratio of Flood to Bankfull Velocity -.663
416 Table E-5. Continued 1 2 3 4 5 Entrenchment Ratio .655 Bankfull Slope (ft/ft) -.617 Manning's n -.600 Valley Segment Slope (%) -.595 Minimum Valley Zone Width (ft) .576 Ratio of Mean Reach Pool and Riffle TW Depths -.574 .572 Reach Valley Slope (%) -.567 No. of Alluvial Bed Features .565 Sinuosity Ratio .551 Hillslope Grade (ft/ft) -.536 Total Alluvial Features .511 .518 Bankfull Area Max/Min Ratio -.500 Bankfull Mean Depth Max/Min Ratio Basin Grade (ft/ft) Bends per 12 Bankfull Widths -.773 MBW to W Ratio .762 Pools per 12 Bankfull Width -.687 Percent A-Soil -.668 Mean Rc/W Ratio .643 Tightest Bend Ratio .611 A+C Soils -.585 Percent D-Soil .572 Width Ratio of Bank Height to Bankfull .551 Total Valley Relief on Wide Section (ft) -.535 Ratio of Wetland Width to Beltwidth Stream Power (lb/s) .898 Unit Stream Power .869 Unit floodplain power .868 Flood Mean Velocity (fps) .775 Valley Relief in the Segment (ft) .731 Bankfull Mean Velocity (ft/s) .696 Flood Stream Power (lb/s) .534 .651 Bankfull Shear Stress (psi) .565 Percent Wetlands Percent Upland
417 Table E-6. Karst sites with a ll variables, rotated component matrix 1 2 3 4 5 Max-Min Ratio of Zone Widths .995 Min Reach Radius of Curvature (ft) .994 Mean Reach RC (ft) .991 Network Magnitude .990 Minimum Reach Width (ft) .986 Width at Bank Height .985 Classification Bankfull Width (ft) .984 No. Valley Transitions .981 Mean Reach Width (ft) .979 Bankfull Wetted Perimeter .975 Minimum Reach XS Area (ft) .974 Classification Cross-Section Area (sq. ft) .967 Mean Reach XS Area .966 Maximum Reach Width (ft) .963 Max-Min Ratio of Zone Lengths .960 Maximum Reach XS Area (ft) .943 Bifurcation Ratio .926 Percent Lakes .923 Mean Distance Between Bends (ft) .922 Meander Beltwidth (ft) .904 W/D Ratio .903 Valley Width at Flood Line .847 Drainage Area (sq. mile) .818 Mean Distance Between Pools (ft) .799 Total Valley Length (ft) .789 Flood Discharge (cfs) .785 .578 Percent Substrate as SAV .782 Maximum Valley Zone Width (ft) .768 Mean Rc/W Ratio .739 Watershed Area to Length Ratio (sq. mi/mile) .708 Percent Canopy Closure -.706 -.557 Watershed Width (ft) .640 Primary Basin Area (sq. miles) .614 .610 Watershed Length (ft) .600 Reach Standard Deviation of Width .567 -.526 Bends per 12 Bankfull Widths .528 Pools 2-4 ft Deep (%) .507
418 Table E-6. Continued 1 2 3 4 5 Mean Reach Riffle TW Depth (ft) .945 Mean Reach TW D (ft) .938 Riffle TW Depth (ft) .937 Min Reach TW Depth (ft) .935 Mean Reach Pool TW Depth (ft) .929 Max Reach Pool TW Depth (ft) .919 Thalweg Flood Depth .892 Stream Power (lb/s) .888 Max Reach Mean Depth (ft) .886 Unit Stream Power .886 Classification Bankfull Depth (ft) .883 Mean Reach Average Depth (ft) .874 Min Reach Mean Depth (ft) .868 No. of Alluvial Valley Features .857 Flood Stream Power (lb/s) .836 Low Bank Height (ft) .826 Bankfull Hydraulic Radius .822 Bankfull Mean Velocity (ft/s) .820 Bankfull Shear Stress (psi) .796 Total Alluvial Features .791 Bankfull Discharge (cfs) .542 .786 Pools >4 ft Deep (%) .782 Valley Segment Sinuosity Ratio .779 Pools per 12 Bankfull Width .749 Reach Standard Deviation of TW D .743 .615 Unit floodplain power .714 No. of Alluvial Bed Features .696 Reach Standard Deviation of XS Area .678 Percent Canopy Closure US DS -.603 -.639 Bank Height Ratio -.636 Pools 1-2 ft Deep (%) -.635 Flood/Bankfull Depth Ratio -.619 -.526 Percent Substrate as Leaf Packs -.619 .533 Ratio of Flood to Bankfull Velocity -.591 Flood Mean Velocity (fps) .567 Transitions per Valley Length (no./mile) -.523 Logs per Stream Length (no./100 ft) -.516
419 Table E-6. Continued 1 2 3 4 5 Width Ratio of Bank Height to Bankfull -.516 Ratio of Mean Reach Pool and Riffle TW Depths -.506 MBW to W Ratio Percent A-Soil .883 A+C Soils .855 Percent D-Soil -.850 Percent C-Soil -.812 Percent Substrate as Bare Muck/Silt -.808 Percent Wetlands -.779 Percent Upland .774 Flood/Bank Height Depth Ratio -.769 Percent Substrate as Bare Sand .746 Basin Drainage Density (LF/SM) .619 Watershed Relief on Longitudinal Axis (ft) .615 Basin Grade (ft/ft) -.566 .576 Ratio of Flood to Bankfull Power -.569 Floodplain n -.548 .510 Ratio of Flood to Bankfull Flow -.530 Percent Substrate as Fine Wood Sinuosity Ratio Hillslope Grade (ft/ft) Tightest Bend Ratio Wetland to Bankfull Width Ratio .950 Minimum Valley Zone Length (ft) .890 Minimum Valley Zone Width (ft) .852 Ratio of Wetland Width to Beltwidth .848 Width of Riparian Wetland (ft) .834 Mean Valley Zone Length (ft) .825 Valley Relief in the Segment (ft) .815 Mean Valley Zone Width (ft) .749 Reach Standard Deviation of Mean D .570 .710 Maximum Valley Zone Length (ft) .511 .666 Ratio of Max Min Reach TW Depths .655 Length of the Valley Segment (ft) .538 .652 Pools per 100 LF .637 Bankfull Width Max/Min Ratio Root Steps per Stream Length (no./100ft) .825
420 Table E-6. Continued 1 2 3 4 5 Bends per 100 LF .819 Width Ratio of Floodplain and Bankfull Channels .818 Valley Segment Slope (%) .701 Entrenchment Ratio .553 Bankfull Slope (ft/ft) .537 Manning's n .515 Total Valley Relief on Wide Section (ft) Percent Substrate as Root Mass Reach Valley Slope (%) Bankfull Area Max/Min Ratio
421 Table E-7. All sites with waters hed variables, rotated component matrix 1 2 3 4 5 Watershed Length (ft) .908 Drainage Area (sq. mile) .907 Primary Basin Area (sq. miles) .894 Watershed Width (ft) .887 Watershed Area to Length Ratio (sq. mi/mile) .864 Network Magnitude .817 Bifurcation Ratio .711 Percent D-Soil -.959 A+C Soils .918 Percent A-Soil .904 Watershed Relief on Longitudinal Axis (ft) .548.556 Basin Drainage Density (LF/SM) .786 Hillslope Grade (ft/ft) .727 Basin Grade (ft/ft) .642 Total Valley Relief on Wide Section (ft) Percent Upland -.917 Percent Wetlands -.515 .782 Percent Lakes Percent C-Soil .850
422 Table E-8. All sites with valley variables, rotated component matrix 1 2 3 4 5 Ratio of Flood to Bankfull Power .844 Mean Valley Zone Length (ft) .842 Ratio of Flood to Bankfull Flow .826 Minimum Valley Zone Length (ft) .760 Flood/Bankfull Depth Ratio .735 Flood/Bank Height Depth Ratio .732 Maximum Valley Zone Length (ft) .686 No. of Alluvial Valley Features .650 Flood Stream Power (lb/s) .575 .502 No. Valley Transitions .908 Maximum Valley Zone Width (ft) .758 Max-Min Ratio of Zone Lengths .731 Max-Min Ratio of Zone Widths .718 Meander Beltwidth (ft) .713 Total Valley Length (ft) .527 .682 Thalweg Flood Depth .588 .673 Flood Discharge (cfs) .552 .664 Total Alluvial Features .547 .549 Length of the Valley Segment (ft) Ratio of Flood to Bankfull Velocity Width of Riparian Wetland (ft) .906 Ratio of Wetland Width to Beltwidth .894 Minimum Valley Zone Width (ft) .890 Wetland to Bankfull Width Ratio .878 Mean Valley Zone Width (ft) .602.655 Valley Segment Sinuosity Ratio Valley Relief in the Segment (ft) .786 Unit floodplain power .779 Flood Mean Velocity (fps) .754 Valley Segment Slope (%) .578 MBW to W Ratio Transitions per Valley Length (no./mile) Width Ratio of Floodplain and Bankfull Channels .500 .713 Valley Width at Flood Line .701 Floodplain n .536
423 Table E-9. All sites with reac h variables, rotated component matrix 1 2 3 4 5 Max Reach Pool TW Depth (ft) .961 Mean Reach Pool TW Depth (ft) .956 Mean Reach TW D (ft) .955 Max Reach Mean Depth (ft) .943 Riffle TW Depth (ft) .934 Mean Reach Riffle TW Depth (ft) .928 Mean Reach Average Depth (ft) .924 Min Reach TW Depth (ft) .899 Classification Bankfull Depth (ft) .871 Low Bank Height (ft) .863 Min Reach Mean Depth (ft) .845 Bankfull Hydraulic Radius .820 Bankfull Discharge (cfs) .808 Reach Standard Deviation of TW D .735 Reach Standard Deviation of Mean D .723 Reach Standard Deviation of XS Area .717 Stream Power (lb/s) .683 Bankfull Mean Velocity (ft/s) .604 Minimum Reach Width (ft) .970 Mean Reach Width (ft) .969 Min Reach Radius of Curvature (ft) .968 Mean Reach RC (ft) .966 Classification Bank full Width (ft) .961 Maximum Reach Width (ft) .947 Minimum Reach XS Area (ft) .940 Mean Reach XS Area .929 Classification Cross-Section Area (sq. ft) .926 Maximum Reach XS Area (ft) .903 Width at Bank Height .869 Mean Distance Between Pools (ft) .823 W/D Ratio .819 Mean Distance Between Bends (ft) .691 Reach Standard Deviation of Width .647 Bankfull Shear Stress (psi) .916 Bankfull Slope (ft/ft) .844 Reach Valley Slope (%) .834 Unit Stream Power .829
424 Table E-9. Continued 1 2 3 4 5 Bends per 100 LF -.515 .560 Manning's n Bankfull Mean Depth Max/Min Ratio .776 Ratio of Mean Reach Pool and Riffle TW Depths .755 Ratio of Max Min Reach TW Depths .720 Bankfull Width Max/Min Ratio .689 Bankfull Area Max/Min Ratio .631 Tightest Bend Ratio .823 Mean Rc/W Ratio .537 .679 Bends per 12 Bankfull Widths -.621 Pools per 12 Bankfull Width -.603
425 Table E-10. All sites with habitat patch variables, rotated component matrix 1 2 3 4 5 Percent Substrate as SAV -.868 Bankfull Wetted Perimeter -.850 Percent Canopy Closure US DS .715 Percent Canopy Closure .704 Percent Substrate as Bare Muck/Silt .768 Logs per Stream Length (no./100 ft) .752 Percent Substrate as Bare Sand -.713 Percent Substrate as Fine Wood .651 No. of Alluvial Bed Features .877 Pools >4 ft Deep (%) .736 Pools 1-2 ft Deep (%) -.665 .537 Percent Substrate as Root Mass .801 Percent Substrate as Emergent Veg -.636 Pools per 100 LF .561 Pools 2-4 ft Deep (%) -.969
426 Table E-11. All sites with dimensionl ess variables, rotated component matrix 1 2 3 4 5 A+C Soils .880 Percent A-Soil .869 Percent D-Soil -.866 Percent Wetlands -.751 Percent Upland .669 Basin Grade (ft/ft) .599 Bank Height Ratio .550 Hillslope Grade (ft/ft) .512 Flood/Bankfull Depth Ratio .805 Flood/Bank Height Depth Ratio .779 Ratio of Flood to Bankfull Power .776 Ratio of Flood to Bankfull Flow .722 Width Ratio of Floodplain and Bankfull Channels .670 Ratio of Flood to Bankfull Velocity -.653 Pools >4 ft Deep (%) .626 Bifurcation Ratio .534 MBW to W Ratio .741 Valley Segment Slope (%) .732 Reach Valley Slope (%) .688 Bankfull Slope (ft/ft) .666 Ratio of Max Min Reach TW Depths .642 .631 W/D Ratio -.637 Percent C-Soil .605 Width Ratio of Bank Height to Bankfull Percent Canopy Closure US DS -.844 Percent Canopy Closure -.840 Percent Substrate as SAV .681 Mean Rc/W Ratio .657 Percent Substrate as Emergent Veg .599 Pools 1-2 ft Deep (%) -.539 Tightest Bend Ratio Percent Substrate as Bare Sand Bankfull Area Max/Min Ratio .743 Bankfull Mean Depth Max/Min Ratio .722 Bankfull Width Max/Min Ratio .692 Ratio of Mean Reach Pool and Riffle TW Depths .513 .681
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436 BIOGRAPHICAL SKETCH John Kiefer II was born in Allentown, P ennsylvania and was raised in south Jersey and north Florida. The oldest of three children, John was named for his paternal grandfather, whose appreciation for nature hel ped inspire his grandsons career path. John II was in the first-ever graduating cla ss of Middleburg High School, Florida. He graduated from the University of Florida in 1989 with a B.S. in Environmental Engineering Sciences and in 1991 with an M. E. His thesis research focused on the biogeochemistry of nutrients and metals in mitigation wetlands at Florida phosphate mines, under the supervision of Tom Cris man, Joe Delfino, and Ronnie Best. John started his career with a phosphate mining company in 1991 and quickly helped Agrico set precedent for the means to restore large headwater swamps and marshes destroyed by mining. Two years la ter he joined another mining company, CF Industries, and as Chief Environmental Engineer there led t eams that planned and implemented an award-winning reclamation program over a nine year period. During 2002, he joined a consulting firm, BCI Enginee rs and Scientists in Lakeland, Florida where he serves as Principal Water Re sources Engineer helping a variety of governmental and mining clients with planning, design, and per mitting for the restoration of radically disturbed watersheds. John is a Professional Engineer r egistered in Florida and is a Certified Professional Wetland Scientist (Society of Wetland Scientists). Stream restoration is a major emphasis in his practice and this Dissertation topic was selected because he wanted better tools fo r restoring Florida streams. John was blessed to marry his soul-mat e, Sarah, in Seward, Alaska about 10 years ago. They enjoy nature travel and are continually am azed by earths bounty. Their young son Nolan aspires to be a paleogeneticist to revive dinosaurs.