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Geochemical evolution of ground water in the Barton Springs segment of the Edwards aquifer

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Geochemical evolution of ground water in the Barton Springs segment of the Edwards aquifer
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Garner, Bradley D.
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University of Texas
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English

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Geology ( local )
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The water quality in a karst (limestone) aquifer changes over time, making the application of traditional hydrogeologic principles difficult or impossible. This researchâ€(tm)s goal was to advance the understanding of the Barton Springs segment of the Edwards aquifer within and around Austin, Texas. This was accomplished by analyzing time#8208;series water#8208;quality data from long, medium, and short time scales. Analysis provided insights into direction of ground#8208;water flow, sources of spring discharge, and mixing of geochemically distinct waters in the aquifer. The results of this research are of interest because of the aquifers role as a drinking water supply, its role as a habitat for the endangered Barton Springs salamander (Eurycea sosorum), and for its central role in creating the popular Barton Springs Pool. Twenty#8208;six years of water#8208;quality data were compared against contemporaneous streamflow and spring discharge rates to evaluate ground#8208;water connection to surface#8208;water processes. Fifteen of 26 wells in this dataset showed a correlation between these measurements. Ion ratios of Mg/Ca, SO4/Cl, and Na/Ca showed that active ground#8208;water processes included dilution by recently#8208;recharged surface water, inconguent dissolution, and mixing with water from a saline zone and an underlying aquifer. Four wells were shown to intersect major flowpaths, and five wells were shown to intersect minor flowpaths. Major ion and Sr isotope data collected over two years from four karst springs (Main, Eliza, Old Mill, and Upper Barton Springs) provided insight into water flow in the aquifer. Main and Eliza were fed by ground water from the same flowpath(s) in the aquifer, as their geochemical compositions were indistinguishable. Old Mill received 4â€"9 percent of its water from a saline zone, as shown by elevated ion concentrations and a quantitative mixing model. Upper Spring obtained some of its water from an isolated subbasin in the aquifer, as indicated by radiogenic 87Sr/86Sr values measured in this subbasin. Oxygen and hydrogen isotope values indicated that ground water was well#8208;mixed over year or longer timescales. Oxygen isotope samples collected from the springs following a rainfall event showed how stormflow recharge flows to the springs. A hydrograph separation using showed an immediate increase in spring discharge following rainfall but a 12#8208;hour delay before storm water reached the spring. This suggested an advancing front of storm water that expelled pre#8208;storm water from the karst conduits. Discharge of pre#8208;storm ground water was reduced by up to 44 percent after rainfall, suggesting that stormflow pressurized the karst conduit system and reduced gradients between the aquifer matrix and conduits. Specific conductance was also an effective and inexpensive tracer of stormflow, on the basis of its strong correlation (r2=0.96) to oxygen isotope values. Resource managers and scientists may be interested in these findings, as the potential for contamination of this spring system is increased after large rainfall events.
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Description
The water quality in a karst (limestone) aquifer changes
over time, making the application of traditional
hydrogeologic principles difficult or impossible. This
researchs goal was to advance the understanding of the
Barton Springs segment of the Edwards aquifer within and
around Austin, Texas. This was accomplished by analyzing
time‐series water‐quality data from long,
medium, and short time scales. Analysis provided insights
into direction of ground‐water flow, sources of
spring discharge, and mixing of geochemically distinct waters
in the aquifer. The results of this research are of interest
because of the aquifers role as a drinking water supply, its
role as a habitat for the endangered Barton Springs
salamander (Eurycea sosorum), and for its central role in
creating the popular Barton Springs Pool.
Twenty‐six years of water‐quality data
were compared against contemporaneous streamflow and spring
discharge rates to evaluate ground‐water connection
to surface‐water processes. Fifteen of 26 wells in
this dataset showed a correlation between these measurements.
Ion ratios of Mg/Ca, SO4/Cl, and Na/Ca showed that active
ground‐water processes included dilution by
recently‐recharged surface water, inconguent
dissolution, and mixing with water from a saline zone and an
underlying aquifer. Four wells were shown to intersect major
flowpaths, and five wells were shown to intersect minor
flowpaths. Major ion and Sr isotope data collected over two
years from four karst springs (Main, Eliza, Old Mill, and
Upper Barton Springs) provided insight into water flow in the
aquifer. Main and Eliza were fed by ground water from the
same flowpath(s) in the aquifer, as their geochemical
compositions were indistinguishable. Old Mill received 4"9
percent of its water from a saline zone, as shown by elevated
ion concentrations and a quantitative mixing model. Upper
Spring obtained some of its water from an isolated subbasin
in the aquifer, as indicated by radiogenic 87Sr/86Sr values
measured in this subbasin. Oxygen and hydrogen isotope values
indicated that ground water was well‐mixed over
year or longer timescales. Oxygen isotope samples collected
from the springs following a rainfall event showed how
stormflow recharge flows to the springs. A hydrograph
separation using showed an immediate increase in spring
discharge following rainfall but a 12‐hour delay
before storm water reached the spring. This suggested an
advancing front of storm water that expelled
pre‐storm water from the karst conduits. Discharge
of pre‐storm ground water was reduced by up to 44
percent after rainfall, suggesting that stormflow pressurized
the karst conduit system and reduced gradients between the
aquifer matrix and conduits. Specific conductance was also an
effective and inexpensive tracer of stormflow, on the basis
of its strong correlation (r2=0.96) to oxygen isotope values.
Resource managers and scientists may be interested in these
findings, as the potential for contamination of this spring
system is increased after large rainfall events.



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i Copyright by Bradley Dean Garner 2005

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ii GEOCHEMICAL EVOLUTION OF GROUND WATER IN THE BARTON SPRINGS SEGMENT OF THE EDWARDS AQUIFER by Bradley Dean Garner, B.S. THESIS Presented to the Faculty of the Graduate School of The University of Texas at Austin in Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE IN GEOLOGICAL SCIENCES The University of Texas at Austin December, 2005

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iii GEOCHEMICAL EVOLUTION OF GROUND WATER IN THE BARTON SPRINGS SEGMENT OF THE EDWARDS AQUIFER APPROVED BY SUPERVISING COMMITTEE: Supervisor: ______________________ Jay L. Banner ______________________ Barbara J. Mahler ______________________ John M. Sharp, Jr.

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iv To Dr. Leon E. Long, who has inspired generations of geology students with his enthusiastic and heartfelt teaching, and who changed the course of my life.

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v ACKNOWLEDGEMENTS This thesis was supported by funding from the Jackson School of Geosciences. Jay Banner (my supervisor) and Barbara Mahler (virtually my co supervisor), paid attention to my needs and had faith in my abilities, often far more than I did myself. Their help immeasurably improved the quality of this thesis. Support from the USGS was greatly appreciated, including Peter VanMetre, Mike Dorsey, Mike Canova, Venezia Chavez, Lynne Fahlquist, Milton Sunvison, Marcus Gary, and all of my other co workers. Special thanks are given to Laura Coplin (USGS), who improved the quality of many of the figures in this thesis. Thanks are also extended to Joe Beery (Barton Springs/Edwards Aquifer Conservation District) and Nico Hauwert (City of Austin) for thoughts and insights into the world of karst aquifers. Analytical assistance and sound scientific advice were provided by Larry Mack (UT), Libby Stern (UT), and Kurt Ferguson (SMU). This thesis benefited from reviews by John Sharp (UT, committee member), David Johns (City of Austin), Greg Stanton (USGS), Brad Wolaver (UT), Brad Cey (UT), and Chris Braun (USGS). For moral support, I thank my family: Steve, Ann, Dana, Ashley, and Oatmeal. My friends: Chris Clark, Amber Guilfoyle, James McDonald, Diane Paulson, Shad Scharlach, Richard Thrapp, and so many others. Thanks to Great Sand Dunes National Park for being there. And oh my, thanks to Christy Sands, who has been more supportive and loving than I could have ever imagined possible. Abstract thanks are given to (a) Don Quixote, for dreaming the impossible dream; (b) Kermit the Frog, for telling all the lovers and dreamers about the Rainbow Connection; (c) Planet Earth, for being such an interesting home; (d) Science, for seeking answers; and (e) Hope, for being “a good thing—maybe the best of things.”

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vi GEOCHEMICAL EVOLUTION OF GROUND WATER IN THE BARTON SPRINGS SEGMENT OF THE EDWARDS AQUIFER by Bradley Dean Garner, M.S. Geo. Sci. The University of Texas at Austin, 2005 SUPERVISOR: Jay L. Banner The water quality in a karst (limestone) aquifer changes over time, making the application of traditional hydrogeologic principles difficult or impossible. This researchÂ’s goal was to advance the understanding of the Barton Springs segment of the Edwards aquifer within and around Austin, Texas. This was accomplished by analyzing time series water quality data from long, medium, and short time scales. Analysis provided insights into direction of ground water flow, sources of spring discharge, and mixing of geochemically distinct waters in the aquifer. The results of this research are of interest because of the aquifers role as a drinking water supply, its role as a habitat for the endangered Barton Springs salamander ( Eurycea sosorum ), and for its central role in creating the popular Barton Springs Pool. Twenty six years of water quality data were compared against contemporaneous streamflow and spring discharge rates to evaluate ground water connection to surface water processes. Fifteen of 26 wells in this dataset showed a correlation between these measurements. Ion ratios of Mg/Ca, SO4/Cl, and Na/Ca showed that active ground water processes included dilution by recently recharged

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vii surface water, inconguent dissolution, and mixing with water from a saline zone and an underlying aquifer. Four wells were shown to intersect major flowpaths, and five wells were shown to intersect minor flowpaths. Major ion and Sr isotope data collected over two years from four karst springs (Main, Eliza, Old Mill, and Upper Barton Springs) provided insight into water flow in the aquifer. Main and Eliza were fed by ground water from the same flowpath(s) in the aquifer, as their geochemical compositions were indistinguishable. Old Mill received 4–9 percent of its water from a saline zone, as shown by elevated ion concentrations and a quantitative mixing model. Upper Spring obtained some of its water from an isolated subbasin in the aquifer, as indicated by radiogenic 87Sr/86Sr values measured in this subbasin. Oxygen and hydrogen isotope values indicated that ground water was well mixed over year or longer timescales. Oxygen isotope samples collected from the springs following a rainfall event showed how stormflow recharge flows to the springs. A hydrograph separation using showed an immediate increase in spring discharge following rainfall but a 12 hour delay before storm water reached the spring. This suggested an advancing front of storm water that expelled pre storm water from the karst conduits. Discharge of pre storm ground water was reduced by up to 44 percent after rainfall, suggesting that stormflow pressurized the karst conduit system and reduced gradients between the aquifer matrix and conduits. Specific conductance was also an effective and inexpensive tracer of stormflow, on the basis of its strong correlation (r2=0.96) to oxygen isotope values. Resource managers and scientists may be interested in these findings, as the potential for contamination of this spring system is increased after large rainfall events.

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viii TABLE OF CONTENTS PAGE Abstract....................................................................................................................... ......... vi Table of Contents .............................................................................................................. viii List of Tables ...................................................................................................................... xii List of Figures .................................................................................................................... xiv 1. Overview of Thesis and the Barton Springs segment of the Edwards aquifer ........................................................................................................... 1 1.1. Introduction and Thesis purpose ...................................................................... 1 1.2. Geologic history of the Barton Springs segment ............................................ 3 1.2.1. Cretaceous deposition and uplift ............................................................... 3 1.2.2. Post Cretaceous burial ................................................................................ 5 1.2.3. Miocene faulting and uplift ........................................................................ 5 1.2.4. Post Miocene aquifer evolution ................................................................. 7 1.2.5. Origin of the saline zone ............................................................................. 9 1.3. Physical hydrogeology—Recharge, discharge, and flow .............................. 11 1.3.1. Recharge—Creekbeds, sinkholes, and soil zone ..................................... 11 1.3.2. Discharge—Springs and wells ................................................................... 12 1.3.3. Ground water flow in the aquifer ............................................................. 14 1.3.4. Digital aquifer models ................................................................................. 16 1.4. Geochemistry of the Barton Springs segment ................................................. 19 1.4.1. Major dissolved ions .................................................................................... 19 1.4.2. Non Ca Mg HCO3 waters in the Barton Springs segment .................... 22 1.4.3. Ratios of ion concentrations ....................................................................... 24 1.4.4. Specific conductance .................................................................................... 25 1.4.5. Thermodynamics and mineral saturation ................................................ 26 1.4.6. Strontium—A notable trace element in karst .......................................... 28 1.4.7. Nitrate—A potential anthropogenic tracer .............................................. 30 1.4.8. The water molecule ...................................................................................... 31 1.5. Motivation for Thesis ......................................................................................... 33 1.5.1. Karst as a scientific frontier ........................................................................ 33 1.5.2. Local need for high quality ground water ............................................... 34 1.5.3. General public outreach .............................................................................. 35 1.6. Organization of Thesis ....................................................................................... 36

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ix 1.7. Data sources ......................................................................................................... 37 1.7.1. Data from 1978–2003 (Chapter 2) ............................................................. 37 1.7.2. Data from 2003–2005 (Chapter 3 and 4) ................................................... 39 2. Investigation of the relationship between surface water flow and karst ground water geochemistry in the Barton Springs segment of the Edwards aquifer ................................................................................ 48 2.1. Abstract ................................................................................................................. 48 2.2. Introduction ......................................................................................................... 49 2.3. Study area ............................................................................................................. 52 2.4. Study approach ................................................................................................... 55 2.5. Methods ................................................................................................................ 56 2.5.1. Sample collection ......................................................................................... 56 2.5.2. Laboratory analytical methods .................................................................. 58 2.5.3. Statistical analysis of specific conductance and flow data …................. 59 2.6. Results ................................................................................................................... 62 2.6.1. Specific conductance .................................................................................... 62 2.6.2. Streamflow and aquifer flow condition .................................................... 62 2.6.3. Statistical test ................................................................................................ 63 2.7. Discussion ............................................................................................................ 64 2.7.1. Geochemical variability at the event scale ............................................... 64 2.7.2. The four well groups ................................................................................... 69 2.7.3. Wells and flowpath intersection ................................................................ 87 2.7.4. Saline zone and Trinity aquifer mixing .................................................... 90 2.7.5. Geographic patterns .................................................................................... 91 2.7.6. Individual well comparisons with other studies ..................................... 93 2.7.7. Value of statistical approach ...................................................................... 96 2.8. Conclusions .......................................................................................................... 98 2.9. Acknowledgements ............................................................................................ 100 3. Variability in aqueous and isotope geochemistry of karst ground water used to infer water sources and hydrogeology of the Barton Springs segment of the Edwards aquifer .............................................................................. 127 3.1. Abstract ................................................................................................................. 127 3.2. Introduction ......................................................................................................... 129 3.3. Study area ............................................................................................................. 132

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x 3.4. Methods ................................................................................................................ 135 3.4.1. Sampling from springs ................................................................................ 135 3.4.2. Sampling from wells .................................................................................... 137 3.4.3. Analytical methods ...................................................................................... 137 3.4.4. Real time parameter monitoring ............................................................... 140 3.5. Results ................................................................................................................... 141 3.5.1. Real time parameter monitoring ............................................................... 141 3.5.2. Major dissolved ions .................................................................................... 142 3.5.3. Strontium, oxygen, and hydrogen isotopes ............................................. 144 3.6. Discussion ............................................................................................................ 145 3.6.1. Major ion geochemistry .............................................................................. 145 3.6.2. Residence time and geochemical variability ............................................ 151 3.6.3. Well mixed ground water during baseflow ............................................. 156 3.6.4. Geochemical evolution of spring water .................................................... 157 3.6.5. Urban infrastructure and Upper Barton Spring ..................................... 161 3.6.6. Saline zone effect on Old Mill Spring ....................................................... 163 3.7. Conclusions .......................................................................................................... 165 3.8. Acknowledgements ............................................................................................ 167 4. Barton Springs during stormflow conditions—Using oxygen isotopes and real time monitoring parameters to quantify water mixing in karst spring discharge, Austin, TX ...................................................................................... 192 4.1. Abstract ................................................................................................................. 192 4.2. Introduction ......................................................................................................... 193 4.3. Study area ............................................................................................................. 196 4.4. Methods ................................................................................................................ 197 4.4.1. Isotope sample collection ............................................................................ 197 4.4.2. Real time parameter monitoring ............................................................... 199 4.4.3. Hydrograph separation ............................................................................... 200 4.5. Results ................................................................................................................... 201 4.5.1. Rainfall ........................................................................................................... 201 4.5.2. Discharge, turbidity, conductance and dissolved oxygen ..................... 201 4.5.3. Oxygen and hydrogen isotopes ................................................................. 202 4.5.4. Hydrograph separation with oxygen isotopes ........................................ 203 4.6. Discussion ............................................................................................................ 204 4.6.1. First arrival of stormflow at springs .......................................................... 204 4.6.2. Stormflow flushes karst conduits .............................................................. 206

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xi 4.6.3. Stormflow suppresses discharge of matrix ground water ..................... 208 4.6.4. Alternative hydrograph separation variables .......................................... 210 4.6.5. Complex signals in real time data ............................................................. 213 4.7. Conclusions .......................................................................................................... 214 4.8. Acknowledgements ............................................................................................ 217 5. Summary ......................................................................................................................... 229 Appendix A. Analytical results for Chapter 2 ............................................................. 233 Appendix B. Analytical results for Chapter 3 .............................................................. 268 Appendix C. Analytical results for Chapter 4 ............................................................. 275 Appendix D. Quality assurance data ............................................................................ 278 D.1. Historical ground water data, 1978–2003 (Chapter 2) .................................. 278 D.2. Major ions, 2003–2005 (Chapter 3) ................................................................... 280 D.3. Strontium isotopes (Chapter 3) ........................................................................ 282 D.4. Oxygen isotopes (Chapters 3 and 4) ............................................................... 285 D.5. Hydrogen isotopes (Chapters 3 and 4) ........................................................... 286 Appendix E. Methods for isotopic analysis ................................................................. 293 E.1. Isotope sampling equipment cleaning ............................................................ 293 E.2. Sample collection ................................................................................................ 293 E.3. Sample storage and data management ........................................................... 294 E.4. Holding time considerations ............................................................................. 295 E.5. Sample analysis ................................................................................................... 297 E.6. Results reporting ................................................................................................. 299 References ........................................................................................................................... 301 Vita ............................................................................................................................... ........ 317

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xii LIST OF TABLES PAGE Table 2 1. Site information for water wells sampled in the Barton Springs segment of the Edwards aquifer, 1978–2003 ........................................ 123 Table 2 2. Summary of correlation between ground water specific conductance, streamflow, and aquifer flow condition, 1978–2003.... 124 Table 2 3. Summary of Chapter 2 findings ............................................................ 125 Table 3 1. Summary of water quality analysis results, 2003–2005 ...................... 189 Table 3 2. Summary statistics of water quality data, 2003–2005 ......................... 190 Table 3 3. Coefficients of variation for water quality data, 2003–2005 .............. 191 Table 4 1. Summary of stormflow arrival times at springs ................................. 228 Table A 1. Specific conductance and associated maximum 10 day creek and spring discharge measurements, 1978–2003 ...................... 234 Table A 2. Full results of correlation test from Chapter 2 ..................................... 251 Table A 3. Analytical results for dissolved major ions, 1978–2003 ...................... 256 Table B 1. Site information springs and wells sampled, 2003–2005 ................... 269 Table B 2. Analytical results for dissolved major ions and strontium, oxygen, and hydrogen isotope ratios, 2003–2005 ............................................... 270 Table C 1. Analytical results for isotope ratios and associated real time monitoring parameters, Main Barton Springs, October 2004 ........... 276 Table C 2. Analytical results for isotope ratios for Eliza, Old Mill, and Upper Barton Springs, October 2004 .................................................... 277 Table D 1. Quality assurance data for dissolved major ions, 1978–2003 ............ 289

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xiii Table D 2. Analytical results of 87Sr/86Sr external laboratory NBS 987 standard analyses, 2003–2005 ................................................................ 290 Table D 3. Analytical results of 18O internal laboratory standards analyses, 2003–2005 ............................................................... 291 Table D 4. Analytical results of 2H replicate analyses, 2003–2005 ..................... 292

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xiv LIST OF FIGURES PAGE Figure 1 1. Study area map .......Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…......... 40 Figure 1 2. Geologic formations and hydrostratigraphy in study area ............... 41 Figure 1 3. Schematic cross section of aquifer ....Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…......... 42 Figure 1 4. Schematic diagram showing incongruent dissolution .......Â…Â…Â….... 43 Figure 1 5. Photographs of the study area .......Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…........ 44 Figure 1 6. Schematic diagram showing Barton Springs Pool .......Â…Â…Â…Â…....... 46 Figure 1 7. Photograph of moldic porosity .......Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…... 47 Figure 2 1. Study area map .......Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…......... 101 Figure 2 2. Schematic cross section of aquifer .......Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â….. 102 Figure 2 3. Distribution of Onion Creek discharge data ..........................Â…Â…Â….. 103 Figure 2 4. Piper diagram showing representative ground waters .......Â…Â…Â….. 104 Figure 2 5. Statistical groupings of wells (C1, C2, P, and N) ......Â…Â…Â…Â…Â…Â….. 105 Figure 2 6. High resolution sampling results of well SVW .......Â…Â…Â…Â…Â…Â….... 106 Figure 2 7. Group C1 geochemistry .......Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…... 107 Figure 2 8. Example of correlation at well FMW .......Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…. 110 Figure 2 9. Correlation between well SVE and Barton Springs discharge .......... 111 Figure 2 10. Group C2 geochemistry .......Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…... 112 Figure 2 11. Group P geochemistry ...Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…......... 115

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xv Figure 2 12. Sulfate in well FOW versus Barton Springs system discharge ......... 118 Figure 2 13. Group N geochemistry .......……………………………………….........119 Figure 2 14. Number of samples compared to range of specific conductance ..... 122 Figure 3 1. Study area map .......………………………………………………......... 169 Figure 3 2. Photographs of sampling locations .......…………………………….... 170 Figure 3 3. Overview of discharge and conductance during study .......……….. 172 Figure 3 4. Major ion concentration range plot .......…………………………….... 173 Figure 3 5. Piper diagram showing all Chapter 3 ground water samples .......... 174 Figure 3 6. Carbonate geochemistry modeling diagrams .......…………………... 175 Figure 3 7. Na/Cl ratio in study ………………………………………………......... 177 Figure 3 8. Sr/Ca ratio through time at springs .......…………………………….... 178 Figure 3 9. Correlation tests between Sr/Ca, Mg/Ca, and residence time .....….. 179 Figure 3 10. Mg/Ca and Sr/Ca values compared with other studies .………….... 180 Figure 3 11. Samples plotted against global meteoric water line .......………….... 181 Figure 3 12. Sr/Ca—87Sr/86Sr variations in the Barton Springs segment .......….. 182 Figure 3 13. Potential sources of strontium in the study area .………...……......... 184 Figure 3 14. Map of 87Sr/86Sr values across study area .………………………….... 185 Figure 3 15. SO4/Cl—Sr/Ca variations in the Barton Springs segment ....……….. 187 Figure 3 16. Hypothetical mixing model between spring MSP and well ALB ..... 188 Figure 4 1. Study area map .......………………………………………………......... 218

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xvi Figure 4 2. Time series of discharge on creeks .......Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…. 219 Figure 4 3. Time series of real time parameters at Main Barton Spring .......Â…... 220 Figure 4 4. Samples plotted against the global meteoric water line ..Â….Â…......... 221 Figure 4 5. Hydrograph separation using 18O .......Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â….... 222 Figure 4 6. Time series showing isotopic changes at all springs .......Â…Â…Â…Â…... 223 Figure 4 7. Schematic diagram of karst conduit pressurization .......Â…Â…Â…Â….... 224 Figure 4 8. Correlation tests between 18O and real time parameters .......Â…Â….. 226 Figure 4 9. Hydrograph separation using specific conductance .......Â…Â…Â…Â…... 227 Figure D 1. Time series of measured 87Sr/86Sr standard values .......Â…Â…Â…Â…Â…... 288 Figure E 1. Photograph of equipment used for water sample filtration .....Â…Â…. 300

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1. Overview of Thesis and the Barton Springs segment of the Edwards aquifer 1.1. INTRODUCTION AND THESIS PURPOSE The Barton Springs segment of the Edwards aquifer within and around Austin, Texas, is a karst limestone aquifer that has received increased attention from the scientific community over the last 30 years. Karst aquifers are important natural resources; worldwide, one out of every four persons obtains their drinking water from a karst aquifer (Ford and Williams, 1989). However, their complex internal structure has made the application of traditional hydrogeologic principles difficult if not impossible. Basic issues such as direction of ground water flow, sources of spring discharge, and transport of contaminants often remain poorly understood in even the most well studied karst aquifers. As such, scientists must use innovative methods for understanding these systems. The Barton Springs segment of the Edwards aquifer (herein referred to as the Barton Springs segment) is a hydrologically isolated portion of the much larger karst Edwards aquifer of central and south Texas. The Edwards aquifer is one of the most permeable and productive aquifers in the United States, and over 1.7 million people rely on it as a source of drinking water (Edwards Aquifer Authority, 2004). Within the Edwards aquifer, the Barton Springs segment extends from Town Lake in Austin

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to the south southwest toward the town of Buda (Figure 1 1). The aquifer is bounded on the south by a ground water divide, on the north by the regional base level of the Colorado River, on the west by a large fault, and on the east by a zone of low permeability known as the saline zone (Abbott, 1975; Slade et al., 1986; Sharp and Banner, 1997). The aquifers overall hydrogeology is affected by the Balcones Fault Zone, a zone of en echelon normal faults that trend from the southwest to the northeast across the aquifer. Some of these faults provide pathways for rapid ground water flow, while others may act as barriers to flow (Slade et al., 1986; Hauwert and Vickers, 1994). Locally, many stakeholders have an interest in the ground water quality of the Barton Springs segment. Stakeholders include recreational users of spring discharge, domestic and agricultural users of ground water from wells, and a federally listed endangered species that uses the aquifer as its habitat (Sharp and Banner, 1997). Because of these stakeholders, a substantial body of scientific research exists for the Barton Springs segment. Previous ground water quality studies have dealt with major ion geochemistry (Senger and Kreitler, 1984; Slade et al., 1986; Clement, 1989; Oetting et al., 1996; City of Austin, 1997), suspended sediment transport (Mahler et al., 1999; Mahler, 2003), effects from stormwater recharge (Andrews et al., 1984; Mahler and VanMetre, 2000), urbanization (St. Clair, 1979; Garcia Fresca Grocin, 2004), ground water levels and flow (Slade et al., 1985; Barrett

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and Charbeneau, 1997; Scanlon et al., 2003; Hauwert et al., 2005), and isotope geochemistry (Oetting et al., 1996). The purpose of this thesis is to advance the understanding of the Barton Springs segment by investigating (a) major ion geochemistry of the ground water and its relation to surface water processes, (b) temporal changes in major ion and isotope geochemistry as tools for understanding ground water flow and evolution, and (c) short term water quality changes at karst springs caused by stormflow from large rain events. 1.2. GEOLOGIC HISTORY OF THE BARTON SPRINGS SEGMENT 1.2.1. Cretaceous deposition and uplift The geologic history of the Barton Springs segment spans over 110 million years. It begins with rocks deposited during the lower Cretaceous period, about 110 million years ago (Rose, 1972). The Barton Springs segment of the Edwards aquifer is contained within the Edwards Limestone and the Georgetown Limestone (Figure 1 2; herein referred to jointly as the aquifer rocks). South of the Barton Springs segment, Rose (1972) divides the Edwards Limestone into a lower Kainer Formation and an upper Person Formation, with nine distinct members therein. In the Barton Springs segment, these nine members are equivalent to Members 1 through 5 of the Edwards Limestone (Small et al., 1996; Sharp and Banner, 1997).

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About 100 million years ago, the recently deposited Edwards Limestone was uplifted and subaerially exposed (Woodruff and Abbott, 1979; Prezbindowski, 1981; Maclay, 1995; Small et al., 1996). As rainwater (or meteoric water) infiltrated into these high standing carbonate sediments, some of the carbonate rock dissolved. This dissolution enlarged the void spaces in the rock, in a process known as karstification. This Cretaceous period karstification was not extensive (Abbott, 1975), as evidence of so called paleokarst (e.g., sediment filled cavities not associated with more recent karstification) is found only rarely in the aquifer rocks. After this period of Cretaceous erosion and diagenesis, the Georgetown Limestone was deposited disconformably atop the Edwards Limestone. By the convention of Folk (1974), the Edwards and Georgetown Limestones largely are pure chemical rocks, containing less than 10 percent non carbonate material. Non carbonate material, while ubiquitous in limestone, is infrequently studied in detail. In the Barton Springs segment, much of the non carbonate material is organic matter associated with deposition (Deike, 1987). Additional non carbonate material within the aquifer rocks includes the clay minerals kaolinite, illite, and illite/smectite (Lynch et al., 2004). This is comparable to other karst systems; for example, kaolinite clay and quartz grains were found in the aquifer rocks of a Missouri karst system (Peterson and Wicks, 2003).

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The Del Rio Clay (a smectitic, carbonaceous shale formation) overlies the Georgetown Limestone (Rose, 1972). During later periods of aquifer evolution including the present day, the Del Rio Clay has served as an upper confining layer for the aquifer. After the Del Rio Clay, additional marine and non marine sediments were deposited during the Gulfian series of geologic time. 1.2.2. Post Cretaceous burial In the early Tertiary, the aquifer rocks and overlying confining layers were covered by thick terrigenous clastic deposits associated with the uplift of the Rocky Mountains and subsequent progradation of the Gulf of Mexico Coastal Plain. Owing to their complete burial during this period of time, there was no freshwater flow system established in the aquifer rocks. As a result, meteoric digenesis did not occur, as meteoric water could not infiltrate into and flow freely through the void spaces in the Cretaceous aquifer rocks (Abbott, 1975). Therefore, the ground water present in the aquifer rock pore spaces was essentially stagnant, and was probably in chemical equilibrium with the rock matrix (Abbott, 1975). 1.2.3. Miocene faulting and uplift In the Miocene epoch, about 15 million years ago, tectonic activity resulted in a zone of en echelon normal faults (Rose, 1972). This zone of normal faults extended

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about 545 kilometers, from Del Rio to Waco, Texas. Near Austin, these faults cut through the Edwards and Georgetown Limestones and displaced blocks of these units relative to one another (Figure 1 3). This faulting apparently was associated with subsidence of the Gulf of Mexico sedimentary basin. Weakness in this zone of faulting already existed as a result of mountain building activity during the Pennsylvanian Ouachita orogeny. Maximum displacement across the entire fault zone was about 520 meters (Woodruff and Abbott, 1979). The largest single fault, the Mount Bonnell fault, became the western boundary of the Barton Springs segment. Significant movement along this fault juxtaposed the aquifer rock against the relatively impermeable Glen Rose Formation (Figure 1 3). Following uplift, erosion of the material above the Edwards and Georgetown Limestones (Figure 1 2) by surface streams was enhanced as a result of the increased topographic relief. Regionally, the base level of this downcutting activity was (and is today) controlled by the Colorado River (Woodruff and Abbott, 1979). By the mid or late Miocene, sufficient overlying material had been stripped away to allow infiltration of meteoric water into the Edwards and Georgetown Limestones. Meteoric water entered the recharge zone, flowed through the aquifer, and exited through springs, thus establishing a through flow system (Abbott, 1975; Woodruff

PAGE 23

and Abbott, 1979). The subsequent 15 million years saw this through flow system evolve into the aquifer structure seen today (Slade et al., 1986). 1.2.4. Post Miocene aquifer evolution Ample time has passed since the establishment of the through flow system for substantial meteoric diagenesis to occur. Meteoric diagenesis is a complex set of chemical processes that alter limestone as a result of the influx of rainwater (James and Choquette, 1984). One process in meteoric diagenesis is dedolomitization, wherein the more highly soluble dolomite is dissolved and calcite is precipitated directly in its place. Dedolomitization is probably the dominant diagenetic process occurring in the present day Barton Springs segment (Maclay, 1995). Meteoric diagenesis also includes incongruent dissolution, a process similar to dedolomitization. In incongruent dissolution, metastable minerals such as high magnesium calcite and aragonite are dissolved, and the more chemically stable low magnesium calcite is co precipitated (Figure 1 4) (James and Choquette, 1984). High magnesium calcite is about ten times more soluble than calcite (Moore, 1989). In some places, almost all of the original aquifer rocks primary porosity (i.e., intergranular pore spaces) has been occluded by calcite that precipitated during meteoric diagenesis. This loss of primary porosity has been offset by the

PAGE 24

corresponding development of large secondary porosity such as large void spaces and conduits (Maclay and Small, 1983). Today, the aquifer rock in the freshwater zone (Figure 1 1) is tan to buff colored, calcitic, recrystallized, dense, and contains large void spaces typical of karst aquifers (Maclay and Small, 1983; Maclay, 1995). Where these large void spaces are interconnected, there exists the potential for significant ground water movement. Well connected large void spaces are referred to as karst conduits, and are of great interest in the hydrologic study of karst aquifers. These void spaces are not uniformly distributed in the aquifer rock; for example, the distinct members of the Edwards Limestone (Figure 1 2) have varying lithologies which have undergone variable amounts of meteoric diagenesis (Small et al., 1996). Once started, the process of karst conduit development tends to be self sustaining and self accelerating. As chemical dissolution increases the diameter of a conduit, the conduit can transmit more ground water because of its high hydraulic conductivity and low gradient (Palmer, 1991). This leads to an increased volume of chemically aggressive (i.e., calcite undersaturated) ground water passing through the conduit, which then leads to further, accelerated dissolution. If a conduit grows to a sufficient size, it may become a master conduit. Enlargement of Barton Springs segment conduits may have also occurred via mechanical erosion (Mahler et al., 1999). While flow in karst conduits is typically

PAGE 25

turbulent and tranquil (Gale, 1984; Halihan et al., 2000), the flow velocities of 6 to 13 kilometers per day observed along major flow routes in the Barton Springs segment are probably sufficient to internally erode conduits in the aquifer (Hauwert et al., 2005). Both chemical and physical erosion of conduits in the Barton Springs segment has led to a prominent set of conduits that have developed along the northeast trending Balcones fault zone (Figure 1 3). These master conduits are now deeply engrained into the aquifer (Abbott, 1975). The presence of master conduits has been further confirmed by Senger (1983), who found that changes in water levels at Barton Springs Pool affected ground water levels in wells several kilometers away within minutes, suggesting that these wells intersect a highly transmissive conduit system that is in direct hydraulic communication with the pool. 1.2.5. Origin of the saline zone The presence of master conduits in the aquifer might explain the existence of the saline zone along the eastern boundary of the Barton Springs segment (Figure 1 1). Hydrologically, the saline zone boundary appears to be a deeply ingrained bypass boundary (Abbott, 1975). As the process of conduit enlargement progressed and accelerated through geologic time in the freshwater zone, progressively more meteoric water flowed through these conduits at the expense of flow through other

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areas of the aquifer. Apparently, the saline zone was one such area that master conduits eventually cut off from the main flow of through flowing meteoric water. Thus, the saline zone failed to develop large secondary porosity, and retained much of its original depositional character. Alternatively, Hauwert and Vickers (1994) proposed that faults with large displacements offset the aquifer rocks of the saline zone from the aquifer rocks of the freshwater zone, thus impeding fluid flow into or out of the saline zone. Regardless of the underlying hydrologic and/or structural reasons for the saline zones existence, it is apparent that the saline zone has undergone relatively little meteoric water circulation (Abbott, 1975). Consequently, these rocks have retained much of their original lithologic character and have undergone relatively little diagenesis (dedolomitization, incongruent dissolution, etc.) (Prezbindowski, 1981; Maclay, 1995). Rocks from the saline zone are gray to brown, dolomitic, and pyritic, with occasional gypsum and celestite deposits (Maclay and Small, 1983). Saline zone rocks retain much of their original primary sucrosic porosityup to 28 percent in one core sample (Deike, 1987). However, this porosity is poorly connected and results in the lower permeability of the saline zone relative to the freshwater zone (Abbott, 1975; Maclay, 1995). Despite the lithologic differences between saline zone and freshwater zone rocks, it has been shown that rocks from

PAGE 27

both zones are time correlative (Deike, 1987). This clearly demonstrates the profound changes that meteoric diagenesis can impart to limestone. 1.3. PHYSICAL HYDROGEOLOGYRECHARGE, DISCHARGE, AND FLOW 1.3.1. RechargeCreekbeds, sinkholes, and soil zone An estimated 85 percent of aquifer recharge is provided by the five principal surface streams that cross the recharge zone (Figure 1 1) (Slade et al., 1986; Slagle et al., 1986). Recharge water enters the aquifer through sinkholes, swallets, and fractures in the creekbeds (Figure 1 5). These focused recharge sources can provide large volumes of recharge water rapidly to the aquifer. Additional sources of recharge are presumed to be minor in comparison to creek recharge. Infiltration of recharge water through upland sinkholes and soil zones has been difficult to quantify precisely, although there is research ongoing (N. Hauwert, University of Texas, personal comm., 2005; A. Lindley, University of Texas, personal comm., 2005). Urban infrastructure such as leaking municipal water supply pipes and sewer pipes may also contribute to recharge, especially during low flow conditions (St. Clair, 1979; Sharp and Banner, 1997; Garcia Fresca Grocin, 2004; Christian, in preparation), although this has been difficult to quantify. There may also be cross formational flow from other hydrostratigraphic units (see Chapter 2), but the quantity is generally expected to be small compared to other recharge

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sources (Smith and Hunt, 2004). St Clair (1979) proposed that some aquifer recharge may occur near Tom Miller dam, although now this is viewed as unlikely on the basis of potentiometric surface maps (Senger, 1983). 1.3.2. DischargeSprings and wells The main discharge point for the Barton Springs segment is a collection of four springs known as the Barton Springs system (Figures 1 1 and 1 5). These springs discharge water at a long term average rate of 50 ft3/s (1.4 m3/s), or about 30 million gallons per day (110,000 m3/day) (Slade et al., 1986). Historically, this discharge rate has varied from about 9 to 150 ft3/s (0.25 to 4.2 m3/s) (Slade et al., 1986). The combined discharge of these four springs accounts for over 90 percent of natural (i.e., not pumped) discharge from the aquifer (Hauwert and Vickers, 1994). One of these springs (Main Barton Spring) fills Barton Springs Pool, a local recreational resource of significant popularity and attention (Figure 1 6). When Barton Creek is not in flood stage, the water in this pool is about 21 degrees Celsius, and is well known for its striking blue green clarity. Over 300,000 people swim in this pool annually (City of Austin, 1997). The four springs are located within 1 kilometer of each other (Figure 1 1). Main Barton Spring (MSP) is located underwater in Barton Springs Pool, and discharges from a solution enlarge cave; spring MSP water also discharges at the

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surface from a fracture in the rocks, and water samples are collected from here (Figure 1 5). Eliza Spring (ESP) is located on the northwest side of Barton Creek in a concrete amphitheater and near a concession stand. Old Mill Spring (OSP) is located on the southeast side of Barton Creek in a stone enclosure and downstream from Barton Springs Pool. Upper Barton Spring (USP) is located in the creekbed of Barton Creek, 0.5 km upstream of Barton Springs Pool. These springs have United States Geological Survey (USGS) site identifiers (Table B 1), and some have been monitored for many years. Ground water in the Barton Springs segment also discharges at Cold Springs, located on the banks of the Colorado River about 4 kilometers north of the Barton Springs system. Discharge rates from this spring are generally small, and studies have shown that this spring is not connected to the larger part of the aquifer (Hauwert and Vickers, 1994; Hauwert et al., 2005). Cold Spring has been studied by Andrews et al. (1984), St. Clair (1979), and Good (2000), among others. It is also being presently studied by a graduate student at The University of Texas at Austin (J. Thompson, University of Texas, 2005, personal comm.). Discharge rates and geochemistry of Cold Springs are beyond the scope of this thesis. Other notable discharge from the Barton Springs segment is from approximately 970 active wells drilled into the aquifer. In 2004, these wells pumped 2.5 billion gallons of water, equivalent to a constant withdrawal rate of about 10 ft3/s

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(0.3 m3/s) (Smith and Hunt, 2004). This is equivalent to about 20 percent of the mean discharge from the Barton Springs system. The geochemistry of ground water in some of these wells is considered in Chapters 2 and 3. 1.3.3. Ground water flow in the aquifer Ground water flow in the Barton Springs segment is generally to the north northeast, following the trend of the Balcones Fault Zone (Figure 1 1 and 1 3). Over time, direction of flow varies with changes in aquifer flow condition and resulting changes in the potentiometric surface (Slade et al., 1986). Ultimately, the ground water flows to the Barton Springs system. Ground water does not usually flow across the southern ground water divide (Hauwert et al., 2005), although it has been suggested that it may do so under very high aquifer flow conditions (Maclay, 1995) and/or low aquifer flow conditions (Guyton and Associates, 1958). While ground water flow in the Barton Springs segment appears simple on a regional scale, it is complex on a local scale (Sharp and Banner, 1997). The aquifer can be classified as a double porosity medium, with conduits and intergranular porosity having very different hydraulic properties and spatial distribution. In karst systems, conduits account for very little ground water storage but transmit most of the ground water (Sharp, 1993; Maloszewski et al., 2002). Furthermore, in the Barton Springs segment, the conduits are non uniformly distributed throughout the aquifer

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rock (Small et al., 1996). For example, Member 3 of the Edwards Limestone (Figure 1 2) is a dense argillaceous mudstone that has almost no conduit development (Small et al., 1996), and may act as a semi confining layer (Smith and Hunt, 2004). Because of double porosity and its non uniform distribution, traditional hydrogeologic methods have proven difficult in the Barton Springs segment, because common assumptions underlying classic hydrologic equations are often violated in karst aquifers. Some have suggested that the Barton Springs segment is a triple porosity medium, with fractures, conduits, and intergranular spaces comprising three distinct media (Sharp, 1993; Halihan et al., 2000; Scanlon et al., 2003). Furthermore, research on a karst system in Missouri revealed that substantial ground water may flow through the void spaces in non carbonate sediment deposited in karst conduits (Peterson and Wicks, 2003), suggesting that some karst aquifers can even be thought of as quadruple porosity media. In the face of this complexity, dye tracing has proven to be one of the most straightforward and useful techniques for understanding ground water flow in karst aquifers (Quinlan et al., 1995). Dye trace studies have been carried out extensively in the Barton Springs segment (Hauwert et al., 2005). Hauwert et al. (2005) found that a major conduit system flows along the eastern boundary of the aquifer, which is consistent with flowpaths inferred from potentiometric surface maps (Slade et al.,

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1986). The dye trace studies also measured straight line ground water transit times exceeding 10 kilometers per day. 1.3.4. Digital aquifer models Despite the inherent complexity and non ideality of a karst aquifer, several attempts to create a digital computer model of the Barton Springs segment have been attempted, all with some degree of apparent success at predicting spring discharge and/or aquifer ground water levels. Slade et al. (1985) created a digital computer model that divided the aquifer into a 21 by 29 two dimensional grid. This type of approach, which uses a number of finite elements, is known as a distributed parameter model. Within each of 318 active grid cells, physical aquifer properties were either estimated from well data, or were calculated by calibrating the model with known ground water level data. Essentially, this model conceptualized the Barton Springs segment as a porous medium aquifer (e.g., sandstone). Slade et al. (1985) underscore the fact that their model only has broad, regional scale predictive abilitiesone should not necessarily expect the water level in any one well to match their model. Barrett (1996) created a lumped parameter model for the aquifer, wherein the aquifer was represented as five cells (or tanks, of a sort) that represent the five creeks that recharge the aquifer. Compared to distributed parameter models, lumped

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parameter models are very simple, as they contain little spatial information and require much less calibration data than distributed parameter models. Interestingly, this parsimonious approach to modeling the Barton Springs segment predicted spring discharge rates just as well as more complex distributed parameter models. It also is appealing because resource managers are not intimidated by it and are therefore more likely to use it in decision making (Barrett and Charbeneau, 1997). Scanlon et al. (2003) created a distributed parameter model similar in nature to that of Slade et al. (1985). There was a large increase in the number of active cells in the Scanlon model compared to the Slade model (7043 versus 318 active cells, respectively). The Scanlon model was able to predict both spring discharge rates and ground water levels, although it required a substantial effort to calibrate properly. In spite of the increased number of cells, the Scanlon model is still only one vertical layer thick. While it is difficult to create multiple vertical layers in models, there is increasing evidence that hydraulic properties of the Barton Springs segment vary significantly in the vertical direction (Barrett and Charbeneau, 1997), possibly because of lithologic differences or differing degrees of karstification (B.J. Mahler, U.S. Geological Survey, personal comm., 2005). The model of Scanlon et al. (2003) was recalibrated by Smith and Hunt (2004) to focus on the effects of severe drought, by using data from a drought in the 1950s for calibration. Smith and Hunt found that a repeat of this large drought combined

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with pumping rates from 2004 might cause the Barton Springs system intermittently to stop flowing, and might negatively impact 19 percent of the wells in the Barton Springs segment. All of the digital models described here implicitly treat the Barton Springs segment as an equivalent porous medium (e.g., sandstone) aquifer, where the standard rules of hydrogeology (e.g., Darcys law) apply. All things considered, these models have attained some degree of success in prediction of spring discharge and/or ground water levels, at least on a regional scale. Clement (1989) suggested that this counterintuitive success of porous medium models at the regional scale may be because interconnected cavernous porosity and faults distribute pressure changes over large areas. A recent study for the Edwards aquifer south of the Barton Springs segment has modeled the aquifer as a true double porosity medium, by incorporating discrete conduits into the model (Lindgren et al., 2005). Aquifer water levels and spring discharge rates were simulated in a finite difference model after extensive model calibration using known water level and spring discharge rates. Palmer (1991) suggested that double porosity models are unlikely to be successful, because the convoluted, non uniform, generally non predictable patterns of fractures and conduits can be mathematically modeled only with great difficulty.

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1.4. GEOCHEMISTRY OF THE BARTON SPRINGS SEGMENT Insight can be gained into the functioning of a karst aquifer by studying the chemical properties of its ground water, including its dissolved constituents. In theory, ground water composition is affected by (1) mineral availability, (2) mineral purity, (3) the amount of rock surface area in contact with ground water, (4) exposure time between ground water and rock, and many other factors (Hem, 1985). This section describes several geochemical tools that can be used to study ground water in the Barton Springs segment. 1.4.1. Major dissolved ions Typically, 95 percent or more of the dissolved ions in natural waters are a combination of calcium (Ca2+), magnesium (Mg2+), sodium (Na+), potassium (K+), bicarbonate (HCO3 ), chloride (Cl), sulfate (SO4 2 ), and nitrate (NO3 ) (Herczeg and Edmunds, 2000). In karst aquifers, strontium (Sr2+) is also usually considered a major ion. The major ion geochemical signature of karst ground water reflects the initial geochemical signature of the recharging surface water, over which is imprinted the interaction of the ground water with the rock through which it flows (Kehew, 2001, p. 9). Rain and recharging surface water contain carbonic acid, a weak acid that forms from the interaction of water with carbon dioxide in the atmosphere and soils.

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In karst terrane, this slightly acidic water dissolves the carbonate rock matrix, releasing Ca2+, Mg2+, Sr2+, and HCO3 ions into solution until an equilibrium concentration is reached or the water exits the aquifer. This process is not instantaneous; several days or more are required to approach within 90 percent of equilibrium of calcite (White, 1988). Most ground water in karst aquifers is calcium bicarbonate (Ca HCO3) or calcium magnesium bicarbonate (Ca Mg HCO3), reflecting the overwhelming preponderance of calcite and dolomite and the high solubility of these minerals. Other major ions in karst ground water can come from trace quantities of elements in the limestone (for example, Sr2+) or from other minerals sometimes associated with limestone deposits, such as gypsum (CaSO4), pyrite (FeS2), and clay particles with iron or manganese oxide coatings. Surface recharge is an additional source of major ion species, as it contains ions associated with the soil zone through which the water has moved and with which the water has reacted. In agricultural or urbanized areas, anthropogenic contaminants such as fertilizers and wastewater effluent also may be sources of major ion species such as Na+, K+, and NO3 (Freeze and Cherry, 1979, p. 413). In the Barton Springs segment, a saline zone to the east of the aquifer and an underlying aquifer (Trinity aquifer) are both potential sources of several ion species, including Na+, Cl, and SO4 2 Under some hydrologic conditions,

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water from the saline zone and Trinity aquifer may flow into the Barton Springs segment (Slade et al., 1986; City of Austin, 1997; Smith and Hunt, 2004). The overall geochemical character of a water sample can be represented visually with a Piper diagram, which is a group of two trilinear diagrams (one for cations and one for anions) and a diamond shaped diagram representing the composition of the water for both major dissolved cations and anions (Piper, 1944; Freeze and Cherry, 1979, p. 249). The triangles and diamond are subdivided into smaller areas that indicate which groups of ions dominate the aqueous geochemistry. The Piper diagram allows classification through visual inspection of the hydrochemical facies corresponding to each water sample (Back, 1961). Piper diagrams have the advantage of allowing comparison of multiple water samples on the same diagram, so that mixing and evolution of ground waters is visually evident. Because Piper diagrams display only relative proportions of ions, they are independent of the effects of dilution. When considering the major ions dissolved in water, complications may arise as a result of chemical complexities. For example, at 500 mg/L total dissolved solids, the effective concentration (or activity) of divalent cations such as Ca2+ may be only 70 percent of the actual concentration (Hem, 1985). As another example, when SO4 2 concentrations above 1000 mg/L, over 50 percent of dissolved calcium exists as a the

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aqueous neutral complex CaSO4 0 (Hem, 1985). It is especially important to consider these non idealities if mineral saturation states are being calculated (see 1.4.5). 1.4.2. Non Ca Mg HCO3 waters in the Barton Springs segment Water in the Barton Springs segment is mostly Ca HCO3 or Ca Mg HCO3. However, there are two important sources of ions (other than Ca2+, Mg2+, and HCO3 ) that interact with the aquifer. These two sources, the saline zone and the Trinity aquifer, both contain high concentrations of dissolved solids, usually above 1000 mg/L. Highly saline ground waters are notoriously complex and varied in their geochemical composition and chemical evolution. The saline zone borders the Barton Springs segment along its eastern boundary (Figure 1 1). Ground water in the saline zone flows slowly because of low aquifer permeability, and appears to undergo substantial water rock interaction. The saline zone has at least five distinct hydrochemical facies throughout the regional extent of the Edwards aquifer. Following the terminology of Clement (1989), facies D is the zone that borders the eastern edge of the Barton Springs segment. Facies D ground waters generally are classified as sodium chloride (Na Cl) saline waters, although there is some variability in their composition (Hauwert and Vickers, 1994). Several processes appear to contribute to the varying geochemical composition of facies D, including gypsum dissolution, dedolomitization, ion

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exchange with clays, sulfate reduction, halite dissolution, mixing with brines, and interaction with igneous intrusions (Sharp and Clement, 1988; Oetting et al., 1996). The oil field brines that are hypothesized to mix with saline zone ground water have a complex history that some have tried to unravel. The Na Ca Cl composition of these oil field brines may be the result of conversion of plagioclase and halite into albite at high temperatures and pressures (Land and Prezbindowski, 1981). Mixing of these Na Ca Cl brines with dilute meteoric water that slowly circulates into the saline zone may account for the observed salinity levels in the saline zone. While a regional scale study such as that of Sharp and Clement (1988) suggests that the saline zone in the Barton Springs segment is of relatively uniform composition, geochemical variability has been observed in facies D on a local scale. Hauwert and Vickers (1994) reported that the ground water chemistry of wells in the saline zone varies with ground water levels, with periods of high recharge being equated with lower sodium concentrations and higher calcium concentrations. It was suggested that this variability is the result of mixing of different ground water types, which is consistent with other studies of brines that have shown mixing to be a major factor in their variable composition (e.g., Musgrove and Banner, 1993). The underlying Trinity aquifer is another source of highly mineralized ground water that may flow into the Barton Springs segment (i.e., cross formational

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flow). While some cross formational flow undoubtedly does occur between the Trinity aquifer and the Barton Springs segment, it is not clear how much occurs, when or where it occurs, or even which direction of flow the hydraulic gradient allows (Hauwert and Vickers, 1994). An investigation into the vertical hydraulic gradient between these two aquifers found that ground water may flow out of the Barton Springs segment into the Trinity aquifer (Smith and Hunt, 2004, p. 9). The possibility of cross formational flow from the Trinity aquifer is considered in Chapter 2. 1.4.3. Ratios of ion concentrations In a karst aquifer with relatively uniform lithology, Mg/Ca and Sr/Ca molar ratios can be used as indicators of ground water residence time (Musgrove and Banner, 2004). Recharging water that is undersaturated with respect to calcite (CaCO3) will dissolve calcite and undergo a rapid increase in Ca2+ and HCO3 concentration until calcite saturation is reached (Palmer, 1991). Subsequently, incongruent dissolution will dissolve metastable minerals such as high magnesium calcite and dolomite (CaMg(CO3)2), while stable minerals such as low magnesium calcite precipitate (Figure 1 4) (James and Choquette, 1984). This process leads to an increase of Mg2+ and Sr2+ concentrations relative to Ca2+ (i.e., higher Mg/Ca and Sr/Ca

PAGE 41

ratios) because Mg2+ and Sr2+ are preferentially excluded from the newly precipitated stable minerals (James and Choquette, 1984; Musgrove and Banner, 2004). Visual evidence of the dissolution of metastable minerals can be observed by inspecting carbonate rocks that contain void spaces shaped like marine shells (Figure 1 7). These shells, originally secreted as the metastable mineral aragonite, have been dissolved by meteoric water while the surrounding calcite based carbonate mud has remained and been recrystallized into micrite. Other ion ratios that may indicate water sources involve the ions SO4 2 Na+, and Cl. Temporal changes in concentrations of these ions at a well or spring might signal an influx of recharge water from the surface, water from the saline zone, or water from another source. Ratios of ion concentrations, such as Na/Cl and Cl/SO4, can sometimes be used to infer geochemical process and to further distinguish water types and sources. 1.4.4. Specific conductance Specific conductance is a measure of the amount of electrical current water can transmit, and is related to the ionic strength, or total amount of dissolved solids, of a water sample (Hem, 1982). Because of the relative ease of measuring specific conductance, it is a widely used master variable in geochemical studies, and is used throughout this thesis.

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Rain has very low specific conductance (Freeze and Cherry, 1979, p. 238; Herczeg and Edmunds, 2000); surface water has a higher specific conductance resulting from chemical reactions with the land surface, soils, and the streambed; ground water typically has a higher specific conductance than surface water resulting from the dissolution of the rock matrix of the aquifer. Water that has recharged a karst aquifer recently will have a lower specific conductance than ground water that has been in contact with the rock for a longer period of time (Freeze and Cherry, 1979, p. 241). As the ground water interacts with the aquifer rock, its specific conductance increases, indicating increasing residence time. Specific conductance usually is used interchangeably with conductivity. Technically, however, specific conductance is a measurement that has had a correction applied that takes into account the large effect that temperature has on conductivity (Hem, 1985). Specific conductance is normalized to 25 degrees Celsius, whereas conductivity is not (Hem, 1985). This thesis always refers to this measurement by the full name of specific conductance. 1.4.5. Thermodynamics and mineral saturation Combining the principles of thermodynamics with ion concentrations, it is possible to calculate the chemical aggressiveness of water, that is, its propensity to

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dissolve various minerals. Calcite is the most common mineral in limestone, and the so called saturation index with respect to calcite can be calculated for the water. The calcite saturation index (log SIcalcite) is the logarithm of the ratio of the ion activity product of the sample and the solubility product for calcite, and is an indication of how close a water sample is to being in thermodynamic equilibrium with calcite (Stumm and Morgan, 1995). Negative values indicate that the solubility product exceeds the ion activity product and that the water is undersaturated with respect to calcite, indicating that the water should dissolve limestone. Positive values indicate water that is oversaturated with respect to calcite, indicating that calcite should precipitate from the water. Values between 0.1 and 0.1 are considered to indicate saturation (i.e., in chemical equilibrium with calcite). Typically, ground water flowing slowly through small pore spaces in limestone or calcitic soils will reach calcite saturation after flowing only a few meters (Bishop and Lloyd, 1990; Palmer, 1991). Saturation indices for carbonate minerals such as calcite are very sensitive to temperature, and a temperature correction should be applied to the calcite solubility product whenever possible (Hem, 1985). Also, effective concentrations (i.e., activities) of ions should be corrected for total ionic strength, particularly divalent cations such as Ca2+ (Hem, 1985). Failing to apply these corrections can result in

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unrealistic saturation index calculations that are not useful or appropriate for interpretation. 1.4.6. StrontiumA notable trace element in karst Strontium (Sr) is a trace element that behaves similarly to calcium and magnesium, and is present in trace amounts in limestone. Dissolved strontium (i.e., Sr2+) may be present in karst ground water as the result of simple carbonate mineral dissolution. However, Sr2+ in karst ground water may also be derived from the process of incongruent dissolution. Thus, Sr2+ concentration can be an indicator of residence time, similar to Mg2+ concentration (see section 1.4.3). Strontium is also abundantly present in evaporite deposits such as anhydrite and gypsum, which can occur in trace quantities in karst aquifers (Jacobson and Wasserburg, 2005). Any study that examines the major dissolved ions in karst aquifers should probably also consider Sr. Strontium has several naturally occurring isotopes. 87Sr is the product of the radioactive decay of 87Rb, and is referred to as a radiogenic isotope (Faure, 1986, p. 118). Normalized against the non radiogenic 86Sr isotope, a measurement of 87Sr/86Sr can be made. Values of 87Sr/86Sr can vary widely in different rocks, depending on the age of the rock and its initial Rb/Sr ratio (Faure, 1986, p. 119). Because of the slow

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decay rate for 87Rb to 87Sr (t1/2 = 48.8 Ga), the 87Sr/86Sr ratio is essentially constant for any mineral (McNutt, 2000). The 87Sr/86Sr value of the worlds oceans has varied considerably through geologic time (Burke et al., 1982). This ocean isotopic composition, which is uniform at any one moment in time (Capo and DePaolo, 1992), is recorded directly in carbonate minerals that precipitate from seawater. Because oceanic Sr2+ is obtained from input from all of the worlds rivers, it tends to reflect relative continental weathering rates, and has what can be called an average value. Sr2+ obtained exclusively from detrital sediments usually is more radiogenic than Sr obtained from carbonate rocks, which generally originate from the oceans. Thus, a karst ground water sample with an 87Sr/86Sr value that is more radiogenic than the aquifer carbonate rock may have derived some of its Sr2+ from detrital sediments (Stueber et al., 1984). Many studies have shown that Sr2+ isotopic composition in ground water and surface water often is controlled by the balance between weathering of carbonate material and silicate material (Banner et al., 1994; Banner et al., 1996; Han and Liu, 2004). 87Sr/86Sr ratios can provide complementary information to major ion concentration information when studying karst aquifers, and can provide information about ground water evolution (Banner et al., 1994). In some cases, Sr isotopes can provide insights into ground water sources that cannot be gained

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merely from dissolved ion concentration information alone (Banner et al., 1994; Vallejos et al., 1997; Frost and Toner, 2004). Note that Sr isotopic data, however, should always be paired with major ion geochemical data. Without the benefit of additional data, sources of Sr in the environment are likely to be misidentified (McNutt, 2000). 1.4.7. NitrateA potential anthropogenic tracer Nitrate (NO3 ) is an ion that, at elevated concentrations, might indicate an anthropogenic source, and may also indicate the presence of other anthropogenic contaminants. Because nitrate is not present in limestone and dolomite deposits, its presence in ground water results from processes other than calcite/dolomite dissolution. Sources of NO3 include fertilizers, manure, septic tanks, municipal sewage treatment systems, decaying plant debris, soil zones, and nitrogen oxide emissions (Freeze and Cherry, 1979, p. 413). Nitrate concentrations below 2 mg/L (measured as nitrogen) are generally assumed to come from natural sources such as plants and soils (Mueller and Helsel, 1996; Wisconsin Department of Natural Resources, 2003). Nitrate is very soluble, and once present in aerated water generally can be lowered in concentration only by mixing with more dilute water or through uptake by plants or other organisms. Excess NO3 in aquatic systems leads to eutrophication and has various adverse health effects on humans; the Maximum

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Contaminant Level (MCL) allowed in drinking water is 10 mg/L measured as nitrogen (United States Environmental Protection Agency, 2005). The majority of measured nitrate concentrations are below 2 mg/L in Barton Springs segment ground water, and nitrate has never been detected above the EPA MCL in Barton Springs segment ground water (City of Austin, 1997). Even though nitrate concentrations from Main Barton Spring discharge (in the Barton Springs system) have always measured below 2 mg/L, statistical analysis of nitrate concentrations from 1937 to 1999 indicates an upward trend through time (Turner, 2000), which may be associated with anthropogenic contamination. Nitrate concentrations above 2 mg/L are found in a few ground water samples from wells, and are considered in Chapter 2. 1.4.8. The water molecule The isotopic composition of oxygen and hydrogen that comprise the water molecule (H2O) can be analyzed, and the ratios of one isotope to another (namely 18O/16O and 2H/1H) can be used to study hydrologic processes (Clark and Fritz, 1997, p. 36). Evaporation of seawater from the oceans induces fractionation in these light, stable isotopes, and thereby changes the isotopic composition of atmospheric water vapor and the rainfall later created over continents. This relation between oxygen and hydrogen isotope fractionation from oceans has been well characterized by

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studying the global isotopic composition of rainfall (Craig, 1961). The so called global meteoric water line (GMWL) derived from these studies serves as a starting point for investigations of ground water flowing through an aquifer. Individual rainfall events that recharge an aquifer typically have a unique isotopic fingerprint that reflects the origin, travel path, and rainout history of the storm. In Chapter 4, the isotopes of oxygen trace the flow of recent rainfall through the Barton Springs segment, following in the mold of studies carried out in other karst aquifers (e.g., Siegenthaler and Schotterer, 1984; Lakey and Krothe, 1996; Desmarais and Rojstaczer, 2002). Oxygen isotopes are used in Chapter 4 to develop a new conceptual model for ground water flow in the Barton Springs segment. The isotopic ratios 18O/16O and 2H/1H are usually reported in delta ( ) notation (Coplen, 1994), whereby isotopic composition of a sample is expressed relative to the isotopic composition of a known standard (namely standard mean ocean water, or SMOW). This is mainly because it is difficult to analytically determine absolute ratios for these isotopes (Clark and Fritz, 1997, p. 6), but it is also a convenient format in which to read and compare the ratios (i.e., whole numbers instead of ratios much less than 1).

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1.5. MOTIVATION FOR THESIS 1.5.1. Karst as a scientific frontier It is difficult to understand karst aquifers. Their double, triple, and perhaps even quadruple porosity makes the application of traditional hydrologic equations (e.g., Darcys Law) questionable at best. Karst aquifers force scientists to find innovative methods for characterizing their behavior. For example, the geochemistry of ground water in a karst aquifer varies over time, sometimes over very small time scales (Shuster and White, 1971). This behavior is generally not observed in porous medium (e.g., sandstone) aquifers, and presents an opportunity to study a time domain signal that is not available to investigators of porous medium aquifers. Karst aquifers are also prone to contamination, and as such deserve special attention. This vulnerability to contamination is because of their ability to transmit ground water quickly and their relative inability to filter and reduce pollutants in ground water (Ford and Williams, 1989). As stated by John Black, in fractured media, contaminants appear where we dont expect, and appear there faster than we predicted (J.M. Sharp, University of Texas, written comm., 2003) There have been infamous cases of karst aquifer contamination, such as E. Coli bacterial contamination in Walkerton, Ontario, that led to illnesses and deaths (Worthington et al., 2002). Again, this type of rapid change in water quality is not observed as

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frequently in porous medium aquifers, and karst hydrologists must find innovative ways to characterize the mobility of contaminants. 1.5.2. Local need for high quality ground water Several stakeholders have an interest in the ground water quality of the Barton Springs segment. First, the Barton Springs system is the only known habitat for a federally protected endangered species of salamander ( Eurycea sosorum ; Figure 1 5). Second, the Barton Springs system supplies water for Barton Springs Pool, a popular swimming pool that is enjoyed by over 300,000 visitors annually and is colloquially referred to as the crown jewel of Austin. Finally, one of Austins three inlets for municipal water is directly downstream from the Barton Springs systems discharge into Town Lake. Under drought conditions, up to 90 percent of inflow into Town Lake can be discharge from the Barton Springs system (Slade et al., 1986). Thus, although derived from surface water sources, Austin municipal water contains some indirect discharge from the Barton Springs system. The Barton Springs segment has been shown to undergo rapid changes in water quality, similar to most karst aquifers. Increases in bacteria concentrations have been observed in wells and springs of the Barton Springs segment after rainfall (Andrews et al., 1984), although there have been no major outbreaks of illness as a result of this phenomenon. Also, increases in anthropogenic pesticides have been

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detected in the Barton Springs system after rainfall (Mahler and VanMetre, 2000). Finally, urbanization may be leading to long term increases in contaminant concentrations (Turner, 2000). Because of the many stakeholders, there is a pressing need for monitoring, quantification, and investigation of these changes in water quality. 1.5.3. General public outreach As nearly 20 percent of the Earths land surface is covered by karst terrane (White, 1988), and 20 percent of the United States is underlain by limestone or dolomite (Quinlan, 1989), many areas rely on aquifers in these parent rocks for potable water. Worldwide, one out of every four persons obtains their drinking water from a karst aquifer (Ford and Williams, 1989). Karst springs present a unique scientific opportunity for the scientific community to connect with the general public. Desmarais and Rojstaczer (2002) point out that the springs usually associated with karst are one of the few signs of the influence of ground water hydrology visible on the Earths surface, and often attract public attention to the otherwise largely unseen world of ground water. In Texas, Barton Springs, San Marcos Springs, Comal Springs, San Antonio Springs, and San Solomon Springs all are examples of major karst springs that attract significant attention from the public. Some of these springs have even become

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lightning rods, of sorts, for political and environmental debates about public policy. The Barton Springs system may be the best example of this lightning rod effect in all of Texas. For example, alleged contamination of the water in Barton Springs Pool in 2003 was the front page headline in a major Austin newspaper (Austin American Statesman, 2003). 1.6. ORGANIZATION OF THESIS This thesis is divided into five chapters. Chapter 1 (this chapter) presents an overview of the Barton Springs segment of the Edwards aquifer. A basic explanation of the aquifer is given, previous scientific studies are reviewed, and basic geochemical concepts used throughout this thesis are explained. Chapter 2 is an analysis of a long term (26 year) ground water quality dataset. The data, consisting of specific conductance and major ion analyses from wells and springs, are synthesized and analyzed using statistical methods and traditional geochemical analysis. Chapter 3 is an analysis of two years of sampling of the Barton Springs segment. The isotopes of strontium, oxygen, and hydrogen are used as additional hydrologic tools, and the dataset also is much higher resolution (i.e., more samples collected per unit time) than that of Chapter 2. Chapter 4 is an analysis of two weeks of intense sampling of the Barton Springs segment in order to quantify temporal

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changes in ground water quality that occur on the scale of hours to days. Finally, Chapter 5 is a summary of the findings of this thesis. Chapters 2 through 4 were written as self contained journal style papers, each capable of standing on its own. Nevertheless, the chapters are presented in a progression from the large scale to the small scale. Chapter 2 is a 26 year dataset, Chapter 3 is a two year dataset, and Chapter 4 is a two week dataset. The Barton Springs segment reveals complexity and useful insight at all three of these time scales. In the interest of disclosure, note that Garner et al. (in press), a USGS Scientific Investigation Report (SIR), was written by the author of this thesis. This SIR was written with the understanding that some of its contents would eventually be incorporated into this thesis. All of Chapter 2 and sections of all other chapters incorporate portions of the SIR into their contents. 1.7. DATA SOURCES 1.7.1. Data from 19782003 (Chapter 2) The ground water quality data used in Chapter 2 were collected by the USGS (Slade et al., 1979; United States Geological Survey, 1980; Slade et al., 1981). From 1978 to 1983, ground water samples from 26 water wells were collected and analyzed several times a year for numerous water quality parameters, including

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specific conductance and major ions including nitrate. From 1983 to 2003, approximately 11 of the original 26 wells continued to be sampled periodically. Over the years, some sampling sites and analyses were added while others were dropped. Sampling intervals also changed through time, and occasionally years were skipped altogether. Surface water discharge measurements for the five principal creeks in the study area (Figure 1 1) have been recorded by the USGS since 1978. These values were measured at gaging stations along creeks that recharge the aquifer. The discharges are computed from stage discharge relationships that have been developed for each of the sites and that are updated regularly by manual discharge measurements made with current flow meters (Buchanan and Somers, 1969). There are occasional gaps in the dataset, but overall it represents a fairly continuous record of surface water flow across the Barton Springs segment. Discharge data for the Barton Springs system have been recorded since 1978. Discharge rates are determined on the basis of ground water levels in a nearby well, much as a stage discharge relation is used. The relation between the water level in the well and the spring discharge is well defined, provided that the water level in Barton Springs Pool remains constant. When the water level in the pool changes, for example if it drops when the gates to the lower dam are opened or rises when the upper dam is overtopped by Barton Creek, the established rating can no longer be

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used. The relation is periodically verified and refined through the use of manual stream gaging measurements. Summaries of these data have been published (Senger, 1983; Slade et al., 1986), and most of the data are available from published USGS annual data reports. A comprehensive compilation of all data is available in Garner et al. (in press), and a subset of these data is provided in the appendixes of this thesis. 1.7.2. Data from 20032005 (Chapters 3 and 4) In mid 2003, the USGS began a new sampling program for the Barton Springs segment that was carried out concurrently with existing monitoring programs. Samples were collected every two weeks in August 2003 and September 2003, and every three weeks from June 2004 to June 2005. The major ion data presented in Chapter 3 are the product of this sampling effort. On each sampling trip, several additional sample bottles were filled for the purpose of isotope ratio analysis. The isotope ratio data presented in Chapters 3 and 4 are the product of this effort, and all isotope ratio analytical results are available in the appendixes of this thesis.

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Figure 1 1 Map of the Barton Spring segment of the Edwards aquifer (afterSlade et al., 1986). For additional spring site information, see Table B 1. NDowntown Austin Town of Buda S a l i n e z o n e b o u n d a ry5 km d i v i d eG r o u n d w a t e r Recharge Zone Confined Zone Creek Generalized Flow Direction EXPLANATIONFreshwater zone enlarged study area E d w a r d s a q u i f e r 400 km 0 N0 Spring Barton CreekUpper Barton Spring (USP) Main Barton Spring (MSP) Old Mill Spring (OSP) Eliza Spring (ESP)P o o lTown Lake 300 m 0 BARTON SPRINGS SYSTEM B a r t o n C re e k W i l l i a m s o n C r e e k S l a u g h te r C re e k B e a r C re e k O n i o n C r e e k

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Figure 1 2 Geologic formations associated with the Barton Springs segmentand surrounding regions. Confining units are shaded blue, and the Barton Springs segment is shaded green. Near San Antonio, the nomenclature of Rose (1972) is used (left side of figure). In the Barton Springs segment, the Basal Nodular Member is identified as the Walnut Formation, and serves as a confininglayer for the aquifer (right side of figure) (modified from Sharp and Banner, 1997, with data from Small et al., 1996). Barton Springs segment Near San Antonio, Texas WALNUT FORMATION Basal Nodular Member DolomiticMember KirschbergEvaporite Member GrainstoneMember Regional Dense Member Collapsed Member Leached Member Marine Member Cyclic MemberEDWARDS GROUP KainerFormation Person FormationDEL RIO CLAY GLEN ROSE LIMESTONE GEORGETOWN LIMESTONE Member 1 Member 2 Member 3 Member 4 Member 5 EDWARDS LIMESTONE ( d i s c o n f o r m i t y ) HYDROSTRATIGRAPHIC EXPLANATION Barton Springs segment of the Edwards aquifer Confining layer

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Figure 1 3 Schematic diagram of the Barton Springs segment of the Edwards aquifer. Recharge water enters the aquifer through the beds of creeks as they cross the recharge zone. Water in the aquifer flows generally to the north northeast, generally along solution enlarged conduits that act at highly preferential flowpaths. The majority of aquifer water eventually discharges at the far northeast corner of the aquifer at the Barton Springs system. Aquifer formation Confining layer Solution enlarged conduit Flow direction EXPLANATION NOT TO SCALE Infiltration & recharge Preferential flow along fractures and conduits Generalized flow direction Discharge at Barton Springs system

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Figure 1 4 Schematic diagram showing the principle of incongruent dissolution. (a) High magnesium calcite and low magnesium calcite crystals are added to deionized water; (b) The chemically aggressive water begins to dissolve both HMC and LMC, although chemical kinetics cause HMC to dissolve more rapidly than LMC; (c) saturation is reached with LMC, but HMC still continuesto dissolve because it is about 10 times more soluble than LMC. Continued dissolution of HMC drives LMC to supersaturation, and a LMC overgrowth begins to form on the original crystal of LMC; (d) reaction has proceeded until all HMC has been dissolved. The LMC overgrowth has grown, and some of the Sr2+and Mg2+have been preferentially excluded from the newly precipitated overgrowth and are at elevated levels in the water (modified from James and Choquette, 1984). HMC LMC HMC LMC (a)(b) (c) (d) LMC LMC Ca2+Mg2+Sr2+HCO3 Ca2+Mg2+Sr2+HCO3 Ca2+Mg2+Sr2+HCO3 LMC overgrowth Reaction Progressdeionized water

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Figure 1 5a Onion Creek, immediately upstream of where it crosses onto the Barton Springs segment recharge zone. All of the water seen in this photo entered the Barton Springs segment as recharge within hours after this photograph was taken. Figure 1 5b. Cripple Crawfish sinkhole, a karst feature in the creekbedof Onion Creek. A water vortex indicates rapid infiltration of water into the Barton Springs segment. As of 2005, this sinkhole has been covered by a man made structure that prevents excessive sediment from entering the cave (K. Thuesen, City of Austin, written comm., 2005). Photograph courtesy of NicoHauwert (City of Austin). Figure 1 5c. Eastward looking aerial photo of Barton Springs Pool, which is filled by Main Barton Spring (MSP). Over 300,000 visitors visit this site annually, and it is a centerpiece of local political and environmental dialog. Photograph courtesy of the City of Austin. Figure 1 5d. Old Mill Spring (OSP), one of the four springs in the Barton Spring System. A rock wall was built to contain the spring in the 1930s, but the spring is no longer accessible to the public because of safety issues and its designation as an endangered species habitat. Figure 1 5e. The Barton Springs salamander ( Euryceasosorum), a federally listed endangered species. The salamanders only known habitat is the Barton Springs system (springs MSP, ESP, OSP, and USP). Adults reach about 6 cm in length and retain their gills throughout their entire life cycle. The salamander is very sensitive to changes in water quality (Mahler and Lynch, 1999). Photograph by W. Meinzer(U.S. Fish and Wildlife Service).

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(a) (b) (c) (d) (e)

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Figure 1 6 Schematic diagram showing a plan view of the two modes of operation of Barton Spring Pool with respect to flow in Barton Creek. (a) Under most conditions, the pool is filled solely by discharge from Main Barton Spring, while any surface water flow in Barton Creek is diverted around the pool by a dam;(b) under very high stormflow conditions, surface water flow in Barton Creek overtops the upper dam. During these flood conditions, access to Main Barton Spring for water quality sampling is difficult or impossible. Barton CreekBarton Springs Pool Main Barton Spring (MSP) OrificeDiversion Tunnel Barton Creek N U p p e r D a m L o w e r D a m EXPLANATION Surface Water Flow Spring Flow(a) Barton Creek Barton Springs Pool Main Barton Spring Orifice Diversion Tunnel Barton Creek N (b) Barton Creek200 m 0 200 m 0

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Figure 1 7 Polished slab of limestone showing moldicporosity typical of meteoric diagenesis and dissolution of metastableminerals. Some marine pelecypodand gastropod shells are initially deposited as the metastablemineral aragonite, and are subsequently dissolved upon exposure to meteoric water. The surrounding low magnesium calciticmud is not dissolved. This process creates a rock with high porosity but low permeability. Permeability may be enhanced by solution enlargement of these original pores, although this is not seen here. Photo is of the Cedar Park Limestone, time correlative with the upper Walnut Formation and lower Edwards Limestone, as seen on an exterior wall of the University of Texas Geology building. 10 cm 0

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2. Investigation of the relationship between surface water flow and karst ground water geochemistry in the Barton Springs segment of the Edwards aquifer 2.1. ABSTRACT Historical ground water geochemistry data from the Barton Springs segment of the Edwards aquifer were analyzed to determine the relation between ground water geochemistry in 26 wells, flow rates in five creeks that provide recharge to the aquifer, and aquifer flow condition as measured by the discharge rate of a karst spring. Twenty six years of arbitrarily timed specific conductance measurements in wells were compared to contemporaneous aquifer flow conditions and surface water discharge rates. Using a non parametric statistical test, the wells were divided into groups with similar statistical properties. Specific conductance in 9 of the 26 wells exhibited a negative statistical correlation to streamflow or aquifer flow condition. This was interpreted as evidence of an influx of low ionic strength recharge water during periods of high surface flow: four wells were concluded to intersect major aquifer flowpaths, and five were concluded to intersect minor aquifer flowpaths. Six wells had a positive correlation between specific conductance of and aquifer flow condition, which was not interpreted as reflecting intersection of a flowpath, but

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rather as the influence of some other process. Of the 17 wells that did not have a negative correlation between specific conductance and streamflow, no conclusions regarding flowpath intersection were drawn. In some cases, data for wells might not have indicated intersection with a flowpath because of small sample sets. Aquifer ground water was generally calcium bicarbonate to calcium magnesium bicarbonate, although some water compositions deviated from this. Multiple geochemical processes were identified that may affect well geochemistry. On the basis on SO4/Cl and Mg/Na concentration ratios, some wells seemed to receive a portion of their water from the saline zone to the east, which may extend as a saltwater lens under the freshwater portion of the aquifer. Other wells may have received some of their water from the underlying Trinity aquifer, especially when aquifer flow conditions are high. Despite the arbitrary sampling interval of this historic record, use of statistical methods to distinguish between wells controlled by various processes appeared to have value. 2.2. INTRODUCTION In karst aquifers, surface water can enter the aquifer as focused recharge through fractures, cavities, or sinkholes and move rapidly through the system via solution enlarged fractures or conduits to discharge from springs or wells. Although ground water is stored throughout the pore spaces in the carbonate rock, the

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majority of ground water transport occurs through these solution enlarged cavities and conduits (Ford and Williams, 1989; Sharp, 1993; Maloszewski et al., 2002). As a result, recently infiltrated ground water moving through these conduits has little time to equilibrate with the rock matrix, and bears a geochemical signature similar to that of surface water. Because of their high hydraulic conductivity, these conduits also are usually major flowpaths in the aquifer. To understand the way in which a karst aquifer functions, it is desirable to find the locations of these flowpaths. One approach to locating flowpaths is to identify wells that intersect them, and map the geography of these wells and infer flowpaths between them, using their major ion geochemical signatures as verification of the findings. Several approaches can be used to identify wells that intersect major conduits and flowpaths. Pump tests can identify wells with very high specific capacities, which may be related to intersection of large conduits. Monitoring of physical, chemical, and biological parameters during storm flow conditions may also identify those wells that intersect flowpaths (Andrews et al., 1984). Dye trace studies monitoring the arrival or non arrival of a dye injected at the surface in nearby wells can use this information to map connections between individual recharge locations and wells (Hauwert et al., 2005). In this study, an alternative to these physical approaches is presenteda 26 year record of the aqueous geochemistry of water in wells is used to identify wells that intersect major flowpaths.

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Specific conductance is a physical measurement of the amount of electrical current that water can transmit, and a direct reflection of the ionic strength, or total amount of dissolved solids, in the water (Hem, 1982). Rain has very low specific conductance (Herczeg and Edmunds, 2000); surface water has a higher specific conductance resulting from chemical reactions with the land surface, soils, and the streambed; ground water typically has a higher specific conductance than surface water resulting from the dissolution of the rock matrix of the aquifer. Thus, specific conductance can act as a tracer of infiltrated surface water with low specific conductance. Because of their close connection with the surface water system, the geochemistry of karst springs can be extremely variable (Shuster and White, 1971). In response to precipitation events, focused recharge moves rapidly through fractures and conduits into the aquifer and springs. As a result, a rapid decrease in total dissolved solids occurs, which gradually increases back to a value more representative of interaction with the rock matrix (e.g., Ryan and Meiman, 1996; Desmarais and Rojstaczer, 2002). In this study, this concept is extended to wells, with the hypothesis that the geochemistry of water in a well that intersects a fracture or conduit along an aquifer flowpath should respond in a similar manner, that is, the specific conductance should decrease in response to the influx of recent recharge.

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A high sampling frequency is desirable for investigating the relation between surface water and ground water in a karst aquifer (e.g., Dreiss, 1989; Lakey and Krothe, 1996). However, the dataset for this study generally does not contain high frequency sampling intervals (hours to days). Nevertheless, it is hypothesized that a large data ensemble even from infrequent and arbitrarily timed sampling carried out over 26 years contains some of the same information as data from a study with a high sampling frequency. 2.3. STUDY AREA The Barton Springs segment of the Edwards aquifer (herein referred to as the Barton Springs segment) is a karst aquifer that extends south southwest of Austin. It is bounded to the north by the Colorado River, to the south by a ground water divide, to the west by its contact with the Glen Rose Formation, and to the east by a zone of low permeability (Maclay and Land, 1988) containing brackish to saline (> 1000 mg/L total dissolved solids) ground water known as the saline zone (Figure 2 1). Previous studies have characterized the lithology, structure, and physical and chemical hydrogeology of the Barton Springs segment. The aquifer material is composed principally of Cretaceous limestone that has undergone multiple episodes of karstification (Rose, 1972; Maclay, 1995; Small et al., 1996). In the Miocene epoch,

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tectonic activity created a zone of normal faulting, resulting in enhanced karstification and the aquifer structure and behavior seen today (Slade et al., 1986). The aquifer is generally highly transmissive, with some measured straight line transit times exceeding 10 kilometers per day (Hauwert et al., 2005). The Barton Springs segment resides within the Edwards and Georgetown Limestones, is underlain by the less permeable Walnut and Glen Rose Formations, and is overlain by the less permeable Del Rio Clay (Rose, 1972). In the recharge zone, the aquifer is unconfined, that is, the aquifer rock outcrops on the surface. The confined zone is defined by the area where the Del Rio Clay and younger rocks overlie the Edwards and Georgetown Limestones (Figure 2 2). The dissolved ion chemistry of Barton Springs segment ground water is generally calcium bicarbonate (Ca HCO3) to calcium magnesium bicarbonate (Ca Mg HCO3) containing less than 500 mg/L total dissolved solids, although significant variations in dissolved constituents and molar ratios have been observed (Senger and Kreitler, 1984). Studies such as Andrews et al. (1984) have shown that some geochemical variability is attributable to episodic recharge of meteoric water in response to storms. About 85 percent of the recharge to the aquifer is estimated to occur through karst features in the creek beds of Barton, Williamson, Slaughter, Bear, and Onion Creeks (Slade et al., 1986). These are ephemeral creeks that cross the recharge zone

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from west to east (Figure 2 1). Examples of karst features are fractures, faults, and sinkholes. Additional sources of recharge include upland infiltration through sinkholes and fractures, urban infrastructure, and cross formational flow from other hydrostratigraphic units (Sharp and Banner, 1997). Flow in the aquifer is generally to the north northeast, following the trend of the Balcones Fault Zone, although direction of flow varies with changes in aquifer flow condition and resulting changes in the potentiometric surface (Slade et al., 1986). Discharge from the aquifer is from springs and wells. The primary discharge point is a cluster of springs at the northeastern edge of the aquifer known as the Barton Springs system (Figure 2 1). Combined long term mean discharge from the three major orifices in the system is about 50 ft3/s (Slade et al., 1986). Additional ground water is withdrawn from the aquifer by pumping from domestic, livestock, and public supply wells. In 2004 there were an estimated 970 active wells pumping from the Barton Springs segment, with annual ground water withdrawals of about 2.5 billion gallons per year (Smith and Hunt, 2004), equivalent to a constant withdrawal rate of about 10 ft3/s (0.3 m3/s). Since 1978, the United States Geological Survey (USGS) has collected about 600 water quality samples from 26 of these wells (Figure 2 1 and Table 2 1), and these geochemical data are used in this studys analysis.

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2.4. STUDY APPROACH The approach taken here was to evaluate historical geochemical data from 26 wells in the Barton Springs segment (Table 2 1) in the context of contemporaneous surface water flow data and aquifer flow condition data, under the hypothesis that recharging water and variable aquifer flow conditions can result in variations in well geochemistry. The approach was to use statistical correlations between specific conductance in wells, discharge rates in streams, and aquifer flow condition to identify those wells connected to fractures or major flowpaths. Major ion geochemistry data from the wells were used to better understand the geochemical processes affecting the ground water. Discharge values from gaging stations along Barton, Williamson, Slaughter, Bear, and Onion Creeks were used as measures of streamflow (Figure 2 1). High flow in the creeks was assumed to indicate recent rainfall and associated recharge. The discharge rate of the Barton Springs system was used as an indicator of aquifer flow condition. High flow rates were assumed to indicate high aquifer flow conditions. Aquifer flow condition thus is represented by a single value that measures the overall state of the Barton Springs segment with respect to ground water storage and flow velocity. Senger (1983) confirmed that, like most springs, the discharge rate of the Barton Springs system is directly controlled by the amount of water stored in the Barton Springs segment.

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Specific conductance was used as an overall measurement of ground water geochemistry. However, as variations in specific conductance do not indicate which dissolved ion concentrations are changing, the major ion geochemistry of the ground water was interpreted to determine what geochemical processes might be occurring. 2.5. METHODS 2.5.1. Sample collection Ground water samples were collected by the USGS from 1978 to 2003, from privately owned domestic and livestock wells and municipal wells (Table 2 1) in which a variety of construction and plumbing techniques were used. Most wells were completed entirely within the Edwards aquifer (Edwards and Georgetown Limestones), and steel casing was used to seal off formations that are not part of the aquifer (e.g., Del Rio Clay, Buda Limestone, etc.; Figure 2 2). Almost all wells were completed in the aquifer as open hole. Most wells did not penetrate the full thickness of the aquifer; generally, drillers followed a two step process (Maclay, 1995): (1) drill to the top of the aquifer and install casing, and (2) drill until a cavernous zone is encountered or the bottom of the aquifer is reached. Three wells in the recharge zone (GHW, SLR, and FOW) were drilled partly into the underlying Walnut and Glen Rose Formations and therefore were drilled partly into the Trinity aquifer (N. Houston, U.S. Geological Survey, written comm., 2005). Because of

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permeability differences in the aquifer rock, wells may have yielded water that is a mixture of several permeable zones, and variable pumping rates and times may have affected this mixing (Hem, 1985). Samples were collected from wells at points in the plumbing upstream of pressure tanks or treatment equipment in order to obtain a sample representative of aquifer water. Water was abstracted from the well by either using an electric submersible pump, or by hand bailing. Samples were collected after purging at least three casing volumes of water from the well and after readings of field parameters (temperature, pH, and specific conductance) had stabilized. Beginning in 2001, USGS National Water Quality Assessment Program sampling protocols and analytical schedules were incorporated into the sampling program (Koterba et al., 1995). Specific conductance was measured and recorded during all USGS sampling events at wells. The instrument models used to take this measurement changed over the years, but standard procedures were consistently followed (Radtke et al., 1998a). Instruments were calibrated using at least two standard solutions of known specific conductance and documented. Specific conductance measurements were taken after at least three well volumes of water were purged from wells (United States Geological Survey, 1984; Wilde et al., 1999). The final reported specific conductance

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value was typically computed as the median value of five readings taken over a 15 minute period. Water samples for major ion analysis were collected and filtered through 0.45 m cellulose filters. Anion samples were dispensed into pre rinsed polyethylene bottles. Cation samples were placed in pre rinsed acid cleaned polyethylene bottles, and the sample was preserved with a strong acid to a pH of less than two. Samples were promptly chilled on ice in dark conditions, and shipped to the USGS National Water Quality Laboratory (NWQL) for analysis. 2.5.2. Laboratory analytical methods Analytical methods at the NWQL changed over the period of investigation. Major cations were analyzed by atomic absorption spectroscopy (Fishman and Friedman, 1989, p. 137,263,393,425), by atomic emission spectroscopy (Fishman, 1993, p. 101), and most recently by inductively coupled plasma mass spectrometry. Prior to 1990, chloride concentration was determined using titrimetric or colorimetric methods (Fishman and Friedman, 1989, p. 151 159), and sulfate concentration was measured using turbidimetric analysis by formation of barium sulfate. After 1990, chloride and sulfate were measured using ion chromatography (Fishman, 1993, p. 19). Nitrate (NO3 ) was analyzed using ion chromatography or cadmium reduction diazotization colorimetry (Fishman, 1993, p. 157). Based on the findings of

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Andrews et al. (1984), concentration of nitrite (NO2 ) was assumed to be negligible, thus the measured nitrate+nitrite parameter was assumed to solely indicate nitrate concentration. Trace elements such as strontium were assumed to be of negligible concentrations, and ion complexation was assumed to be negligible. Despite variations in collection and analysis methods, this study assumes that methods have been sufficiently consistent to allow side by side comparison of major ion concentrations. Two additional criteria were used to screen analytical results from the large historical record. First, wells with fewer than six specific conductance measurements were excluded, as they did not provide a sufficient record for statistical analysis. Second, water analyses with a charge balance error greater than 5 percent were excluded (Freeze and Cherry, 1979, p. 97), similar to methods employed by other researchers synthesizing large historic datasets (e.g., Uliana and Sharp, 2001) 2.5.3. Statistical analysis of specific conductance and flow data Data were compared to see if there was a statistical relation between streamflow rates and specific conductance measured in well water, and between aquifer flow condition and specific conductance measured in well water. For each specific conductance value, data for the previous ten days of streamflow in the five creeks were inspected, and the maximum mean daily streamflow rate for each creek

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for that 10 day period was recorded (Appendix A, Table A 1). The relations between the specific conductance data and corresponding streamflow measurements were compared using the non parametric Spearman rho rank test (Helsel and Hirsch, 1995). A non parametric correlation test such as Spearmans rank correlation was used because the surface water flow and spring discharge data do not follow a normal distribution (Figure 2 3). For the comparison of specific conductance and aquifer flow condition, the Spearman rho test was used to test the relation between specific conductance and Barton Springs system discharge for the day that the specific conductance measurement was collected. Barton Springs system discharge rates were determined by measuring ground water levels in a nearby well and using a stage discharge relationship (rating curve) to compute discharge. This rating curve was periodically refined with manual discharge measurements taken using a current velocity meter (Buchanan and Somers, 1969). The Spearman rho test measures the strength of association between two variables (Helsel and Hirsch, 1995). The data for each variable are ranked, and the differences between the ranks analyzed as ) 1 ( 6 12 2n n d (Eq. 2 1) where d is the difference in ranks and n is the number of ranks. varies from 1 to 1; a of 1 expresses a perfect monotonic negative relation, and an of 1 expresses a

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perfect monotonic positive relation. Spearmans (rho) is analogous to the Pearson r, the product moment correlation coefficient, in that it expresses the proportion of the variability accounted for, but on the basis of ranks. Basic summary statistics were used to describe properties of water samples in a general way. Minimum, maximum, arithmetic mean, and median are examples of common summary statistics used in this study. Median values for groups of wells were computed using a two step process. First, the median value for each well was computed. Then, the median of these median values was computed, and this is the number reported. This two step procedure was necessary to avoid sampling bias arising from variable numbers of samples taken from each well. Without this two step process, median values would be disproportionately influenced by wells with large sample sets, and wells with small sample sets would have comparatively little effect on the average value. Coefficients of variation (Cv) also were computed for several geochemical parameters. Cv is defined as the standard deviation divided by the arithmetic mean, and is a quantitative measurement of the degree to which numbers in a set deviate from the mean value.

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2.6. RESULTS 2.6.1. Specific conductance The specific conductance dataset for the 26 wells contains 689 values ranging from 388 to 1530 microsiemens per centimeter ( S/cm) (Appendix A; Table A 1). Eight wells have only six specific conductance values, the minimum number required for inclusion in this study, and four wells have more than 50 values. The widest range (445 to 1530 S/cm) occurs in water from well SVE, and the narrowest range (480 to 495 S/cm) occurs in water from well ISD. One half of the wells had water with less than 100 S/cm variation. The median Cv for specific conductance for all well samples is 0.035, with a range of 0.011 to 0.283. 2.6.2. Streamflow and aquifer flow condition The streamflow dataset consists of approximately 9,000 mean daily streamflow values for each of the five creeks. Williamson and Slaughter Creeks have discharge data available for the entire period from 1978 to 2003, data for Bear and Onion Creeks span 94 percent of this period, and data for Barton Creek span 76 percent of this period. Streamflow data for Barton Creek were unavailable from 1983 to 1988, thus 31 percent of specific conductance samples could not be tested against Barton Creek discharge. These full listing of these data are omitted from this study for brevity, but are available in their entirety in Garner et al. (in press).

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2.6.3. Statistical test Results from the non parametric correlation test between specific conductance, streamflow rates, and aquifer flow condition (Appendix A; Table A 2) were used to divide the 26 wells into distinct populations. Fifteen of the 26 wells exhibit a statistically significant relation between well water specific conductance and streamflow or aquifer flow condition (p < 0.05 confidence level). The wells were further divided into four groups (Table 2 2, Figure 2 5). Wells in group C1 exhibit a negative correlation between specific conductance and streamflow, and a negative correlation between specific conductance and aquifer flow condition. Wells in group C2 exhibit a negative correlation between specific conductance and streamflow only. Wells in group P exhibit a positive correlation between specific conductance and aquifer flow condition. Wells in group N do not exhibit a correlation between specific conductance, streamflow, or aquifer flow condition. The statistical analyses produced some spurious correlations resulting from autocorrelation between the streamflow rates in the different creeks. Autocorrelation occurs when a widespread rainfall produces proportional changes in flow on all five creeks; the geochemistry in well water may be influenced by flow in only one or two of the creeks, but will be correlated to flow in all five. For

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example, the specific conductance of samples from well MCH is correlated with flow in Barton, Williamson, and Slaughter Creeks, but as MCH is far upgradient from (south of) these creeks, it is unlikely that flow in these creeks has an influence on the geochemistry of the well water. Spurious correlations were determined on the basis of location of the wells and creeks and existing information on direction of flow. These determinations were made conservatively and with caution, as direction of flow in karst terrane is often difficult to ascertain and can be temporally variable. 2.7. DISCUSSSION 2.7.1. Geochemical variability at the event scale To provide a frame of reference for considering the long term relation between surface water and ground water in a karst aquifer, a high frequency sampling event (hours to days) in this studys dataset is considered in this section. Well SVW exhibits a long term statistical correlation between the specific conductance of its water and streamflow in all five creeks; the strongest correlation is with Bear Creek (Table 2 2). In October 1994, well SVW was sampled at 6 to 12 hour intervals beginning 2 days after a rain event. The results of this sampling provide an opportunity to investigate how the geochemistry of a well changes in response to rain and resulting flow in a nearby creek at a short time scale.

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Flow in all five recharging creeks increased on October 7, 1994. The highest mean daily flow was recorded at Barton Creek (476 ft3/s), followed by Slaughter Creek (99 ft3/s), Williamson Creek (73 ft3/s), Bear Creek (33 ft3/s), and Onion Creek (30 ft3/s). Fifteen samples were collected at well SVW from October 9 at 7:00 AM to October 15 at 12:30 PM. Over the sampling period, specific conductance in water from well SVW ranged from 570 to 678 S/cm. The lowest specific conductance value was measured in the first sample, collected two days after maximum streamflow. From a comparison of flow in Barton Creek and specific conductance in SVW, it appears that well water responded rapidly to an influx of recharge from one of the nearby creeks (Barton or Williamson) (Figures 2 1 and 2 6a). However, the data indicate that specific conductance had probably already reached the minimum value of 570 S/cm and had begun to rise before the first sample was collected. Thus, the lowest specific conductance value and its timing in response to creek flow for this event is unknown. The rapid response to streamflow (less than two days) suggests that the 10 day criteria for response to stream flow for the statistical comparison of specific conductance to peak streamflow is reasonable. The increase in specific conductance in well SVW water was followed by a subsequent decrease, which indicates that this well may obtain recharge from more than one creek; the first decrease occurred less than 2 days after rainfall, and the

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second decrease occurred about 4 days after rainfall (Figure 2 6a). Although Hauwert et al. (2005) suggest that this well is located in a small aquifer subbasin and does not receive recharge from multiple creeks, it is possible that transient flowpaths are activated during high recharge periods. Alternatively, it could have received recharge from two different recharge points in the same creek. In a plot representing the storm related samples from well SVW on a Piper diagram (Figure 2 6b), the points representing the 15 samples overlie one another, indicating that the changes in specific conductance largely are attributable to dilution rather than to mixing with another ground water type. The dilution likely results from infiltration of surface water containing fewer dissolved ions. There is a slight shift along the calcium magnesium axis, which could simply indicate a change in residence time (Musgrove and Banner, 2004). Changes in log SIcalcite values over time are consistent with the hypothesis of two influxes of recharge water into well SVW (Figure 2 6c). Log SIcalcite values were low in the first sample, indicating a very recent influx of surface water. As the undersaturated surface water mixed with ground water presumably in equilibrium with calcite, the saturation index increased, before decreasing with the second influx of surface water. The second influx of recharge water was not as undersaturated as the first, indicating that effects from the rainfall had began to decrease after four days.

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During the sampling period, the Mg/Ca molar ratio for water in well SVW increased from 0.35 to 0.47, suggesting that low ionic strength stormflow water began to react with the aquifer and evolve. Alternatively, this behavior could also result as influx of recharging water ceases and is replaced in well SVW by more geochemically evolved ground water that was in the aquifer prior to the recharge event. Concentrations of other ions in the samples from well SVW varied in response to flow in Barton and Williamson Creeks (Figure 2 6d). Na+ and Cl concentrations were lowest in the first samples collected. Following an increase in Na+ and Cl concentrations that mimicked that of specific conductance, these concentrations decreased again (probably in response to a second influx of recharge water). In the first sample collected, molar concentrations of Na+ to Cl are about 1:1, indicating a potential NaCl (halite) source from surface water, but in the final samples molar concentration ratios of Na+ to Cl are about 0.75:1, suggesting that water in this well under steady state conditions is more enriched in Cl than Na+. Sulfate (SO4 2 ) concentrations increased in the first few samples, but the lowest concentrations were in the second influx of surface water (Figure 2 6d). This suggests that the two different influxes have different sources or have the same source but follow different flowpaths.

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Nitrate (NO3 ) concentrations were lowest in the first samples collected, suggesting that the influx of surface water has a lower NO3 concentration than the ground water. Concentrations of NO3 in streamflow associated with storm events in creeks repeatedly have been observed to be less than those in water discharging from the Barton Springs system (City of Austin, 1997). After the initial recovery from the first influx of surface water, NO3 concentrations closely track Cl concentrations (Figure 2 6d). Overall, this well typifies the geochemical response of a well on a major flowpath, with specific conductance, ion concentrations, and ionic ratios varying on the scale of days following a recharge event (Figures 2 6). The results of this analysis suggest that wells in a karst aquifer can intersect flowpaths that connect to surface water source areas. Because of this connection, changes in surface water flow affect the geochemistry of these wells over short time scales. The following section considers this same type of effect, but using a dataset that replaces high frequency sampling with sampling over a long time period under variable hydrologic conditions.

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2.7.2. The four well groups 2.7.2.1. Group C1 wells Four wells in Group C1 (FMW, KCH, SLR, and SVE) (Figure 2 7a; Table 2 2) have specific conductance that is negatively correlated to flow in one or more of the five recharging creeks, and also negatively correlated to aquifer flow condition (as measured by discharge from the Barton Springs system). When aquifer flow conditions are high and streamflow rates are high, wells in group C1 are more likely to have water with lower specific conductance values than when aquifer flow conditions are low and streamflow rates are low. This suggests that these wells intersect major flowpaths or conduits that transport recharge from the surface through the aquifer, and that these flowpaths respond to overall aquifer flow conditions, integrating water from a large volume of the aquifer. Examples of the correlations between specific conductance at one of the wells (FMW), flow in Slaughter Creek, and discharge from Barton Springs are shown in Figure 2 8. The Spearmans (rank correlation coefficients) for wells in group C1 are among the highest for the wells tested; forty three percent of all rank correlation coefficients with magnitudes greater than 0.5 are from group C1 (Table 2 2). Of note is a strong correlation ( =0.63) between specific conductance in well SLR water and flow in Bear Creek. Although the general direction of flow in the aquifer is to the NNE, this well responds to flow in Bear Creek to the north (Figure 2 1), which is

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inconsistent with dye traces that have demonstrated this to be an area of eastward flow (Hauwert et al., 2005). One explanation for this behavior could be flowpaths in the vadose zone that only carry water during high streamflow. Specific conductance in group C1 well water samples ranges from 445 to 1530 S/cm, with a median value of 653 S/cm. Specific conductance varies more for this group of wells than for the other three groups, with a median Cv of 0.053. Within group C1, well SVE water has both the minimum and maximum specific conductance values, and has the highest Cv (0.23) of the four wells. The hydrochemical facies of group C1 wells range from Ca HCO3 to Ca Mg HCO3 (Figure 2 7b). Water samples from wells FMW and SLR, and to a slightly lesser extent well KCH, exhibit few geochemical changes other than dilution. Well SVE water trends toward a more sulfate type signature. Mean logSIcalcite values for water from wells in group C1 are about zero (saturated) for wells KCH and SVE, and about 0.2 (oversaturated) for FMW and SLR. During periods of high streamflow and aquifer flow conditions, logSIcalcite values vary less and are typically closer to zero for wells KCH, SVE, and SLR. During periods of no flow in the creeks and low aquifer flow conditions, logSIcalcite values are more variable in both the undersaturated and supersaturated directions. Because group C1 exhibits a correlation with streamflow and aquifer flow condition, it should be the most likely group of wells to exhibit systematic logSIcalcite variability as

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a result of recharge, but it is not. The results of logSIcalcite analysis for this long term record are unclear. Although there is a clear relation between logSIcalcite values and recent surface water reaching a well on a short time scale (Figure 2 6c), the long term record does not effectively capture these changes. This may be because long term samples are collected at somewhat arbitrary intervals, even after large rainfall events. There is also be a seasonal variation in calcite saturation in some recharge water (Banner et al., 2004), making an infrequently and arbitrarily sampled dataset difficult to analyze without a way to account for seasonal variability. Because of the unclear results of logSIcalcite analyses, they are not considered in later sections of this study. The Mg/Ca molar ratio for group C1 wells ranges from 0.3 to 0.9. Median values of Mg/Ca generally increase from southwest to northeast, following the general gradient of flow in the aquifer (Figure 2 2, 2 7b). This is consistent with the chemical process of incongruent dissolution, which creates elevated Mg/Ca ratios as residence time increases (see Chapter 1, section 1.4.3). Thus, water in downgradient wells, on average, has had a longer aquifer residence time than water from upgradient wells. Wells SVE and SLR show a correlation between Mg/Ca ratios and specific conductance when the highest 70 percent of specific conductance values are considered (Figure 2 7b). This correlation suggests that ionic strength is proportional to residence time for wells SVE and SLR, during periods when there is

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little recharge (that is, during baseflow conditions). Wells FMW and KCH do not exhibit this relationship. SO4/Cl and Mg/Na ratios can be used to identify water that is flowing into the Barton Springs segment from the underlying Trinity aquifer or the saline zone. Trinity aquifer water is characterized by a higher SO4 2 concentration relative to Cl and a higher Mg2+ concentration relative to Na+ (Figure 2 4). Conversely, saline zone water is distinguished by a higher Cl concentration relative to SO4 2 and a higher Na+ concentration relative to Mg2+ (Figure 2 4) (Sharp and Clement, 1988). Water in some group C1 wells shows evidence of mixing with the saline zone and Trinity aquifer under some conditions, as well as dilution by surface water (Figures 2 7c and 2 7d). Well SVE has the greatest range of SO4/Cl and Mg/Na ratios in group C1; during periods of low streamflow and aquifer flow conditions, water in well SVE appears to contain some proportion of water from the saline zone. Although SO4 2 concentration in well SVE is not linearly correlated to flow in Slaughter Creek, concentrations above 100 mg/L occur almost exclusively during periods of low (less than 4 ft3/s) or no flow in Slaughter Creek (Figure 2 9a). Sulfate concentration is inversely proportional to discharge at Barton Springs (Figure 2 9b). This evidence suggests that the source of the SO4 2 in well SVE is influx from the saline zone, which is suppressed when aquifer flow conditions and streamflow rates are high. This is supported by the relative increase in Na+ concentration with respect

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to Mg2+ (Figure 2 7d). Senger (1983) and Slade et al. (1986) have suggested that well SVE might receive some ground water from the saline zone. Well SLR appears to be receiving a small amount of water from the Trinity aquifer, on the basis of slight enrichment in sulfate relative to chloride and magnesium relative to sodium (Figures 2 7c and 2 7d). Drill logs indicate that well SLR is completed in formations that underlie the Barton Springs segment. Samples from wells KCH and FMW have little variability in their SO4/Cl and Mg/Na ratios, suggesting that variations in their geochemical composition is caused primarily by dilution from surface water during periods of high streamflow and aquifer flow conditions. Nitrate concentrations are consistently below 2 mg/L in wells FMW, SLR, and SVE, but range from 3.8 to 8.6 mg/L in well KCH, with a median concentration of 4.9 mg/L. Nitrate concentrations at all wells are independent of specific conductance, which suggests that there is no relation between NO3 concentrations and recent recharge (Figure 2 7e). Elevated NO3 concentrations appear to be related to localized sources rather than connection to incoming recharge solely, as all the wells in this group have geochemical variations that are affected by recharge but only one has high NO3 concentrations. However, given that well KCH had the highest NO3 concentrations of all 26 wells in this report, the data suggest that a well that is well connected to surface recharge (such as in group C1) might be more vulnerable to localized sources of contamination than one that is not. While the

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source of NO3 in well KCH cannot be determined from the data reported here, historically there was a goat ranch near this well (D. Johns, City of Austin, written comm., 2005), and agricultural runoff is a known source of NO3 in ground water. In summary, group C1 wells appear to intersect major aquifer flowpaths. As low ionic strength recharge water from the surface reaches these wells, total dissolved solids concentrations decrease and hydrochemical facies evolve toward more Ca HCO3. Two wells in this group show evidence of some mixing with water from the saline zone and Trinity aquifer: the hydrochemical facies of water samples from well SVE change in response to low streamflow and low aquifer flow condition, suggesting that water from the saline zone reaches this well under these conditions, and well SLR is well drilled into the Trinity aquifer. 2.7.2.2. Group C2 Wells For the five wells in group C2 (BDW, HWD, MCH, SVN, SVW) (Figure 2 10a; Table 2 2), specific conductance is negatively correlated with flow in one or more recharging creeks, but is not correlated with aquifer flow condition. This suggests that these wells intercept recharging surface water from creeks but are not connected to a major aquifer flowpath or conduit. Specific conductance values in group C2 wells range from 388 to 710 S/cm, with a median value for the five wells of 560 S/cm. The minimum, maximum, and

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median values for this group are the lowest of the four groups, indicating that water in these wells is less mineralized than that in wells in the other groups. The median Cv for group C2 specific conductance is 0.042, making it the group with the second highest variability after group C1, and underscoring its connection to surface recharge. Well SVN has both the minimum and maximum specific conductance values, encompassing the full range for group C2, and its Cv for specific conductance is the highest of group C2 wells (0.13). SVN undergoes large changes in stage, occasionally going dry to the bottom of its drilled interval (M. Dorsey, U.S. Geological Survey, personal commun., 2005) and its water level changes rapidly in response to flow in Barton Creek (Slade et al., 1986). The hydrochemical facies of ground waters in group C2 are Ca HCO3 to Ca Mg HCO3 (Figure 2 10a), which are similar to those of group C1 (Figure 2 7a). There is slight evolution in the water in wells SVN and SVW toward a more chloride sulfate type water, suggesting contribution of ions from a source other than surface water. Generally, group C2 geochemical variability is more tightly constrained than that of group C1, suggesting that fewer processes affect the geochemical composition of group C2 wells. The wells in group C2 have about the same range of Mg/Ca as wells in group C1, but they vary little for individual wells except BDW (Figure 2 10b). There is no apparent relation between Mg/Ca ratios and geography for group C2 wells,

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consistent with the hypothesis that group C2 wells intersect isolated flowpaths, and thus are not influenced by the cumulative effects of large catchment areas in the aquifer. Unlike group C1 there is no apparent relation between Mg/Ca and specific conductance for any wells (Figure 2 10b). Geochemical variability is more tightly constrained in group C2 than in group C1 (Figure 2 10c and 2 10d; compare to Figures 2 7c and 2 7d). Generally, there is little to no evidence for mixing with waters from the saline zone or Trinity aquifer. Samples from wells BDW and HWD have the smallest variations in SO4/Cl ratios in this group and some variability in Mg/Na ratios, suggesting that their geochemical composition is affected by dilution from surface water during periods of high streamflow, resulting in lower residence time water and lower Mg2+ concentrations. Well MCH may contain water with a small amount of mixing from the Trinity aquifer. Well SVW samples are somewhat enriched in SO4 2 relative to Cl, but their Mg/Na ratios are relatively constant. This suggests that the source of SO4 2 in well SVW water is something other than the Trinity aquifer or the saline zone, for example dissolution of gypsum. Nitrate concentrations in wells in group C2 are consistently less than 2 mg/L with the exception of well SVW, in which NO3 concentrations range from 1.5 to 3.0 mg/L. Well SVN has low concentrations of nitrate (< 1 mg/L) over a wide range of specific conductance values, but if the other four wells are viewed together

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statistically there is an increase in nitrate concentration with an increase in specific conductance (Figure 2 10e). If specific conductance is interpreted as a measure of the proportion of high residence time ground water in relation to recent recharge water, then the increase in NO3 coupled with the increase in specific conductance suggests that the ground water has higher ambient concentrations of NO3 than the surface water. Well SVN has relatively constant NO3 concentrations, and is the one well in group C2 that has high proportions of Cl under low recharge conditions, suggesting that SVN may receive some of its water from an unidentified source. In summary, wells in this group are connected to minor aquifer flowpaths that are well connected to the surface. Flowpaths intersected by group C2 wells probably have smaller catchment areas than those in group C1; to use an analogy from surface water hydrology, these flowpaths are the tributaries as opposed to the trunks. Similarly to group C1, dilution by low ionic strength surface recharge appears to be a dominant process for some wells in this group. Group C2 wells have constrained hydrochemical facies, and show very little evidence of mixing with the saline zone or Trinity aquifer. This suggests that their geochemical composition is affected dominantly by differing amount of limestone dissolution and variable water residence times. In effect, when there is no streamflow, group C2 wells receive their water from diffuse flow from the nearby and surrounding matrix portion of the

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limestone rock. Nitrate concentrations in group C2 wells generally indicate a natural source of nitrate. 2.7.2.3. Group P Wells For the six wells in group P (FOW, GHW, LWK, ROL, SVS, WGF) (Figure 2 11a; Table 2 2), specific conductance is positively correlated with aquifer flow condition. When aquifer flow conditions are high, water samples from wells in this group are more likely to have higher specific conductance values than when aquifer flow conditions are low. This behavior is the inverse of that seen in groups C1 and C2, in which high aquifer flow conditions or high surface water flows are correlated with low specific conductance of the ground water. Except for well ROL, specific conductance in group P wells is not correlated with surface water flow. Wells LWK and WGF had only six specific conductance measurements, the minimum for inclusion in the statistical analysis. The smaller the sample size, the less likely a well is to show a correlation between specific conductance and streamflow or aquifer flow conditions, as the number of samples collected during periods when the ground water in these wells was under surface water influence might have been insufficient to indicate that influence. Specific conductance values for group P wells range from 480 to 1160 S/cm, with a median value of 603 S/cm. The median Cv for specific conductance for the

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six wells in Group P is 0.033, the lowest among groups C1, C2, and P. Four of the wells (GHW, LWK, SVS, WGF) have a specific conductance range of less than 100 S/cm. Well ROL has the widest range (480 to 1160 S/cm), representing the full range of variation for this group. The wide range in specific conductance for this well suggests that it may be connected to an aquifer flowpath, despite its lack of a negative correlation with streamflow or aquifer flow conditions. The wells with the strongest correlation to aquifer flow condition in group P are LWK ( =0.88) and WGF ( =0.94) (Table 2 2). Correlations for LWK and WGF are based on the minimum six data points and less than 60 S/cm of variation in specific conductance. Wells ROL and FOW are the only wells in any group for which specific conductance is positively correlated to streamflow (Barton and Slaughter Creeks, Table 2 2). ROL is located in a subbasin thought to be hydrologically isolated from Barton Springs and the majority of the aquifer (Hauwert et al., 2005). FOW is located far upgradient of Barton Creek, and specific conductance in this well is not correlated to flow in either Williamson or Slaughter Creek. The positive correlation between specific conductance in these two wells and streamflow likely is the result of autocorrelation between streamflow and aquifer flow condition. The hydrochemical facies of ground waters in group P vary from Ca HCO3 to Ca Mg HCO3 to Ca Mg SO4 (Figure 2 11a). Four of the six wells (GHW, LWK, SVS, and WGF) are Ca HCO3 to Ca Mg HCO3 waters, similar to the dominant

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hydrochemical facies of the other three groups. Most of the variation in relative proportions of major ions is accounted for by Ca2+ and Mg2+. In contrast, wells FOW and ROL trend toward SO4 and Cl type facies, respectively. FOW and ROL also have the greatest Cv for specific conductance in group P. Drill logs indicate that well GHW is drilled into formations that underlie the Barton Springs segment, but its Ca Mg HCO3 chemistry indicates Edwards Limestone water. Given the positive correlation between specific conductance and aquifer flow condition in group P, an inverse relation between specific conductance and residence time (Mg/Ca ratio) might be expected for all group P wells. However, Mg/Ca ratios are generally independent of specific conductance for most wells in group P (Figure 2 11b). Well ROL is an exception to this, in that its Mg/Ca ratios (residence time indicators) decrease as specific conductance values increase. The fact that this is only observed for well ROL suggests that some other process is occurring, or that Mg/Ca is not an effective measure of residence time for group P wells. Well ROL is known to have a local source of anthropogenic contamination, which may the source of its inverse relation between specific conductance and Mg/Ca ratios. Well FOW has a direct relation between Mg/Ca ratios and specific conductance, but this is most likely due to cross formational flow from the Trinity Aquifer during high aquifer flow conditions.

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Some wells in group P show evidence of mixing with the Trinity aquifer, while others have an unclear explanation for their geochemical variability. Wells FOW and SVS are enriched in SO4 2 relative to Cl and Mg2+ relative to Na+ under high flow conditions, which is the geochemical signature of the underlying Trinity aquifer (Figure 2 11c and 2 11d). Sulfate concentrations in well FOW can reach up to about four times the baseline level, but this occurs only when Barton Springs system discharge exceeds about 85 ft3/s (Figure 2 12). Other studies have also suggested that sulfate rich water from the underlying Trinity aquifer (Figure 2 2) enters well FOW when aquifer flow conditions are high (Hauwert and Vickers, 1994; City of Austin, 1997), and these results are consistent with drill logs indicating that well FOW is partially drilled into the Trinity aquifer (N. Houston, U.S. Geological Survey, written comm., 2005). Similar Trinity aquifer mixing is apparent in well SVS, and is seen in well GHW to a lesser extent. This suggests that cross formational flow from the Trinity aquifer occurs in the Barton Springs segment, particularly during high aquifer flow conditions. Thus for these wells, the positive correlation between aquifer flow conditions and specific conductance is the result of mixing with high sulfate Trinity aquifer water. These findings are supported by a quantitative mixing model (e.g., Banner et al., 1989); a hypothetical mixture between an average Barton Springs segment groundwater and an average Trinity aquifer water yields a line

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along which samples from wells SVS and FOW plot closely (Figures 2 11c and 2 11d). In contrast, water in well ROL has proportions of SO4 2 relative to Cl and Mg2+ relative to Na+ that are more or less constant (Figure 2 11c) with perhaps a slight enrichment in Cl. This geochemical signature corresponds to neither the Trinity aquifer nor the saline zone. One explanation for excess Cl and increased specific conductance with high aquifer flow conditions is contamination from surface water; the use of well ROL was discontinued several years ago because of defective well casing that allowed contaminated surface water to easily reach the water table (City of Austin, 1997). Wells LWK and WGF have small datasets that do not indicate a clear source of geochemical variability. Nitrate concentrations in this group are generally less than 2 mg/L except for well SVS samples, which have a median NO3 concentration of 3 mg/L (Figure 2 11e). Although the specific source of elevated NO3 in SVS is not known, it is located near an urbanized region of the aquifer with numerous potential NO3 sources such as landscaping, septic systems, and wastewater infrastructure. Well GHW has the lowest average NO3 concentration in group P, and is located in the southwest quadrant of the aquifer, far upgradient from the more urbanized areas of the watershed.

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In summary, the water in the wells in group P has a tendency to become more mineralized during periods when aquifer flow conditions are high. For some wells, this may result from cross formational flow from the Trinity aquifer during high aquifer flow conditions. Urbanization may be another source of increased mineralization during high aquifer flow conditions. Yet another possible explanation for increased mineralization during high aquifer flow conditions is that conduits may reach a maximum capacity, and ground water may temporarily back up into large caves that are typically unsaturated (Halihan et al., 1998). These caves may contain soluble minerals (e.g., gypsum) that are rarely accessed. The specific conductance values have less variation than does that in groups C1 and C2, and four of the wells have a range in specific conductance of less than 100 S/cm. On the basis of statistical and geochemical data, all of the group P wells except ROL are interpreted as not intersecting flowpaths. 2.7.2.4. Group N Wells The 11 wells in Group N (BCK, BPS, CNE, HND, ISD, JBS, PLS, RAB, SNL, TNR, and WBG; Figure 2 13a; Table 2 2) do not show a statistically significant correlation to streamflow or aquifer flow condition. so none of these wells are interpreted as intersecting a flowpath. However, of the 11 wells in group N, five wells had the minimum number of specific conductance values for testing (six

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values), and eight wells had fewer than the median number of specific conductance measurements for this study (23 values). Only three other wells from the other three groups had the minimum number of six conductance values. In effect, many of the wells in group N may be in this group simply because of the number and timing of samples was insufficient to correlate significantly to streamflow or aquifer flow conditions. Specific conductance values for wells in Group N range from 460 to 1190 S/cm, with a median value for the 11 wells of 581 S/cm. The median Cv for specific conductance for group N is 0.029, the lowest value of any group. This group also contains the well with the single highest Cv among all wells in this study (well RAB, Cv = 0.283). Wells BPS, PLS, and TNR have Cvs of 0.029, 0.025, and 0.026 respectively; these low values are consistent with the hypothesis that they do not intersect flowpaths. Ground water represented by group N has diverse hydrochemical facies, from Ca HCO3 to Na K Cl SO4 (mixed) water types (Figure 2 13a). As this group includes all wells that do not fall into the other three groups, they are not necessarily expected to have similar geochemical compositions or even be controlled by similar geochemical processes; rather, they are in this group by default. Water in most of the wells is a Ca HCO3 to Ca Mg HCO3 water type, similar to that in most of the other wells in this report. Two wells, CNE and WBG, have geochemical signatures

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unlike those of waters from any other wells in this report, which may be a result of their proximity to the saline zone. The geochemical compositions of wells CNE and WBG (Figure 2 13a) approach the geochemical composition of the saline zone well (Figure 2 4), suggesting saline zone influence. Well RAB has variable hydrochemical facies that are similar to variations in well SVE (group C1). Group N has the largest range of Mg/Ca, from 0.3 to 1.1, of the four groups (Figure 2 13b). Individual wells in group N have smaller individual Mg/Caranges than the group as a whole, with the greatest range occurring in well TNR (0.3 0.7). The wells with the largest mean values are wells CNE and WBG, further evidence that these wells have a different geochemical signature. Interestingly, the Mg/Ca ratio of well RAB is almost unvarying despite its range in hydrochemical facies. On the basis of ion ratios (Figures 2 13c and 2 13d), some wells in group N show evidence of mixing with the saline zone. Well CNE is enriched in Cl relative to SO4 2 and enriched in Na+ relative to Mg2+, indicating geochemical influence from the saline zone. Well WBG has a cation signature corresponding to saline zone influence (Figure 2 13d), but the anion signature is less conclusive (Figure 2 13c). These findings are supported by a quantitative mixing model (Banner et al., 1989); by progressively mixing an average Barton Springs segment water samples with average saline zone water, it is apparent that samples from wells CNE and WBG plot near this line (Figures 2 13c and 2 13d). The samples do not perfectly fall along this

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mixing line, but that is probably due to the known spatial variability of the saline zones geochemical composition (Sharp and Clement, 1988; Hauwert and Vickers, 1994). The geochemical composition of well RAB is extremely variable (Figures 2 13a and 2 13b). Although the concentration of SO4 2 is elevated relative to Cl, the Mg2+ Na+ relation is not indicative of either a Trinity aquifer or saline zone source, suggesting an alternative source of SO4 2 such as dissolution of gypsum. Well TNR shows evidence of mixing with water from the Trinity aquifer. Well TNR is located only 15 meters away from well BDW, yet the two wells have different geochemical compositions. This is consistent with the spatial heterogeneity observed in karst aquifers (e.g., Sharp, 1993; Malard and Chapuis, 1995; Long and Putnam, 2004, among many others), and is a reminder that geographic patterns in karst aquifers are difficult to generalize. Nitrate concentrations in all wells in Group N are below 2 mg/L except for one sample in well JBS (Figure 2 13e). Wells CNE and WBG have the lowest NO3 levels of the 26 wells in this report. These two wells are near the chemically reducing saline zone (Sharp and Clement, 1988), so the low NO3 levels may be the result of denitrification, a biological process that converts NO3 to nitrogen gas under anoxic conditions (Freeze and Cherry, 1979, p. 415). Denitrification has been documented in several karst aquifers, including the Lincolnshire Limestone of

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England (Bishop and Lloyd, 1990) and the Illinois sinkhole plain aquifer (Panno et al., 2001). In summary, few generalizations can be made about wells in group N. Most of the wells in this group have fewer specific conductance measurements than the other groups, which decreases the likelihood that the samples would reflect periods when ground water chemistry was influenced by recharge through streambeds. In other words, their sample sets were too small to adequately capture the range of geochemical changes that they typically undergo. In other cases, there may be unidentified processes affecting the geochemical composition of well water; for example, well RAB is thought to intersect a highly transmissive conduit system of the aquifer (Senger, 1983), but changes in its geochemical composition are apparently not correlated to streamflow or aquifer flow condition. Ultimately, there is probably no single unifying hydrologic explanation for wells in group N, and it is difficult to make general statements about processes controlling these wells. 2.7.3. Wells and flowpath intersection This section synthesizes the evidence from the previous four sections, and the results are also summarized in Table 2 3. Some wells appear to intersect major flowpaths, as their geochemical composition is affected by recharging surface water. These wells also appear to integrate water flowing from a large up gradient part of

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the aquifer, as reflected by a negative correlation between specific conductance and aquifer flow condition. Other wells intersect smaller tributary flowpaths that are well connected to the surface, but whose water reflects the geochemistry of a small, localized area when streams are not flowing. These wells have specific conductance that is negatively correlated to streamflow, but not aquifer flow condition. Some wells have no geochemical evidence of intersection of flowpaths, but may be receiving cross formational flow from the underlying Trinity aquifer under high aquifer flow conditions. Finally, the geochemistry of some wells is influenced by mixing with water from the saline zone under low flow conditions. Wells in group C1 (FMW, KCH, SLR, SVE) are hypothesized to intersect major aquifer flowpaths that integrate water from a large area of the aquifer, based on their tendency to have less mineralized water when aquifer flow conditions and streamflow are high (Table 2 3). Most group C1 wells have a Ca HCO3 water type. The water type changes that do occur are a result of lower Mg/Ca ratios during periods of high recharge (shorter residence time), and dilution of SO4 2 during periods of high recharge. Mg/Ca ratios in these wells increase in a downgradient direction, reflecting longer travel times in a downgradient direction, and consistent with the hypothesis that these wells interest flowpaths that receive water from large sections of the aquifer. Wells that intersect major flowpaths are affected by the quality of recharging surface water, which suggests they may be vulnerable to

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localized sources of contamination. High NO3 levels in well KCH might be evidence of this. Additionally, because these wells are interpreted as receiving water from a large catchment area and a relatively large volume of the aquifer, they are likely to be susceptible to contamination from distant sources. Wells in group C2 (BDW, HWD, MCH, SVN, SVW) are interpreted as intersecting minor, or tributary, flowpaths in the aquifer (Table 2 3). Group C2 wells generally maintain a Ca HCO3 water type. Wells that intersect minor flowpaths are affected by the geochemistry of recharging surface water, which suggests they are vulnerable to contamination from localized sources. However, as these wells do not intersect the main trunk of flow in the aquifer, they may be less vulnerable than group C1 wells to contamination outside of the watershed of the stream to which they are connected. Because these wells are affected by surface water recharge only during periods of creek flow, they probably are vulnerable to contamination principally during periods of recharge. Wells in groups P and N do not display evidence of intersecting aquifer flowpaths. The statistical test used for this report, however, could not distinguish between (a) wells that are not on major flowpaths, (b) wells that are controlled by unknown geochemical processes, and (c) wells placed in this group because of their small sample size. It may be that some of these wells do not intersect flowpaths, and

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that others do but were not sampled at times when there was a surface water influence on ground water. 2.7.4. Saline zone and Trinity aquifer mixing Evidence presented here suggests that water flows from the Trinity aquifer into the Barton Springs segment under some hydrologic conditions. In particular, water from three wells in group P (FOW, GHW, and SVS) shows evidence for mixing with the Trinity aquifer during high aquifer flow conditions (Table 2 3). This suggests that the direction of the vertical gradient between the two aquifers is temporally variable, and that the hydraulic heads in the two aquifers are not necessarily comparable or even proportional to one another. Well RAB may also sometimes receive cross formational flow from the Trinity aquifer, although this hypothesis is made mostly on the basis of one water sample whose geochemical composition is very different from other samples from this well. Well SLR water also shows evidence for mixing with the Trinity aquifer, but this is expected behavior, as drill logs indicate that it was drilled into the upper section of the Trinity aquifer. Water from the saline zone may mix with water in the Barton Springs segment, and this behavior generally is associated with wells that intersect flowpaths (wells KCH, SVE, and SVW). For these wells, this mixing is associated with low

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streamflow and/or low aquifer flow conditions, suggesting that an absence of water recharging the aquifer or lowering of the potentiometric surface associated with low aquifer flow conditions (Slade et al., 1986) allows influx of water from the saline zone. Two other wells (CNE and WBG) also show evidence for saline zone mixing, probably because of their proximity to the saline zone (Figure 2 1). The saline zone may exist as a saltwater lens that extends under the freshwater part of the aquifer. Three of the deepest wells along the eastern edge of the aquifer (SVE, CNE, and WBG) show evidence of saline zone mixing, while three more shallow wells along the eastern edge (BPS, HND, and PLS) do not show evidence of saline zone mixing. Well SVE is the deepest well in this study but only shows saline zone influence under low aquifer flow conditions, which suggests that the saline zone (or a lower lens thereof) may migrate from east to west as a function of aquifer flow condition. Studies in the San Antonio segment of the Edwards aquifer to the south have demonstrated the existence of a temporally varying saline zone lens (Groschen, 1994). 2.7.5. Geographic patterns One of the most striking characteristics of karst aquifers is their extreme heterogeneity; wells in close proximity may exhibit very different hydrogeologic and geochemical characteristics (Malard and Chapuis, 1995; Long and Putnam, 2004).

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The intersection of a fracture or conduit is likely to have a greater effect on well water geochemistry than the location of the well along the regional gradient. For example, in this report wells TNR and BDW are located within 15 meters of one another, yet have distinct geochemical compositions and were placed in different groups (group N and C2, respectively). However, a few observations concerning geography and geochemistry can be made. In group C1 wells, Mg/Ca ratios tend to increase in a downgradient direction. This trend is interpreted as reflecting a longer residence time in a downgradient direction, and is consistent with the hypothesis that group C1 wells intersect flowpaths that integrate water from large volumes of the aquifer. Generalized aquifer flow routes were delineated by Hauwert and others (2005), and the conclusion that group C1 wells (FMW, KCH, SLR, SVE) intersect major flowpaths is mostly supported by their findings. This is not observed for the other three groups of wells, which are subject to more localized influences. In karst aquifers, fractures and conduits occupy a very small proportion of the total aquifer volume, and the likelihood of a well intersecting a major conduit is relatively small. Wells that intersect minor flowpaths are, with one exception, located in the recharge zone (Figure 2 5). This is consistent with the intersection of minor flowpaths. Because there is no direct connection between the land surface and confined zone, any confined zone flowpath must be long enough to reach the

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recharge zone. Thus, longer flowpaths are more likely to be major flowpaths, in the same way that stream length in surface water systems is usually proportional to the size of the catchment area. 2.7.6. Individual well comparisons with other studies Wells for which data were analyzed in this study have been sampled by other studies whose objective was to assess relation of ground water geochemistry to surface water processes. Andrews et al. (1984) and St. Clair (1979) reported high levels of fecal streptococci bacteria in well JBS (up to 44,000 colonies per 100 mL), suggesting a connection to surface water and/or contamination from wastewater. This studys analysis placed well JBS in group N, and no conclusions were made concerning flowpath intersection. One possibility is that well JBS does intersect a flowpath, but the small specific conductance dataset in (13 values) could not establish this connection. Another possibility is that bacterial contamination of well JBS was caused by a localized source such as a septic tank or leaking wastewater infrastructure. A sewage lift station in nearby Dry Creek historically has experienced numerous accidental sewage releases (Hauwert and Vickers, 1994), and is a probable source for bacterial contamination in well JBS. This is consistent with the data of Andrews et al. (1984), as specific conductance and bacteria levels do not

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co vary in well JBS, as would be expected with low ionic strength surface water recharge. Senger and Kreitler (1984) reported a hydrologic connection between wells RAB and SVE and Barton Springs Pool; water level changes in the pool result in nearly simultaneous water level changes in these two wells. This suggests that these wells intersect transmissive conduits that connect to the Barton Springs system. Similarly, Hauwert and Vickers (1994) suggested that well SVE has good hydraulic connection to recharge areas after observing a one foot rise in water levels following a rainfall event in August, 1994. Hauwert and Vickers (1994) also reported that well RAB contained 2.1 mg/L total petroleum hydrocarbons (TPH) in 1993, suggesting an anthropogenic source of contamination for this well. These findings are consistent with this studys conclusions for well SVE, and are not contradicted by this studys inconclusive results for well RAB. Hauwert and Vickers (1994) reported several instances of sediment filling well holes or discharging with pumped well water, and hypothesize that the presence of sediment in a well or its water may indicate that the well intersects a flowpath with rapidly moving water. Such sediment may originate from the land surface (allochthonous) or from within the aquifer (autochthonous) (Mahler et al., 1999). Hauwert and Vickers (1994) reported that well SVN accumulated over 100 feet (30 m) of sediment accumulation from 1978 to 1993, consistent with this

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studys conclusion that it intersects a minor flowpath. Well SVS was reported to contain fine cream colored sediment in its pumped water, although this studys findings were inconclusive for well SVS. Similarly, well HND was reported to have a small amount of sediment (less than 50 mg/L total suspended solids) in its pumped water, but this studys findings were inconclusive for this well. Hauwert et al. (2005) reported positive the detection of a dye from a dye trace in well SVW. The dye had been injected in Williamson creek several days earlier, suggesting that well SVW intersects a flowpath that connects to Williamson Creek. Their finding is consistent with the conclusions of this study. The City of Austin (1997) conducted an investigation with some of the same major ion data used in this study. They concluded that wells KCH, ROL, SVW, FMW, and BDW may be affected by urbanization, which is consistent with this studys findings that these wells intersect flowpaths. The City of Austin also identified well SVS as potentially being affected by urbanization. Well SVS was placed in this studys group P, and the processes controlling its behavior are not well understood. Finally, wells RAB and TNR were noted as having potential impacts from urbanization (City of Austin, 1997), while this studys findings were inconclusive.

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2.7.7. Value of statistical approach The results of this investigation demonstrate that a long term geochemical dataset can be of value in characterizing the degree to which wells intersect karst features. Although analysis of multiple samples collected at intervals of hours to days after rainfall remains the most effective way to evaluate the influence of surface water on ground water geochemistry, this study shows that if a sufficient amount of data exists, historical long term data can be analyzed statistically to asses surface water ground water interaction in a karst aquifer. However, there are some limitations to the statistical approach taken here. In those parts of a karst aquifer where transport occurs, the geochemistry can vary greatly and rapidly. The effects of recharging surface water may be extreme but ephemeral, occurring over only a small proportion of the hydrologic year. If the timing of sampling is random, many water samples may reflect baseflow conditions during which the geochemistry varies little. Thus, either a large number of samples, or random chance, is required to collect samples that reflect the range of geochemical variability that may occur at a site. Five of the 11 wells in the group for which no statistically significant relations were observed (group N) had the minimum number of specific conductance measurements, suggesting that six specific conductance measurements may be too few samples to capture the range of geochemical variability possible in a well (Figure 2 14). Thus, wells with small sample sets and

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no statistically significant negative relation between specific conductance and either streamflow or aquifer flow condition cannot be definitively interpreted as not intersecting a flowpath, but rather as having insufficient evidence for interpretation as intersecting a flowpath. Four of the wells in this study with the greatest geochemical variability (SVN, FOW, ROL, and SVE) had more than 30 specific conductance measurements (Figure 2 14); all four of these wells had statistically significant relations and were placed into groups C1, C2, or P. This suggests that a large sample set may be necessary to capture geochemical variability and connection to surface water processes or flowpath intersection. However, another possible explanation is that wells with the largest sample sets were deliberately selected for extended sampling on the basis of variability in geochemical composition observed early on during the sampling program. In other words, large sample set size and large geochemical variability may not be independent. Finally, while 85 percent of aquifer recharge is estimated to derive from the five recharging creeks (Slade et al., 1986), this report was unable to quantitatively consider the estimated remaining 15 percent of recharge (referred to as upland recharge). There is some evidence that upland recharge may rapidly reach some group C1 and C2 wells (particularly the shallow well SLR). The data available for this study cannot be used to determine the degree to which wells are affected by

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upland recharge. However, it is likely that periods of upland recharge and stream flow are correlated, and thus the statistical approach taken here may have identified some wells as being affected by stream flow when in fact they are receiving upland recharge. Current ongoing research may address the quantification of upland recharge rates (N. Hauwert, University of Texas, written comm., 2005; A. Lindley, University of Texas, personal comm., 2005). 2.8. CONCLUSIONS Ground water geochemistry data from the Barton Springs segment of the Edwards aquifer were analyzed to determine the relation between geochemistry in wells, streamflow, and overall aquifer flow condition as measured by Barton Springs system discharge. Twenty six years of arbitrarily timed specific conductance measurements were compared to surface water discharge rates and aquifer flow conditions using a non parametric statistical test. From the results of the statistical test, four groups of wells were identified: (1) Group C1negative correlation with streamflow and aquifer flow condition, (2) Group C2negative correlation with streamflow only, (3) Group Ppositive correlation with aquifer flow condition, and (4) Group Nno correlation to aquifer flow condition or streamflow. On the basis of the statistical test and geochemical evidence, generalizations about aquifer function were made. Four wells (FMW,

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KCH, SLR, SVE) intersect major aquifer flowpaths, and five wells (BDW, HWD, MCH, SVN, SVW) intersect minor aquifer flowpaths. For the remaining 17 wells, no conclusions were reached regarding connection to flowpaths. Analysis of major ion geochemistry indicated that most samples collected from wells belong to the Ca HCO3 and Ca Mg HCO3 hydrochemical facies, although some wells contain water with other hydrochemical facies. These variable facies are the result of processes such as incongruent calcite/dolomite dissolution, variable residence time, and dissolution of some non carbonate minerals such as gypsum. Some wells (KCH, SVE, SVW, CNE, WBG) show evidence of ground water mixing with water from the eastern saline zone, which may exist as a saltwater lens partially extending under the freshwater zone of the aquifer. This is reflected in elevated levels of Cl relative to SO4 2 and of Na+ relative to Mg2+. Some wells show evidence of mixing with water from the underlying Trinity aquifer (wells FOW, GHW, SLR, SVS, BCK, and TNR). This is reflected in elevated levels of SO4 2 relative to Cl and of Mg2+ relative to Na+. In some cases (SLR, FOW, GHW) this is because the wells penetrate the Trinity aquifer, but in others (SVS, BCK, TNR) the mixing appears to occur as cross formational flow from the Trinity when aquifer flow conditions are high. This long term historical dataset has proven to be useful for gaining hydrologic insight into flowpaths, water mixing, and geochemical evolution of water

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in the Barton Springs segment of the Edwards aquifer. Given the arbitrary nature of the 26 year USGS sampling program for the Barton Springs segment of the Edwards aquifer, it seems noteworthy that the approach taken by this study was useful. Eagleson (1991) states that long term data collection programs provide the basis for understanding hydrologic systems, and that seems to be true for this study. 2.9. ACKNOWLEDGEMENTS Data for this study was collected by the USGS, and funded in part by the City of Austin Watershed Protection and Development Review Department. Thanks are extended to David Johns (City of Austin) for providing his insights into the Barton Springs segment and for reviewing this paper. This quality of this manuscript was improved by a review from Greg Stanton (USGS). Additional thanks are given to Barbara Mahler (USGS), Milton Sunvison (USGS), and Peter VanMetre (USGS) for their keen scientific insight. General thanks are extended to the many scientists and technicians who scrupulously collected, analyzed, and archived the 26 years of data used by this study. Finally, thanks are extended to the many landowners and city authorities who allowed access to their wells.

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Figure 2 1 Location of the Barton Springs segment of the Edwards aquifer in the Austin, Texas area, major creeks, and data collection sites, 19782003.

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Figure 2 2 Schematic diagram of the Barton Springs segment of the Edwards aquifer. Recharge water enters the aquifer through the beds of creeks as they cross the recharge zone. Water in the aquifer flows generally to the north northeast, generally along solution enlarged conduits that act at highly preferential flowpaths. The majority of aquifer water eventually discharges at the far northeast corner of the aquifer at the Barton Springs system. Aquifer formation Confining layer Solution enlarged conduit Flow direction EXPLANATION NOT TO SCALE Infiltration & recharge Preferential flow along fractures and conduits Generalized flow direction Discharge at Barton Springs system

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Figure 2 3 Histogram showing the non normal distribution of Onion Creek mean daily discharge data, 1978003. The data are skewed to the right, and there are 8 outlier values that are significantly higher than all other values. The other creeks in the study area (Barton, Williamson, Slaughter, and Bear Creeks) show a similar distribution. Therefore, a non parametric statistical test that does not assume a normal distribution was used when comparing these data against specific conductance of water in wells. 0 1000 2000 3000 4000 5000 6000 7000 8000 0 50 51 100 101 150 151 200 201 250 251 300 301 350 351 400 401 450 451 500 501 550 551 600 601 650 651 700 > 700Mean daily discharge rate for Onion Creek (ft3/s)Number of data points

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Figure 2 4 Piper diagram showing relative proportions of dissolved ions in a visual format. Representative water samples from Main Barton Spring show observed geochemical variability seen at this site through time. Samplesfrom wells in the saline zone (state well numbers YD 58 50 840, YD 58 50 301, YD 58 50 302, and YD 58 50 304) are shown for reference, and selected samples from wells completed in the underlying Trinity aquifer (state well numbers YD 58 50 409 and YD 58 49 603) are shown for reference. Geochemical data for three of the foursaline zone wells was provided by the City of Austin (designated as CoAin map explanation). EXPLANATION Main Barton Spring, 1987 6 YD5850840 (Saline zone) YD5850301 (Saline zone, CoA) YD5850302 (Saline zone, CoA) YD5850304 (Saline zone, CoA) YD5850409 (Trinity aquifer) YD5849603 (Trinity aquifer) Ca Mg Na+K Cl SO4S O4+ C lC a + M gHCO3

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Figure 2 5 A nonparametric statistical test between specific conductance in wells, discharge rates of creeks, and aquifer flow condition divides sampled wells into four groups. Group C1 wells are negatively correlated to aquifer flow condition and streamflow. Group C2 wells are negatively correlated to streamflowonly. Group P wells are positively correlated with aquifer flow condition, and Group N wells are not correlated to either aquifer flow condition or streamflow.

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Figure 2 6 Results of high frequency sampling of well SVW, October 9, 1995. (a) Specific conductance increases, decreases, and increases again in response to streamflow; (b) Water samples from this event plot in the same region of aPiper diagram, suggesting dilution as a primary process; (c) Calcite saturation indicies increase after flow in Barton Creek and/or Williamson Creek probably lowered them to undersaturated values; (d) Concentrations of dissolved ions show a response to streamflow. (a)O c t 7 O c t 9 O c t 1 1 O c t 1 3 O c t 1 5 O c t 5500 400 300 200 100 0 700 650 600 550 500Barton Creek streamflow Williamson Creek streamflow Specific conductance in well SVW EXPLANATION Cl HCO3SO4Na+K Ca MgS O4+ C lC a + M gCreek discharge (ft3/s) Specific conductance ( S/cm) (b) (c) (d) Ion concentration (mmol/L)500 400 300 200 100 0Creek discharge (ft3/s) O c t 7 O c t 9 O c t 1 1 O c t 1 3 O c t 1 5 O c t 5 0.8 0.6 0.4 0.2 0.0EXPLANATION Barton Creek streamflow Williamson Creek streamflow ClNa+SO4 2 NO3 Creek discharge (ft3/s) logSIcalcite0.4 0.2 0.0 0.2 0.4 0.6 0.8 1.0 500 400 300 200 100 0EXPLANATION Barton Creek discharge Williamson Creek discharge logSIcalciteof well SVW samplesO c t 7 O c t 9 O c t 1 1 O c t 1 3 O c t 1 5 O c t 5 ClNa+SO4 2 NO3 calcite saturation calcite undersaturation

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Figure 2 7a Trilineardiagram showing the relations between concentrations of major ions in water sampled from group C1 wells screened in the Barton Springs segment of the Edwards aquifer, Austin, Texas, 19782003. FMW KCH SLR SVE EXPLANATIONCa Mg Na+K Cl SO4S O4+ C lC a + M gHCO3

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Figure 2 7b Mg/Ca molar ratios compared against specific conductance of water samples from group C1 wells. FMW KCH SLR SVE EXPLANATION FMW KCH SLR SVE EXPLANATIONFigure 2 7c SO4/Cl ratios compared against SO4 2 concentrations of water samples from group C1 wells.Mg/Ca (mol/mol)0.8 0.6 0.4 0.2 0.0 1.0 1.2 Specific conductance ( S/cm) 200400 600800 1,000 1,2001,4001,600log(SO4/Cl) (g/g)log (SO4 2 ) (mg/L) 1.0 0.5 0.0 0.5 1.0 1.5 2.0 0.00.5 1.01.5 2.0 2.53.03.5 Trinity aquifer water samples Saline zone water samplesP o t e n t i a l s a l i n e z o ne m i x i n g P o t e n t i a l s a l i n e z o ne m i x i n gP o t e n t i a l T r i n i t y a q u i f e r m i x i n g

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Figure 2 7d Mg/Na ratios compared against Mg2+concentrations of water samples from group C1 wells. Figure 2 7e NO3 concentrations compared against specific conductance measurements of water samples from group C1 wells. FMW KCH SLR SVE EXPLANATION FMW KCH SLR SVE EXPLANATIONlog(Mg2+) (mg/L) 1.01.2 1.41.6 1.8 2.0 0.8 0.4 0.0 0.4 0.8 1.2 Specific conductance ( S/cm)NO3 (mg/L)8.0 6.0 4.0 2.0 0.0 350550 750950 1,150 1,3501,550log (Mg/Na) (g/g)Trinity aquifer water samples Saline zone water samples P o t e n t i a l s a l i n e z o n e m i x i n gP o t e n t i a l Tr i n i t y a q u i f e r m i x i n g

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Figure 2 8 Specific conductance in well FMW as a function of (a) maximum 10 day discharge of Slaughter Creek; and (b) aquifer flow condition as measured by discharge of the Barton Springs system. In both cases, the compared values are inversely proportional when compared by a nonparametric statistical test. The linear regression line shown on the graphs is calculated using parametric statistics, and is shown for illustrative purposes only.(a) (b) 520 540 560 580 520 540 560 580 020406080100120 0.1110100Specific conductance ( S/cm) Specific conductance ( S/cm)Maximum 10 day discharge in Slaughter Creek (ft3/s) Discharge at Barton Springs system (ft3/s)

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Figure 2 9 Sulfate concentration in well SVE, and its variation as a function of (a) maximum 10 day discharge in Slaughter Creek; and (b) aquifer flow conditionas measured by Barton Springs system discharge. In both cases, a nonparametric statistical test shows a statistically significant negative correlation between the compared values. The linear regression line shown on graphs (b) is calculated using parametric statistics, and is shown for illustrative purposes only.020406080100120 051015202530 600 400 200 0 600 400 200 0 (b) (a)SO4 2 concentration (mg/L)Maximum 10 day discharge in Slaughter Creek (ft3/s) Discharge at Barton Springs system (ft3/s)SO4 2 concentration (mg/L)

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Figure 2 10a Trilineardiagram showing the relations between concentrations of major ions in water sampled from group C2 wells screened in the Barton Springs segment of the Edwards aquifer, Austin, Texas, 19782003. Ca Mg Na+K Cl SO4S O4+ C lC a + M gHCO3 EXPLANATION BDW HWD MCH SVN SVW

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Figure 2 10c SO4/Cl ratios compared against SO4 2 concentrations of water samples from group C2 wells. Figure 2 10b Mg/Ca molar ratios compared against specific conductance of water samples from group C2 wells. Mg/Ca (mol/mol) log(SO4/Cl) (g/g)log (SO4 2 ) (mg/L) Specific conductance ( S/cm) EXPLANATION BDW HWD MCH SVN SVW 200400 600800 1,000 1,2001,4001,600 0.8 0.6 0.4 0.2 0.0 1.0 1.2 1.0 0.5 0.0 0.5 1.0 1.5 2.0 0.00.5 1.01.5 2.0 2.53.03.5EXPLANATION BDW HWD MCH SVN SVW Trinity aquifer water samples Saline zone water samplesP o t e n t i a l s a l i n e z o ne m i x i n g P o t e n t i a l s a l i n e z o ne m i x i n gP o t e n t i a l T r i n i t y a q u i f e r m i x i n g

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Figure 2 10e NO3 concentrations compared against specific conductance measurements of water samples from group C2 wells. Figure 2 10d Mg/Na ratios compared against Mg2+concentrations of water samples from group C2 wells.log (Mg/Na) (g/g)log(Mg2+) (mg/L) Specific conductance ( S/cm) NO3 (mg/L)8.0 6.0 4.0 2.0 0.0 350550 750950 1,150 1,3501,550 1.01.2 1.41.6 1.8 2.0 0.8 0.4 0.0 0.4 0.8 1.2EXPLANATION BDW HWD MCH SVN SVW EXPLANATION BDW HWD MCH SVN SVW Trinity aquifer water samples Saline zone water samples P o t e n t i a l s a l i n e z o n e m i x i n gP o t e n t i a l Tr i n i t y a q u i f e r m i x i n g

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Figure 2 11a Trilineardiagram showing the relations between concentrations of major ions in water sampled from group P wells screened in the Barton Springs segment of the Edwards aquifer, Austin, Texas, 19782003. Ca Mg Na+K Cl SO4S O4+ C lC a + M gHCO3 EXPLANATION FOW GHW LWK ROL SVS WGF

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Figure 2 11c SO4/Cl ratios compared against SO4 2 concentrations of water samples from group P wells. Samples from wells FOW and SVS plot along a line representing a hypothetical mixture between well PLS and averageTrinity water, suggesting that Trinity aquifer water reaches these wells. Figure 2 11b Mg/Ca molar ratios compared against specific conductance of water samples from group P wells. Mg/Ca (mol/mol)Specific conductance ( S/cm) 200400 600800 1,000 1,2001,4001,600 0.8 0.6 0.4 0.2 0.0 1.0 1.2log(SO4/Cl) (g/g)log (SO4 2 ) (mg/L) 1.0 0.5 0.0 0.5 1.0 1.5 2.0 0.00.5 1.01.5 2.0 2.53.03.5 FOW GHW LWK ROL SVS WGF EXPLANATION FOW GHW LWK ROL SVS WGF EXPLANATION Trinity aquifer water samples Saline zone water samplesP o t e n t i a l s a l i n e z o ne m i x i n g 5 0 % P L S : 5 0 % T r i n i t y0 % P L S : 1 0 0 % m e a n T r i n i t y Hypothetical mixing line between well PLS and Trinity aquifer water 0 % P L S : 1 0 0 % S a l i n e 5 0 % P L S : 5 0 % S a l i n e

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Figure 2 11e NO3 concentrations compared against specific conductance measurements of water samples from group P wells. Figure 2 11d Mg/Na ratios compared against Mg2+concentrations of water samples from group P wells. Samples from wells FOW and SVS plot nearly along a line representing a hypothetical mixture between well PLS and averageTrinity water, suggesting that Trinity aquifer water reaches these wells.log(Mg2+) (mg/L) 1.01.2 1.41.6 1.8 2.0 0.8 0.4 0.0 0.4 0.8 1.2 Specific conductance ( S/cm)NO3 (mg/L)8.0 6.0 4.0 2.0 0.0 350550 750950 1,150 1,3501,550 FOW GHW LWK ROL SVS WGF EXPLANATION FOW GHW LWK ROL SVS WGF EXPLANATIONlog (Mg/Na) (g/g) 5 0 % P L S : 5 0 % T r i n i t y0 % P L S : 1 0 0 % m e a n T r i n i t y Trinity aquifer water samples P o t e n t i a l s a l i n e z o n e m i x i n g 5 0 % P L S : 5 0 % S a l i n e0 % P L S : 1 0 0 % S a l i n e

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Figure 2 12 Sulfate concentration in well FOW as it relates to aquifer flow condition as measured by discharge of the Barton Springs system. Sulfate concentration about 70 mg/L only occur in this well when aquifer flow condition is higher than an amount corresponding to 85 ft3/s of Barton Springs system discharge.020406080100120 250 200 150 100 50 0 SO4 2 concentration (mg/L)Discharge at Barton Springs system (ft3/s) maximum SO4 2 concentration below 85 ft3/s

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Figure 2 13a Trilineardiagram showing the relations between concentrations of major ions in water sampled from group N wells screened in the Barton Springs segment of the Edwards aquifer, Austin, Texas, 19782003. Ca Mg Na+K Cl SO4S O4+ C lC a + M gHCO3 EXPLANATION BPS HND ISD JBS PLS SNL TNR BCK CNE RAB WBG

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Figure 2 13c SO4/Cl ratios compared against SO4 2 concentrations of water samples from group N wells. Variations in well RAB composition cannot be explained simply by simple water mixing between well PLS and the mean composition of Trinity aquifer water used in this study. Figure 2 13b Mg/Ca molar ratios compared against specific conductance of water samples from group N wells. Mg/Ca (mol/mol)Specific conductance ( S/cm) 200400 600800 1,000 1,2001,4001,600 0.8 0.6 0.4 0.2 0.0 1.0 1.2log(SO4/Cl) (g/g)log (SO4 2 ) (mg/L) 1.0 0.5 0.0 0.5 1.0 1.5 2.0 0.00.5 1.01.5 2.0 2.53.03.5 BCK BPS CNE HND ISD JBS PLS RAB SNL TNR WBG EXPLANATION BCK BPS CNE HND ISD JBS PLS RAB SNL TNR WBG EXPLANATION Trinity aquifer water samples Saline zone water samplesP o t e n t i a l s a l i n e z o ne m i x i n g 5 0 % P L S : 5 0 % T r i n i t y0 % P L S : 1 0 0 % m e a n T r i n i t y Hypothetical mixing line 0 % P L S : 1 0 0 % S a l i n e 5 0 % P L S : 5 0 % S a l i n e

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5 0 % P L S : 5 0 % T r i n i t y0 % P L S : 1 0 0 % m e a n T r i n i t y Figure 2 13e NO3 concentrations compared against specific conductance measurements of water samples from group N wells. Figure 2 13d Mg/Na ratios compared against Mg2+concentrations of water samples from group N wells. Samples from well RAB do not show evidence of being a mixture between well PLS water and average Trinity aquifer water. Samples from wells CNE and WBG apparently mix with the saline zone.log(Mg2+) (mg/L) 1.01.2 1.41.6 1.8 2.0 0.8 0.4 0.0 0.4 0.8 1.2 Specific conductance ( S/cm)NO3 (mg/L)8.0 6.0 4.0 2.0 0.0 350550 750950 1,150 1,3501,550 BCK BPS CNE HND ISD JBS PLS RAB SNL TNR WBG EXPLANATION BCK BPS CNE HND ISD JBS PLS RAB SNL TNR WBG EXPLANATIONlog (Mg/Na) (g/g)Trinity aquifer water samples P o t e n t i a l s a l i n e z o n e m i x i n g 5 0 % P L S : 5 0 % S a l i n e0 % P L S : 1 0 0 % S a l i n e

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Figure 2 14 Comparison between the number of samples collected from a welland the range of measured specific conductance values for that well.Generally, wells with a larger number of values have a larger range of specific conductance values, suggesting that small sample sets may not capture the full rangeof geochemical variability that is possible within the water of a well. 0 400 800 1200 010203040506070Number of specific conductance values measured from a wellRange of specific conductance values for all samples from a well Group C1 wells Group C2 wells Group P wells Group N wells EXPLANATION

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Table 2 1 Wells sampled in Chapter 2, range of sampling dates, and the number of analyses available for each well.Site ID State well number 1USGS site identifier 2Range of years well was sampled Number of specific conductance measurements Number of major ion water analyses BC K YD 58 50 101 301317097513801 1978 63 BDWLR 58 57 311 300646097533202 1990 2314 BPSLR 58 58 403 300453097503301 1978 5335 CNELR 58 58 704 303138097511501 1978 65 FMWYD 58 50 412 301106097520501 1981 3119 FOWYD 58 50 408 301031097515801 1978 4 327 GHWLR 58 57 202 300639097571001 1978 2414 HNDYD 58 50 502 301113097485401 1978 159 HWDYD 58 50 401 301038097500401 1978 65 ISDLR 58 57 901 300148097532101 1978 65 JBSYD 58 42 926 301634097470001 1978 135 KCHYD 58 50 406 301148097503501 1978 6038 LW K LR 58 58 105 300640097513501 1978 65 MCHYD 58 50 704 300813097512101 1978 4 831 PLSYD 58 50 520 301226097480701 1988 3220 RABYD 58 42 915 301526097463201 1993 1611 ROLYD 58 42 813 301628097474001 1978 3923 SLRLR 58 49 903 300847097545801 1978 1811 SNLYD 58 42 809 301553097482801 1978 66 SVEYD 58 50 216 301356097473301 1978 4 929 SVNYD 58 50 217 301432097480001 1978 3520 SVSYD 58 50 215 301339097483701 1978 5131 SVWYD 58 50 211 301423097495901 1978 65 4 6 TNRLR 58 57 303 300646097533201 1978 2615 WBGYD 58 50 810 300803097483801 1978 65 WGFYD 58 50 206 301414097483601 1978 66 1 For locating wells in Texas Water Development Board databases, among others(e.g., ). 2 For locating wells in United States Geological Survey databases(e.g., ).

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Table 2 2 Grouping of wells on the basis of the results of a Spearman rank correlation test between specific conductance, streamflow rates in creeks, and aquifer flow condition as measured by discharge rate of the Barton Springs system. Site ID Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek Aquifer flow condition Group C1 2FM W 0.55 0.47 0.71 KCH 0.26 0.47 0.39 SLR 0.63 0.63 SVE 0.50 0.44 0.39 0.40 0.69 Group C2 3BD W 0.47 HWD 0.90 M CH 0.46 0.42 0.43 0.44 0.42 SV N 0.50 0.63 0.54 0.35 0.41 SV W 0.39 0.28 0.41 0.47 0.31 Group P 4FO W 0.320.50 GHW 0.41 LW K 0.88 ROL0.530.330.46 SVS 0.29 WG F 0.94 Group N 5BC K BPS CNE HND ISD JBS PLS RAB SNL TNR WBG 1 Numeric values are correlation strengths (rho) for significant correlations (p < 0.05). 2 Negative correlation between specific conductance and both streamflow and aquifer flow condition. 3 Negative correlation between specific conductance and streamflow. 4 Positive correlation between specific conductance and aquifer flow condition. 5 No correlation between specific conductance and discharge rates. Spearman Rho correlation strengths versus specific conductance 1

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Table 2 3 Summary of Chapter 2 findings.Site ID State well number Saline zone mixing? Trinity aquifer mixing?Comments Wells intersecting major flowpaths FMWYD 58 50 412Residence time variation is source of geochemical variability. KCHYD 58 50 406small Saline zone mixing suggested, although not near saline zone. High nitrate concentrations. SLRLR 58 49 903yesShallow well drilled into Trinity aquifer along western edge of study area. SVEYD 58 50 216yessmallSaline zone mixing at low aquifer flow condition and streamflow. Wells intersecting minor flowpaths BDWLR 58 57 311Residence time variation is source of geochemical variability. HWDYD 58 50 401 MCHYD 58 50 704small SVNYD 58 50 217 Can t be sampled under low aquifer levels. Probably gets water very directly from Barton Creek. SVWYD 58 50 211small High nitrate concentrations. Identified as a flowpath well by another study. Unknown / no conclusions BCKYD 58 50 101yesSmall dataset. BPSLR 58 58 403 Large unvarying water quality record. High residence time. No saline zone mixing despite proximity to saline zone. CNELR 58 58 704yesSmall dataset. Pronounced mixing with nearby saline zone. FOWYD 58 50 408yes Drilled into Trinity aquifer. Mixing from Trinity aquifer during high aquifer levels. GHWLR 58 57 202yes Shallow well, small dataset, drilled into Trinity aquifer at western edge of study area. HNDYD 58 50 502Small dataset. ISDLR 58 57 901Small dataset.

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Table 2 3. (cont.) Summary of Chapter 2 findings.Site ID State well number Saline zone mixing? Trinity aquifer mixing?Comments Unknown / no conclusions (cont.) JBSYD 58 42 926 Relatively small dataset. High bacteria and NO3 levels, suggesting local contamination source. LWKLR 58 58 105 Small dataset. Slight Ca2+ and HCO3 increases during high aquifer flow conditions. PLSYD 58 50 520Large unvarying water quality record. RABYD 58 42 915maybeUnusual geochemical behavior controlled by unidentified processes. ROLYD 58 42 813 Unusual geochemical behavior. Excess Cl may be anthropogenic. Well was plugged due to bacterial contamination. SNLYD 58 42 809Small dataset. SVSYD 58 50 215yesMixing with Trinity aquifer during high aquifer levels. TNRLR 58 57 303yesLocated 50 ft away from well BDW, but different geochemical behavior. WBGYD 58 50 810yesSmall dataset. Pronounced mixing with nearby saline zone. WGFYD 58 50 206 Small dataset. Slight Ca2+ and HCO3 increase during high aquifer levels.

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3. Variability in aqueous and isotope geochemistry of karst ground water used to infer water sources and hydrogeology of the Barton Springs segment of the Edwards aquifer 3.1. ABSTRACT Mixing of ground water, quantification of residence time, and delineation of flowpaths and catchment areas can be difficult to investigate in karst aquifers. Two years of water quality sampling from springs and wells in a karst aquifer within and around Austin, Texas, proved to be useful for the investigation of these processes. Ground water in the Barton Springs segment of the Edwards aquifer was generally Ca HCO3 to Ca Mg HCO3, and was near saturation with respect to calcite. Oxygen and hydrogen isotope values indicated that ground water is well mixed over long periods of time. The Sr/Ca ratio was found to be an effective indicator of ground water residence time, suggesting that incongruent dissolution was an active process in the aquifer. In addition to carbonate minerals, geochemical modeling indicated that gypsum and/or pyrite may be reacting with ground water. Na/Cl molar ratios for samples were mostly less than 1, and may indicate anthropogenic contamination or ion exchange with clay minerals. 87Sr/86Sr values and major ion concentrations from four hydrologically connected springs suggested that spring discharge was a

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mixture of different waters present in the aquifer, consistent with the expected behavior of karst aquifers. Temporal variation in spring 87Sr/86Sr values may have suggested multiple sources of Sr in the study area. Main Barton and Eliza Springs appeared to receive ground water from the same flowpath in the aquifer, as their geochemical compositions were indistinguishable. Old Mill Spring received some water from the saline zone along the eastern boundary of the aquifer, as indicated by elevated Na+, Cl, and SO4 2 concentrations. Main and Eliza Springs also showed evidence of mixing with the saline zone, but only when spring discharge rates were low. Elevated NO3 concentrations at Upper Barton Spring suggested anthropogenic contamination, and elevated K+ concentrations during high flows suggested that surface water from nearby Williamson Creek reached this spring. Water samples from Upper Barton Spring and four nearby wells had the most radiogenic 87Sr/86Sr values in the study area, and are located in an isolated aquifer subbasin. This studys high resolution geochemical dataset demonstrated that evaluation of temporal and spatial variability in isotopic composition and dissolved ion concentrations of karst ground water can provide insights into the functioning of these complex systems.

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3.2. INTRODUCTION It is difficult to understand karst aquifers. Their double, triple, and perhaps even quadruple porosity makes the application of traditional hydrologic equations difficult or impossible (see Chapter 1). To better understand these complex systems, scientists collect water samples from wells and springs, and use variations in dissolved ion concentrations and isotope ratios in the samples to understand how ground water flows and evolves in a karst aquifer. A karst spring is the mouthpiece of a karst aquifer (B.J. Mahler, U.S. Geological Survey, personal comm., 2004), that is, karst springs are integrators of water in their aquifers, and are recommended as ideal sites to study aquifer wide processes (Quinlan, 1989). However, the geochemistry of karst springs varies over time (Shuster and White, 1971), and sampling a karst spring at a single moment in time is unlikely to adequately capture the true nature or scope of the processes affecting the springs water. Studying the temporal changes in the aqueous and isotope geochemistry of a karst spring can yield insights into aquifer function. The major ions dissolved in water (Ca2+, Mg2+, Na+, K+, HCO3 Cl, and SO4 2 ) typically comprise more than 95 percent of the dissolved load of natural waters (Herczeg and Edmunds, 2000). Concentrations of these ions can be used as geochemical endmembers to understand regional flowpaths (e.g., Uliana and Sharp, 2001) and mixing of ground water from different aquifer zones (e.g., Musgrove and

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Banner, 1993; Swarzenski et al., 2001). For example, in a karst aquifer with relatively uniform lithology, variable dissolved Mg2+ and Ca2+ concentrations can indicate variable ground water residence times (Musgrove and Banner, 2004). Strontium (Sr) is an alkaline earth trace metal with a chemical behavior similar to calcium. Despite its low abundance in the Earths crust, it is present in significant quantities in karst aquifers. Thus, strontium is often analyzed in karst studies. Similar to Mg/Ca ratios, variations in Sr/Ca ratios can be indicators of variable residence time (Musgrove and Banner, 2004). Sr2+ in karst ground water generally represents first order control of the geology on the strontium concentration (Banner, 2004). That is, strontium concentrations in rainfall and surface water are very low, and what strontium does exist in solution is derived from the soil and rock formations through which the ground water flows (Frost and Toner, 2004). Strontium has several naturally occurring isotopes, the ratios of which can be used as identifiers of water sources (Swarzenski et al., 2001), water rock interaction (Musgrove and Banner, 1993), and water mixing (Banner et al., 1989; Lee and Krothe, 2001). When Sr2+ is dissolved from a mineral, the aqueous solution takes on the 87Sr/86Sr ratio of the mineral (Banner, 2004); if multiple minerals with different 87Sr/86Sr values are dissolved, then the aqueous 87Sr/86Sr ratio will be an intermediate value reflecting the relative mixing of these minerals (Banner and Hanson, 1990). Sr2+ dissolved from silicate material (e.g., many soils) usually is more radiogenic than

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Sr2+ dissolved from carbonates (Banner, 2004), and several studies have shown that Sr isotopic composition in ground water and surface water is often controlled by the balance between the weathering of carbonate and silicate minerals (Han and Liu, 2004; Musgrove and Banner, 2004). Strontium isotope ratios complement non isotopic data well, and can provide insights that cannot be gained merely from dissolved ion concentration data (Banner et al., 1994; Vallejos et al., 1997; Frost and Toner, 2004). Variations in the abundances of oxygen and hydrogen isotopes in the water molecule (H2O) have been studied for over 50 years. Early studies focused on precipitation, the origin of waters, and paleotemperature reconstructions of oceans (e.g., McCrea, 1950; Epstein and Mayeda, 1953; Craig, 1961). Oxygen and hydrogen isotopes also can be used to trace aquifer flowpaths (e.g., Lakey and Krothe, 1996), to estimate evapotranspiration (e.g., Scanlon, 2000), to quantify recharge amounts and timing (e.g., Jones and Banner, 2000), and to estimate elevation of recharge (Yurtsever and Gat, 1981; Ciais and Jouzel, 1994; Kattan, 1997). If temperatures are low and evaporation is not an active process in a system, oxygen and hydrogen isotopes are ideal conservative tracers of water flow, because they are integrated into the water molecule itself (Gat, 1981; Kendall et al., 1995). This is in contrast to solute isotopes (e.g., dissolved Sr2+), whose isotopic compositions are wholly influenced by water rock interaction (Katz et al., 1998).

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Scientists are forced to find innovative methods for characterizing the behavior of karst aquifers. Questions regarding ground water residence time, flowpaths, and water mixing are difficult to answer, especially when studies fail to account for the temporal variability inherent in karst. In this study, springs were sampled many times over two years, and the results of this sampling showed that water residence time varies, flowpaths to karst springs are numerous, and ground water is a mixture of several different distinct waters. 3.3. STUDY AREA The Barton Springs segment of the Edwards aquifer (herein referred to as the Barton Springs segment) is a karst aquifer that extends south southwest of Austin. It is bounded to the north by the Colorado River, to the south by a ground water divide, to the west by its contact with the Glen Rose Formation, and to the east by a zone of low permeability (Maclay and Land, 1988) containing brackish to saline (> 1000 mg/L total dissolved solids) ground water known as the saline zone (Figure 3 1). The aquifer rock is composed principally of limestone and dolomite from the Cretaceous period. The aquifer has undergone multiple episodes of karstification and extensive meteoric diagenesis (Rose, 1972; Maclay, 1995; Small et al., 1996). In the Miocene epoch, tectonic activity created a zone of en echelon normal faults,

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resulting in enhanced karstification and the aquifer structure and behavior seen today (Slade et al., 1986). The aquifer is generally highly transmissive, with some measured straight line transit times exceeding 10 kilometers per day (Hauwert et al., 2005). An estimated 85 percent of recharge to the aquifer occurs through karst features in the creek beds of Barton, Williamson, Slaughter, Bear, and Onion Creeks (Slade et al., 1986). These are ephemeral creeks that cross the recharge zone from west to east (Figure 3 1). Additional sources of recharge include upland infiltration through sinkholes and fractures, infiltration through soil zones (Musgrove and Banner, 2004), leakage of urban infrastructure (Garcia Fresca Grocin, 2004), and cross formational flow from other hydrostratigraphic units (City of Austin, 1997; Sharp and Banner, 1997). Flow in the aquifer generally is to the north northeast, following the trend of the Balcones Fault Zone, although the exact direction of flow varies with changes in aquifer flow condition and resulting changes in the potentiometric surface (Slade et al., 1986). As expected in a limestone aquifer, the geochemical composition of ground water in the Barton Springs segment can generally be classified as calcium bicarbonate (Ca HCO3) to calcium magnesium bicarbonate (Ca Mg HCO3) facies, following the nomenclature of Back (1961). Although most Barton Springs

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segment water is Ca HCO3 or Ca Mg HCO3, significant variations in dissolved constituents and molar ratios have been observed (Senger and Kreitler, 1984). The main discharge point for the aquifer is the Barton Springs system, which is comprised of Main Barton Spring, Eliza Spring, Old Mill Spring, and Upper Barton Spring (herein referred to as MSP, ESP, OSP, and USP, respectively) (Figure 3 2). Combined long term mean discharge from MSP, ESP and OSP is about 50 ft3/s (1.4 m3/s) (Slade et al., 1986). MSP is the largest of the four springs by far, generally discharging over five times more water than the other three springs combined (Slade et al., 1986). Additional ground water is withdrawn from the aquifer by pumping from domestic, livestock, and public supply wells (Figure 3 2e). In 2004 there were an estimated 970 active wells pumping from the Barton Springs segment, with an annual ground water withdrawal of about 2.5 billion gallons (Smith and Hunt, 2004), equivalent to a constant withdrawal rate of about 10 ft3/s (0.3 m3/s). The east side of the aquifer is bounded by the saline zone, which contains concentrations of dissolved ions exceeding 1000 mg/L TDS. The saline zone has many processes that contribute to its unusual chemical and isotopic signatures, including gypsum dissolution, incongruent carbonate dissolution, ion exchange, sulfate reduction, fluid mixing, and interaction with igneous intrusions (Sharp and

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Clement, 1988; Oetting et al., 1996). It is generally a minor concern for local resource managers because of its high salinity and low ground water productivity. 3.4. METHODS 3.4.1. Sampling from springs Samples were collected from the four springs that comprise the Barton Springs system (Figure 3 1). All samples except for two were collected by immersing containers 12 feet (0.3.6 m) below the water surface near the spring orifice, and avoiding contact with the atmosphere and standing surface water (Wilde et al., 1999). Two samples on November 24, 2004 from springs MSP and USP were collected using a peristaltic pump and tubing fed into the springs, as the spring outlets were covered by surface water from record floods in nearby Barton Creek. Samples were collected in 3 liter Teflon or 1 liter polyethylene containers, placed on ice and returned to the United States Geological Survey (USGS) Austin laboratory for processing. There, sample water was filtered through 0.45 m cellulose filters, using a peristaltic pump and tygon tubing that had been cleaned (Appendix E; Figure E 1). Filtered water was used to fill two 125 mL polyethylene bottles for major ion analysis. One of the bottles had been pre cleaned with trace element grade (TEG) HCl, and its contents were preserved with TEG HNO3 to a pH < 2. Samples were refrigerated and shipped to the USGS National Water Quality Lab

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for analysis. Prior to use, all bottles and sampling equipment had been soaked in Liquinox soap, soaked in TEG HCl, and rinsed with deionized water (DIW) (Horowitz and Sandstrom, 1998). For Sr isotope analysis, filtered water was dispensed into a 30 mL polyethylene sample bottle that had been pre cleaned in a clean laboratory using Micro soap solution, 30 percent TEG HNO3, and DIW (Appendix E). Sr isotope sample bottles were always the last to be filled by filtered water; this allowed the filtration system to be purged multiple times and minimized Sr isotope sample contamination. Prior to October 23, 2004, Sr isotope samples were collected directly from springs and received no filtration. Another study from the Barton Springs segment found that filtration did not measurably affect the 87Sr/86Sr ratio for samples with low total suspended solids (Christian, in preparation). All unfiltered samples in this study had very low turbidity (< 2 Nephelometric Turbidity Units). Oxygen and hydrogen isotope samples were collected directly from spring orifices into 7 mL glass vials, ensuring that there was no air in the sample container. Samples caps were wrapped in ParaFilm to minimize evaporation, and were refrigerated pending further analysis.

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3.4.2. Sampling from wells Ground water samples were collected from 12 wells completed in the Barton Springs segment (Figure 3 1 and 3 2; Table B 1). Ground water was extracted by electric submersible pump. Samples were collected at points in the plumbing upstream of pressure tanks or treatment equipment in order to obtain a sample representative of aquifer water. Samples were collected after at least three well volumes of water had been purged from the well, and after real time field parameters (pH, temperature, conductivity) values had stabilized (Wilde et al., 1999). Sample containers used for well water sampling were the same as those used for spring sampling. Filtration was employed for major ion samples, but not isotope samples. Methods used in this ground water sampling followed protocols outlined by the USGS National Water Quality Assessment Program (Koterba et al., 1995). 3.4.3. Analytical methods Major ion samples were analyzed by the USGS National Water Quality Laboratory. Cation concentrations were measured using inductively coupled plasma mass spectrometry, and anion concentrations were measured using ion exchange chromatography (Fishman, 1993, p. 19). Samples were analyzed within 180 days of collection, per USGS sampling guidelines. Carbonate species

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concentrations were determined in the field using the inflection point titration method with 1.6N sulfuric acid (Radtke et al., 1998b). Based on the findings of Andrews et al. (1984), nitrite (NO2 ) concentrations were assumed to be negligible in samples, thus the measured nitrate+nitrite parameter was assumed to indicate solely nitrate concentration. Silica concentrations were determined, but are not reported here. Blank and replicate analyses for major ions comprised approximately ten percent of the total analyzed samples (Appendix D). Strontium isotope samples were analyzed at The University of Texas at Austin in the laboratory of Dr. Jay Banner. Each sample was evaporated and then redissolved in 3N HNO3. This solution was passed through a Sr spec resin column to selectively sequester dissolved Sr2+. Sr2+ was eluted from the column using 0.1N HNO3. The eluted solution was evaporated, redissolved in 0.01N phosphoric acid, and dispensed onto a tantalum filament. The filament was placed into a Finnigan MAT 261 thermal ionization mass spectrometer. The heated and ionized sample was analyzed in dynamic collection mode. Analyses of the NBS 987 standard (mean=0.710265, n=10) ensured that results were precise. External precision for analyses was estimated to be 0.000015 or better, and a replicate analysis fell within this range of precision. A blank analysis of water dispensed in the laboratory contained less than 10 picograms of Sr, and a blank analysis of water dispensed at the sampling site (and treated as a normal sample) contained about

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150 picograms of Sr. These low background concentrations of Sr, which were measured using isotope dilution, are more than three orders of magnitude smaller than the lowest Sr2+ concentrations measured in water samples (see also Appendix D). All strontium samples except for two were analyzed within 13 months of collection, and the majority were analyzed within five months. Strontium isotope ratios are reported as the ratio of 87Sr to 86Sr (87Sr/86Sr). Oxygen isotope samples were analyzed at The University of Texas at Austin in the laboratory of Dr. Libby Stern. Samples were dispensed into glass vials filled with carbon dioxide gas, and were allowed to equilibrate with this gas for 8 hours at 40C. The carbon dioxide gas was fed into a light isotope mass spectrometer alternately with a reference gas of known isotopic composition (Epstein and Mayeda, 1953). Approximately one third of analyzed samples were internal lab standards, and external precision was estimated to be 0.1 or better. The majority of oxygen isotope samples were analyzed within 5 months of collection. Hydrogen isotope samples were analyzed at Southern Methodist University. Samples were passed over depleted uranium metal at 800C (Bigeleisen et al., 1952), which reduced the hydrogen in the water molecule to H2 gas. The H2 gas was collected onto activated carbon, and then analyzed by mass spectrometer. Internal laboratory standards were analyzed frequently, but not reported by the lab. The lab reports that standard and duplicate analyses define an analytical precision of 1.2

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or better. Oxygen and hydrogen isotopes are reported using delta notation (Gonfiantini, 1981; Coplen, 1994), and are referenced to standard mean ocean water (SMOW). 3.4.4. Real time parameter monitoring Real time water quality parameters were monitored by the USGS at spring MSP during the study. A Hydrolab was placed into a submerged solution enlarged fracture through which the majority of spring MSP discharge flows. Specific conductance and discharge rate were measured and recorded every 15 minutes. Discharge rate was calculated by measuring the ground water level in a nearby well. The water level in this well has been correlated to spring discharge using a stage discharge relationship, with periodic discharge measurements made downstream of the spring using a current meter and standard USGS methods (Buchanan and Somers, 1969). Mean daily values were calculated from measured 15 minute values using established USGS methods. Rainfall data were obtained from the City of Austin Flood Early Warning System, an electronically monitored network of rainfall gauges located throughout the study area. Rainfall is difficult to quantify with high precision and accuracy because of numerous biases introduced by measurement equipment (Groisman and Legates, 1994). However, this study used rainfall data only to identify the general

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occurrence of rain, and not to quantify it rigorously. Thus, measurement biases were not considered to be significant. 3.5. RESULTS 3.5.1. Real time parameter monitoring There were 497 mean daily values measured for site MSP from August 6, 2003 to December 23, 2003 and from June 20, 2004 to June 10, 2005. Specific conductance ranged from 520 to 680 microsiemens per centimeter ( S/cm), and discharge ranged from 37 to 130 ft3/s (1.0 to 3.7 m3/s; Figure 3 3; Appendix E). The maximum discharge rate, recorded in March 2005, may have been underestimated because of changes in the behavior of the stage discharge relationship at very high discharge rates (Asquith and Gary, 2005). There was a major rainfall event in June 2004, October 2004, and November 2004 (Figure 3 3). The maximum daily rainfall amount during the study period (about 5 inches, or 120 mm) was measured on November 21, 2004. This rainfall event produced major flooding in the Austin area, and probably substantially altered the geochemistry of the spring samples collected on November 24, 2004.

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3.5.2. Major dissolved ions There were 25 sampling events for each of the four springs in the Barton Springs system (Figure 3 3). Generally, major ion analyses were performed on all 25 sets of samples. Major ion analyses were not carried out in September and early October 2004 for springs ESP, OSP, and USP (Table 3 1). Some analytical results were excluded, or should be interpreted with care. Because of an apparent sample or analysis error, the major ion sample from well SVN sampled in 2005 was excluded from the dataset. In this sample, ion concentrations were approximately half of what the long term record suggested as a normal analysis for this well, despite the pH and specific conductance values appearing to be correct (V.A. Chavez, U.S. Geological Survey, 2005, personal comm.). On the basis of rainfall data, it was determined that a sample from site USP on October 23, 2004 was affected by intense rainfall 14 hours earlier, and was excluded from this baseline dataset. This late October 2004 storm event is considered separately in Chapter 4. Finally, dissolved ion concentrations from all four springs on November 24, 2004 showed considerable departure from all other measurements during the study period, and were probably affected by flooding associated with an extremely large rainfall event. Because they do not reflect baseline conditions as the other samples in this study, samples from this day are generally excluded from analysis.

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Summary statistics for the eight analyzed ions are presented in tabular format (Table 3 2) and graphical format (Figure 3 4). Full results are presented in Appendix B (Table B 2). With one exception, the ranges of ion concentrations observed in springs MSP, ESP, and OSP were smaller than the ranges of values for wells (Figure 3 4). Spring USP had samples with lower concentrations than any wells for Mg2+, Na+, Cl, and Sr2+. All four springs had samples with lower values for Mg2+ than observed in wells. Samples from springs generally contained about 500 mg/L total dissolved solids (TDS), measured as the sum of all ion concentrations. The coefficient of variation was calculated for each ion for all wells considered together as a group, and for each spring individually (Table 3 3). The coefficient of variation (Cv) is calculated as the standard deviation divided by the mean, and quantitatively reflects the variability in a set of numbers. Considered together as a group, water samples from wells had the highest Cvs for all major ions. Among the four springs, the largest Cvs were observed in samples from spring USP. All samples except for one (well ALB) were calcium bicarbonate (Ca HCO3) or calcium magnesium bicarbonate (Ca Mg HCO3) facies (Figure 3 5). Samples from spring OSP plotted closer to Na+, K+, Cl, and SO4 2 hydrochemical facies than samples from the other three springs. Samples from spring USP plotted closer to a pure Ca HCO3 water than any other samples in the study. The sample from well ALB was a sodium chloride sulfate (Na Cl SO4) water, and the total dissolved solids

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concentration was about three times greater than that of any other sample in the study. 3.5.3. Strontium, oxygen, and hydrogen isotopes 87Sr/86Sr ratios were measured for 45 water samples from wells and springs (Table 3 1; Table B 2). The range of 87Sr/86Sr values in the study area was from 0.7076 to 0.7084. The lowest value was measured in well FOW water, a well whose water is known to mix with water from the Trinity aquifer (see Chapter 2). The highest value was measured in well SVS. Mean values of 87Sr/86Sr for the Barton Springs system were 0.70796 (n=13) at spring MSP, 0.70795 (n=7) at spring ESP, 0.70802 (n=7) at spring OSP, and 0.70812 (n=12) at spring USP. At each spring, all measured values were within analytical uncertainty of each other; that is, there was no measurable temporal variability in 87Sr/86Sr values at any spring. 87Sr/86Sr values from springs MSP and ESP were within analytical uncertainty of each other (i.e., neither spatial nor temporal 87Sr/86Sr variation between springs MSP and ESP). 87Sr/86Sr ratios from spring OSP samples were more radiogenic than, and did not overlap, samples from MSP and ESP. 87Sr/86Sr ratios in samples from spring USP were more radiogenic than those from the other three springs, and never overlapped with samples from the other springs (Figure 3 14a and Table 3 2; considered later in the study).

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Results of oxygen and hydrogen isotope analyses were plotted against one another (Figure 3 11) to evaluate their position relative to the global meteoric water line (GMWL) (Craig, 1961). Deviations to the right of this line can indicate evaporation, water mixing, (Clark and Fritz, 1997, p. 36) or water rock interaction (Faure, 1986, p. 450). Generally, samples should not plot to the left the GMWL as some this studys samples do. These samples probably do in fact, plot on the GMWL, and their apparent deviation from the GMWL probably is related to analytical uncertainty and a small number of samples. There were samples with only oxygen isotope analyses or hydrogen isotope analyses (Table B 2). While these could not be plotted to evaluate their position relative to the GMWL, their values are comparable to those of samples that were plotted against the GMWL. 3.6. DISCUSSION 3.6.1. Major ion geochemistry The major ion geochemistry of ground water reflects the initial geochemistry of the recharging surface water, over which is imprinted the interaction of the water with the rock through which it flows (Kehew, 2001, p. 9). In karst aquifers, meteoric water enters the aquifer and partially dissolves the carbonate rock matrix (typically calcite, CaCO3), releasing Ca2+ and HCO3 ions into solution until an equilibrium concentration is reached or the water exits the aquifer. Incongruent dissolution of

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metastable mineral phases (e.g., aragonite and high magnesium calcite) can also contribute quantities of Mg2+ and Sr2+ into solution. Because of the overwhelming preponderance of carbonate minerals in the rock, karst ground water is generally expected to be Ca HCO3 or Ca Mg HCO3. This is the case for all water samples in the Barton Springs segment (Figure 3 5), except for the sample from well ALB, which is located in the saline zone. In theory, dissolution of calcite and other carbonate minerals proceeds according to the equation: XCO3(s) + H2O(l) + CO2(g) < > X2+(aq) + 2HCO3 (aq) (Eq. 3 1) where X is a group II metal such as Ca, Mg, or Sr. This equation is an oversimplification of the actual dissolution processescarbonate minerals are rarely pure, and this equation ignores the speciation of HCO3 into CO3 2 and H2CO3 (although this effect is negligible at the pH values of Barton Springs segment ground water). In spite of its oversimplification, this conceptual equation demonstrates that in a system composed of nothing but dissolving carbonate minerals, one mole of dissolved Ca2+, Mg2+, and Sr2+ is produced for every two moles of dissolved HCO3 a 1:2 ratio. Thus, if the sum of Ca2+, Mg2+, and Sr2+ are plotted against HCO3 water samples from a pure carbonate aquifer will fall on a line with a slope of 1:2 (Figure 3 6a).

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Barton Springs segment waters plot close to, but decidedly above the line that represents the 1:2 slope of pure carbonate dissolution. This suggests a source of excess divalent cations (Ca2+, Mg2+, and Sr2+) or a process that reduces aqueous HCO3 concentrations. Two likely sources of excess divalent cations are the evaporite minerals gypsum (CaSO4H2O) and anhydrite (CaSO4) (herein both referred to as gypsum). Using PHREEQC geochemical modeling software (Parkhurst and Appelo, 1999), a second line representing the addition of gypsum to the aquifer can be plotted (Figure 3 6a). This new line is closer to Barton Springs segment water samples, although gypsum dissolution adds dissolved SO4 2 a species which is not represented on Figure 3 6a. By subtracting SO4 2 concentration from the total divalent cation concentration, gypsum dissolution no longer affects the graph (Figure 3 6b). Because Barton Springs segment water samples plot closer to the theoretical 1:2 line on Figure 3 6b, this suggests that gypsum may be present and actively dissolving in the aquifer. The chemical behavior of gypsum in karst ground water is virtually indistinguishable from the chemical behavior of pyrite (FeS2) (P.C. Bennett, University of Texas, written comm., 2005). Thus, Figure 3 6b may also suggest the presence of pyrite in the aquifer. Both gypsum and pyrite are known to occur in the aquifer rocks (Deike, 1987; Maclay, 1995), and gypsum has been found to be a

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significant source of dissolved ions in other karst aquifers (Jacobson and Wasserburg, 2005). Examination of the other major dissolved ions reveals small but geochemically significant quantities of Na+ and Cl. These ions can be derived from limestone, in which there are occasional crystals of halite (NaCl) associated with intense evaporation of seawater during deposition. Theoretically, halite dissolution proceeds according to the equation: NaCl > Na+(aq) + Cl (aq) (Eq. 3 2) which indicates that the Na/Cl molar ratio should equal 1 for a water sample that has dissolved halite. However, all spring samples except for three have Na/Cl values less than 1, and the majority of well water samples also have Na/Cl values less than 1 (Figure 3 7). This suggests that there is a non halite source for these ions, or that some process adds Cl ions and/or removes Na+ ions from solution. Furthermore, the Na/Cl ratio does not change appreciably as specific conductance of water samples changes (Figure 3 7), indicating that the Na+ and Cl sources and/or processes do not change as total dissolved solids vary. One possible source for Cl may be urban infrastructure (St. Clair, 1979; City of Austin, 1997; Sharp and Banner, 1997; Christian, in preparation) such as leaking sewer pipes, septic tank drain fields, and leaking municipal water supply pipes. For

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exmaple, Austin municipal water is treated with chlorine gas, which eventually converts to reduced Cl according to the equation (Droste, 1997): Cl2(g) + H2O > HOCl(aq) + H+ + Cl (Eq. 3 3) Further progression of this reaction leads to the breakdown of the HOCl molecule, leading to a further increase in Cl concentration. The net result of this reaction is a reduction in pH and an addition of Cl ions. This reduction in pH can then be offset and masked by the increased dissolution of carbonate minerals that it promotes. Another explanation for Na/Cl values less than one is ion exchange reactions, in which Na+ ions are exchanged for divalent cations such as Ca2+ (e.g., Land and Prezbindowski, 1981). This is commonly associated with clay minerals, which are known to be present in the Barton Springs segment (Mahler et al., 1999). Ion exchange reactions appear to play a role in the geochemistry of other karst aquifers as well, such as the Madison aquifer of South Dakota (Jacobson and Wasserburg, 2005). Nitrate (NO3 ) can be an indicator of anthropogenic contamination, and has been measured in the Barton Springs segment for over 25 years (Chapter 2). The highest concentrations in springs during this study (up to 3 mg/L measured as nitrogen) are found at spring USP. According to dye trace studies (Hauwert et al., 2005), this spring resides within an isolated subbasin of the Barton Springs segment, and its discharge is derived from a highly urbanized area of the recharge zone.

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However, Cl concentrations are another indicator of anthropogenic contamination, and are not unusually high in spring USP. This suggests that there is a source of NO3 that is not high in Cl(e.g., probably not leaking sewer lines). One possible source of elevated NO3 is landscaping fertilizer, the application of which is known to occur throughout the study area (City of Austin, 1997). Well ALB (Figure 3 1) is located in the saline zone and its water has a hydrochemical facies of Na Cl SO4 (Figure 3 5). This is consistent with the previously defined hydrochemical facies for the saline zone (Sharp and Clement, 1988), and verifies that the saline zone is indeed a potential source of Na+, Cl, and SO4 2 ions. These same ions increase in concentration at springs MSP, ESP, and OSP during low discharge rates, suggesting that these springs discharge some water from the saline zone. Hauwert et al. (2005) estimated a maximum saline zone contribution to spring discharge of 3 percent, and Senger (1983) estimated a maximum of 10 percent. The low permeability of the saline zone (Maclay and Land, 1988) suggests that movement of ground water into or out of the saline zone is slow, and will probably never be more than a minor contributor to spring discharge. Spring USP does not have elevated Na+, Cl, and SO4 2 concentrations, which is consistent with the hypothesis that it receives ground water from an isolated aquifer subbasin that has no contact with the saline zone.

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3.6.2. Residence time and geochemical variability For all four springs, the ion with the highest Cv is Sr2+, followed by NO3 (Table 3 3). This is different than in other karst aquifers, where Ca2+ and HCO3 are the ions with the most variable concentrations (Shuster and White, 1971; Dreiss, 1989; Panno et al., 1996). This suggests that, unlike many karst aquifers, overall geochemical variability in Barton Springs system discharge is not dominantly controlled by calcite and dolomite equilibrium. In fact, saturation indices for springs water can be calculated using PHREEQC (Parkhurst and Appelo, 1999), and show that water from springs MSP, ESP, and OSP is nearly saturated with respect to calcite (mean log SIcalcite = 0.13 for each of MSP, ESP, and OSP), and water from spring USP is only slightly undersaturated with respect to calcite (log SIcalcite = 0.21). In light of this calculation, it is not surprising that ions with the two lowest Cvs are Ca2+ and HCO3 for all springs except spring OSP where the Cvs for Ca2+ and SO4 2 are lowest (note also Figure 3 4 ranges of Ca2+ and HCO3 ). Sr2+ is the ion with the highest Cv in all four springs (Table 3 3). Knowing that spring waters are close to saturation with respect to calcite, this suggests that incongruent dissolution is a dominant geochemical process in the Barton Springs segment. In incongruent dissolution, a recharging water that is undersaturated with respect to calcite (CaCO3) will rapidly dissolve calcite and undergo an increase in Ca2+ concentration until calcite saturation is reached (Palmer, 1991). Subsequently,

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incongruent dissolution of metastable minerals such as high magnesium calcite and dolomite (CaMg(CO3)2) will result in increased Mg2+ concentrations, while Ca2+ concentrations remain essentially constant owing to the simultaneous co precipitation of more stable minerals such as low magnesium calcite (James and Choquette, 1984). This behavior has been observed in the Lincolnshire Limestone of England (Edmunds and Walton, 1983), as well as cave dripwaters in the Edwards aquifer (Musgrove and Banner, 2004). Maclay (1995) reported that dedolomitization, a process similar to incongruent dissolution, is active in the present day phreatic zone of the Edwards aquifer. The chemical kinetics of incongruent dissolution suggest that Sr2+ and Mg2+ concentrations can be used as indicators of ground water residence time (Musgrove and Banner, 2004). In order to compensate for variable amounts of calcite dissolution, Mg2+ and Sr2+ are normalized to Ca2+, and we hypothesize that Mg/Ca and Sr/Ca ratios will be indicators of residence time. Residence time is usually not a directly measurable quantity, but we can use the discharge rate from the Barton Springs system (Figure 3 3) as a proxy for residence time. This is probably a valid proxy, as higher discharge rates are associated with higher ground water levels (Senger, 1983) and faster ground water flow velocities (Hauwert et al., 2005). Figure 3 8 visually suggests that there is a correlation between Barton Springs discharge and Sr/Ca ratios.

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On the basis of a strong linear correlation with spring discharge rates, Mg/Ca and Sr/Ca are effective indicators of residence time for springs MSP, ESP, and OSP (Figure 3 9). The mean r2 correlation coefficient for Mg/Ca for these three springs is 0.51, and for Sr/Ca is 0.74. This suggests that Sr/Ca is a better indicator of residence time in the Barton Springs segment than Mg/Ca. Note that samples from November 24, 2004 were omitted from these correlation calculations, as these samples were taken during record floods and represent unusual aquifer conditions. Inclusion of these data reduces the correlation coefficients a small amount. Mg/Ca and Sr/Ca at spring USP do not strongly correlate with Barton Spring system discharge. One possibility is that incongruent dissolution is not a prominent process in the isolated subbasin (Hauwert et al., 2005) that supplies water to springs USP. This basin is small and has shorter residence time than the majority of the Barton Springs segment. Furthermore, shorter residence times suggest that a larger volume of meteoric water has flowed through this subbasin, and that meteoric diagenesis may have already dissolved many of the metastable minerals that bear Mg2+ and Sr2+. Another possibility for a poor correlation between spring discharge and spring USP Sr/Ca is that spring USP residence time is incorrectly measured by Barton Springs system discharge. Barton Springs system discharge is a measurement of the combined discharge of MSP, ESP, and OSP, and does not

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include spring USP (Asquith and Gary, 2005). For example, on December 23, 2003, spring USP was not flowing, while the other three springs were. Values of Mg/Ca and Sr/Ca from the Barton Springs system are consistent with Mg/Ca and Sr/Ca values reported from cave dripwaters by Musgrove and Banner (2004). While their dripwater sites are not located within the Barton Springs segment, they are in analogous geologic formations and are located within 100 km of the Barton Springs segment. Spring discharge samples (i.e. Barton Springs system samples from this study) have higher average residence times than cave dripwater samples, as dripwaters represent rainfall that has only recently infiltrated through the vadose zone (Figure 3 10). Concentrations of Cl and Na+ (non carbonate ions) change in response to discharge rates, much in the same way that Mg2+ and Sr2+ change. After Sr2+ and NO3 the ions with the highest Cv values are Cl at springs MSP and ESP, Na+ at spring OSP, and K+ at spring USP (Table 3 3). Elevated levels of Na+ and Cl correspond to periods of low spring discharge at springs MSP, ESP, and OSP (Senger and Kreitler, 1984). This suggests that Na+ and Cl might be indicators of residence time much in the same way as Mg2+ and Sr2+. While this may be true from a statistical point of view, the underlying geochemical explanation probably is not residence time, as Na+ and Cl are associated with very soluble minerals (e.g., halite) that do not undergo incongruent dissolution. Several studies have proposed that the

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saline zone on the eastern boundary of the Barton Springs segment is a source of Na+, Cl, and SO4 2 (Senger and Kreitler, 1984; Slade et al., 1986; City of Austin, 1997), or alternatively that the underlying Trinity aquifer is a source (City of Austin, 1997). Potentiometric surface maps during low ground water levels indicate that gradients favor movement of ground water from the saline zone into the freshwater zone, while potentiometric surface maps from periods of high ground water levels indicate little ground water movement out of the saline zone (Slade et al., 1986). Dye trace studies also propose a major aquifer flowpath along the boundary of the freshwater and saline zones (Hauwert et al., 2005). The high Cv value for K+ at spring USP (Table 3 3) is associated with high aquifer flow levelsthe highest K+ concentration measured in this study was at spring USP on November 24, 2004, during record floods in the study area. K+ is generally not associated with dissolution of limestone rock, and its source may be external to the aquifer. High K+ levels have been measured in Williamson Creek (Christian, in preparation), and dye trace studies have shown that Williamson Creek contributes water to spring USP (Hauwert et al., 2005). This suggests that during periods of high ground water levels and high streamflow rates on Williamson Creek, spring USP may contain a high percentage of recently recharged surface water from Williamson Creek (see also Chapter 4 and section 3.6.4).

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3.6.3. Well mixed ground water during baseflow Samples with both 18O and 2H values can be plotted against the global meteoric water line (Craig, 1961) to investigate water mixing and evaporation (Figure 3 11) (e.g., Darling and Bath, 1988; Lakey and Krothe, 1996). Studies in other karst aquifers have shown that oxygen and hydrogen isotopes in ground water may show long term, attenuated, time delayed variability reflecting seasonal variations in rainfall distribution and/or its isotopic ratios (e.g., Vallejos et al., 1997; Cane and Clark, 1999; Jones and Banner, 2000; Maloszewski et al., 2002). There is no evidence for this behavior in the Barton Springs segment, although the number of samples with both 18O and 2H analyses is small. 18O and 2H values from the Barton Springs segment are similar to long term mean rainfall isotopic values reported for central Texas (International Atomic Energy Agency, 2005). This suggests that recharge water that enters the Barton Springs segment becomes well mixed and homogenized, similar to findings in other karst aquifers (e.g., Jones and Banner, 2000). Mixing and homogenization of karst ground water may be explained by the aquifer conceptual model presented in Chapter 4 (Figure 4 7). This model suggests that ground water flowing through karst conduits can be forced into the diffuse (or matrix) portion of the aquifer under some conditions. This forcing of ground water through the small intergranular pore

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spaces may explain the well mixed ground waters observed in the Barton Springs segment. It is also possible that Barton Springs segment ground water is not spatially homogeneous, and that spring discharge is a combination of isotopically distinct waters (e.g., Greene, 1997) that mix in some proportion. Two potential recharge sources that can have different isotopic ratios are discrete recharge features in streambeds, and diffuse recharge that has passed through the soil zone. However, water from soil zones presumably would show evidence of evaporation (e.g., Herczeg et al., 1997; Vallejos et al., 1997), which would be detectable as a deviation to the right of the GMWL. As such a deviation is not observed in Barton Springs segment data, this suggests that evaporation effects are minor in the Barton Springs segment, similar to some other karst aquifers (e.g., Jones and Banner, 2000). However, evidence for evaporation (i.e., significant deviation to the right of the GMWL) is observed in the San Antonio segment of the Edwards aquifer to the south (Fahlquist and Ardis, 2004), suggesting that it may occur in the Barton Springs segment as well. 3.6.4. Geochemical evolution of spring water To better understand the systematics of Sr isotopes in the Barton Springs segment, 87Sr/86Sr ratios are compared to the Sr/Ca residence time indicator (Figure

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3 12a). Major ions, in combination with isotopes of strontium (87Sr/86Sr), are a powerful tool to gain insights into ground water flow and evolution (McNutt, 2000; Banner, 2004). As ground water flows through an aquifer, it progressively takes on the Sr isotopic composition of the aquifer rock. For example, in the Madison Limestone aquifer of Wyoming, Frost and Toner (2004) found that recharge water entered the aquifer with an 87Sr/86Sr value of 0.721, and acquired the Sr isotopic value of the limestone rock (0.709) after only seven days. Strontium isotope ratios can be used to quantify mixing of waters with unique 87Sr/86Sr values. In the Floridan aquifer, 87Sr/86Sr variability in ground water is believed to be a result of mixing of ground waters from silicate aquifers with ground waters from carbonate aquifers (Katz et al., 1997). Musgrove and Banner (1993) found evidence of regional scale mixing of North American mid continent brines using Sr isotopes. Swarzenski et al. (2001) identified the source of a submarine spring in Florida as the nearby Floridan aquifer using Sr isotopes. Ultimately, all ground water in an aquifer originates as rainfall. Rainfall has a distinctive geochemical and Sr isotopic signature (Musgrove and Banner, 2004), but the concentrations of Sr2+ in rainfall are so small that they are unlikely to influence the 87Sr/86Sr ratios of karst ground water (Banner, 2004). As an example, Frost and Toner (2004) measured a Sr2+ concentration of 0.04 mg/L for recharge water entering the Madison aquifer. After seven days in the aquifer, the Sr2+ concentration

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increased to 0.3 mg/L, and the measured 87Sr/86Sr value was comparable to the aquifer rock. In addition to carbonate minerals contributing Sr2+ to ground water, Jacobson and Wasserburg (2005) noted that Sr is abundant in gypsum deposits, which are known to occur in trace quantities in karst aquifers, including the Barton Springs segment (Deike, 1987). In the Barton Springs segment, there are numerous potential sources of strontium (Figure 3 13). Musgrove and Banner (2004) reported that 87Sr/86Sr ratios in central Texas cave dripwaters are affected by carbonate rock, overlying soils, and trace amounts of clay minerals present in some of the more argillaceous limestone units. Generally, in a karst aquifer the limestone bedrock is expected to be the dominant first order control of the Sr isotopic composition due to its large volume and Sr concentration (Banner, 2004). Other sources of Sr in the study area include saline zone ground water, Trinity aquifer ground water, argillaceous bedrock that has radiogenic 87Sr/86Sr values, and anthropogenic sources (Oetting, 1995; Musgrove, 2000; Christian, in preparation). However, most of these sources (excluding possibly soils) are expected to be minor sources of Sr relative to the large amount of Sr available for dissolution in the Edwards and Georgetown Limestones. Soils are potentially a significant source of Sr in the central Texas, and values of 87Sr/86Sr derived from these soils have been shown to be significantly higher than those of

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Cretaceous carbonate rock (Figure 3 13) (Cooke et al., 2003; Cooke, 2005; Christian, in preparation). Throughout the Barton Springs segment, there is a wide range of residence times, while there is only a moderate range of 87Sr/86Sr values (0.7076 to 0.7084). Compared to ground water from wells in the aquifer, water discharging from the Barton Springs system has a narrow range of residence times and Sr isotopic values (0.7079 to 0.7081; Figure 3 12b). An initial hypothesis might be that Barton Springs system discharge is a weighted average (i.e., a mixture) of ground waters of varying residence times and Sr isotopic compositions, which is consistent with the concept of karst aquifers as heterogeneous, double porosity systems (Sharp, 1993). Although 87Sr/86Sr values are within analytical uncertainty at each individual spring, there is apparent variability within this analytical uncertainty (Figure 3 12b). Under the assumption that this variability (i.e., a hyperbolic shape for springs MSP, ESP, and OSP) is not an artifact of analytical methods, the general trend of this variability can be somewhat accounted for by progressively mixing water from spring USP with water from well BPS. (Figure 3 12b). Well BPS has been shown to have very little geochemical variability in its long term record (Chapter 2), suggesting that its water represents a high residence time, highly evolved water from the freshwater zone of the Barton Springs segment. Spring USP apparently has small residence time, and its radiogenic 87Sr/86Sr values may reflect surface water or

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soil processes (see next section, 3.6.5). The fluid mixing line on Figure 3 12 is approximately the same as a water evolution line, if it is assumed that the selected endmember waters (spring USP and well BPS) represent the geochemical composition of one single source of Sr2+ and Ca2+. Deviation from this line, seen in samples from springs MSP, ESP, and OSP, might be the result of spatial and temporal variability of the fully evolved water sample represented by well BPS, or additional endmembers that are mixing or reacting with ground water. Mixing between spring USP and well BPS endmembers cannot fully account observed geochemical variability (Figure 3 13b), but that is probably because there are multiple sources of Sr that affect concentrations and isotopic composition in the Barton Springs segment. In the following sections, several additional Sr sources are considered. 3.6.5. Urban infrastructure and Upper Barton Spring Christian (in preparation) suggests that higher 87Sr/86Sr values of surface water in the study area are related to leaking urban infrastructure (water and sewage pipes), although soils are also a potential source. Austin municipal water (i.e., drinking water) is obtained from the Colorado River, a river whose watershed includes a large exposure of Precambrian basement rock (the Llano Uplift). Several minerals in this billion year old basement rock have high Rb/Sr ratios (e.g., mica,

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potassium feldspar) (Faure, 1986, p. 136), and water that reacts with these minerals will have radiogenic 87Sr/86Sr values (Oetting, 1995; Christian, in preparation). Austin municipal water has 87Sr/86Sr values that are more radiogenic than soil or carbonate rock in the study area (Figure 3 13). If leaking urban infrastructure causes this municipal water to recharge the Barton Springs segment, wells and springs with urban infrastructure in their catchment areas may have more radiogenic 87Sr/86Sr values for their ground water. Another possibility is that overlying soils are the cause of the radiogenic 87Sr/86Sr values in Austin area surface water and ground water, although Christian (in preparation) considers this unlikely on the basis of an extensive investigation that included surface water major ion concentrations, 87Sr/86Sr values obtained from trees along Austin creeks, and several other lines of evidence. The Cold Springs ground water basin is highly urbanized (St. Clair, 1979; Hauwert et al., 2005), and more radiogenic 87Sr/86Sr ratios are observed in wells and springs that obtain ground water from this area (Figure 3 14). Wells FON, SVS, SVW, and SVN all reside within this subbasin, and contain the most radiogenic 87Sr/86Sr values in this study (Figure 3 14). These radiogenic 87Sr/86Sr values may result directly from leaking urban infrastructure recharging the aquifer, consistent with the hypothesis of Christian (in preparation). Alternatively, radiogenic Sr may also recharge the aquifer from Williamson Creek, which drains an urbanized watershed and has 87Sr/86Sr values ranging from 0.7080 to 0.7087 (Christian, in

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preparation). This would be consistent with the findings of dye trace studies (Hauwert et al., 2005) that show water from Williamson Creek reaching well SVW and other Cold Springs subbasin wells within several days. The Cold Springs subbasin and the associated Sunset Valley subbasin have been shown to supply a majority of the discharge for spring USP (Hauwert et al., 2005). Spring USP has the highest 87Sr/86Sr values of the four springs, which is consistent with some if its water being derived from Williamson Creek or an urbanized area. This also is consistent with geochemical evidence presented elsewhere in this chapter (section 3.6.1). 3.6.6. Saline zone effect on Old Mill Spring On the basis of SO4/Cl and Sr/Ca ratios alone, spring MSP water samples appear to be of intermediate composition between spring OSP and USP (Figure 3 15). However, spring MSP geochemical composition cannot be merely explained as a two endmember mixture between springs USP and OSP, as 87Sr/86Sr values for spring MSP samples are not intermediate between those of springs USP and OSP (Figure 3 14). This suggests that more than two endmembers contribute to the geochemical variability of spring MSP, or that spring USP geochemical composition is independent of the other three springs (see previous sections of this chapter).

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On the basis of major ion concentrations, samples from spring OSP show evidence of mixing with the saline zone. Spring OSP samples have high Sr/Ca values (i.e., high residence time; Figure 3 15b), which is consistent with the slower and longer flowpath from which some of this springs discharge derives (Hauwert et al., 2005). Spring OSP samples have low SO4/Cl ratios (i.e., elevated Cl concentrations), and Cl is a dominant ion in the saline zone (Sharp and Clement, 1988). Mean values of 87Sr/86Sr for spring OSP are 0.70802, which is intermediate between the measured saline zone values (0.70806, well ALB), and the mean value for spring MSP discharge (0.70796). This suggests that spring OSP discharges a mixture of water from the primary aquifer flowpath that leads to spring MSP (Hauwert et al., 2005), and from the saline zone. On the basis of a hypothetical mixing model between spring MSP and well ALB, about 4 percent of spring OSP discharge may be from the saline zone (Figure 3 16). This range of mixing percentages is comparable to those of Hauwert et al. (2005) (3 percent) and Senger (1983) (maximum of 10 percent). However, the Sr concentrations of spring OSP do not match the mixing model well (Figure 3 16). Furthermore, the saline zone endmember (well ALB) may not represent the geochemical composition of the saline zone accurately, as spatial and temporal geochemical variability exists within the saline zone (Hauwert and Vickers, 1994).

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This is the first time that 87Sr/86Sr has been measured over such a large space and time scale in the Barton Springs segment. The initial insights into ground water flow that Sr isotopes provide are first steps toward a much larger picture. Future work, particularly on the origin of the radiogenic 87Sr/86Sr values in spring USP and the Cold Springs subbasin, may lead to further insight into aquifer processes. 3.7. CONCLUSIONS During the period of study, spring water in the Barton Springs segment was generally Ca HCO3 to Ca Mg HCO3 facies, as predicted for karst aquifers. Unlike some karst systems, however, spring water in the Barton Springs segment generally was close to saturation with respect to calcite. Spring water samples showed evidence of variable residence time and incongruent dissolution, as indicated by increases in Sr/Ca during low spring discharge conditions. Sr/Ca ratios were an effective measure of water residence times for Main Barton, Eliza, and Old Mill Springs. Upper Barton Spring did not show residence time and incongruent dissolution effects as strongly as Main Barton, Eliza, and Old Mill springs. There were dissolved ions not associated with carbonate minerals (i.e., Na+, Cl, SO4 2 and NO3 ) present in Barton Springs segment ground water. Na/Cl molar ratios less than 1 suggest a source of excess Cl or a sink for Na+. Explanations include an anthropogenic source of Cl and ion exchange with clays. Increases in

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Na+, Cl, and SO4 2 at Main Barton, Eliza, and Old Mill Springs were associated with low discharge rates, and probably represent influx of ground water from the saline zone. On the basis of a two endmember mixing model, between 4 and 9 percent of the spring OSP discharged appears to have been derived from the saline zone. Oxygen and hydrogen isotope values indicated that ground water in the aquifer mixes over year or longer time scales. The oxygen and hydrogen data in this study are somewhat sparse, however, and higher resolution sampling might reveal the variations in isotopic composition observed in other karst aquifers. 87Sr/86Sr values and dissolved major ion concentrations at the Barton Springs system suggested that spring water was a mixture of different ground waters present in the aquifer. This is consistent with the behavior expected in double porosity systems such as karst aquifers. Apparently varibility in 87Sr/86Sr values at each individual spring suggested multiple sources of Sr in the study area, although the limestone aquifer rock is expected to be the dominant source for ground water with high residence time. Springs MSP and ESP are geochemically indistinguishable from one another, suggesting that they receive ground water from the same aquifer flowpath(s). This is consistent with the findings of Chapter 4. However, this is inconsistent with the findings of Hauwert et al. (2005), who reported the detection of an injected dye trace at Main Barton Spring but not Eliza Spring. They suggested that Main Barton Spring

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obtains some of its water from the Sunset Valley flow route, and that this flow route does not reach Eliza Spring. Samples from Upper Barton Spring and four wells (FON, SVS, SVW, and SVN) had the most radiogenic 87Sr/86Sr values in this study. Also, high concentrations of K+ occurred at Upper Barton Spring during high aquifer discharge rates. This suggests that Williamson Creek, which also had high 87Sr/86Sr values and K+ concentrations, contributed to Upper Barton Springs discharge. Elevated concentrations of NO3 in Upper Barton Spring suggest an anthropogenic source. Radiogenic 87Sr/86Sr ratios may be associated with leaking urban infrastructure, the water of which is derived from the Colorado River and the Llano Uplift. This study presents the most high resolution geochemical dataset ever collected for the Barton Springs segment. Future research should benefit from the observations made by this study. Additional monitoring, especially high resolution monitoring of wells, could help to better characterize the geochemical variability in the aquifer. 3.8. ACKNOWLEDGEMENTS Thanks are extended to the U.S. Geological Survey and the Texas Commission on Environmental Quality for staffing and funding the real time and major ion data collection program used for this study. Funding for isotopic analyses

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was provided by the Jackson School of Geosciences. Thanks are also extended to Jay Banner and Libby Stern for access to analytical facilities, and Larry Mack and Kurt Ferguson for assistance with isotope ratio analysis.

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Upper Barton Spring (USP)P o o lOld Mill Spring (OSP) Eliza Spring (ESP)B a r t o nS p r i n g sC r e e kDam Spring and Site ID Creek Flow Direction N RAB SVN SVE SVS SVW FOW PLS MCH BDW BPS ALB FON see (b)B a r t o nC r e e kW i l l i a m s o nC r e e kS l au g h t e rC r e e kB e a rC r e e kO ni o nC r e e k ABCStudy Area Well and Site ID Creek Confined Zone Recharge ZoneG r o u n dw a t e rd i v i d eS a l i n ez o n eb o u n d a r yB a r t o nMain Barton Spring (MSP) EXPLANATION EXPLANATION(b) (a)150 m 0 N 5 km 0 ABC B a t h h o u s eFigure 3 1a Map of the Barton Springs segment of the Edwards Aquifer, showing wells sampled in 2004 and 2005. Figure 3 1b. Map of the Barton Springs system, and the four springs that were sampled from 20032005.

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Figure 3 2a Main Barton Spring (MSP). Samples were collected from a fissure near the pooldiving board. Figure 3 2b. Eliza Spring (ESP). Samples were collected from a constructed detention pool. Figure 3 2c. Old Mill Spring (OSP). Samples were collected near the rock wall constructed to contain the spring discharge. Figure 3 2d. Upper Barton Spring (USP). Samples were collected from a prominent orifice in Barton Creek streambed. Figure 3 2e. Sampling point for well MCH, a typical configuration for most domestic well sampling points.

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(a) (b) (c) (e) (d)

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Figure 3 3 Time series graph showing Barton Springs system discharge, spring MSP specific conductance, average area weekly rainfall, samplingevents at the Barton Springs system, and sampling events at wells. Specific conductance is plotted with increasing values toward the bottom, in order to highlight its general correlation with spring discharge rates. 0 4 8Rainfall (in) A u g 0 3D e c 0 3Ju n 0 4A u g 0 4 D e c 0 4A p r 0 5700 40 60 80 100 120 140Barton Springs system discharge (ft3/s)500 600Sp. Cond. ( S/cm) B a r t o n S p r i n gs d i s c h a r g eSpring MSP specific conductance mean Austin rainfall Barton Springs system discharge Spring sampling event Spring MSP Specific conductanceEXPLANATION Well sampling event

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Figure 3 4 Ranges of ion concentrations for the Barton Springs segment, 2003005. There are no units for the abscissa, and ordinate has a logarithmic scale showing molar concentrations. .001 .01 .1 1 10 100 Ca Mg Na K HCO3Cl SO4NO3SrIon concentration (mmol/L) M S P E S P O S P U S P W e l l sEXPLANATION

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Figure 3 5 Piper diagram showing major ion water analyses from 20032005 from the Barton Springs segment. The one outlier point is well ALB, which receives some of its water from the saline zone (see text section 3.6.1).Ca Mg Na+K Cl SO4S O4+ C lC a + M gHCO3 Wells USP OSP ESP MSP EXPLANATION Well ALB Well ALB Well ALB

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Figure 3 6a. Comparison of water samples with the theoretical 1:2 calcite dissolution line, which samples would plot along if the only mineral they reacted with was calcite. When gypsum is added as a dissolving mineral (dashed line, logSIgypsum= 1.5), the theoretical dissolution line shifts up and changes in slope. As all samples in the Barton Springs segment plot above the pure calcite line, this suggests that gypsum or a similar mineral may be present in the aquifer. Figure 3 6b. By subtracting SO4 2 from the ordinate, gypsum dissolution no longer distinguishes the two lines of figure (a). The two lines now overlap, and water samples plot closer to the theoretical calcite dissolution line,suggesting that gypsum and/or pyrite is actively dissolving in the aquifer.

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(b) 1.5 2.0 2.5 3.0 3.5 4.0 3.04.05.06.07.0HCO3 (mmol/L)Ca2++ Mg2+(mmol/L)(a) Wells USP OSP ESP MSPEXPLANATIONc a l c i t e d i s s o l u t i o nc a l c i t e a n d g y p s u m d i s s o l u t i o n 1.5 2.0 2.5 3.0 3.5 4.0 3.04.05.06.07.0HCO3 (mmol/L)Ca2++ Mg2+ SO4 2 (mmol/L)c a l c i t e a n d g y p s u m d i s so l u t i o n Wells USP OSP ESP MSPEXPLANATION

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Figure 3 7 Na/Clmolar ratios are generally less than 1 in the Barton Springs segment, suggesting a source other than halite source (Na/Cl=1) for these ions. Na/Clratios do not vary systematically with specific conductance, suggesting that the source of these ions does not change as specific conductancechanges. Well ALB is off scale with a specific conductance of 3000 S/cm and Na/Clof 1.17, and well BPS is off scale with a specific conductance of 610 S/cm and Na/Clof 0.15. 0.5 0.7 0.9 1.1 1.3 400500600700800Specific conductance (uS/cm)Na/Cl(mol/mol) Well ALB3000 Well BPS.15 Wells USP OSP ESP MSP EXPLANATION Halite dissolution (Na/Cl=1)

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Figure 3 8 Time series plot showing systematic variation of Sr/Ca in water samples from springs MSP, ESP, OSP, and USP. Discharge from the Barton Springs system, as measured by real time monitoring equipment, is shown for comparison.B ar t on S p r i n g s 0 2 4 6 8 Aug 03 Oct 03Jun 04Sep 04Dec 04Mar 05Sr/Ca (mol/mol) x 100050 70 90 110 130 Jun 05Barton Springs system discharge (ft3/s) (ft s y s t e m d i s c h a r g e USP OSP ESP MSP EXPLANATION

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Figure 3 9. Comparison of Sr/Ca ratios and Barton Springs system discharge, and comparison of Mg/Ca ratios and Barton Springs system discharge. The linear correlation and corresponding r2are shown as well. r2= 0.71 2 4 6 8Sr/Ca (mol/mol) x 1000 0.2 0.3 0.4 0.5Mg/Ca (mol/mol) 2 4 6 8 0.2 0.3 0.4 0.5 2 4 6 8 0.2 0.3 0.4 0.5 0 1 2 3 607590105120 0.2 0.3 0.4 0.5 607590105120Barton Springs system discharge (ft3/s) MSP ESP OSP USP EXPLANATION(a) (b) (c) (d) (e) (f) (g) (h)r2= 0.73 r2= 0.78 r2= 0.06 r2= 0.04 r2= 0.46 r2= 0.52 r2= 0.56

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Figure 3 10 Comparison of Mg/Ca and Sr/Ca ratios from Barton Springs segment water samples with dripwatersamples from central Texas caves (Musgorverand Banner, 2004). Cave dripwatersamples are collected from Inner Space Caverns (Georgetown, Texas) and Natural Bridge Caverns (San Antonio, Texas), and represent water infiltrating through the vadose zone and fallinginto the open space of a cave. Cave dripwatershave lower Sr/Ca and Mg/Ca ratios than any spring samples from the Barton Springs system, which is consistent withthe hypothesis that Mg/Ca and Sr/Ca are measurements of ground water residence time. 0.0 0.2 0.4 0.6 0.8 1.0 0246810Sr/Ca (mol/mol) x 1000Mg/Ca (mol/mol) Wells USP OSP ESP MSP EXPLANATION Central Texas cave dripwaters Barton Springs system spring discharge

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Figure 3 11 Oxygen and hydrogen isotopic values from the Barton Springs segment, plotted with the global meteoric water line (Craig, 1961) for comparison. The GMWL (Craig, 1961) and data from other studies are shown forcomparison. All of the values plot near both the GMWL and each other. Analytical uncertainty is shown for one data point. Annual Average Rainfall (Waco, TX; IAEA, 2005) Well, Saline zone (Oettinget al., 1996) Well, San Antonio (Groschenand Buszka, 1997) Well, Saline zone (ALB) Spring USP Spring OSP Spring ESP Spring MSP EXPLANATION 18O (SMOW)2H (SMOW)G l o b a l m e te o r i c w a t e r l i n e ( C r a i g 1 9 6 1 ) 6 5 4 3 2 10 35 25 15 5analytical uncertainty

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Figure 3 12a Sr/Ca87Sr/86Sr variations in the Barton Springs segment. A wide range of residence times and a moderate range of Srisotope values exist in the study area. A hypothetical mixing line between (1) average spring USP composition (Table 3 2) and well BPS (large historical record showing little geochemical variability; Chapter 2) indicates one potential pathway of water evolution in the Barton Springs segment. Figure 3 12b Inset of (a). Variation in isotopic composition for springs is within analytical uncertainty, but may suggest an evolution toward lessradiogenic values as residence time increases. This could be explained by evolving a low residence time spring USP sample toward a well BPS sample. Deviation fromthis line might be the result of spatial and temporal variability in well BPS geochemical composition. Analytical uncertainty is shown for for a few samples.

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0 20 40 60 80 100 0.70760.70780.70800.70820.708487Sr/86SrSr/Ca (mol/mol) x 1000ALB saline zone well BPS FOW, Trinity aquifer mixing FON 0 2 4 6 8 0.707900.707950.708000.708050.708100.7081587Sr/86SrSr/Ca (mol/mol) x 1000 see (b) SVS SVN SVW ESP OSP USP Wells and site ID MSP EXPLANATIONABCPLS BDW SVE ESP OSP USP Wells and site ID MSP EXPLANATIONABC RAB MCH Uncertainty(a) (b)h y p o t h e t i c a lm i xi n g 95:5 mix Average USP (100:0) 90:10 mixh y p o t h e t i c a l m i x i n g w i t h w e l l B P S 50:50 mix 25:75 mix

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Figure 3 13 Potential sources of strontium in the Barton Springs segment,and surrounding areas. Data from this study are shown, as well as data gathered from other studies.Carbonate and evaporite rocks, central Texas 1 Barton Springs system springs Barton Springs segment freshwater zone Saline zone ground water, Facies D 1 Surface water, Williamson Creek 4Municipal tap water for City of Austin 4 Surface water, Barton Creek 4 San Antonio, hydrologically active wells 3 San Antonio, Hydrologically stagnant wells 3 0.7070 0.7080 0.7090 0.7100Soils, central Texas 2Cave dripwaters, central Texas 2Ground water, Edwards aquifer 2 1Oetting(1995)2Musgrove (2000)3Groschenand Buzska(1997)4Christian (in preparation)5Cooke et al. (2003) 87Sr/86Sr REFERENCES Soils, Gillespie county (60 km to the west) 5 Soils, Austin area 4

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Figure 3 14a. Graph showing the range of 87Sr/86Sr values for four springs (MSP, ESP, OSP, USP) from August 2003 to June 2005, and the range of 87Sr/86Sr values for 12 wells sampled in May and June 2005. Wells are divided into three colors: (1) green wells with 87Sr/86Sr less than all spring values; (2) black wells with values within the range of all springs; and (3) red wells with values higher than all springs. Figure 3 14b. Map of study area showing 87Sr/86Sr values for wells and springs. Well and spring symbols are shaded according to the designation of (a). A yellow shaded area shows the delineation of the Sunset valley and Cold Springs groundwater basins as mapped by Hauwert et. al (2005). The wells with the most radiogenic 87Sr/86Sr values are located in this basin, and radiogenic 87Sr/86Sr values at spring USP suggest that it discharges water from this basin.

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N .70799 .70819 .70801 .70832 .70816 .70763 .70788 .70798 .70788 .70789 .70806 .70827 inset Well and 87Sr/86Sr Creek Confined Zone Recharge Zone EXPLANATION(b) OSP: 0.70800 0.70803 ESP: 0.70794 0.70796 MSP: 0.70793 0.70797 0.7076 0.7077 0.7078 0.7079 0.7080 0.7081 0.7082 0.7083 0.708487Sr/86Sr MSP USP OSP ESP (a) Sunset valley and Cold Springs basin (Hauwert et al., 2005) Spring and 87Sr/86Sr USP: 0.70811 0.70814 i n d e f i n i t e b o u n d a r y Wells Wells Wells 5 km 0 150 m 0

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0.8 0.6 0.4 0.2 0.0 0.2 3 2 10log (Sr/Ca) (mol/mol)log (SO4/Cl) (mol/mol) Wells USP OSP ESP MSP EXPLANATION Figure 3 15b Inset of (a), excluding wells, with shaded areas indicating samples with 87Sr/86Sr values that are within analytical uncertainty of each other. 0.5 0.4 0.3 0.2 3.0 2.8 2.6 2.4 2.2 2.0log(Sr/Ca) (mol/mol)log(SO4/Cl) (mol/mol)Increasing residence time Figure 3 15a SO4/ClSr/Ca variations in wells and springs of the Barton Springs segment. High SO4/Cl ratios are associated with the Trinity aquifer, while low SO4/Cl ratios may be associated with the saline zone. Sr/Ca is a measure of water residence time. 87Sr/86Sr = 0.708187Sr/86Sr = 0.707987Sr/86Sr = 0.7080 Saline zone mixing

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Figure 3 16 Sr87Sr/86Sr variations for springs MSP and OSP, and saline zone well ALB. A mixing line between well ALB geochemical composition andthe mean geochemical composition for spring MSP is shown, along with tickmarks indicating progressive mixing of these two endmembers. On the basis of 87Sr/86Sr values, about 4 percent of spring OSP discharge may be from the saline zone. However, the Srconcentrations of spring OSP do not fit this mixture well, and the saline zone endmember may not represent a uniform geochemical composition ofthe saline zone. 0 5 10 15 20 25 0.707940.707960.707980.708000.708020.708040.7080687Sr/86SrSrconcentration (mg/L)Spring MSP (100:0) Saline zone well ALB (0:100) 95:5 70:30 50:50 20:80 90:10 Well ALB OSP MSP EXPLANATION Mixing line between well ALB and mean geochemical composition of spring MSP, with proportions noted95:5

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Table 3 1 Summary of analysis results from Barton Springs segment water quality sampling, 2003. I1SrHOISrHOISrHOISrHOISrHO 08/06/03 08/20/03 09/03/03 09/16/03 09/25/03 09/30/03 2 2 12/23/03 06/21/04 307/07/04 07/21/04 08/04/04 08/25/04 09/15/04 10/04/04 10/23/04 11/24/04 12/14/04 01/03/05 01/26/05 02/16/05 03/09/05 03/30/05 04/20/05 05/11/05 3 3 3 06/09/05 1 Abbreviations for analysis types: IDissovled major ion SrDissolved 87Sr/86Sr analysis O 18O analysis H 2H analysis 2 Only well ALB was sampled. 3 Wells BDW, BPS, FON, FOW, MCH, PLS, RAB, SVE, SVN, SVS, and SVW were sampled. Sampling date Wells Upper Barton Spring (USP) Main Barton Spring (MSP) Old Mill Spring (OSP) Eliza Spring (ESP)

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Table 3 2 Summary statistics for ion concentrations and isotope ratios in the Barton Springs system, 2003.All 12 wells MSP ESP OSP USP mean std devmean std devmean std devmean std devmean std dev range (n)range (n)range (n)range (n)range (n) pH 7.0 0.17.0 0.17.0 0.16.9 0.27.1 0.1 6.8 7.2 (25)6.8 7.2 (25)6.7 7.2 (25)6.6 7.1 (23)6.9 7.4 (25) Cond 637 30636 30719 40632 40684 400 ( S/cm) 565 678 (25)550 684 (25)636 848 (25) 4 66 662 (23) 4 45 2600 (25) Ca 93 594 693 595 580 15 (mg/l) 84 104 (24)83 103 (22)85 107 (22)85 104 (21) 4 6 125 (24) Mg 21 221 223 222 328 11 (mg/l) 12 24 (24)13 24 (22)17 26 (22)8.3 25 (21)17 76 (24) Na 14 215 227 310 124 64 (mg/l) 11 19 (24)12 21 (22)15 32 (22)5 12 (21)5 320 (24) K 1.3 0.11.3 0.11.6 0.11.3 0.21.7 2.4 (mg/l) 1.1 1.7 (24)1.2 1.7 (22)1.3 1.9 (22)1.1 2.2 (21)0.7 13 (24) HCO3325 14322 16316 22337 25315 43 (mg/l) 280 350 (24)270 340 (22)260 250 (22)260 370 (21)230 370 (24) Cl 24 325 3 4 4 318 338 88 (mg/l) 16 31 (24)17 35 (22) 4 0 50 (22)7 20 (21)7 450 (24) SO429 330 3 4 4 226 3 4 9 105 (mg/l) 26 25 (24)26 36 (22) 4 0 47 (22)16 29 (21)7 530 (24) NO3 N 1.3 0.21.2 0.21.2 0.22.1 0.41.3 0.8 (mg/l) 0.9 1.7 (23)0.9 1.6 (23)0.9 1.5 (23)0.9 3.5 (22)0.05 3.0 (21) Sr 0.83 0.250.87 0.280.94 0.210.40 0.103.7 5.5 (mg/l) 0.4 1.4 (24)0.4 1.5 (22)0.64 1.4 (22)0.10 0.52 (21)0.15 21 (24)87Sr/ 0.707960.707950.708020.708120.7080286Sr 0.70728 74 (13)0.70745 96 (7)0.70800 03 (7)0.70811 14 (6)0.70763 832(12) 18O 4.0 0.1 4.0 0.1 4.0 0.1 4.0 0.2 4.0 0.1 () 4.1 3.9 (4) 4.1 3.8 (4) 4.1 3.8 (4) 4.2 3.8 (3) 4.1 3.9 (3) 2H 26 1 25 2 25 3 22 4 25 3 () 28 25 (7) 26 23 (5) 28 21 (5) 26 16 (5) 29 21 (12) Springs Para meter

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Table 3 3. Coefficients of variation (Cv) for major ion concentrations and field parameters in the Barton Springs segment, 2003. Among the four springs, the highest Cv values are for the Sr2+ and NO3 ions.Site IDpHCondCa2+HCO3 K+Mg2+Na+ClSO4 2 NO3 Sr2+MSP 1.7% 4 .4%5.7% 4 .4%8.3%11%11%12%10%14%30% ESP 2.0% 4 .7%6.2% 4 .9%7.9%11%13%14%10%15%32% OSP 1.6%5.2%5.4%6.9%8.0%9.0%12%6.3% 4 .3%15%23% USP 2.4%6.7% 4 .9%7.3%18%16%14%16%12%21%25% Wells 2.0%59%19%13%140% 4 0%270%240%210%60%150% All units are % coefficient of variation (standard deviation / mean)

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4. Barton Springs during stormflow conditionsUsing oxygen isotopes and real time monitoring parameters to quantify water mixing in karst spring discharge, Austin, TX 4.1. ABSTRACT Four hydrologically connected karst springs in the Barton Springs segment of the Edwards aquifer in Austin, Texas, were monitored for physical, chemical, and isotopic parameters after a three inch (75 mm) rainfall. Oxygen isotope samples were collected at 12 to 48 hour intervals, and showed an evolution toward more isotopically depleted values after rainfall, suggesting that recent rainfall carried by surface creeks (stormflow) entered the aquifer and reached the springs within 14 hours. Discharge, specific conductance, dissolved oxygen, and turbidity were measured every hour at one spring, and showed substantial changes after rainfall. The maximum discharge of stormflow from springs occurred between 40 and 80 hours after rainfall, and each spring had a unique response to stormflow. A hydrograph separation created for one of the springs using oxygen isotope values showed a rapid increase in discharge at the onset of rainfall, but 14 hours until the first arrival of stormflow. This suggests that that pre storm water was expelled from the karst conduit system ahead of the advancing front of stormflow. The

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hydrograph separation also showed that discharge of pre storm water (from the aquifers diffuse matrix) was suppressed by stormflow in the aquifer, suggesting that increased pressure in karst conduits reduced the hydraulic gradients that normally allow matrix water to drain into conduits. Turbidity measurements indicated that a front of turbid water was at the leading edge of stormflow as it passed through aquifer conduits. Dissolved oxygen values generally tracked changes in specific conductance values, but these changes were neither simultaneous nor equal in magnitude, suggesting that another process acted upon dissolved oxygen in the ground water. There was a strong correlation between specific conductance and oxygen isotope values, suggesting that specific conductance may act as an inexpensive and conservative tracer of stormflow. This study showed that high resolution monitoring of a karst spring can reveal information about aquifer hydrology during stormflow conditions, which may be of use to both resource managers and the scientific community. 4.2. INTRODUCTION Karst springs are renegades in the world of hydrogeology, especially when there is intense rainfall in their catchment area. In response to rainfall, spring discharge can become turbid, specific conductance can undergo large changes over a few hours (Andrews et al., 1984), and increased concentrations of anthropogenic

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contaminants may be detected in the discharge water (Mahler and VanMetre, 2000). Studies of karst springs during these stormflow conditions have attributed this behavior to stormflow water recharging the aquifer, traveling rapidly through solution enlarged conduits, and arriving at springs with very little chance to disperse into the more diffuse (matrix) portion of the aquifer (Siegenthaler and Schotterer, 1984; Hess and White, 1988; Dreiss, 1989; Lakey and Krothe, 1996; Ryan and Meiman, 1996; Desmarais and Rojstaczer, 2002; Liu et al., 2004). This fractured rock aquifer response to rainfall is difficult to incorporate into a conceptual model; a porous medium aquifer (e.g., sandstone) tends to mix and homogenize recharge water, and hour scale changes in water quality are rarely observed in porous medium spring discharge. The rapid conveyance of stormflow water to karst spring outlets is analogous to surface water systems, in which recent rainfall enters creeks and mixes with older surface water in quantifiable proportions. For many years, studies have successfully traced recent rainfall through surface water catchments using a variety of chemical and isotopic tracers (Fritz et al., 1976; Buttle, 1994). The stable isotopes of oxygen and hydrogen in the water molecule can be used as conservative tracers (Gat, 1981; Kendall et al., 1995) to trace recharge through a karst aquifer. Under stormflow conditions, oxygen and hydrogen isotopes might potentially vary over a scale of hours to days at karst springs, reflecting the input of

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recent rainfall to the system. Individual rainfall events that recharge an aquifer typically have a unique isotopic fingerprint that reflects the origin, travel path, and rainout history of the storm (Craig, 1961). Over periods of many years, these individual rainfall fingerprints usually are averaged and mixed together in ground water systems. As a result, non stormflow ground water generally reflects the mean isotopic composition of regional rainfall (Darling and Bath, 1988; Lakey and Krothe, 1996), with minor variations (if any) showing an attenuated and time delayed signal representing seasonal rainfall isotopic variability (Vallejos et al., 1997; Cane and Clark, 1999; Maloszewski et al., 2002). Individual rainfall events, however, typically have widely varying isotopic compositions, and can provide a potential tracer of flow through the aquifer, with pre storm and stormflow waters as endmembers in a two component mixing model. The isotope geochemistry of a karst spring can be used to (a) detect arrival times of stormflow at springs, (b) separate a hydrograph into its stormflow and pre storm water components (e.g., Lakey and Krothe, 1996), and (c) evaluate any non conservative behavior of water isotopes in the system. Each of these is considered in a study carried out on a karst aquifer near Austin, Texas, during October, 2004.

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4.3. STUDY AREA The Barton Springs segment of the Edwards aquifer (herein referred to as the Barton Springs segment) is a karst aquifer that extends south southwest of Austin, Texas (Figure 4 1). It is bounded to the north by the Colorado River, to the south by a ground water divide, to the west by its contact with relatively impermeable bedrock, and to the east by a zone of low permeability known as the saline zone (Slade et al., 1986; Sharp and Banner, 1997). Aquifer material consists mainly of Cretaceous limestone that has undergone multiple episodes of karstification (Small et al., 1996). In the Miocene epoch, tectonic activity created a zone of normal faulting, resulting in karstification and the aquifer structure and behavior seen today (Slade et al., 1986). The aquifer is generally highly transmissive, with some measured straight line transit times exceeding 10 km per day (Hauwert et al., 2005). A major source of recharge to the aquifer is from five ephemeral losing streams that cross the recharge zone (Figure 4 1); these creeks are estimated to provide approximately 85 percent of total recharge to the aquifer. The remaining 15 percent of recharge is derived mostly from precipitation which falls directly on the recharge zone and enters the aquifer (Slade et al., 1986). During large rainfall events (stormflow conditions), the isotopic composition of water in the five recharging creeks is expected to be controlled strongly by the isotopic composition of the rainfall (Fritz et al., 1976; Buttle, 1994).

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Ground water flow in the Barton Springs segment generally is to the north northeast, following the trend of the Balcones Fault Zone. The water generally discharges from the Barton Springs system, a cluster of four springs that account for over 90 percent of the natural discharge from the aquifer (Figure 4 1) (Hauwert and Vickers, 1994). The quantity and quality of water that discharges from the Barton Springs system varies over time, especially under stormflow conditions, during which stormflow water travels rapidly through solution enlarged conduits and arrives within hours at the Barton Springs system (Andrews et al., 1984; City of Austin, 1997; Mahler and Lynch, 1999; Mahler, 2003). 4.4. METHODS 4.4.1. Isotope sample collection Unfiltered water samples were collected at 12 to 48 hour intervals from the Barton Springs system following a rainfall event on October 23, 2004 from about 12:00 am to 6:00 am. Samples had also been collected from the springs two months earlier (August 25). There had been very little rainfall between these samples and the October rain, thus these pre storm samples were assumed to represent a homogeneous reservoir of water in the aquifer. Flow weighted composite samples were collected during the storm from Onion and Bear creeks, which provide recharge to the aquifer. Automated

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equipment pumped individual water samples from these creeks into Teflon sample containers at 3 hour intervals. In the laboratory, individual samples were combined using creek hydrographs to create flow weighted composites, or average, water samples (Wilde et al., 1999). Unfiltered water samples were taken from these composites and analyzed for their 18O and 2H values. Oxygen isotope samples were analyzed at The University of Texas at Austin on a isotope ratio mass spectrometer by equilibrating the sample with CO2 gas and subsequently analyzing the CO2 isotope ratios (Epstein and Mayeda, 1953). Twenty two samples of an internal lab standard were used during analysis, and all were within 0.1 of the standard value. Hydrogen isotope samples were analyzed at Southern Methodist University on a Finnigan MAT mass spectrometer. Samples were passed over depleted uranium metal at 800C and the liberated hydrogen gas was collected and analyzed (Bigeleisen et al., 1952). A limited number of samples were chosen for analysis of 2H, on the basis of oxygen isotope results. Minimum and maximum values of 18O were assumed to indicate corresponding 2H analyses that might be useful for interpretation. Oxygen and hydrogen isotope ratios were expressed in delta notation (Coplen, 1994), and were referenced to standard mean ocean water (SMOW).

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4.4.2. Real time parameter monitoring One spring (Main Barton Spring) was monitored with a pressure transducer and Hydrolab equipment. This equipment was placed into a submerged solution enlarged fracture through which the majority of the spring discharge flows. Values for discharge, specific conductance, turbidity, and temperature were measured and recorded every 15 minutes. Small gaps (one hour or less) in this data arising from equipment malfunction or data transmission errors were filled in by linear interpolation. The 15 minute dataset was converted into an hourly dataset by calculating the mean parameter value using the four measurements taken during the hour. Surface creeks were monitored for discharge during the study period. Stage levels were correlated to discharge measurements using stage discharge relationships (Buchanan and Somers, 1969), which had been established for the sites. Rainfall data were obtained from the City of Austin Flood Early Warning System, an electronically monitored network of rainfall gauges located throughout the study area. The purpose of these data was to identify the occurrence of rainfall, and the results are not used quantitatively.

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4.4.3. Hydrograph separation A pre storm/stormflow two component mixing model (Fritz et al., 1976; Banner and Hanson, 1990; Kendall et al., 1995; Lakey and Krothe, 1996) was used to perform hydrograph separations on Main Barton Spring. The equations are straightforward derivations of mass balance equations describing discharge and the flux of different endmembers through the system, as expressed by QMIX = QPRESTORM + QSTORM (Eq. 4 1) QMIXMIX = QPRESTORMPRESTORM + QSTORMSTORM (Eq. 4 2) and combining (Eq. 4 1) and (Eq. 4 2) yields ) ( ) (PRESTORM STORM PRESTORM MIX MIX STORMQ Q (Eq. 4 3) where QMIX is the measured discharge of the spring, QSTORM and QPRESTORM are the discharge contributed by stormflow and pre storm water, and MIX, PRESTORM, and STORM are measured isotopic values of the reservoirs of mixed and unmixed waters. QMIX values were equal to the hourly discharge values measured by real time monitoring. MIX values were obtained from 12 to 48 hour sampling of the springs, PRESTORM values were from samples collected two before rainfall, and STORM was obtained from the flow weighted composite samples from two creeks. As there were more discharge readings than isotope results, hourly isotopic values were estimated using linear interpolation.

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While this equation makes use of isotopic delta values, any conservative parameter can be used, provided that values for both endmembers are known. With this in mind, we substituted several real time monitoring parameters into this equation and compared those results with those from oxygen isotopes. Several assumptions are needed for this hydrograph separation approach (Dreiss, 1989), including that pre storm water is uniformly distributed throughout the aquifer matrix, and that stormflow water has an isotopic composition sufficiently different from that of pre storm water (Katz et al., 1998). 4.5. RESULTS 4.5.1. Rainfall Rainfall lasted from about 12:00 am to 6:00 am on October 23, 2004. Rainfall amounts ranged from 1.9 to 3.8 inches (48 mm), with a mean amount of 2.8 inches (71 mm). There was also a small rainfall on October 27 (less than 0.5 inches, or 13 mm), and another rainfall event on November 1 (about 1.5 inches, or 38 mm). Stream discharge rates that resulted from this rainfall are shown in Figure 4 2. 4.5.2. Discharge, turbidity, conductance, and dissolved oxygen Real time monitoring of Main Barton Spring beginning at the onset of rainfall resulted in 323 sets of hourly values (Figure 4 3). Discharge ranged from 60 ft3/s

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(1.7 m3/s) on October 23, 2004 at 12:00 am to 76 ft3/s (2.2 m3/s) on November 5, 2004, the end of the study period. Discharge began to increase within 30 minutes after the onset of rainfall, and reached a maximum of 72 ft3/s twenty four hours later; throughout the remainder of the study period, discharge remained above 70 ft3/s. Turbidity increased from zero Nephelometric Turbidity Units (NTU) at the onset of rainfall to a maximum of 17 NTU 16 hours later, and then declined over the next several days. Discharge and turbidity showed relatively simple monotonic increases and decreases, although they did not experience these changes at the same time or in a manner proportional to each other (Figure 4 3). The initial specific conductance reading of 657 microsiemens per centimeter ( S/cm) began to decrease about 8 hours after the onset of rainfall. Dissolved oxygen values ranged from 6.2 milligrams per liter (mg/L) at the onset of rainfall to a maximum of 6.9 mg/L 36 hours later, and began changing 8 hours after the onset of rainfall. Specific conductance and dissolved oxygen showed complex temporal changes (Figure 4 3), with multiple local maxima and minima, and changes in slope. 4.5.3. Oxygen and hydrogen isotopes The twenty nine 18O analyses from the four springs yielded values between 5.2 and 3.8 (Figure 4 3; Tables C 1 and C 2). The most isotopically depleted values were: Main Barton Spring 4.5, Upper Barton Spring 5.2, Old Mill

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Spring 4.4, and Eliza Spring 4.4. Flow weighted composite samples from Bear Creek and Onion Creek both had 18O values of 5.0. The pre storm sample from August 25, 2004 had a 18O value of .8, which is similar to the reported long term mean 18O composition of rainfall in central Texas (.7) (International Atomic Energy Agency, 2005). This suggests that the assumption of a well mixed homogeneous aquifer prior to the storm was reasonable. Five samples analyzed for 2H had values ranging from 38 to 16. Two samples taken simultaneously on October 25, 2004 had identical 2H values of 30, suggesting that analytical techniques were carried out appropriately. Comparison of 18O and 2H (Figure 4 4) indicates that these samples plot closely to the global meteoric water line (GMWL) (Craig, 1961). 4.5.4. Hydrograph separation with oxygen isotopes The result of a hydrograph separation for Main Barton Spring using 18O values and (Eq. 4 5) is shown in Figure 4 5. The stormflow endmember was taken to be the value of the creek composite samples, and the pre storm endmember was taken to be the mean 18O value measured from the four springs on August 25, 2004. Over long time periods, pre storm isotopic composition does vary a small amount (from 4.1 to 3.9; see Chapter 3), but is assumed to have remained constant from August 2004 through October 2004, as little rainfall occurred during this time.

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Similarly, the isotopic composition of rainfall probably changes over space and time, but this was assumed to be negligible relative to the effects imparted by stormflow conditions. It was not possible to create a hydrograph separation for Eliza, Old Mill, and Upper Barton Springs. The discharge rates of these three springs were not measured, and therefore there was no hydrograph available. 4.6. DISCUSSION 4.6.1. First arrival of stormflow at springs Each spring shows a unique response to stormflow, as measured by changes in oxygen isotope composition. This suggests that stormflow water arrives at the four springs at different times, and/or that each spring discharge stormflow water from different sources. Three of the springs (Main, Eliza, and Old Mill) display comparable behavior, while Upper Barton Spring has a truly unique isotopic response (Figure 4 6; Table 4 1). At Main Barton Spring, oxygen isotope ratios began to slightly shift toward more isotopically depleted values by 14 hours after the onset of rainfall (i.e., the first collected sample), suggesting that stormflow water reached this spring in about 14 hours (Table 4 1). This is consistent with previous observations of changes in specific conductance and turbidity after rainfall at Main Barton Spring (City of

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Austin, 1997; Mahler and Lynch, 1999). These studies reported the arrival of stormflow in about 12 hours, although the arrival time was as short as 5 hours during periods of high spring discharge. Oxygen isotope ratios at both Main Barton Spring and Eliza Spring reached a minimum value about 60 hours after onset of rainfall (Table 4 1). As in Chapter 3, there are no measurable geochemical differences between Main Barton Spring and Eliza Spring (Chapter 3), and dye trace studies have generally shown these two springs to be very closely connected (Hauwert et al., 2005). Old Mill Spring isotope ratios reached a minimum value about 80 hours after the onset of rainfall (Table 4 1). Geochemical evidence (Chapter 3) and dye trace studies (Hauwert et al., 2005) suggest that ground water reaches Old Mill Spring by a longer and slower flow path along the far eastern boundary of the aquifer, consistent with the oxygen isotope data in this study. Upper Barton Spring responds to stormflow conditions more quickly than the other three springs, with large changes in isotopic composition seen in less than 14 hours (i.e., isotopic values had already changed significantly prior to the collection of the first sample). Oxygen isotopes values reached a minimum about 48 hours after the onset of rainfall, 12 hours earlier than at Main Barton and Eliza Springs (Table 4 1). This suggests that either Upper Barton Spring has less pre storm water available for mixing, or that a large amount of stormflow water was able to

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enter shallow conduits rapidly from a nearby creek and discharge from Upper Barton Spring. Upper Barton Spring may have a smaller catchment area a more shallow flow system, and thus shorter flowpaths; for this type of spring, a fast response to stormflow would be expected (Dreiss, 1989). Independent dye tracing studies (Hauwert et al., 2005) found that Upper Barton Spring resides within a small and isolated subbasin in the aquifer, which is consistent with these findings. Geochemical evidence is also consistent with these observations (Chapter 3). 4.6.2. Stormflow flushes karst conduits Until 14 hours after the onset of rainfall, pre storm water accounted for over 95 percent of all Main Barton Spring discharge, even as overall discharge rates rose by 15 percent (from 60 to 69 ft3/s; Figure 4 5). Thus, during the first 14 hours after the onset of rainfall, pre storm water was pushed out of the aquifer by the recent influx of recharging stormflow water, a phenomenon known as a pressure pulse. This flushing behavior has been observed at many karst springs, although the geochemical composition of the flushed ground water can vary. In some cases, specific conductance increases during this flushing event, and is interpreted as mobilization of ground water with a longer residence time (Desmarais and Rojstaczer, 2002). In other cases, as in this study, specific conductance does not change during the flushing (Hess and White, 1988; Lakey and Krothe, 1996; Ryan

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and Meiman, 1996), suggesting that ground water already present in the conduits is merely expelled, as opposed to another source of ground water being forced into the conduits. In theory, only a fully submerged phreatic conduit can propagate a pressure pulse instantaneously (Ryan and Meiman, 1996). Surprisingly, however, some researchers have observed rapid pressure pulse propagation in unsaturated zone (i.e., perched) karst springs (Siegenthaler and Schotterer, 1984). This may be because once a karst conduit in the unsaturated zone is filled with water, it can effectively propagate a pressure pulse in the same manner as a fully submerged phreatic conduit (B.J. Mahler, U.S. Geological Survey, written comm., 2005). Following the method of Ashton (1966), we can integrate across these 14 hours to arrive at 3,200,000 ft3 (91,000 m3) of ground water representing the minimum volume of the conduits actively involved in this storm event. This method assumes a single source of recharge and plug flow conditions. A single conduit 18 cm in width, 25 m tall (an average saturated thickness), and 20 km long (approximate north south length of the aquifer) has a volume of about 3,200,000 ft3 (90,000 m3). While a conduit of these dimensions approximates the measured conduit volume, it is unlikely that there is one single conduit running the length of the aquifer. It is more likely that the first stormflow water to arrive at Main Barton Spring is from a nearby source such as Barton Creek or Williamson Creek.

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4.6.3. Stormflow suppresses discharge of matrix ground water Fourteen hours after the onset of rainfall, stormflow water began to arrive at Main Barton Spring (Figure 4 5), but the discharge rate did not increase. Instead, stormflow water progressively became an increasingly larger proportion of spring discharge (up to 56 percent), while pre storm water discharge was suppressed. One explanation for this behavior is that the reservoir of pre storm water had been depleted and could no longer contribute discharge to the spring. This is unlikely, as total aquifer volume is large compared to the volume of stormflow water. Another explanation for suppression of pre storm water discharge is that stormflow water pressurized the karst conduit system. This would have the effect of reducing gradients between the conduits and the aquifer matrix (Figure 4 7) (Dreiss, 1989). The aquifer matrix, being the major source of pre storm water in a karst aquifer (Sharp, 1993), was unable to drain water into the karst conduit system as effectively during these stormflow conditions. In fact, over small spatial scales, matrix to conduit gradients may have even been reversed, allowing stormflow water to enter the diffuse aquifer matrix. The reduction of matrix to conduit gradients may be analogous to bank storage effects seen in surface water hydrograph analyses. Pinder and Jones (1969) hypothesized that rivers with permeable alluvial valleys that normally discharge

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ground water to streams may have their gradients reversed during floods. This effect temporarily inhibits the discharge of ground water, and actually stores some surface water in the river valley alluvium. This bank storage effect appears to have an analogue in karst caves and conduit systems, where intense flooding can temporarily reverse the typical matrix to conduit hydraulic gradient (Palmer, 1991). Traditionally, resource managers have been more concerned with water quantity that water quality. Thus, because both its volume is small and residence time in the aquifer is short, stormflow water has usually not been considered significant by resource managers (Atkinston, 1977). However, from a water quality perspective, the ability of stormflow water to suppress the discharge of pre storm water may greatly increase the potential for anthropogenic contaminants to discharge from karst springs. This is because surface water (stormflow water) is generally more contaminated than the ground water (pre storm water) (Mahler and VanMetre, 2000). After 72 hours, the suppression of pre storm water by stormflow water began to decline at Main Barton Spring. This suggests either that there was no longer stormflow water available to enter the aquifer, or that stormflow water was prevented from entering. As most of the five creeks do not have direct contact with the water table, it seems more likely that the observed recession of creek discharge (Figure 4 3) accounted for the decrease in stormflow water discharge. The findings

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presented here fit the flush dilute recover model for a karst spring proposed by Desmaris and Roczaster (2002), although suppress is a more appropriate word than dilute for this study. The rapid rise and slow recession of Main Barton Spring discharge (Figure 4 3) is consistent with stormflow response in some karst aquifers (Atkinston, 1977), while it is inconsistent with karst aquifers that undergo both sharp discharge rises and recessions (Lakey and Krothe, 1996). This is probably related to (a) watershed size; (b) nature of the rainfall event; and (c) degree of conduit dominance. Halihan and Wicks (1998) suggested that a pipe flow model can account for this full range of behavior when the correct pipe size is chosen. 4.6.4. Alternative hydrograph separation variables Samples from the springs analyzed for both 18O and 2H plot close to the GMWL (Figure 4 4), suggesting that oxygen and hydrogen isotopes were conservative tracers of flow during the period of study. However, it is desirable to find alternative variables for hydrograph separations, as oxygen isotope analysis is time consuming and expensive relative to other geochemical measurements. Because of budget and time limitations, this studys sampling interval for oxygen isotopes (12 to 48 hours) was relatively coarse. Thus, this study may have missed subtle but significant temporal variations in pre storm and stormflow contribution to

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spring discharge. In this section, high resolution real time monitoring parameters are considered as alternatives hydrograph separation variables, under the assumption that oxygen isotopes created a correct hydrograph separation to which comparisons can be made. Turbidity is not an appropriate hydrograph separation variable, as it did not follow the pattern shown by oxygen isotope ratios. Turbidity reached a maximum value just as the first stormflow water reached Main Barton Spring, and then declined somewhat exponentially during the next four days (Figure 4 3). It is not possible to calibrate a two endmember mixing model to fit turbidity to the shape of the 18O hydrograph separation. Dissolved oxygen concentrations do not produce an effective hydrograph separation, insofar as there is not a high degree of correlation between dissolved oxygen concentrations and oxygen isotope values (Figure 4 8). It is not clear what process/processes caused changes in dissolved oxygen concentrations, but it is apparently was not conservative two endmember water mixing. There is a strong linear correlation (r2 = 0.96) between 18O values and specific conductance values (Figure 4 8), thus specific conductance was tested as an effective and inexpensive hydrograph separation variable. For the pre storm endmember, the value measured for Main Barton Spring at the onset of rainfall was used (657 S/cm, October 23, 2004 at 12:00 am). For stormflow water, a value of 480 S/cm was

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chosen, such that the specific conductance hydrograph separation (Figure 4 9) approximated the shape and volume of the 18O hydrograph separation (Figure 4 5). With the aid of 315 additional data points, fine scale temporal changes not captured with oxygen isotopes are observable. For example, the suppression of pre storm water between 14 and 72 hours after the onset of rainfall was apparently not a smooth curve, as suggested by the oxygen isotope hydrograph separation. With the increased resolution of the specific conductance hydrograph separation (Figure 4 9), the effects of a small rainfall event on November 1 can be observed; this rainfall created a response in the spring similar to the larger rainfall on October 23. There is also evidence of a small specific conductance spike on October 28, which is a geochemical response to the lowering of the level of Barton Springs Pool. Main Barton Spring is normally submerged by this pool, and lowering of the pool level leads to geochemical changes in spring discharge (City of Austin, 1997; Mahler, 1997; Mahler and Lynch, 1999) that are not related to stormflow water. During lowered pool levels, specific conductance does not operate correctly as a hydrograph separation variable, as this geochemical change represents a third mixing endmember unaccounted for in this study (B.J. Mahler, U.S. Geological Survey, written comm.., 2005).

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4.6.5. Complex signals in real time data The complex structure of the specific conductance time series signal at Main Barton Spring (Figure 4 3) is probably the result of individual conduits and catchment areas delivering stormflow water to the spring at different rates and by different routes. This behavior commonly is observed in karst springs (e.g., Siegenthaler and Schotterer, 1984; Hess and White, 1988; Liu et al., 2004). Turbidity values at Main Barton Spring indicated the passage of a turbid front of water located at the leading edge of stormflow water as it flowed toward Main Barton Spring (Figure 4 3). One explanation is that conduits and large void spaces may act as settling basins during non stormflow conditions (Vineyard, 1960), and this sediment front might be the result of turbulent, high velocity stormflow re entraining and transporting previously deposited sediment (Mahler and Lynch, 1999; Massei et al., 2003) Historical observations at Main Barton Spring have noted that maximum turbidity values following rainfall events are lower when there has been another recent rainfall (City of Austin, 1997; Mahler and Lynch, 1999), consistent with a settling basin hypothesis. In addition to settling out of recharge water, aquifer sediment may also originate from the aquifer rock itself (autochthonous), although x ray diffraction analyses of sediment discharged from Main Barton Spring do not support this hypothesis (Lynch et al., 2004).

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Dissolved oxygen concentrations show a complex time series signal (Figure 4 3). Coarse visual inspection suggests that dissolved oxygen concentrations are inversely correlated with specific conductance values. However, dissolved oxygen does not strongly correlate with specific conductance, as the correlation between 18O and dissolved oxygen is not as strong as the correlation between 18O and specific conductance (Figure 4 8). This suggests that some other process affects the concentration of dissolved oxygen in Main Barton Spring discharge. This process is not well understood. One hypothesis, left to future studies to test, is that molecular diffusion of oxygen in water allows it to mix between pre storm and stormflow water more freely than the bulk water molecules. Another hypothesis is that atmospheric air present in vadose zone conduits at the onset of rainfall becomes trapped by rapidly recharging stormflow water, and is forcefully dissolved into this water (B.J. Mahler, U.S. Geological Survey, written comm., 2005). 4.7. CONCLUSIONS Storm water that entered the Barton Springs segment of the Edwards aquifer through losing streams traveled rapidly to the four springs of the Barton Springs system. Analysis of a hydrograph separation for Main Barton Spring showed that pre storm water was pushed out of major aquifer conduits by an advancing wave of stormflow recharge from creeks. Stormflow water arrived at the Barton Springs

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system in less than 14 hours, with different arrival times observed at each of the four springs. Because of karst conduit pressurization, discharge of pre storm water from the diffuse matrix of the aquifer was suppressed, and a large proportion (up to 56 percent) of Main Barton Spring discharge consisted of recently recharged stormflow water whose aquifer residence time was only several hours. On the basis of the Main Barton Spring hydrograph separation, these findings generally fit the flush dilute recover model for a karst spring proposed by Desmaris and Roczaster (2002). However, instead of dilute, the word suppress is more fitting. This suppression of longer residence time ground water may be of interest to resource managers, as stormflow conditions reduce the already limited mitigation abilities that karst aquifers have for water treatment. Oxygen isotopes worked well for hydrograph separation purposes, but were sampled too infrequently to capture hour scale geochemical changes. Specific conductance was well correlated with 18O values, and when used for hydrograph separation produced results very similar to those of 18O, but with higher temporal resolution. Specific conductance is an effective, low cost, high resolution measurement relative to oxygen isotopes, although it is not an appropriate hydrograph separation variable when the water level in Barton Springs Pool is actively changing. Presently, it is not possible to construct accurate hydrograph

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separations for the other three springs (Eliza, Old Mill, Upper Barton Springs), as their discharge rates are not measured. Turbidity and dissolved oxygen concentrations in Main Barton Spring discharge showed complex time series signals that provided different information on aquifer processes. Turbidity values recorded the passage of a wave of turbid water at the leading edge of the stormflow water as it moved through the karst conduit system. This may be the result of remobilization of settled out sediment, similar to the behavior of a settling basin. The time series signal for dissolved oxygen generally tracked that of specific conductance, but did not change simultaneously with specific conductance. This suggests that some other process affected the arrival of dissolved oxygen to Main Barton Spring. It may be possible to infer more about aquifer functioning by critical evaluation of the dissolved oxygen time series signal. High resolution monitoring of karst springs revealed substantial information about aquifer processes during stormflow conditions. The findings of this study may be of use to resource managers and future scientific investigations. Strontium isotope ratios could be analyzed to further constrain the sources of stormflow water; for example, strontium isotope ratios should become more radiogenic during stormflow conditions, reflecting the input of surface water that has reacted with soil zones. Major dissolved ion concentrations might also allow discernment of various

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water sources. Finally, concentrations of anthropogenic contaminants (pesticides, volatile organic compounds, etc.) might verify the aquifers sensitivity to contamination predicted by this study. 4.8. ACKNOWLEDGEMENTS Funding for this studys isotopic analyses was provided by the Univeristy of Texas Jackson School of Geosciences. Funding for USGS real time monitoring was provided by the Texas Commission on Environmental Quality. Thanks are extended to B. Mahler, L. Mack, M. Gary, and L. Stern for their help in analyzing and interpreting these data. Reviews from B. Wolaver and B. Cey improved the quality of this paper.

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Figure 4 1 The Barton Springs segment of the Edwards aquifer. Five creeks cross approximately from west to east, and supply recharge to the aquifer through their streambeds. Water in the aquifer flows generally to the east northeast, toward the Barton Springs system, which is the main discharge point for theaquifer. Bear Creek site Onion Creek site N Recharge Zone Confined Zone Downtown Austin Town of Buda Creek Real time monitoring equipment General ground water flow direction Barton CreekUpper Barton Spring Main Barton Spring Old Mill Spring Eliza Spring P o o lTown Lake300 m 0 5 km 0 EXPLANATION Surface water sampling site

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0.01 0.1 1 10 100 1000 10000Creek discharge rate (ft3/s) O c t 2 2 O c t 2 4 O c t 2 6 O c t 2 8 O c t 3 0 N o v 1 N o v 3 N o v 5 Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion CreekFigure 4 2 Discharge rates measured for Barton, Williamson, Slaughter, Bear, and Onion creeks in response to the October 23, 2004 rainfall event.Discharge data were collected by the USGS. Site identifiers for Barton, Williamson, Slaughter, Bear, and Onion creeks are 08155240, 08158920, 08158840, 08158810, and08158700, respectively.Duration of rainfall

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Figure 4 3 Multiple physical, chemical, and isotopic values for Main Barton Spring in October and November, 2004. The initial value for 18O (shown as an open square) is from August 25, 2004, and is assumed to represent theinitial pre storm isotopic composition of the aquifer. The timing of the beginning of the rainfall event is indicated by the vertical dashed line. 680 640 600 560 O c t 2 4 O c t 2 6 O c t 2 8 O c t 3 0 N o v 1 N o v 3 N o v 55.8 6.2 6.6 7.0 60 70 80 3.8 4.2 4.6 5.0 16 8 018O (SMOW) Discharge (ft3/s) Spec. Cond. (S/cm) Turbidity (NTU) Dissolved oxygen (mg/L) Both creek composite samples 18O Barton Springs system discharge Specific conductance Turbidity Dissolved oxygen discrete samples

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Figure 4 4 Samples analyzed for both 18O and 2H plotted with the Global meteoric water line of Craig (1961). Samples plotted close to the line, suggesting that water behaved in a conservative manner during the study period. There is no evidence for evaporation or water rock interaction. Upper Barton Spring Main Barton SpringG l o b a l m e t e o r i c w a t e r l i n e 6 5 4 3 2 10 40 30 20 10 02H (SMOW)EXPLANATION analytical uncertainty 18O (SMOW)

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Figure 4 5 Hydrograph separation for Main Barton Spring using measured oxygen isotope values. Total volumes of storm and pre storm water during the period shown (i.e., the areas under the curves) are indicated. Turbidity measurements are shown for reference at the bottom of the graph, and indicate that turbidity values were highest during the first 24 hours after rainfall. Pre storm water (68%) Stormflow water (32%) 20 40 60 80 0Discharge (ft3/s) and turbidity (NTU)t u r b i d i t yO c t 2 3 O c t 2 5 O c t 2 7 O c t 2 9 O c t 3 1 N o v 2 N o v 4

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Figure 4 6 Oxygen isotope values for the Barton Springs system from October to November, 2004. Two flow weighted composite creek samples with identical isotopic compositions are shown as a dotted line. During the study period, the isotopic composition of spring discharge evolved toward that of the creek samples before returning to a pre storm value. One sample from Upper Barton Spring measured a more depleted 18O value than the composite sample measured. 5.2 4.8 4.4 4.0 11/618O (SMOW) composite creek samplesO c t 2 3 O c t 2 5 O c t 2 7 O c t 2 9 O c t 3 1 N o v 2 N o v 4 Upper Barton Spring Main Barton Spring Eliza Spring Old Mill Spring EXPLANATION

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Figure 4 7 Schematic diagram showing the phenomenon of karst conduit pressurization from stormwater. (a) Under non stormflow conditions, water from the diffuse (or matrix) areas of the aquifer drains into highly permeable conduits and travels to the spring outlet (shown schematically as a watertap). This draining is relatively slow because of the low hydraulic conductivity of the matrix, shown schematically by beds of sand in the two basins, which representreservoirs of matrix water; (b) During stormflow conditions, stormflow water (shown in red) enters conduits directly from high elevation streambeds and travels rapidly to the spring outlet. During this time, pressure (i.e. hydraulic head)in the conduit increases, as indicated by elevated water levels in the two monitoring wells. This decreases the gradient from the matrix into the conduit. In some areas, stormflow water goes into storage in the matrix, to be later discharged when non stormflow conditions return.

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Monitoring wells drilled into conduit Matrix reservoir Matrix reservoir Outlet No recharge entering aquifer Stormflow water enters rapidly Gradient reversed, still low head in matrix High head in wellsC o n d u i t i s p r e s s u r i z e d Increased discharge rate(b) (a)L o w e r h e a d i n c o n d u i t a l l o w s m a t r i x r e s e r v o i r s t o d r a i nSand in reservoir bottom slows Draining rate Mixture of matrix and stormflow

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Figure 4 8 Comparison of Main Barton Spring 18O values with real time water quality parameters collected concurrently by monitoring equipment in Main Barton Spring. (a) Correlation with turbidity is very poor; (b) Correlation with dissolved oxygen is poor; and (c) Correlation is very strong with specificconductance. r2= 0.10 4.6 4.4 4.2 4.0 3.8 0481216Turbidity (NTU)18O ( SMOW) r2= 0.02 4.6 4.4 4.2 4.0 3.8 5.86.06.26.46.66.8Dissolved oxygen (mg/L) r2= 0.96 4.6 4.4 4.2 4.0 3.8 550580610640670 Specific conductance ( S/cm)(a) (b) (c) 18O ( SMOW) 18O ( SMOW)

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Figure 4 9 Hydrograph separation for Main Barton Spring showing dischargeof stormflow and pre storm water. This separation uses a pre storm specific conductance value of 657 S/cm, the value measured at Main Barton Spring at the onset of rainfall. Specific conductance for the stormflow waterendmember was calculated by calibrating this separation to the oxygen isotope hydrograph separation, such that the total volumes of water (i.e., areas under the curves) matched. 0 40Spring discharge (ft3/s)Pre storm water (68%) Stormflow water (32%) 80O c t 2 3 O c t 2 5 O c t 2 7 O c t 2 9 O c t 3 1 N o v 2 N o v 420 60

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Table 4 1 Summary of stormflow water arrival times for the October, 2004 rainfall event in the Barton Springs segment.Spring name First arrival of stormflow water following rainfallArrival evidence 2Maximum stormflow water discharge following rainfall Main Barton Spring about 14 hours 1Changes in 18O, specific conductance, dissolved oxygen, and turbidity. about 60 hours Eliza Spring over 14 hours, probably no more than 26 hours Changes in 18O about 60 hours Old Mill Springabout 14 hours Changes in 18O about 80 hours Upper Barton Springless than 14 hours Changes in 18O about 48 hours 1 Arrival times of stormflow water also documented in City of Austin (1997), Andrews et al. (1984). and Mahler and Lynch (1999). Minimum historic observed value is 5 hours, when aquifer discharge rates are at very high levels. 2 Unpublished data shows several other lines of evidence for arrival of stormflow water, including changing dissolved major ion concnetrations, and real time parameters measured at springs other than Main Barton Spring.

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5. Summary This researchs goal was to advance the study of karst (limestone) aquifers by analyzing time series water quality data in the Barton Springs segment of the Edwards aquifer. The water quality in a karst aquifer changes over time, making the application of traditional hydrogeologic principles difficult or impossible. Basic issues such as direction of ground water flow, sources of spring discharge, and transport of contaminants often remain poorly understood in even the most well studied karst aquifers. As such, scientists must use innovative methods for understanding these systems. This aquifer is of interest because of its central role in creating the popular Barton Springs Pool, its use as a drinking water supply, and its being the only habitat for the endangered Barton Springs salamander ( Eurycea sosorum ). Water samples collected over 26 years by a long term USGS monitoring program were analyzed to determine the relation between ground water geochemistry and rates of aquifer recharge and discharge. On the basis of a non parametric statistical test, 58 percent of sampled wells showed a correlation between specific conductance and streamflow rates or spring discharge. These correlations resulted from (a) dilution of ground water by recently recharged surface water, (b) variable residence times of ground water, and (c) mixing between aquifer freshwater and nearby saline waters. These inferences were made on the basis of

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changes in specific conductance, Mg/Ca, SO4/Cl, and Mg/Na ratios. Four wells (FMW, KCH, SLR, SVE) appeared to intersect major aquifer flowpaths, and five wells (BDW, HWD, MCH, SVN, SVW) intersected minor aquifer flowpaths. For the remaining 17 wells that did not have a negative correlation between specific conductance and streamflow or spring discharge, no conclusions regarding flowpath intersection were drawn. Some wells seemed to receive a portion of their water from the saline zone to the east, which may extend as a saltwater lens under part of the freshwater portion of the aquifer. Other wells may be receiving some of their water from the underlying Trinity aquifer, especially when aquifer flow conditions are high. Given the arbitrary nature of the 26 year USGS sampling program for the Barton Springs segment of the Edwards aquifer, it seems noteworthy that the approach taken by this study had value. Water quality data collected over 2 years from the four Barton Springs (Main, Eliza, Old Mill, and Upper Barton Springs) were used to understand water flow in the aquifer. Oxygen and hydrogen isotope values indicated that ground water is well mixed over long periods of time. Spring water showed evidence of variable residence time and incongruent dissolution, as indicated by increases in Sr/Ca during low spring discharge conditions. Sr/Ca ratios were an effective measure of water residence times for Main, Eliza, and Old Mill Springs. In addition to the limestone aquifer rock, 87Sr/86Sr values indicated that urban infrastructure, soil zones,

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and the saline zone are potential sources of dissolved strontium. Main and Eliza Springs apparently received ground water from the same aquifer flowpath(s), as their major ion and isotope compositions were indistinguishable at all times. Upper Barton Spring received some of its water from an isolated subbasin in the aquifer, as indicated by the more radiogenic 87Sr/86Sr values measured in this subbasin. There were dissolved ions not associated with carbonate minerals (i.e., Na+, Cl, SO4 2 and NO3 ) present in Barton Springs segment ground water. Ratios of Na/Cl less than one suggest an anthropogenic source of Cl or ion exchange with clays. Increases in Na+, Cl, and SO4 2 at Main, Eliza, and Old Mill Springs are associated with low discharge rates, and probably represent influx of ground water from the saline zone. Between 4 and 9 percent of the discharge from spring OSP appeared to originate from the saline zone, as determined by a quantitative mixing model. For 2 weeks after a large rainfall event, water samples were collected to understand how storm related recharge flows to Main Barton Spring. Storm water that entered the Barton Springs segment of the Edwards aquifer through losing streams traveled rapidly to the Barton Springs system. A hydrograph separation using oxygen isotopes showed an immediate increase in spring discharge following rainfall but a 14 hour delay before storm water first reached the spring. This suggested that an advancing front of storm water expelled pre storm water from the karst conduits. After arrival of stormflow water at Main Barton Springs, the

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discharge of pre storm water from the diffuse matrix of the aquifer was suppressed, and a majority (up to 56 percent) of spring discharge consisted of recently recharged stormflow water with an aquifer residence time of only hours. This can be explained by the process of karst conduit pressurization. Oxygen isotopes worked well for hydrograph separation purposes, but were sampled too infrequently to capture hour scale geochemical changes. Specific conductance measurements were strongly correlated to 18O values, and when used for hydrograph separation produced results similar to those of 18O, but with higher temporal resolution. Turbidity and dissolved oxygen at Main Barton Spring showed complex time series signals that provided different information on aquifer processes. Turbidity values recorded the passage of a wave of turbid water at the leading edge of the stormflow water, which may be the result of remobilization of previously accumulated sediment. The time series signal for dissolved oxygen generally tracked that of specific conductance, but did not change simultaneously with specific conductance. This suggests that some other process affected the arrival of dissolved oxygen to the spring. The results of this research show that karst water quality changes over long, medium, and short time scales. These changes can indicate the potential for contamination, can enable resource managers to make better decisions, and can help scientists better understand the behavior of karst aquifers, the veritable renegades of hydrogeology.

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APPENDIX A. Analytical results for Chapter 2 This appendix contains most of the analytical results and statistical test results discussed in Chapter 2, including specific conductance data and corresponding streamflow and aquifer flow condition data (Table A 1), results of the statistical test used in the study (Table A 2), and analytical result from dissolved major ion analyses (Table A 3). Omitted from this appendix are the approximately 9,000 mean daily discharge values for each of the five creeks and the Barton Springs system. Inclusion of these raw data values would add considerably to the bulk of this thesis. For these data, the reader is directed to Garner et al. (in press), which is provided free of charge in digital format by the USGS.

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Table A 1. Specific conductance measurements from wells in the Barton Springs segment, and associated maximum 10 day discharge rates for creeks and the Barton Springs system, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) BC K 6 / 28 / 1978630310.70.20.1 BC K 7 / 17 / 1979630100170.92.12.516 BC K 8 / 28 / 1980659 4 10.00.00.00.11.1 BC K 8 / 11 / 198153899110.00.52.219 BC K 8 / 10 / 1982618 4 91.10.00.10.41.2 BC K 7 / 19 / 1983649847.71.42290 BD W 6 / 14 / 1990593 4 9 4 10.50.61.830 BD W 8 / 22 / 1990603260.60.50.00.02.2 BD W 3 / 19 / 199156585877.66.41168 BD W 5 / 7 / 199158499105108.020151 BD W 8 / 13 / 1991600752.50.00.20.46.5 BD W 4/ 30 / 1992594115943.5 4 .78.581 BD W 1 / 22 / 199359010026216219.0231 BD W 1 / 25 / 199358910026216219.0231 BD W 5 / 8 / 19935841081231.2161073 BD W 5 / 11 / 19935931081231.2161073 BD W 5 / 15 / 19935891081230.0161073 BD W 8 / 18 / 1993594860.50.00.00.10.5 BD W 4/ 15 / 1994591 4 76.70.00.00.38.4 BD W 6 / 14 / 19955901043471210832294 BD W 4/ 25 / 1996582250.70.00.00.10.9 BD W 7 / 8 / 19975851133220.92126510 BD W 4/ 21 / 199858798790.08.97.596 BD W 6 / 11 / 199959573210.01.41.4 4 .9 BD W 6 / 2 / 2000591222.50.00.00.11.2 BD W 6 / 5 / 2001595103 4 30.01.73.371 BD W 6 / 5 / 2002606887.20.00.10.73.8 BD W 5 / 20 / 2003577102120.00.31.312 BPS7 / 12 / 1978580250.00.0 BPS7 / 24 / 1978572210.31.1 BPS8 / 24 / 1979588949.61.81.8 4 .110 BPS8 / 1 / 1980583540.40.00.00.31.3 BPS8 / 29 / 1980578 4 00.00.00.00.11.0 BPS7 / 30 / 1981583103291.01.4 4 .250 BPS8 / 12 / 198156898110.00.42.117 BPS7 / 19 / 198258660 4 .10.00.51.410 BPS7 / 22 / 1983539847.71.42290 BPS6 / 27 / 1984584270.00.00.0 4 .6 BPS9 / 13 / 1984590260.00.00.00.2 Date Site ID Maximum 10 day discharge rates Specific conduc tance

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Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) BPS2 / 20 / 1985586726.31.68.393 BPS6 / 19 / 1985580702.4 4 .05.6145 BPS8 / 9 / 1985598640.00.20.915 BPS1 / 14 / 1986579781.52.65.254 BPS5 / 3 / 198650062593.26.438 BPS6 / 24 / 198659184132016216 BPS6 / 25 / 198659284132016216 BPS9 / 3 / 1986589610.00.00.45.8 BPS2 / 11 / 1987588801.33.28.976 BPS5 / 20 / 1987595100122.62.838 BPS6 / 1 / 198759111014993 4 1392 BPS8 / 19 / 19876051100.00.01.633 BPS2 / 29 / 1988589610.10.60.98.5 BPS5 / 3 / 1988575501.40.11.17.8 BPS7 / 19 / 1988572 4 52.00.00.87.5 BPS8 / 17 / 1988597 4 51.20.00.03.2 BPS2 / 27 / 1989596271.00.30.00.12.4 BPS5 / 3 / 198958333150.20.03.45.4 BPS7 / 17 / 1989563558.92.00.22.912 BPS8 / 29 / 1989581330.40.00.00.02.7 BPS1 / 29 / 1990585180.60.00.00.00.4 BPS6 / 5 / 199058750 4 17.11.02.580 BPS8 / 14 / 1990566311.60.00.10.02.2 BPS3 / 22 / 19915868587.07.66.41168 BPS5 / 15 / 1991569992616838 4 8218 BPS8 / 13 / 1991591752.50.00.20.46.5 BPS 4/ 30 / 1992589115943.5 4 .78.581 BPS8 / 28 / 1992584125 4 .20.00.00.59.5 BPS5 / 11 / 19935841081231.2161073 BPS8 / 19 / 1993539860.40.00.00.00.3 BPS8 / 20 / 1993579860.40.00.00.00.3 BPS 4/ 14 / 1994578 4 76.90.00.00.39.5 BPS6 / 14 / 19955851043471210832294 BPS5 / 9 / 1996576250.60.00.00.00.5 BPS7 / 8 / 19975751133220.92126510 BPS 4/ 22 / 199856598760.08.47.293 BPS6 / 11 / 199959173210.01.41.4 4 .9 BPS6 / 2 / 2000592222.50.00.00.11.2 BPS6 / 12 / 2001593100210.01.02.2 4 1 BPS6 / 6 / 2002596887.20.00.10.73.8 BPS5 / 22 / 2003591102110.00.31.312 Site IDDate Specific conduc tance Maximum 10 day discharge rates

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Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) CN E 7 / 24 / 19781040210.31.1 CN E 7 / 11 / 19791060102275.2 4 .72.618 CN E 9 / 4 / 19801030380.00.00.00.00.5 CN E 8 / 12 / 198199698110.00.42.117 CN E 8 / 11 / 19821020 4 91.10.00.00.31.5 CN E 7 / 21 / 19831060847.71.42290 FM W 8 / 11 / 198153199110.00.52.219 FM W 8 / 4 / 1982566511.10.00.10.52.0 FM W 7 / 19 / 1983568847.71.42290 FM W 6 / 19 / 1985547702.4 4 .05.6145 FM W 8 / 8 / 1985567640.00.21.015 FM W 1 / 15 / 1986545781.52.65.254 FM W 5 / 3 / 198656862593.26.438 FM W 6 / 25 / 198656484132016216 FM W 9 / 3 / 1986568610.00.00.45.8 FM W 2 / 9 / 1987552831.33.49.381 FM W 5 / 21 / 1987553100122.62.838 FM W 6 / 1 / 198753511014993 4 1392 FM W 8 / 18 / 19875641100.00.01.634 FM W 2 / 25 / 1988573630.10.61.28.6 FM W 5 / 3 / 1988574501.40.11.17.8 FM W 2 / 23 / 1989560280.90.30.00.11.4 FM W 5 / 1 / 198960036190.30.03.77.3 FM W 7 / 17 / 1989585558.92.00.22.912 FM W 8 / 21 / 1989587360.60.00.00.03.5 FM W 3 / 5 / 1991571871068.5141582 FM W 5 / 7 / 199156199105108.020151 FM W 8 / 19 / 199156171 4 67107 4 21158 FM W 4/ 28 / 1992545115115 4 .76.21198 FM W 1 / 21 / 199353610026216219.0231 FM W 1 / 24 / 199353710026216219.0231 FM W 1 / 28 / 199353710026216219.0231 FM W 5 / 8 / 19935351081231.2161073 FM W 5 / 11 / 19935341081231.2161073 FM W 5 / 15 / 19935281081230.0161073 FM W 8 / 16 / 1993537870.50.00.00.10.5 FM W 4/ 8 / 1994563 4 76.90.00.00.39.5 Site IDDate Specific conduc tance Maximum 10 day discharge rates

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Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) F OW 6 / 28 / 1978620310.70.20.1 F OW 7 / 10 / 1979620102275.2 4 .72.618 F OW 8 / 28 / 1980686 4 10.00.00.00.11.1 F OW 8 / 11 / 198159599110.00.52.219 F OW 8 / 10 / 1982595 4 91.10.00.10.41.2 F OW 7 / 19 / 1983597847.71.42290 F OW 8 / 8 / 1985641640.00.21.015 F OW 1 / 14 / 1986624781.52.65.254 F OW 5 / 1 / 198663562593.26.426 F OW 6 / 25 / 198674884132016216 F OW 9 / 3 / 1986610610.00.00.45.8 F OW 2 / 10 / 1987625831.33.49.381 F OW 5 / 20 / 1987647100122.62.838 F OW 6 / 1 / 198763011014993 4 1392 F OW 8 / 26 / 19876871070.00.01.121 F OW 5 / 6 / 1988670501.40.11.17.8 F OW 7 / 18 / 1988643 4 52.00.00.87.5 F OW 8 / 17 / 1988705 4 51.20.00.03.2 F OW 2 / 27 / 1989660271.00.30.00.12.4 F OW 5 / 3 / 198964733150.20.03.45.4 F OW 7 / 26 / 1989602 4 82.50.30.01.65.5 F OW 2 / 9 / 199065822 4 .38.60.00.11.5 F OW 6 / 19 / 1990645 4 77.00.00.40.516 F OW 8 / 14 / 199164875 4 .1125.91.76.5 F OW 5 / 1 / 1992771115853.4 4 .28.175 F OW 1 / 21 / 199386310026216219.0231 F OW 1 / 24 / 199389510026216219.0231 F OW 1 / 28 / 199378410026216219.0231 F OW 5 / 7 / 19937751081231.2161073 F OW 5 / 14 / 19937911081231.2161073 F OW 5 / 27 / 1993758108 4 20.05.05.232 F OW 8 / 17 / 1993697870.50.00.00.10.5 F OW 4/ 18 / 1994645 4 6 4 .90.00.00.38.2 F OW 6 / 19 / 19957601022811210832172 F OW 5 / 7 / 1996635260.70.00.00.00.5 F OW 7 / 9 / 19976161132730.01723 4 55 F OW 4/ 23 / 199865298730.07.96.890 F OW 6 / 11 / 199965473210.01.41.4 4 .9 F OW 6 / 1 / 2000712222.70.00.00.11.4 F OW 6 / 19 / 200174297130.00.81.729 F OW 6 / 5 / 2002660887.20.00.10.73.8 F OW 5 / 21 / 2003747102120.00.31.312 Site IDDate Specific conduc tance Maximum 10 day discharge rates

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Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) GH W 7 / 12 / 1978660250.00.0 GH W 7 / 9 / 1979670103275.2 4 .72.618 GH W 8 / 29 / 1980666 4 00.00.00.00.11.0 GH W 8 / 12 / 198165098110.00.42.117 GH W 8 / 16 / 1982666 4 61.10.00.00.21.9 GH W 7 / 21 / 1983667847.71.42290 GH W 6 / 19 / 1985659702.4 4 .05.6145 GH W 8 / 9 / 1985648640.00.20.915 GH W 1 / 13 / 1986644781.53.05.761 GH W 5 / 1 / 198667762593.26.426 GH W 6 / 25 / 198667684132016216 GH W 9 / 2 / 1986671620.00.00.45.8 GH W 2 / 11 / 1987672801.33.28.976 GH W 5 / 20 / 1987685100122.62.838 GH W 5 / 31 / 198765610514993 4 1392 GH W 8 / 19 / 19876831100.00.01.633 GH W 2 / 24 / 1988655630.10.61.28.6 GH W 5 / 9 / 1988670500.20.11.17.8 GH W 7 / 14 / 1988670 4 72.00.00.87.5 GH W 8 / 10 / 1988635 4 30.00.00.011 GH W 2 / 23 / 1989640280.90.30.00.11.4 GH W 5 / 3 / 198966833150.20.03.45.4 GH W 7 / 26 / 1989638 4 82.50.30.01.65.5 GH W 8 / 30 / 1989640320.40.00.00.02.7 HND7 / 5 / 1978560280.00.0 HND7 / 11 / 1979580102275.2 4 .72.618 HND9 / 8 / 1980559380.18.80.00.229 HND8 / 11 / 198158999110.00.52.219 HND8 / 10 / 1982575 4 91.10.00.10.41.2 HND7 / 20 / 1983 4 75847.71.42290 HND6 / 18 / 1985516703.45.56.1186 HND8 / 8 / 1985580640.00.21.015 HND1 / 13 / 1986575781.53.05.761 HND5 / 2 / 198655962593.26.438 HND6 / 23 / 198656384132016216 HND9 / 3 / 1986600610.00.00.45.8 HND2 / 11 / 1987607801.33.28.976 HND5 / 20 / 1987633100122.62.838 HND6 / 1 / 198756411014993 4 1392 Site IDDate Specific conduc tance Maximum 10 day discharge rates

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Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) HWD6 / 28 / 1978560310.70.20.1 HWD7 / 9 / 1979560103275.2 4 .72.618 HWD8 / 28 / 1980575 4 10.00.00.00.11.1 HWD8 / 18 / 198155196160.30.3 4 .314 HWD8 / 4 / 1982563511.10.00.10.52.0 HWD7 / 22 / 1983553847.71.42290 I SD7 / 12 / 1978 4 86250.00.0 I SD7 / 11 / 1979 4 80102275.2 4 .72.618 I SD9 / 4 / 1980 4 87380.00.00.00.00.5 I SD8 / 12 / 1981 4 8298110.00.42.117 I SD8 / 11 / 1982 4 95 4 91.10.00.00.31.5 I SD7 / 22 / 1983 4 89847.71.42290 J BS7 / 17 / 1978550240.00.00.0 J BS7 / 16 / 1979580100270.92.22.618 J BS8 / 27 / 1980587 4 10.10.00.00.11.1 J BS8 / 4 / 1981570102211.01.4 4 .238 J BS 4/ 22 / 1982570 4 620307.93.28.4 J BS 4/ 23 / 19825765031307.93.214 J BS 4/ 26 / 19825765136309.43.223 J BS8 / 9 / 1982592501.10.00.10.41.1 J BS5 / 21 / 198358977392327265 J BS5 / 22 / 198358879392327265 J BS5 / 23 / 198358682392327265 J BS5 / 25 / 198359084392327265 J BS7 / 18 / 1983586847.71.42290 KCH7 / 5 / 1978640280.00.0 KCH7 / 10 / 1979620102275.2 4 .72.618 KCH8 / 28 / 1980660 4 10.00.00.00.11.1 KCH8 / 11 / 198162199110.00.52.219 KCH8 / 10 / 1982652 4 91.10.00.10.41.2 KCH7 / 19 / 1983670847.71.42290 KCH6 / 24 / 19856127233288.0300 KCH8 / 7 / 1985635650.00.21.016 KCH5 / 1 / 198667662593.26.426 KCH6 / 24 / 198665184132016216 KCH8 / 29 / 1986674640.00.00.45.8 KCH2 / 9 / 1987641831.33.49.381 KCH5 / 18 / 19876601001.00.52.338 KCH6 / 1 / 198764411014993 4 1392 KCH8 / 19 / 19876751100.00.01.633 KCH3 / 9 / 1988655580.20.61.17.8 KCH5 / 10 / 1988703500.00.10.7 4 .7 Site IDDate Specific conduc tance Maximum 10 day discharge rates

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Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) KCH7 / 11 / 1988672 4 71.00.00.12.2 KCH8 / 11 / 1988691 4 31.10.00.011 KCH2 / 27 / 1989690271.00.30.00.12.4 KCH5 / 2 / 198969335160.30.03.55.6 KCH7 / 21 / 1989676525.82.00.12.17.7 KCH8 / 29 / 1989668330.40.00.00.02.7 KCH2 / 7 / 199062222 4 .38.60.00.11.5 KCH6 / 5 / 199066550 4 17.11.02.580 KCH8 / 15 / 1990657301.20.00.00.02.2 KCH3 / 11 / 199164287956.7111475 KCH5 / 6 / 199163699105108.020151 KCH8 / 13 / 1991650752.50.00.20.46.5 KCH 4/ 29 / 1992623115104 4 .05.29.890 KCH1 / 20 / 19936529826216219.0231 KCH1 / 23 / 199365010026216219.0231 KCH1 / 26 / 199365210026216219.0231 KCH5 / 6 / 19936411081231.2161073 KCH5 / 9 / 19936391081231.2161073 KCH5 / 12 / 19936411081231.2161073 KCH5 / 27 / 1993644108 4 20.05.05.232 KCH8 / 18 / 1993664860.50.00.00.10.5 KCH 4/ 12 / 1994652 4 76.90.00.00.39.5 KCH10 / 10 / 199465239 4 7673993330 KCH10 / 10 / 199466039 4 7673993330 KCH10 / 10 / 199465139 4 7673993330 KCH10 / 11 / 199465739 4 7673993330 KCH10 / 11 / 199465439 4 7673993330 KCH10 / 11 / 199465239 4 7673993330 KCH10 / 12 / 199465339 4 7673993330 KCH10 / 12 / 199465339 4 7673993330 KCH10 / 12 / 199465339 4 7673993330 KCH10 / 13 / 199465539 4 7673993330 KCH10 / 13 / 199465539 4 7673993330 KCH10 / 14 / 199465739 4 7673993330 KCH10 / 14 / 199465739 4 7673993330 KCH10 / 15 / 199465839 4 7673993330 KCH10 / 15 / 199465839 4 7673993330 KCH10 / 16 / 199466039 4 7673993330 KCH6 / 19 / 19956411022811210832172 KCH5 / 6 / 1996648260.70.00.00.00.5 KCH7 / 8 / 19975681133220.92126510 KCH 4/ 21 / 199862898790.08.97.596 KCH6 / 9 / 199968376350.01.91.65.3 Site IDDate Specific conduc tance Maximum 10 day discharge rates

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Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) LW K 8 / 8 / 1978 4 80247.6143.5 LW K 7 / 11 / 1979 4 99102275.2 4 .72.618 LW K 8 / 29 / 1980 4 96 4 00.00.00.00.11.0 LW K 8 / 18 / 1981 4 9996160.30.3 4 .314 LW K 8 / 17 / 1982 4 93 4 61.10.00.00.21.9 LW K 7 / 21 / 1983 4 99847.71.42290 M CH7 / 5 / 1978540280.00.0 M CH7 / 5 / 1979540105130.82.914 M CH8 / 28 / 1980570 4 10.00.00.00.11.1 M CH8 / 11 / 198153799110.00.52.219 M CH8 / 11 / 1982528 4 91.10.00.00.31.5 M CH7 / 20 / 1983 4 76847.71.42290 M CH6 / 19 / 1985519702.4 4 .05.6145 M CH8 / 9 / 1985540640.00.20.915 M CH1 / 13 / 1986537781.53.05.761 M CH5 / 1 / 198652162593.26.426 M CH6 / 24 / 198655584132016216 M CH9 / 2 / 1986550620.00.00.45.8 M CH2 / 10 / 1987554831.33.49.381 M CH5 / 18 / 19875531001.00.52.338 M CH5 / 30 / 19875129814993 4 1208 M CH8 / 17 / 19875601100.00.01.634 M CH2 / 22 / 1988519640.20.61.28.6 M CH5 / 3 / 1988536501.40.11.17.8 M CH7 / 11 / 1988557 4 71.00.00.12.2 M CH8 / 10 / 1988552 4 30.00.00.011 M CH2 / 21 / 1989584280.90.20.00.12.4 M CH5 / 2 / 198954035160.30.03.55.6 M CH7 / 24 / 1989538 4 93.70.00.11.75.0 M CH8 / 29 / 1989547330.40.00.00.02.7 M CH1 / 31 / 1990587170.70.00.00.00.4 M CH6 / 12 / 1990 4 85 4 9 4 13.80.72.580 M CH8 / 21 / 1990542270.90.50.00.02.2 M CH3 / 13 / 199151887746.08.71265 M CH5 / 15 / 1991531992616838 4 8218 M CH8 / 13 / 1991554752.50.00.20.46.5 M CH 4/ 30 / 1992564115943.5 4 .78.581 M CH1 / 22 / 199350410026216219.0231 M CH1 / 25 / 199350310026216219.0231 M CH5 / 8 / 19935211081231.2161073 M CH5 / 11 / 19935211081231.2161073 M CH5 / 15 / 19935251081230.0161073 Site IDDate Specific conduc tance Maximum 10 day discharge rates

PAGE 258

Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) M CH8 / 18 / 1993550860.50.00.00.10.5 M CH 4/ 15 / 1994506 4 76.70.00.00.38.4 M CH6 / 14 / 19955501043471210832294 M CH5 / 7 / 1996555260.70.00.00.00.5 M CH7 / 8 / 19975551133220.92126510 M CH 4/ 22 / 199853498760.08.47.293 M CH6 / 6 / 199954578760.73.42.47.8 M CH6 / 29 / 200053864 4 90.0235.45.2 M CH6 / 20 / 200155496120.00.81.626 M CH6 / 4 / 2002558887.20.00.10.73.8 M CH5 / 20 / 2003565102120.00.31.312 PLS2 / 26 / 1988568620.10.61.28.6 PLS5 / 4 / 1988574501.40.11.17.8 PLS7 / 14 / 1988551 4 72.00.00.87.5 PLS8 / 11 / 1988564 4 31.10.00.011 PLS2 / 28 / 1989548271.00.30.00.12.4 PLS5 / 2 / 198958235160.30.03.55.6 PLS7 / 25 / 1989572 4 93.10.00.11.65.5 PLS8 / 30 / 1989542320.40.00.00.02.7 PLS2 / 7 / 199055022 4 .38.60.00.11.5 PLS6 / 8 / 1990559 4 9 4 13.80.82.580 PLS8 / 15 / 1990543301.20.00.00.02.2 PLS3 / 18 / 199153385877.66.41168 PLS5 / 15 / 1991545992616838 4 8218 PLS8 / 13 / 1991558752.50.00.20.46.5 PLS5 / 1 / 1992543115853.4 4 .28.175 PLS1 / 21 / 199356010026216219.0231 PLS1 / 24 / 199355910026216219.0231 PLS1 / 28 / 199355910026216219.0231 PLS5 / 14 / 19935551081231.2161073 PLS5 / 28 / 1993559108 4 20.05.05.232 PLS8 / 17 / 1993560870.50.00.00.10.5 PLS 4/ 12 / 1994546 4 76.90.00.00.39.5 PLS6 / 19 / 19955611022811210832172 PLS 4/ 25 / 1996544250.70.00.00.10.9 PLS7 / 8 / 19975501133220.92126510 PLS 4/ 21 / 199852898790.08.97.596 PLS6 / 11 / 199956473210.01.41.4 4 .9 PLS6 / 1 / 2000573222.70.00.00.11.4 PLS6 / 8 / 2001590102260.01.22.755 PLS5 / 23 / 2002570921.90.00.10.4 4 .2 PLS5 / 21 / 2003576102120.00.31.312 Site IDDate Specific conduc tance Maximum 10 day discharge rates

PAGE 259

Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) R A B5 / 6 / 19935961081231.2161073 R A B5 / 9 / 19935681081231.2161073 R A B5 / 12 / 19935781081231.2161073 R A B5 / 27 / 1993569108 4 20.05.05.232 R A B8 / 17 / 1993570870.50.00.00.10.5 R A B 4/ 15 / 1994522 4 76.70.00.00.38.4 R A B6 / 27 / 199550798990.0181296 R A B5 / 6 / 1996504260.70.00.00.00.5 R A B7 / 9 / 19975421132730.01723 4 55 R A B 4/ 21 / 199852598790.08.97.596 R A B6 / 8 / 199975577510.02.02.06.8 R A B5 / 31 / 2000555232.80.00.00.11.4 R A B6 / 7 / 2001532102300.01.32.858 R A B6 / 3 / 2002617887.20.00.10.73.8 R A B5 / 30 / 2003119098140.00.10.76.1 R O L6 / 26 / 1978 4 90321.20.20.1 R O L7 / 10 / 1979521102275.2 4 .72.618 R O L8 / 27 / 1980559 4 10.10.00.00.11.1 R O L8 / 4 / 1981528102211.01.4 4 .238 R O L8 / 9 / 1982532501.10.00.10.41.1 R O L7 / 18 / 1983546847.71.42290 R O L6 / 20 / 1985 4 80711.93.25.2116 R O L8 / 7 / 1985586650.00.21.016 R O L1 / 15 / 1986610781.52.65.254 R O L5 / 2 / 198657162593.26.438 R O L6 / 23 / 198658584132016216 R O L9 / 3 / 1986586610.00.00.45.8 R O L2 / 9 / 1987624831.33.49.381 R O L5 / 18 / 19876081001.00.52.338 R O L6 / 1 / 198759811014993 4 1392 R O L8 / 17 / 19876421100.00.01.634 R O L2 / 22 / 1988587640.20.61.28.6 R O L5 / 6 / 1988622501.40.11.17.8 R O L7 / 18 / 1988585 4 52.00.00.87.5 R O L8 / 16 / 1988596 4 51.20.00.03.2 R O L2 / 27 / 1989583271.00.30.00.12.4 R O L5 / 1 / 198957936190.30.03.77.3 R O L7 / 17 / 1989615558.92.00.22.912 R O L8 / 25 / 1989607340.50.00.00.03.5 R O L1 / 30 / 1990572170.60.00.00.00.4 R O L6 / 12 / 1990596 4 9 4 13.80.72.580 R O L8 / 14 / 1990608311.60.00.10.02.2 Site IDDate Specific conduc tance Maximum 10 day discharge rates

PAGE 260

Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) R O L3 / 13 / 199161287746.08.71265 R O L5 / 6 / 199158599105108.020151 R O L8 / 19 / 199163871 4 67107 4 21158 R O L 4/ 29 / 1992694115104 4 .05.29.890 R O L6 / 23 / 199211601002427.81720241 R O L1 / 20 / 19936549826216219.0231 R O L1 / 23 / 199363010026216219.0231 R O L1 / 26 / 199362510026216219.0231 R O L5 / 6 / 19936351081231.2161073 R O L6 / 1 / 1993642108 4 20.05.05.232 R O L8 / 13 / 1993660880.50.00.00.10.5 R O L 4/ 12 / 1994597 4 76.90.00.00.39.5 SLR7 / 11 / 1978700250.00.0 SLR7 / 5 / 1979630105130.82.914 SLR9 / 4 / 1980680380.00.00.00.00.5 SLR8 / 18 / 198158396160.30.3 4 .314 SLR8 / 17 / 1982625 4 61.10.00.00.21.9 SLR7 / 20 / 1983600847.71.42290 SLR5 / 1 / 198665662593.26.426 SLR6 / 24 / 198664084132016216 SLR9 / 2 / 1986655620.00.00.45.8 SLR2 / 10 / 1987624831.33.49.381 SLR5 / 19 / 1987642100122.62.838 SLR5 / 30 / 19876359814993 4 1208 SLR8 / 18 / 19876361100.00.01.634 SLR2 / 22 / 1988575640.20.61.28.6 SLR5 / 3 / 1988707501.40.11.17.8 SLR7 / 11 / 1988721 4 71.00.00.12.2 SLR8 / 9 / 1988727 4 30.00.00.011 SLR2 / 21 / 1989736280.90.20.00.12.4 SNL6 / 26 / 1978 4 60321.20.20.1 SNL7 / 10 / 1979525102275.2 4 .72.618 SNL8 / 27 / 1980503 4 10.10.00.00.11.1 SNL8 / 4 / 1981 4 62102211.01.4 4 .238 SNL8 / 9 / 1982 4 68501.10.00.10.41.1 SNL7 / 18 / 1983 4 94847.71.42290 SV E 10 / 12 / 1978820240.40.00.3 SV E 7 / 18 / 1979 4 45100170.92.12.414 SV E 9 / 8 / 1980807380.18.80.00.229 SV E 8 / 19 / 198163896350.30.3 4 .339 SV E 8 / 30 / 19821530 4 30.20.00.00.12.1 SV E 6 / 24 / 19858387233288.0300 Site IDDate Specific conduc tance Maximum 10 day discharge rates

PAGE 261

Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) SV E 8 / 12 / 1985936630.00.10.811 SV E 1 / 15 / 1986913781.52.65.254 SV E 5 / 2 / 198689762593.26.438 SV E 6 / 24 / 1986101084132016216 SV E 8 / 29 / 1986874640.00.00.45.8 SV E 2 / 10 / 1987610831.33.49.381 SV E 5 / 19 / 1987614100122.62.838 SV E 5 / 31 / 198760210514993 4 1392 SV E 8 / 19 / 19876031100.00.01.633 SV E 2 / 24 / 1988704630.10.61.28.6 SV E 5 / 3 / 1988833501.40.11.17.8 SV E 7 / 11 / 1988910 4 71.00.00.12.2 SV E 8 / 9 / 1988917 4 30.00.00.011 SV E 2 / 21 / 1989857280.90.20.00.12.4 SV E 5 / 2 / 198989735160.30.03.55.6 SV E 7 / 21 / 1989975525.82.00.12.17.7 SV E 8 / 25 / 1989949340.50.00.00.03.5 SV E 1 / 30 / 1990942170.60.00.00.00.4 SV E 6 / 6 / 199097950 4 17.10.82.580 SV E 8 / 15 / 1990973301.20.00.00.02.2 SV E 3 / 5 / 1991916871068.5141582 SV E 5 / 6 / 199190799105108.020151 SV E 8 / 19 / 199179671 4 67107 4 21158 SV E 4/ 28 / 1992601115115 4 .76.21198 SV E 1 / 21 / 199362010026216219.0231 SV E 1 / 24 / 199361610026216219.0231 SV E 1 / 28 / 199361810026216219.0231 SV E 5 / 7 / 19936161081231.2161073 SV E 5 / 10 / 19936251081231.2161073 SV E 5 / 14 / 19936231081231.2161073 SV E 5 / 28 / 1993626108 4 20.05.05.232 SV E 8 / 16 / 1993652870.50.00.00.10.5 SV E 4/ 12 / 19941020 4 76.90.00.00.39.5 SV E 6 / 14 / 19958671043471210832294 SV E 5 / 9 / 1996840250.60.00.00.00.5 SV E 7 / 9 / 19976741132730.01723 4 55 SV E 4/ 22 / 199859698760.08.47.293 SV E 6 / 9 / 199973376350.01.91.65.3 SV E 5 / 31 / 2000850232.80.00.00.11.4 SV E 6 / 14 / 200177099150.00.92.033 SV E 8 / 7 / 20027601051160.02.111111 SV E 5 / 28 / 2003626101140.00.10.87.2 Site IDDate Specific conduc tance Maximum 10 day discharge rates

PAGE 262

Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) SV N 10 / 13 / 1978500240.40.00.3 SV N 7 / 17 / 1979 4 80100170.92.12.516 SV N 8 / 19 / 198151796350.30.3 4 .339 SV N 5 / 17 / 19825067217201942492581960 SV N 6 / 20 / 1985 4 10711.93.25.2116 SV N 8 / 7 / 1985 4 96650.00.21.016 SV N 1 / 15 / 1986 4 66781.52.65.254 SV N 5 / 2 / 198638962593.26.438 SV N 6 / 24 / 1986 4 4284132016216 SV N 8 / 29 / 1986514640.00.00.45.8 SV N 2 / 10 / 1987388831.33.49.381 SV N 5 / 19 / 1987 4 80100122.62.838 SV N 5 / 31 / 1987 4 0910514993 4 1392 SV N 8 / 19 / 19876301100.00.01.633 SV N 2 / 24 / 1988510630.10.61.28.6 SV N 3 / 5 / 1991560871068.5141582 SV N 5 / 6 / 199154799105108.020151 SV N 8 / 19 / 1991 4 8071 4 67107 4 21158 SV N 4/ 29 / 1992 4 69115104 4 .05.29.890 SV N 1 / 20 / 1993 4 539826216219.0231 SV N 1 / 23 / 1993 4 6110026216219.0231 SV N 1 / 26 / 1993 4 5510026216219.0231 SV N 5 / 6 / 1993 4 471081231.2161073 SV N 5 / 9 / 1993 4 711081231.2161073 SV N 5 / 12 / 1993 4 801081231.2161073 SV N 6 / 1 / 1993 4 64108 4 20.05.05.232 SV N 8 / 16 / 1993549870.50.00.00.10.5 SV N 6 / 19 / 1995 4 601022811210832172 SV N 7 / 9 / 19975331132730.01723 4 55 SV N 4/ 22 / 199850798760.08.47.293 SV N 6 / 9 / 199950776350.01.91.65.3 SV N 6 / 15 / 200171098140.00.92.033 SV N 8 / 7 / 20025071051160.02.111111 SV N 5 / 28 / 2003603101140.00.10.87.2 SVS8 / 8 / 1978540247.6143.5 SVS7 / 17 / 1979580100170.92.12.516 SVS8 / 28 / 1980620 4 10.00.00.00.11.1 SVS8 / 10 / 198158599110.10.62.320 SVS10 / 7 / 198160084854123.2191150 SVS10 / 8 / 198158886854123.2191150 SVS8 / 9 / 1982584501.10.00.10.41.1 SVS7 / 19 / 1983582847.71.42290 Site IDDate Specific conduc tance Maximum 10 day discharge rates

PAGE 263

Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) SVS6 / 19 / 1985584702.4 4 .05.6145 SVS8 / 7 / 1985592650.00.21.016 SVS1 / 13 / 1986589781.53.05.761 SVS5 / 2 / 198660662593.26.438 SVS6 / 23 / 198660884132016216 SVS8 / 29 / 1986596640.00.00.45.8 SVS2 / 9 / 1987578831.33.49.381 SVS5 / 18 / 19876161001.00.52.338 SVS6 / 1 / 198761511014993 4 1392 SVS8 / 17 / 19876031100.00.01.634 SVS2 / 22 / 1988593640.20.61.28.6 SVS5 / 10 / 1988609500.00.10.7 4 .7 SVS7 / 14 / 1988575 4 72.00.00.87.5 SVS8 / 11 / 1988607 4 31.10.00.011 SVS2 / 21 / 1989607280.90.20.00.12.4 SVS5 / 1 / 198958636190.30.03.77.3 SVS7 / 21 / 1989590525.82.00.12.17.7 SVS8 / 25 / 1989595340.50.00.00.03.5 SVS1 / 30 / 1990602170.60.00.00.00.4 SVS6 / 5 / 199059050 4 17.11.02.580 SVS8 / 14 / 1990568311.60.00.10.02.2 SVS3 / 5 / 1991560871068.5141582 SVS5 / 13 / 1991581992616838 4 8218 SVS8 / 14 / 199160875 4 .1125.91.76.5 SVS5 / 1 / 1992584115853.4 4 .28.175 SVS1 / 22 / 199360310026216219.0231 SVS1 / 25 / 199361010026216219.0231 SVS5 / 7 / 19936141081231.2161073 SVS5 / 10 / 19936131081231.2161073 SVS5 / 14 / 19936141081231.2161073 SVS5 / 28 / 1993615108 4 20.05.05.232 SVS8 / 17 / 1993618870.50.00.00.10.5 SVS 4/ 8 / 1994594 4 76.90.00.00.39.5 SVS6 / 19 / 19956111022811210832172 SVS5 / 2 / 1996592260.70.00.00.10.6 SVS7 / 8 / 19975851133220.92126510 SVS 4/ 22 / 199861698760.08.47.293 SVS6 / 11 / 199959973210.01.41.4 4 .9 SVS6 / 1 / 2000610222.70.00.00.11.4 SVS6 / 18 / 200161397130.00.91.931 SVS6 / 6 / 2002622887.20.00.10.73.8 SVS5 / 19 / 2003620102130.00.31.313 Site IDDate Specific conduc tance Maximum 10 day discharge rates

PAGE 264

Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) SV W 6 / 27 / 1978560320.90.20.1 SV W 7 / 12 / 1979620101275.2 4 .72.618 SV W 8 / 28 / 1980592 4 10.00.00.00.11.1 SV W 8 / 10 / 198156999110.10.62.320 SV W 8 / 10 / 1982597 4 91.10.00.10.41.2 SV W 7 / 19 / 1983601847.71.42290 SV W 6 / 20 / 1985611711.93.25.2116 SV W 8 / 9 / 1985657640.00.20.915 SV W 1 / 15 / 1986622781.52.65.254 SV W 5 / 2 / 198662362593.26.438 SV W 6 / 23 / 198663884132016216 SV W 8 / 29 / 1986659640.00.00.45.8 SV W 2 / 9 / 1987591831.33.49.381 SV W 5 / 18 / 19876611001.00.52.338 SV W 6 / 1 / 198760311014993 4 1392 SV W 8 / 17 / 19876141100.00.01.634 SV W 2 / 22 / 1988637640.20.61.28.6 SV W 5 / 9 / 1988690500.20.11.17.8 SV W 7 / 18 / 1988569 4 52.00.00.87.5 SV W 8 / 11 / 1988658 4 31.10.00.011 SV W 2 / 27 / 1989630271.00.30.00.12.4 SV W 5 / 1 / 198970836190.30.03.77.3 SV W 7 / 17 / 1989650558.92.00.22.912 SV W 8 / 29 / 1989678330.40.00.00.02.7 SV W 1 / 30 / 1990688170.60.00.00.00.4 SV W 6 / 8 / 1990705 4 9 4 13.80.82.580 SV W 8 / 15 / 1990694301.20.00.00.02.2 SV W 3 / 11 / 199165887956.7111475 SV W 5 / 7 / 199164699105108.020151 SV W 8 / 14 / 199168075 4 .1125.91.76.5 SV W 4/ 29 / 1992639115104 4 .05.29.890 SV W 1 / 22 / 199365510026216219.0231 SV W 1 / 25 / 199362110026216219.0231 SV W 1 / 28 / 199360810026216219.0231 SV W 5 / 11 / 19936111081231.2161073 SV W 5 / 15 / 19935851081230.0161073 SV W 6 / 1 / 1993630108 4 20.05.05.232 SV W 8 / 20 / 1993670860.40.00.00.00.3 SV W 4/ 11 / 1994645 4 76.90.00.00.39.5 Site IDDate Specific conduc tance Maximum 10 day discharge rates

PAGE 265

Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) SVW 10/09/94 high resultion sampling, date format is DD HHMM SV W 09 070057035 4 7673993330 SV W 09 130558235 4 7673993330 SV W 09 185559235 4 7673993330 SV W 10 071061139 4 7673993330 SV W 10 130062039 4 7673993330 SV W 10 190561239 4 7673993330 SV W 11 070562439 4 7673993330 SV W 11 130567839 4 7673993330 SV W 11 190063439 4 7673993330 SV W 12 073060039 4 7673993330 SV W 12 190059839 4 7673993330 SV W 13 070060139 4 7673993330 SV W 13 193061939 4 7673993330 SV W 14 073059639 4 7673993330 SV W 14 180059439 4 7673993330 SV W 15 123064539 4 7673993330 SV W 6 / 27 / 199564798990.0181296 SV W 5 / 2 / 1996643260.70.00.00.10.6 SV W 7 / 9 / 19975801132730.01723 4 55 SV W 4/ 21 / 199856898790.08.97.596 SV W 6 / 9 / 199964476350.01.91.65.3 SV W 6 / 1 / 2000662222.70.00.00.11.4 SV W 6 / 6 / 2001659103360.01.42.964 SV W 6 / 3 / 2002646887.20.00.10.73.8 SV W 5 / 19 / 2003644102130.00.31.313 TNR7 / 17 / 1978580240.00.0 TNR7 / 9 / 1979580103275.2 4 .72.618 TNR8 / 29 / 1980592 4 00.00.00.00.11.0 TNR8 / 18 / 198157696160.30.3 4 .314 TNR8 / 16 / 1982584 4 61.10.00.00.21.9 TNR7 / 21 / 1983590847.71.42290 TNR6 / 19 / 1985588702.4 4 .05.6145 TNR8 / 9 / 1985604640.00.20.915 TNR1 / 13 / 1986576781.53.05.761 TNR5 / 3 / 198659262593.26.438 TNR6 / 25 / 198664684132016216 TNR9 / 2 / 1986607620.00.00.45.8 TNR2 / 11 / 1987597801.33.28.976 TNR5 / 19 / 1987605100122.62.838 TNR6 / 1 / 198759511014993 4 1392 TNR8 / 18 / 19876061100.00.01.634 Site IDDate Specific conduc tance Maximum 10 day discharge rates

PAGE 266

Table A 1. (cont.) Specific conductance and discharge rates, 1978.Barton Springs Barton Creek Williamson Creek Slaughter Creek Bear Creek Onion Creek ( S/cm)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s)(f t 3 / s) TNR2 / 25 / 1988597630.10.61.28.6 TNR5 / 9 / 1988598500.20.11.17.8 TNR7 / 18 / 1988599 4 52.00.00.87.5 TNR8 / 9 / 1988600 4 30.00.00.011 TNR2 / 23 / 1989579280.90.30.00.11.4 TNR5 / 2 / 198960335160.30.03.55.6 TNR7 / 26 / 1989592 4 82.50.30.01.65.5 TNR8 / 30 / 1989590320.40.00.00.02.7 TNR2 / 7 / 199055822 4 .38.60.00.11.5 TNR 4/ 30 / 1992593115943.5 4 .78.581 WBG7 / 10 / 1978700260.00.0 WBG7 / 5 / 1979799105130.82.914 WBG8 / 28 / 1980826 4 10.00.00.00.11.1 WBG8 / 11 / 198178899110.00.52.219 WBG8 / 10 / 1982766 4 91.10.00.10.41.2 WBG7 / 20 / 1983767847.71.42290 WG F 6 / 28 / 1978 4 80310.70.20.1 WG F 7 / 17 / 1979520100170.92.12.516 WG F 8 / 27 / 1980500 4 10.10.00.00.11.1 WG F 8 / 10 / 198153799110.10.62.320 WG F 8 / 9 / 1982505501.10.00.10.41.1 WG F 7 / 19 / 1983514847.71.42290 See Table 2 1 for information about site identifiers. Site IDDate Specific conduc tance Maximum 10 day discharge rates

PAGE 267

Table A 2. Results of non parametric Spearman s rho rank correlation test between specific conductance and flow in five creeks and aquifer flow condition.Site ID Specific Conductance Compared ToValid N 1Spearman Rank ( ) 2p level 3BC K Aquifer flow condition6 0.350.50 BC K Barton Creek5 0.560.32 BC K Bear Creek5 0.100.87 BC K Onion Creek5 0.300.62 BC K Slaughter Creek6 0.220.67 BC K Williamson Creek60.180.74 BD W Aquifer flow condition22 0.200.38 BD W Barton Creek22 0.390.07 BD W Bear Creek22 0.470.03 BD W Onion Creek22 0.380.08 BD W Slaughter Creek22 0.370.09 BD W Williamson Creek22 0.230.31 BPSAquifer flow condition520.140.33 BPSBarton Creek310.100.61 BPSBear Creek50 0.070.64 BPSOnion Creek500.000.98 BPSSlaughter Creek52 0.030.85 BPSWilliamson Creek52 0.070.62 CNEAquifer flow condition60.140.78 CNEBarton Creek 4 0.200.80 CNEBear Creek50.560.32 CNEOnion Creek50.560.32 CNESlaughter Creek60.750.08 CNEWilliamson Creek60.790.06 FM W Aquifer flow condition31 0.720.00 FM W Barton Creek18 0.440.07 FM W Bear Creek31 0.320.08 FM W Onion Creek31 0.480.01 FM W Slaughter Creek31 0.550.00 FM W Williamson Creek31 0.150.41 FO W Aquifer flow condition 4 20.320.04 FO W Barton Creek290.500.01 FO W Bear Creek 4 10.140.40 FO W Onion Creek 4 10.210.20 FO W Slaughter Creek 4 20.280.07 FO W Williamson Creek 4 20.190.24

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Table A 2. (cont.) Spearman s rho rank correlation results.Site ID Specific Conductance Compared ToValid N 1Spearman Rank (rho) 2p level 3GH W Aquifer flow condition240.410.05 GH W Barton Creek80.480.23 GH W Bear Creek230.400.06 GH W Onion Creek230.340.12 GH W Slaughter Creek240.250.25 GH W Williamson Creek240.330.11 HNDAquifer flow condition150.300.28 HNDBarton Creek 4 0.800.20 HNDBear Creek14 0.320.27 HNDOnion Creek14 0.440.11 HNDSlaughter Creek15 0.140.63 HNDWilliamson Creek15 0.340.22 HWDAquifer flow condition6 0.520.29 HWDBarton Creek5 0.670.22 HWDBear Creek5 0.900.04 HWDOnion Creek5 0.700.19 HWDSlaughter Creek6 0.610.20 HWDWilliamson Creek6 0.760.08 ISDAquifer flow condition6 0.490.33 ISDBarton Creek 4 0.800.20 ISDBear Creek5 0.200.75 ISDOnion Creek5 0.200.75 ISDSlaughter Creek6 0.460.35 ISDWilliamson Creek6 0.270.60 J BSAquifer flow condition130.160.60 J BSBarton Creek80.070.86 J BSBear Creek120.200.53 J BSOnion Creek120.240.46 J BSSlaughter Creek130.320.29 J BSWilliamson Creek130.270.37 KCHAquifer flow condition60 0.390.00 KCHBarton Creek 4 50.010.96 KCHBear Creek59 0.200.14 KCHOnion Creek59 0.470.00 KCHSlaughter Creek60 0.260.05 KCHWilliamson Creek60 0.050.71

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Table A 2. (cont.) Spearman s rho rank correlation results.Site ID Specific Conductance Compared ToValid N 1Spearman Rank (rho) 2p level 3LW K Aquifer flow condition60.880.02 LW K Barton Creek50.560.32 LW K Bear Creek50.780.12 LW K Onion Creek50.780.12 LW K Slaughter Creek60.250.64 LW K Williamson Creek60.001.00 M CHAquifer flow condition 4 7 0.120.43 M CHBarton Creek31 0.460.01 M CHBear Creek 4 5 0.440.00 M CHOnion Creek 4 6 0.420.00 M CHSlaughter Creek 4 7 0.430.00 M CHWilliamson Creek 4 7 0.420.00 PLSAquifer flow condition310.070.70 PLSBarton Creek270.020.93 PLSBear Creek31 0.020.93 PLSOnion Creek31 0.090.64 PLSSlaughter Creek31 0.090.65 PLSWilliamson Creek31 0.170.37 RABAquifer flow condition150.180.52 RABBarton Creek150.100.72 RABBear Creek15 0.010.98 RABOnion Creek15 0.200.46 RABSlaughter Creek150.010.98 RABWilliamson Creek150.400.14 ROLAquifer flow condition390.460.00 ROLBarton Creek240.530.01 ROLBear Creek380.250.14 ROLOnion Creek380.300.07 ROLSlaughter Creek390.330.04 ROLWilliamson Creek390.160.33 SLRAquifer flow condition18 0.630.01 SLRBarton Creek5 0.800.10 SLRBear Creek16 0.630.01 SLROnion Creek17 0.410.10 SLRSlaughter Creek18 0.440.07 SLRWilliamson Creek18 0.170.50

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Table A 2. (cont.) Spearman s rho rank correlation results.Site ID Specific Conductance Compared ToValid N 1Spearman Rank (rho) 2p level 3SNLAquifer flow condition60.380.46 SNLBarton Creek50.100.87 SNLBear Creek5 0.300.62 SNLOnion Creek5 0.210.74 SNLSlaughter Creek60.200.70 SNLWilliamson Creek60.200.70 SVEAquifer flow condition 4 8 0.690.00 SVEBarton Creek34 0.500.00 SVEBear Creek 4 7 0.390.01 SVEOnion Creek 4 7 0.400.01 SVESlaughter Creek 4 8 0.440.00 SVEWilliamson Creek 4 8 0.150.30 SV N Aquifer flow condition340.020.93 SV N Barton Creek23 0.500.01 SV N Bear Creek33 0.350.04 SV N Onion Creek33 0.410.02 SV N Slaughter Creek34 0.540.00 SV N Williamson Creek34 0.630.00 SVSAquifer flow condition500.290.04 SVSBarton Creek35 0.070.67 SVSBear Creek 4 9 0.100.49 SVSOnion Creek 4 9 0.100.49 SVSSlaughter Creek500.000.98 SVSWilliamson Creek50 0.230.11 SV W Aquifer flow condition64 0.050.68 SV W Barton Creek 4 9 0.390.01 SV W Bear Creek63 0.470.00 SV W Onion Creek63 0.310.01 SV W Slaughter Creek64 0.410.00 SV W Williamson Creek64 0.280.03 TNRAquifer flow condition260.250.22 TNRBarton Creek100.070.85 TNRBear Creek250.060.77 TNROnion Creek250.210.32 TNRSlaughter Creek260.000.98 TNRWilliamson Creek26 0.130.53

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Table A 2. (cont.) Spearman s rho rank correlation results.Site ID Specific Conductance Compared ToValid N 1Spearman Rank (rho) 2p level 3WBGAquifer flow condition60.430.40 WBGBarton Creek 4 0.200.80 WBGBear Creek 4 0.400.60 WBGOnion Creek5 0.400.50 WBGSlaughter Creek60.090.87 WBGWilliamson Creek60.210.69 WG F Aquifer flow condition60.940.00 WG F Barton Creek50.800.10 WG F Bear Creek50.600.28 WG F Onion Creek50.670.22 WG F Slaughter Creek60.720.10 WG F Williamson Creek60.290.58 1 Number of values used to obtain statistical correlation values 2 Number ranging from 1 to 1 showing nature and strength of correlation. 3 Expression of statistical confidence. Values less than 0.05 are statistically significant. See Table 2 1 for information about site identifiers.

PAGE 272

Table A 3. Analytical results for dissolved major ions in Barton Springs segment, 1978. CaMgNaK HCO3Cl SO4NO3 N (mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L) BC K 08/28/807.1659673462.13319500.2 BC K 08/11/817.2538703051.0366810.8 BC K 08/10/826.8618643372.13299580.4 BD W 03/19/917.1565852570.83661271.1 BD W 01/22/936.8590882160.6366107 BD W 01/25/936.8589882160.6366107 BD W 08/18/936.8594962060.6354971.6 BD W 04/15/947.0591902060.63661071.6 BD W 06/14/957.2590832760.8366971.1 BD W 04/25/967.3582922160.63421071.6 BD W 07/08/977.2585752760.73291071.3 BD W 04/21/987.1587803160.83661071.4 BD W 06/11/997.0595881850.63421171.5 BD W 06/02/007.0591881960.6354971.4 BD W 06/05/017.0595792760.8364971.1 BD W 06/05/027.0606902060.63621071.3 BD W 05/20/037.1577762650.8348961.0 BPS08/24/797.0588732661.233111311.4 BPS08/01/807.1583722561.233110221.6 BPS08/29/807.6578732661.033111270.3 BPS07/30/817.0583742671.232910280.1 BPS08/12/817.3568742561.334210251.2 BPS07/19/827.0586752561.232911231.5 BPS07/22/837.8539762671.332912271.4 BPS02/20/857.8586772561.232911251.4 BPS08/09/857.4598742561.233311251.4 BPS01/14/867.2579752671.133811241.4 BPS06/24/867.4591752561.23269271.5 BPS09/03/867.2589752671.133711261.4 BPS02/11/877.1588762661.133712271.4 BPS08/19/877.1605762671.234610271.4 BPS02/29/887.0589772661.334011261.4 BPS08/17/887.3597742661.133111271.4 BPS02/27/897.1596732661.233210271.3 BPS07/17/897.1563752661.234310241.3 Specific conduc tance ( S/cm) pH (stan dard units) Date Site ID

PAGE 273

Table A 3. (cont.) Major ion analysis results, Barton Springs segment, 1978.CaMgNaK HCO3Cl SO4NO3 N (mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L) BPS08/29/897.0581782671.133810251.3 BPS01/29/906.9585722561.232810261.3 BPS08/14/907.1566762661.134213251.2 BPS03/22/917.2586762461.332910271.2 BPS04/30/926.9589812461.234213281.3 BPS08/28/927.2584772461.334214271.4 BPS08/19/937.4539762561.134210261.3 BPS08/20/937.0579792571.232910261.4 BPS04/14/947.1578742461.231710251.3 BPS06/14/957.2585782561.232911231.3 BPS05/09/967.2576762661.131711250.8 BPS07/08/977.2575722461.231711241.3 BPS04/22/987.1565802361.132910241.4 BPS06/11/997.0591742461.132912251.3 BPS06/02/007.1592742461.132911251.1 BPS06/12/017.1593772471.333310251.3 BPS06/06/027.1596752461.134311251.3 CNE07/24/787.3104065 4 1937.8290961600.0 CNE09/04/807.510306139997.9293981700.0 CNE08/12/817.89965938928.2281921700.0 CNE08/11/827.710205939987.3281911800.1 CNE07/21/837.610605938977.4281931700.1 FMW08/11/817.2531821950.8342811.5 FMW08/04/826.9566802260.63421271.7 FMW07/19/837.0568832360.73421081.5 FMW08/08/857.1567822260.63501061.7 FMW01/15/867.1545812250.53461261.7 FMW09/03/867.2568832160.63531061.7 FMW02/09/877.45528419 4 0.8348861.7 FMW08/18/877.5564841950.8350771.6 FMW02/25/887.1573842360.63541171.7 FMW02/23/896.9560822360.63401071.6 FMW08/21/897.3587832360.63561061.5 FMW03/05/917.1571792160.63541151.6 FMW04/28/927.2545811850.73291171.3 FMW01/21/936.95368118 4 0.834278 FMW01/24/937.0537821950.834277 Site IDDate pH (stan dard units) Specific conduc tance ( S/cm)

PAGE 274

Table A 3. (cont.) Major ion analysis results, Barton Springs segment, 1978.CaMgNaK HCO3Cl SO4NO3 N (mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L) FMW01/28/936.8537861950.834277 FMW05/08/937.3535861950.8342771.4 FMW08/16/937.05378719 4 0.8329771.5 FMW04/08/947.1563792260.63421071.7 FO W 06/28/787.2620733571.536015 4 80.7 FO W 07/10/796.6620773581.235015361.1 FO W 08/28/807.2686783581.236015530.1 FO W 08/11/817.2595753180.83661690.9 FO W 08/10/827.0595723080.73541681.1 FO W 07/19/837.1597753180.83661671.1 FO W 08/08/857.0641803781.935415520.7 FO W 01/14/867.1624753380.737020161.0 FO W 09/03/867.2610753190.83541781.1 FO W 02/10/877.5625763280.936812211.0 FO W 08/26/877.3687753781.835614580.8 FO W 08/17/887.2705763881.935014610.6 FO W 02/27/896.9660773491.136815281.0 FO W 02/09/907.0658773791.835914560.8 FO W 05/01/926.977184 4 57 4 .0342141500.2 FO W 01/21/936.9863805485.834210190 FO W 01/24/937.089585569 4 .734212200 FO W 05/07/937.377575 4 86 4 .532991500.1 FO W 04/18/946.9645783391.036618301.1 FO W 06/19/957.176078 4 283.2342131100.5 FO W 05/07/967.26358134101.035418311.0 FO W 07/09/977.0616713090.832918121.1 FO W 04/23/987.1652893590.83541834 4 .6 FO W 06/11/997.0654753190.932919311.2 FO W 06/19/017.07427733100.935918331.1 FO W 06/05/026.96607531100.835718171.2 FO W 05/21/036.974787 4 0111.736719771.2 GH W 07/09/797.2670803761.6 4 1013191.0 GH W 08/29/807.9666783661.3 4 1012140.0 GH W 08/12/817.2650783771.7 4 151610.7 GH W 08/16/826.9666803671.3 4 1512170.9 GH W 07/21/837.2667883571.3 4 1514161.1 Site IDDate pH (stan dard units) Specific conduc tance ( S/cm)

PAGE 275

Table A 3. (cont.) Major ion analysis results, Barton Springs segment, 1978.CaMgNaK HCO3Cl SO4NO3 N (mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L) GH W 08/09/857.1648753571.539410190.9 GH W 01/13/867.0644763871.4 4 1613150.8 GH W 09/02/867.3671813671.3 4 1612160.9 GH W 02/11/877.2672803771.5 4 2013160.8 GH W 08/19/877.1683813771.5 4 0311170.8 GH W 02/24/886.9655823871.6 4 2212170.9 GH W 08/10/887.1635773771.4 4 1011150.8 GH W 02/23/897.1640823771.4 4 0410160.9 GH W 08/30/897.1640803671.4 4 1211140.8 HND07/11/796.6580882181.132015222.1 HND09/08/807.1559722861.134011200.9 HND08/11/817.2589882081.134217131.8 HND08/10/827.1575722871.134212190.9 HND07/20/837.4 4 75691771.226810180.6 HND08/08/857.1580892181.135113221.6 HND01/13/867.0575832281.334014171.5 HND09/03/867.2600842381.233814202.1 HND02/11/877.2607891981.334812202.0 HWD07/09/797.1560772260.933112171.5 HWD08/28/807.1575792160.933110131.7 HWD08/18/817.2551792371.13421811.6 HWD08/04/827.1563792470.932911121.5 HWD07/22/837.5553852370.934213121.6 ISD07/11/796.9 4 80 4 82551.22208210.4 ISD09/04/807.3 4 87562751.030010150.6 ISD08/12/817.3 4 82552761.12939150.4 ISD08/11/827.0 4 95532761.02939170.5 ISD07/22/837.8 4 89562861.22939160.5 JBS07/16/796.7580902081.232014321.7 JBS08/27/807.4587862081.132013260.6 JBS08/04/817.3570862191.131712303.0 JBS08/09/826.9592842091.131714311.6 JBS07/18/837.4586852191.231716281.7 Site IDDate pH (stan dard units) Specific conduc tance ( S/cm)

PAGE 276

Table A 3. (cont.) Major ion analysis results, Barton Springs segment, 1978.CaMgNaK HCO3Cl SO4NO3 N (mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L) KCH07/10/796.66208226131.032018 4 06.4 KCH08/28/807.26608725161.031021 4 8 4 .7 KCH08/11/817.26218225160.932919 4 2 4 .0 KCH08/10/827.06528324160.931723 4 5 4 .8 KCH07/19/837.06708825171.032923 4 5 4 .7 KCH08/07/857.26358624140.93221935 4 .4 KCH08/29/867.36748925150.832819 4 2 4 .5 KCH02/09/877.36418325140.932518357.1 KCH08/19/877.46758325140.932218358.6 KCH03/09/887.26559026181.03162260 4 .9 KCH08/11/887.16918526180.83182252 4 .7 KCH02/27/896.96909025180.932520 4 4 4 .7 KCH08/29/897.26688924180.932627 4 5 4 .6 KCH02/07/907.06228825151.03252031 4 .7 KCH03/11/917.16429025141.03422029 4 .2 KCH04/29/926.56237724120.932923333.8 KCH01/20/937.06528225160.831720 4 4 KCH01/23/936.96508325150.931721 4 4 KCH01/26/937.26528325160.931720 4 7 KCH05/06/937.26418826150.931718 4 3 4 .6 KCH08/18/936.96649225150.93171951 4 .8 KCH04/12/947.06529124150.931723 4 55.6 KCH10/10/946.76528523151.131722385.0 KCH06/19/957.16418424150.930519345.1 KCH05/06/967.26488923160.830522395.1 KCH07/08/977.5568662690.929314173.9 KCH04/21/987.16288925150.930521375.9 LW K 07/11/796.9 4 99602361.327012241.6 LW K 08/29/807.6 4 96592261.32708180.4 LW K 08/18/817.3 4 99622371.32931191.6 LW K 08/17/826.9 4 93592371.326811221.5 LW K 07/21/837.4 4 99602371.428112191.6 M CH07/05/797.0540851781.032011181.1 M CH08/28/807.1570791960.932011121.3 M CH08/11/817.1537821870.832911100.9 M CH08/11/827.6528772071.032910141.1 M CH07/20/837.5 4 76711771.226811160.5 M CH08/09/857.1540801871.030512150.8 Site IDDate pH (stan dard units) Specific conduc tance ( S/cm)

PAGE 277

Table A 3. (cont.) Major ion analysis results, Barton Springs segment, 1978.CaMgNaK HCO3Cl SO4NO3 N (mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L) M CH01/13/867.1537791870.932712140.9 M CH09/02/867.2550852173.333812151.1 M CH02/10/877.1554871870.933112160.9 M CH08/17/877.2560842071.034211161.0 M CH02/22/887.1519812071.031212220.8 M CH08/10/887.1552782170.932811151.0 M CH02/21/897.2584832371.133411210.9 M CH08/29/897.1547812071.032613150.9 M CH01/31/906.9587812360.934610131.2 M CH03/13/917.3518811781.129314240.6 M CH04/30/926.9564941760.932915190.8 M CH01/22/936.9504751671.02931118 M CH01/25/936.9503751660.92931019 M CH05/08/937.3521811771.030511190.5 M CH08/18/936.8550831961.331710150.9 M CH04/15/947.0506711871.026812260.5 M CH06/14/957.1550891660.931710130.5 M CH05/07/967.6555802270.931710140.9 M CH07/08/977.2555871560.929310130.7 M CH04/22/987.0534831870.92931119 4 .0 M CH06/06/997.0545832070.930512180.8 M CH06/29/007.0538791871.330511180.7 M CH06/20/016.8554801871.031112180.6 M CH06/04/027.35587320101.029314171.0 M CH05/20/037.1565851871.031212190.7 PLS02/26/887.1568742471.233212171.5 PLS08/11/887.2564732571.132011161.4 PLS02/28/897.1548752581.232811181.4 PLS08/30/897.0542762471.132811171.4 PLS02/07/907.0550762471.332810171.5 PLS03/18/917.2533762471.031712181.5 PLS05/01/927.0543792471.131715201.4 PLS01/21/936.8560722471.13291217 PLS01/24/937.0559732471.13291217 PLS01/28/936.8559772581.13291217 PLS08/17/936.9560782471.131711171.4 PLS04/12/947.0546782471.132912171.6 PLS06/19/957.2561752371.131712161.5 PLS04/25/966.9544762571.130511161.5 Site IDDate pH (stan dard units) Specific conduc tance ( S/cm)

PAGE 278

Table A 3. (cont.) Major ion analysis results, Barton Springs segment, 1978.CaMgNaK HCO3Cl SO4NO3 N (mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L) PLS07/08/977.3550722471.131712161.5 PLS04/21/987.1528812571.132912171.4 PLS06/01/007.1573752471.032912171.4 PLS06/08/017.0590772471.129913191.4 PLS05/23/027.1570782471.129613181.5 PLS05/21/037.0576772471.231513171.3 RAB05/06/937.35967725121.625616810.6 RAB04/15/947.3522672191.226815370.8 RAB06/27/957.4507661991.224416310.7 RAB05/06/967.35046721101.224416370.6 RAB07/09/977.25426722111.423218 4 90.6 RAB04/21/987.35256620111.328118330.6 RAB06/08/997.27557523131.524421700.6 RAB05/31/007.25557121111.325619510.6 RAB06/07/017.25326721121.325020 4 10.6 RAB06/03/027.36177021121.523922 4 80.6 RAB05/30/037.01190140 4 9273.5271372870.4 ROL07/10/796.7521722071.029013231.1 ROL08/27/807.3559742171.232012170.3 ROL08/04/817.5528762281.030512191.1 ROL08/09/827.0532722081.129313251.0 ROL07/18/837.1546772281.129315241.1 ROL08/07/857.4586862291.132018301.2 ROL01/15/867.1610842391.031022321.3 ROL09/03/867.4586832291.131217311.2 ROL02/09/877.26248822101.131621351.6 ROL08/17/877.26429122101.232119 4 01.5 ROL02/22/887.05878923101.232619341.3 ROL08/16/887.0596852391.031418331.3 ROL02/27/897.3583812291.130916301.0 ROL08/25/897.26078622101.131819321.2 ROL01/30/906.9572782191.230017291.0 ROL03/13/917.26128922111.231728351.5 ROL04/29/926.96949421141.1317 4 1 4 52.0 ROL01/20/937.26548621121.131725 4 0 ROL01/23/936.96308822121.131726 4 2 ROL01/26/936.86258621121.131724 4 1 Site IDDate pH (stan dard units) Specific conduc tance ( S/cm)

PAGE 279

Table A 3. (cont.) Major ion analysis results, Barton Springs segment, 1978.CaMgNaK HCO3Cl SO4NO3 N (mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L) ROL05/06/937.96359322121.131726 4 11.4 ROL08/13/936.96609823121.132925 4 31.5 ROL04/12/947.15978822101.130522381.2 SLR07/05/796.96301001960.5 4 00970.3 SLR09/04/807.16801002060.6 4 009350.5 SLR08/18/817.1583971960.6378910.5 SLR08/17/827.0625982160.6390991.2 SLR07/20/837.3600981950.63789100.7 SLR09/02/867.16551102160.6 4 1410111.1 SLR02/10/877.06241102050.5 4 4010130.7 SLR08/18/877.16361001850.5 4 039100.4 SLR02/22/887.15751002260.53999121.1 SLR08/09/887.17271102560.6 4 169560.1 SLR02/21/897.07361052760.9 4 098600.1 SNL06/26/787.2 4 60671971.028115220.4 SNL07/10/796.8525702081.026015330.5 SNL08/27/807.4503651891.026014240.1 SNL08/04/817.6 4 62651981.028111230.4 SNL08/09/827.0 4 68621881.024414250.3 SNL07/18/837.8 4 94671991.125614260.1 SVE07/18/796.8 4 455818112.922014 4 21.0 SVE08/19/817.36387429112.232912 4 21.3 SVE08/30/827.415301408010011.0317 4 65701.6 SVE08/12/857.29369738 4 43.8336 4 61601.6 SVE01/15/867.19139237 4 83.2334 4 61601.4 SVE08/29/867.18749235 4 43.0318 4 51301.4 SVE02/10/877.4610733091.734616381.3 SVE08/19/877.56036728101.830315261.2 SVE02/24/887.17049034142.732620960.9 SVE08/09/887.091796 4 0393.7332311701.7 SVE02/21/896.98579037343.5334271501.8 SVE08/25/896.994910039 4 0 4 .0326341801.7 SVE01/30/906.994298 4 1 4 1 4 .3332311901.8 SVE03/05/917.391610038 4 0 4 .2342321801.6 SVE04/28/927.16017129112.030522 4 81.3 SVE01/21/936.96207429101.532916 4 3 SVE01/24/937.06167529112.33291750 Site IDDate pH (stan dard units) Specific conduc tance ( S/cm)

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Table A 3. (cont.) Major ion analysis results, Barton Springs segment, 1978.CaMgNaK HCO3Cl SO4NO3 N (mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L) SVE01/28/936.96187629101.53421637 SVE05/07/937.36168029101.532917381.6 SVE08/16/937.16528530112.8256151100.4 SVE04/12/947.01020110 4 6515.7329352502.0 SVE06/14/957.18679232292.331737971.4 SVE05/09/967.48409736343.4390321401.3 SVE07/09/977.26747729191.929328571.4 SVE04/22/987.25967530101.530517361.4 SVE05/31/007.28509534313.1317301340.1 SVE06/14/017.17709031330.1334 4 0931.6 SVE08/07/027.07608930282.032236791.6 SVE05/28/037.16268128101.534517321.5 SV N 07/17/796.8 4 80701871.426011250.3 SV N 08/19/817.2517702081.329314160.3 SV N 08/07/856.9 4 96691871.328314220.4 SV N 01/15/867.4 4 66661981.025917210.3 SV N 08/29/866.8514721981.228112240.4 SV N 02/10/877.3388585513.02125150.2 SV N 08/19/877.4630771783.228812320.8 SV N 02/24/887.2510722181.328114320.3 SV N 03/05/917.55607519151.525630 4 40.2 SV N 01/20/936.9 4 535915111.42201632 SV N 01/23/936.8 4 616015111.42321631 SV N 01/26/936.8 4 556516121.62321532 SV N 05/06/937.5 4 476016111.222016290.1 SV N 08/16/937.15497720111.528117340.5 SV N 06/19/957.1 4 606216122.023217250.2 SV N 07/09/977.25336718121.624421300.1 SV N 04/22/987.45076718141.224422 4 20.6 SV N 06/15/016.87109721201.333838500.3 SV N 08/07/027.25076417151.623126330.1 SV N 05/28/037.26038420171.427230 4 50.3 SVS08/08/787.0540693081.33601262.3 SVS07/17/796.8580712591.23311117 4 .0 SVS08/28/807.0620702891.23501351.1 SVS08/10/817.35857727101.23421473.5 SVS08/09/826.7584682991.33421272.7 SVS07/19/836.9582703091.33421392.6 Site IDDate pH (stan dard units) Specific conduc tance ( S/cm)

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Table A 3. (cont.) Major ion analysis results, Barton Springs segment, 1978.CaMgNaK HCO3Cl SO4NO3 N (mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L) SVS08/07/857.1592732991.33601262.7 SVS01/13/867.0589732991.03561493.0 SVS08/29/867.25967529101.23561383.1 SVS02/09/877.15787726101.335014103.8 SVS08/17/877.36037924101.235012163.9 SVS02/22/887.15938228101.23621316 4 .3 SVS08/11/887.26077231101.13531182.7 SVS02/21/897.1607713191.33481182.5 SVS08/25/897.05957129101.23561282.6 SVS01/30/906.9602712991.23561182.7 SVS03/05/917.1560733091.33541372.3 SVS05/01/927.1584822591.134219203.5 SVS01/22/936.7603772791.13661210 SVS01/25/937.0610792791.13661210 SVS05/07/937.1614782691.136612103.7 SVS08/17/937.0618832791.13661293.9 SVS04/08/947.0594712991.23541283.1 SVS06/19/957.16117927101.13421293.7 SVS05/02/967.75927330101.23291283.0 SVS07/08/977.2585742791.13421393.5 SVS04/22/987.06167828101.135413123.6 SVS06/11/997.0599792791.13421373.1 SVS06/01/007.0610722891.13541282.8 SVS06/06/027.0622832791.035913103.1 SVS05/19/036.9620872691.333314152.7 SV W 06/27/786.65607824101.033118151.9 SV W 07/12/796.96207324211.034032141.7 SV W 08/28/807.0592792490.93421471.8 SV W 08/10/817.2569772390.93291971.4 SV W 08/10/826.85978024101.032921201.7 SV W 07/19/836.96017923121.231722231.2 SV W 08/09/857.16578924141.134831231.8 SV W 01/15/867.06228525130.833132201.6 SV W 08/29/867.06599124121.035922222.0 SV W 02/09/877.45917924110.933117211.4 SV W 08/17/877.36148223120.933721181.9 SV W 02/22/887.16379325141.135424351.5 SV W 08/11/887.16588925121.035321232.1 SV W 02/27/897.16308125121.033723231.9 Site IDDate pH (stan dard units) Specific conduc tance ( S/cm)

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Table A 3. (cont.) Major ion analysis results, Barton Springs segment, 1978.CaMgNaK HCO3Cl SO4NO3 N (mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L) SV W 08/29/897.16789324131.036028232.1 SV W 01/30/906.86889325141.236826272.3 SV W 03/11/917.26589025150.931737 4 11.5 SV W 04/29/927.06398223131.032929321.6 SV W 01/22/936.86558623151.03293131 SV W 01/25/936.86218224131.03292527 SV W 01/28/936.96087924120.93292423 SV W 08/20/936.96709825130.935423242.1 SV W 04/11/947.06459425121.034227212.8 SV W 10/09/94 high resultion sampling, date format is DD HHMM SV W 09 0700 6.35708518101.529316231.5 SV W 09 1305 6.3582861891.330517251.5 SV W 09 1855 6.4592871991.331717261.5 SV W 10 0710 6.36118819101.232918271.6 SV W 10 1300 6.46208920101.234218271.6 SV W 10 1905 6.46129120101.332918271.7 SV W 11 0705 6.86249321111.134219271.7 SV W 11 1305 7.26789721131.234226282.2 SV W 11 1900 6.86349022121.031726222.2 SV W 12 0730 6.86008623111.231722181.9 SV W 12 1900 7.05988022101.231723162.0 SV W 13 0700 6.96018424111.131723162.0 SV W 13 1930 6.96198824101.232920221.8 SV W 14 0730 7.25967923111.030523152.1 SV W 15 1230 6.96459625121.134224252.0 SV W 06/27/957.06478723130.932924301.4 SV W 05/02/967.16439025131.035429192.6 SV W 07/09/977.1580732390.928122132.2 SV W 04/21/987.2568802490.830524122.3 SV W 06/01/006.96629123100.935423202.2 SV W 06/06/016.86599526131.034827291.9 SV W 06/03/027.06469225121.033125242.0 SV W 05/19/036.96449325131.136426291.9 TNR07/09/796.9580782760.936011121.3 TNR08/29/807.75928919120.63601331.3 TNR08/18/817.1576792670.83661411.2 TNR08/16/826.9584912070.63661171.7 TNR07/21/837.4590812770.83661471.2 TNR08/09/857.1604822770.836614201.2 Site IDDate pH (stan dard units) Specific conduc tance ( S/cm)

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Table A 3. (cont.) Major ion analysis results, Barton Springs segment, 1978.CaMgNaK HCO3Cl SO4NO3 N (mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L) TNR01/13/867.0576732980.83701391.1 TNR09/02/867.2607892370.83681371.4 TNR02/11/877.1597792870.737011211.1 TNR08/18/877.2606842560.83681271.4 TNR02/25/887.1597932170.73721281.7 TNR08/09/887.1600922160.73681071.7 TNR02/23/896.9579922170.63621071.6 TNR08/30/897.0590932070.53681071.6 TNR02/07/906.9558942070.7362971.7 WBG07/10/786.27006234323.0281281100.0 WBG07/05/797.47996334 4 43.8260231400.1 WBG08/28/807.5826643550 4 .2281381400.0 WBG08/10/826.97666234 4 33.3281321300.1 WBG07/20/837.57676133382.9281291300.1 WGF06/28/786.7 4 80622361.329015121.1 WGF07/17/796.9520732081.430011151.5 WGF08/27/807.4500642271.22901170.6 WGF08/10/817.45377422101.43171861.6 WGF08/09/827.0505622271.229315121.3 WGF07/19/837.1514662381.429316131.7 Samples with > 5% charge balance error were excluded. See Table 2 1 for information about site identifiers. Site IDDate pH (stan dard units) Specific conduc tance ( S/cm)

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APPENDIX B. Analytical results for Chapter 3 This appendix contains the site information and analytical results for Chapter 3. The site information includes site descriptions and cross references with state well numbers and USGS site identifiers (Table B 1). Analytical results for major ion analyses and strontium, oxygen, and hydrogen isotope analyses are also provided (Table B 2).

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Table B 1 Site information for sites sampled in Chapter 3.Site IDSite Type State well number 1USGS site identifier 2Comments M SPSpring 08155500 M ain Barton Spring; near diving board ESPSpring 08155501Eliza Spring; behind concession stand OSPSpring 08155503Old Mill Spring; southeast of pool USPSpring 08155395Upper Barton Spring; upstream in creekbed ALB WellLR 58 50 840 300747097475401Saline zone well referred to in text BDWWellLR 58 57 311 300646097533202 BPSWellLR 58 58 403 300453097503301 FONWellYD 58 50 417 301142097504701 FOWWellYD 58 50 408 301031097515801 M ixes with trinity aquifer water (Chapter 2) M CHWellYD 58 50 704 300813097512101 PLSWellYD 58 50 520 301226097480701 RABWellYD 58 42 915 301526097463201 SVEWellYD 58 50 216 301356097473301 Sometimes mixes with saline zone (Chapter 2) SV N WellYD 58 50 217 301432097480001 SVSWellYD 58 50 215 301339097483701 SV W WellYD 58 50 211 301423097495901 1 For locating wells in Texas Water Development Board databases, among others(e.g., ). 2 For locating wells in United States Geological Survey databases (e.g., ).

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Table B 2. Analytical results for water quality sampling of the Barton Springs segment, 2003.CaMgNaK HCO3Cl SO4NO3 N Sr 87 Sr / 86 Sr 18 O 2 H Site IDDate(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)()() M SP08/06/036.96368518151.333426281.50.810.70795 27 M SP08/20/037.16438922141.334025271.50.96 M SP09/03/037.16498422141.233626281.51.090.70795 4.1 25 M SP09/16/037.16379122161.532327261.41.22 M SP09/25/037.26639424191.432731291.360.70795 4.1 26 M SP09/30/037.26569124171.435028291.51.380.70796 27 M SP12/23/037.1678 0.70793 M SP06/21/047.06229120151.431226341.10.70 M SP07/07/046.96439619141.334024341.00.56 M SP07/21/046.86329120141.328225331.00.670.70797 M SP08/04/046.96228521141.231724301.10.74 M SP08/25/046.95868922141.232723281.20.830.70796 3.9 25 M SP09/15/046.85978822131.432223271.30.88 M SP10/04/047.16389123141.431724261.31.00 M SP10/23/047.05658923131.332222261.41.13 3.9 M SP11/24/047.05879512111.730516271.70.42 M SP12/14/047.065010020131.334321301.20.630.70797 M SP01/03/057.06509521141.232522301.20.69 M SP01/26/057.16459722141.331622291.20.740.70795 28 M SP02/16/057.06659621141.233224331.20.690.70796 M SP03/09/057.067710420161.331125351.10.61 M SP03/30/056.965510021161.232825331.20.680.70797 M SP04/20/056.864910021151.332124291.20.70 M SP05/11/056.86349522141.233223281.20.690.70796 26 M SP06/09/056.96388822131.333222281.30.710.70795 Specific conduc tance ( S/cm) pH (std. units)

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Table B 2. (cont.) Analytical results for water quality sampling of the Barton Springs segment, 2003.CaMgNaK HCO3Cl SO4NO3 N Sr 87 Sr / 86 Sr 18 O 2 H Site IDDate(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)()() USP08/06/036.96409121111.235319273.50.460.70812 26 USP08/20/037.16389524101.134819272.00.52 USP09/03/037.0638912391.234818262.10.510.70812 4.2 USP09/16/037.0562931981.931614191.70.38 USP09/25/037.16429524111.233918270.48 4.1 23 USP09/30/037.16539324101.234819262.20.500.70813 USP12/23/03 spring not flowing USP06/21/047.06259622101.334219252.00.32 USP07/07/047.06379320111.332120261.70.25 USP07/21/046.96469723101.330920272.00.35 USP08/04/047.06489323111.429220281.90.39 USP08/25/046.86059424111.335118272.10.450.70813 3.8 16 USP09/15/046.6625 2.3 USP10/04/047.0629 2.0 USP10/23/047.0 4 15771661.4267991.60.20 4.6 USP11/24/047.0 4 6685852.22627160.90.10 USP12/14/047.065710222101.434317242.20.28 USP01/03/056.76629523111.233818272.20.36 USP01/26/056.965610024121.437018292.10.440.70814 22 USP02/16/056.76479923101.234919292.20.43 USP03/09/056.766010422111.334217281.90.37 USP03/30/056.765410024111.235119282.20.42 USP04/20/056.765510424111.335319272.10.48 USP05/11/056.66379322101.434417262.00.430.70811 23 USP06/09/056.86559425101.335418272.10.45 pH (std. units) Specific conduc tance ( S/cm)

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Table B 2. (cont.) Analytical results for water quality sampling of the Barton Springs segment, 2003.CaMgNaK HCO3Cl SO4NO3 N Sr 87 Sr / 86 Sr 18 O 2 H Site IDDate(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)()() OSP08/06/036.87258821291.7333 4 6 4 21.40.940.70802 28 OSP08/20/037.17299325291.5329 4 8 4 21.51.15 OSP09/03/037.17328825271.6326 4 7 4 21.51.180.70800 4.1 OSP09/16/037.17279124291.8326 4 5 4 01.51.28 OSP09/25/037.27449426321.732350 4 51.260.70803 4.1 28 OSP09/30/037.27489125301.7333 4 8 4 31.51.350.70800 OSP12/23/037.1848 OSP06/21/047.06718921251.6298 4 1 4 61.00.82 OSP07/07/047.06989121261.5289 4 2 4 70.90.71 OSP07/21/046.96889122251.6265 4 2 4 60.90.80 OSP08/04/047.16998523271.6262 4 4 4 51.00.87 OSP08/25/046.96779324301.7318 4 7 4 41.11.000.70802 3.8 24 OSP09/15/046.7695 1.2 OSP10/04/047.1735 1.3 OSP10/23/047.16369124291.7310 4 6 4 31.31.29 3.9 OSP11/24/047.06869617261.9300 4 0 4 21.50.66 OSP12/14/047.07169722261.7353 4 0 4 41.10.79 OSP01/03/057.07248923271.5314 4 3 4 51.20.81 OSP01/26/057.17179224261.6318 4 1 4 41.20.840.70802 21 OSP02/16/057.07389523261.5322 4 3 4 61.20.84 OSP03/09/057.073710721151.3312 4 2 4 61.20.64 OSP03/30/057.07259724271.5325 4 3 4 51.20.82 OSP04/20/057.071910324281.7327 4 2 4 21.30.88 OSP05/11/056.97239625281.6331 4 3 4 21.30.870.70803 27 OSP06/09/057.07319025281.7331 4 4 4 31.30.88 pH (std. units) Specific conduc tance ( S/cm)

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Table B 2. (cont.) Analytical results for water quality sampling of the Barton Springs segment, 2003.CaMgNaK HCO3Cl SO4NO3 N Sr 87 Sr / 86 Sr 18 O 2 H Site IDDate(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)()() ESP08/06/036.86388519151.333627281.40.870.70796 26 ESP08/20/037.16239322161.333627261.41.05 ESP09/03/037.16308723151.333327271.41.200.70795 4.1 ESP09/16/037.16459022171.532627271.41.30 ESP09/25/037.26759224211.533135321.370.70796 4.0 23 ESP09/30/037.16319023181.433129291.51.470.70795 ESP12/23/037.1684 ESP06/21/047.06239219151.431626341.00.75 ESP07/07/046.96479819141.331125350.90.61 ESP07/21/046.86329320141.328525330.90.72 ESP08/04/047.06238320131.327725301.00.75 ESP08/25/046.95869122151.432624271.10.890.70794 3.8 26 ESP09/15/046.8596 1.2 ESP10/04/047.1641 1.3 ESP10/23/047.15508923141.331523271.31.28 3.9 ESP11/24/046.960010013121.730817281.60.48 ESP12/14/047.065110220131.332821301.10.67 ESP01/03/057.06529320141.232623301.20.70 ESP01/26/057.06479622141.332123291.20.760.70795 26 ESP02/16/057.066710222151.233124331.10.77 ESP03/09/057.068110320161.331725361.10.66 ESP03/30/057.065810021161.332225321.10.71 ESP04/20/057.065010221151.333725291.20.74 ESP05/11/057.06369221141.232523291.20.700.70796 23 ESP06/09/057.06388922141.334423281.20.76 pH (std. units) Specific conduc tance ( S/cm)

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Table B 2. (cont.) Analytical results for water quality sampling of the Barton Springs segment, 2003.CaMgNaK HCO3Cl SO4NO3 N Sr 87 Sr / 86 Sr 18 O 2 H Site IDDate(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)(mg/L)()() ALB09/29/037.226001257632313264 4 4753421.800.70806 4.0 24 CSC09/29/037.4522672581.329213317.86 3.9 HBG09/29/037.3516603362.431193215.00 4.1 BD W 07/13/047.1609912360.83541181.10.15 BPS07/16/047.2607782571.234272371.210.30 FO N 07/08/047.2 4 45 4 62661.42338110.13.67 FO W 07/09/047.17188134110.937019321.30.55 M CH07/12/046.9554861771.131513200.50.23 PLS07/21/047.1580802571.130513191.42.50 RAB07/07/047.35567020131.225124380.70.31 SVE07/15/047.17808930292.134038781.71.90 SV N 07/15/047.35807420191.624831 4 50.20.25 SVS07/16/047.1619802691.13571293.00.46 SV W 07/08/046.96017724100.931422132.00.18 BD W 05/24/057.0606862760.8363971.20.230.70788 26 BPS05/24/057.0616812871.133711261.29.590.70789 23 FO N 05/26/057.3509562781.32701592.72.820.70827 26 FO W 05/26/057.17148238111.136618 4 11.05.570.70763 27 M CH05/25/057.1561862081.031412200.70.260.70798 27 PLS05/27/057.0580802781.332313191.42.680.70788 25 RAB05/23/057.45717324141.325023 4 60.70.350.70799 28 SVE06/15/057.07179132211.833230641.51.540.70801 21 SV N 06/14/057.1619 0.000.70819 29 SVS05/24/057.16248729101.335413133.00.450.70832 25 SV W 05/23/057.07009928141.135726311.80.310.70816 21 Major ion samples analyzed by U.S. Geological Survey. Hydrogen isotope samples analyzed at Southern Methodist University. pH (std. units) Specific conduc tance ( S/cm)

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APPENDIX C. Analytical results for Chapter 4 This appendix contains the analytical results discussed in Chapter 4. Analytical results for Main Barton Spring are presented (Table C 1). Results for Eliza Spring, Old Mill Spring, and Upper Barton Spring are also presented (Table C 2). Omitted from this appendix are the approximately 300 results of hourly monitoring of Main Barton Spring, as well as measurements of stream discharge on the five creeks in the study area. Including these results would have added considerably to the bulk of this thesis. Furthermore, data of this type are not especially useful in hard copy format. For access to this data, the reader is directed to the URL http://waterdata.usgs.gov/ The following USGS site identifiers are useful for obtaining the data: (1) Main Barton Spring, 08155500; (2) Eliza Spring, 08155395; (3) Old Mill Spring, 08155503; (4) Upper Barton Spring, 08155395; (5) Barton Creek, 08155240; (6) Williamson Creek, 08158920; (7) Slaughter Creek, 08158840; (8) Bear Creek, 08158810; and (9) Onion Creek, 08158700.

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Table C 1 Results of oxygen and hydrogen isotope ratio analyses, with accompanying real time physical and geochemical data for Main Barton Spring. Composite samples from creeks (not shown here) had values of 5.0 SMOW for both Bear Creek and Onion Creek.Date and Time Barton Springs discharge (ft3/s) Specific conductance ( S/cm) Dissolved oxygen (mg/L) Turbidity (NTU) 18O () 2H () 08/25/2004 0800 606586.19 < 0.1 1 3.9 25 10/23/2004 1400686366.4713 3.9 10/24/2004 1000715976.655.4 4.3 10/24/2004 2100715736.453.5 4.4 10/25/2004 1030715796.282.2 4.5 29 10/26/2004 0900705795.951.5 4.5 10/27/2004 1100705915.900.4 4.4 10/28/2004 0900705965.920.3 4.3 10/30/2004 1000736025.930.1 29 11/05/2004 1030736186.090.8 4.1 1 Measured value was less than instrument detection limit.

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Table C 2. Results of oxygen and hydrogen isotope ratio analyses for Upper Barton, Old Mill, and Eliza Springs.Date and Time 18O () 2H () 18O () 2H () 18O () 2H () 08/25/2004 0800 3.8 16 3.8 3.8 10/23/2004 1400 4.6 3.9 3.9 10/24/2004 1000 4.0 10/24/2004 2100 5.2 38 4.2 10/25/2004 1030 4.2 4.4 10/26/2004 0900 4.6 4.4 10/27/2004 1100 4.3 10/28/2004 0900 4.2 4.2 4.3 10/30/2004 1000 11/05/2004 1030 4.2 4.0 4.1 Upper Barton Spring Old Mill Spring Eliza Spring

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APPENDIX D. Quality assurance data This appendix presents an analysis of quality assurance and quality control data (QA/QC) associated with this thesis. QA/QC data is used as evidence that methodologies are valid, results are reproducible, and establish the uncertainty in the results reported. This is accomplished using (a) blanks to establish background levels; (b) replicates to ensure reproducibility; and (c) lab standards to determine the efficiency of laboratory analytical methods. D.1. HISTORICAL GROUND WATER DATA, 1978003 (CHAPTER 2) D.1.1. Specific conductance data quality assurance The quality of specific conductance data was monitored through the National Field Quality Assurance (NFQA) program, which began in 1979. For a summary of results from 1979 through 1997, see Stanley et al. (1998). Because quality control is maintained across the years and across different instruments, long term measurement uncertainty is estimated at 5 percent, although measurements made after 1999 should have uncertainties of 3 percent (Wagner et al., 2000).

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D.1.2. Major ion data quality assurance Overall, the major ion dataset analyzed in Chapter 2 had poor quality assurance and quality control. Replicates and blanks for major ion and nitrate analyses were infrequently collected until year 2001 (M.E. Dorsey, U.S. Geological Survey, personal communication, 2005). However, the historic dataset contained instances where multiple water samples were collected within several days of each other, with no intervening change in hydrologic condition. These samples from well BPS in 1980, 1981, 1989, and 1993 can be thought of as sequential replicates. Results from these samples indicate that field and analytical techniques were carried out appropriately, with replicate results being within 5 percent of one another. Despite the minimal amount of QA/QC, the analysis of Chapter 2 was performed with the assumption that methods were carried out appropriately. From year 2001 onward, results of quality control samples suggest that field techniques were carried out appropriately (Table D 1). The only detection in a blank is calcium at 10 g/L, which is over three orders of magnitude less than the smallest environmental sample concentration. A replicate sample as well PLS showed essentially identical concentrations. Throughout the study period, the National Water Quality Laboratory performed ongoing internal quality control, including the use of standard reference materials, laboratory replicates, data review, blind samples, and performance

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evaluation studies (Pritt and Raese, 1995). The results of internal NWQL quality control are not part of the published USGS data record. D.1.3. Data screening Two additional criteria were used to screen some analytical results from the large historical record used in Chapter 2. First, water analyses with a charge balance error greater than 5 percent were excluded. Second, wells with fewer than six specific conductance measurements were excluded, as they did not provide a sufficient record for statistical analysis. D.2. MAJOR IONS, 20032005 (CHAPTER 3) Two years of major ion data were analyzed by the USGS and were used in Chapter 3. The USGS National Water Quality Lab (NWQL) in Denver, Colorado maintains a strict internal QA/QC program, including the use of standard reference materials, laboratory replicates, data review, blind samples, and performance evaluation studies (Pritt and Raese, 1995). An external lab QA/QC program was also developed for this major ion analysis, based upon protocols outlined in Wilde et al. (1999). Overall, 10 percent of all collected samples were designated for QA/QC purposes.

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Major cation (Ca+2, Mg2+, Na+, K+, Sr2+) concentrations, and non carbonate anion (Cl, SO4 2 NO3 ) concentrations were analyzed by the NWQL. Carbonate ion (HCO3 CO3 2 ) were analyzed by the USGS Austin Water Quality laboratory. D.2.1. Cations and non carbonate anions Inorganic grade blank water was sampled and processed identically to standard environmental samples. These blank samples are known as field blanks because the blank analysis traces the full analytical procedure, from sample collection to final analysis. The reported level can be thought of as a background concentration level introduced by the cumulative effects of the entire procedure. Replicate samples were also collected. The style of replicate employed is known as a sequential replicate, wherein samples of water are taken from the same site within minutes of each other. Assuming no very short term variability in the site (including incompletely mixed waters), this method effectively tests the collection, processing, and analysis chain of analysis. D.2.2. Carbonate anions Carbonate ions (HCO3 and CO3 2 ) were measured using titrimetric methods with sulfuric acid, and carbonate speciation was calculated using the inflection point

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method. Quality was assured using field replicates that were sequentially collected and sequentially analyzed. The USGS National Field Quality Assurance program (e.g., Stanley et al., 1998) is implemented to ensure that carbonate ion measurements from individual USGS water quality laboratories are comparable to one another on a nationwide basis. During the period of study, this program sent sets of unknown samples to USGS offices nationwide. These studies were carried out in May 2004 and May 2005. D.2.3. Summary Analysis of this full set of QA/QC data by USGS data evaluators indicated that laboratory techniques were carried out appropriately (B.J. Mahler, U.S. Geological Survey, personal comm., 2005). The USGS does not generally publish results of their QA/QC unless specifically requested by a cooperating agency. These data, however, are of public record and are available on request from the USGS. D.3. STRONTIUM ISOTOPES (CHAPTER 3) D.3.1. NBS 987 standard Analyses of NBS 987 standards (Table D 2) resulted in a mean value of 0.710265 (n=10, 2 =0.000015). The measured values for the NBS 987 standard may have decreased slightly between December 2003 and July 2005 (Figure D 1).

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However, the post July 2005 measurements remained within the analytical uncertainty of the pre July 2005 measurements, so a correction was not applied to any analytical results. D.3.2. Laboratory blanks Laboratory blanks are a way of measuring the background level, or amount of contamination, introduced by the ambient laboratory environment and the analysis procedure. A laboratory blank is prepared for analysis identically to a normal (i.e., environmental) sample, except that a solution of strontium spike of known molarity and isotopic composition is dispensed instead of sample water. In the same way that an environmental sample is processed, a laboratory blank is dried down, passed through Sr spec resin columns, dried down again, and dispensed onto a tantalum filament (see Appendix E). Blank samples were analyzed by isotope dilution. Laboratory and analysis procedures added an insignificant amount of strontium to sample analyses. A laboratory blank analysis in July 2004 contained 4 picograms (pg) of strontium, and a laboratory blank in August 2005 contained 7 pg of strontium. For all environmental sample analyses, a minimum of 2 g (2,000,000 pg) of strontium was dispensed onto a tantalum filament. Thus, the sample to blank

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ratio is over 200,000:1, which is over 2 orders of magnitude above the generally accepted minimum 1,000:1 sample to blank ratio. D.3.3. Field blank A field blank measures the total amount of strontium added by the process of sample collection, processing, and analysis. For a field blank, nanopure water is taken to a sampling site and dispensed into a sampling container. This blank sample is then treated identically to a normal sample, except that a spike solution is added during laboratory work to permit analysis by isotope dilution. Combined sample collection, processing, and analysis methods added an insignificant amount of strontium to sample analyses. A field blank collected in June 2005 and analyzed in August 2005 contained 150 pg of strontium. Because the analysis procedure involved drying down 5 mL of this sample, this suggests that the entire sampling procedure adds approximately 30 pg/mL of strontium. The smallest dissolved Sr concentration analyzed in this thesis was 200 g/L, or 200,000 pg/mL. Thus, the sample to blank ratio is over 6,000:1well above the generally accepted minimum 1,000:1 sample to blank ratio.

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D.3.4. Replicate Sample A replicate analysis was performed in July 2004. Two full separate analyses were performed on water from two separate sample bottles that were collected sequentially from Old Mill Spring (OSP) on Sepember 30, 2003. 87Sr/86Sr values from these two analyses were 0.708009 and 0.707996, which are within the 0.000015 external precision used for reported values in this thesis. These data indicate that sample collection, processing, and analysis methods were reproducible. D.4. OXYGEN ISOTOPES (CHAPTERS 3 AND 4) During analysis, approximately 1 primary laboratory standard sample (Berkeley Tap Water) was analyzed for every 10 environmental samples (Table D 3). All analyses were equal to the accepted standard values, within the standard 0.1 external precision. A secondary laboratory standard sample (BEVO) was also analyzed alongside environmental samples, approximately one standard analyzed for every two environmental samples. The secondary standard measurements were corrected to the accepted standard value, thus correcting for evaporation that may have occurred during sample dispensing and processing. Two sample bottles were sequentially filled from well YD 58 50 231 on September 30, 2003. Each sample bottle was then analyzed independently in January 2005. The two measured values were .85 and .87, which are within the

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0.1 external precision used for reported values in this thesis. These data indicate that sample collection and analysis methods were reproducible. D.5. HYDROGEN ISOTOPES (CHAPTERS 3 AND 4) Hydrogen analyses were performed by the Stable Isotope Laboratory at Southern Methodist University. This laboratory maintained an internal quality assurance program, summarized as follows: At least one in house laboratory standard is analyzed with each set of unknown samples. Isotopic values are determined versus working gas standards that have been calibrated against international standards. International standards are run periodically as a check on the isotopic composition of the working gas standards. (K. Ferguson, Southern Methodist University, written comm., 2005). In addition to internal lab quality assurance, 11 replicates were analyzed. Unlike strontium and oxygen replicates, these replicates were splits taken from a single sample container by the laboratory. As such, these split replicates do not test for temporal variability in water at the site, or variability in sample collection and processing techniques. However, other sequential replicate analyses described in this appendix suggest that these effects were not of concern for the sites and methods in this thesis.

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Results of split replicates (Table D 4) suggest that the standard external precision of 1 for 2H values may not be large enough to encompass the analytical uncertainty seen in these samples, as nearly 50 percent of the replicates analyses had a difference greater than 1. However, these uncertainties did not affect the conclusions reached in this study, as all samples plotted near the global meteoric water line (Figures 3 10 and 4 5).

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Figure D 1 Measurements of the SRM NBS 987 standard as a function of time, using the University of Texas at Austins FinniganMAT 261 thermal ionization mass spectrometer. There may be a slight decreasing trend, but any such trend is within the external 2 precision of 0.000015 noted on the diagram. 0.71020 0.71022 0.71024 0.71026 0.71028 0.71030A u g 0 3D e c 0 3A p r 0 4 A u g 0 4 D e c 0 4 A p r 0 5 A u g 0 587Sr/86Sr

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Table D 1. Quality assurance data for the major ion dataset used in Chapter 2.Site IDDate Specific conductance ( S/cm) Ca (mg/L) Mg (mg/L) Na (mg/L) K (mg/L) HCO3 (mg/L) Cl (mg/L) SO4 (mg/L) NO3 N (mg/L) SEQUENTIAL REPLICATES BPS8/1/1980583722561.233110221.6 BPS8/29/1980578732661.033111270.3 BPS7/30/1981583742671.232910280.1 BPS8/12/1981568742561.334210251.2 BPS7/17/1989563752661.234310241.3 BPS8/29/1989581782671.133810251.3 BPS8/19/1993539762561.134210261.3 BPS8/20/1993579792571.232910261.4 BLANK SAMPLES SVE 6/14/2001< 310.02< .008< .06< .09< .08< .1< .05 SVE 8/8/2002< 3E 0.012< .008< .09< .1< .3< .1< .05 REPLICATE SAMPLE PLS5/23/2002570782471.129613181.5 PLS 5/23/2002572782471.113181.4 1 Concentration was below detection limi t 2 Concentration was below method reporting level, concentration estimate d

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Table D 2. Analytical results for the SRM NBS 987 standard.Analysis Date87Sr/86Sr Internal precision (2 ) 01/05/040.710266 0.000007 01/05/040.710284 0.000008 08/17/040.710272 0.000008 08/17/040.710262 0.000008 08/07/050.710251 0.000008 08/07/050.710260 0.000008 08/14/050.710270 0.000008 08/14/050.710258 0.000007 08/17/050.710268 0.000007 08/17/050.710263 0.000007 Mean: 0.710265 0.000015 (external precision)

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Table D 3. Standards analyzed during 18O analysis at the University of Texas. The primary standard s accepted value was 12.7 and the secondary standard s accepted value was 2.6. The secondary standard measurements were corrected to the accepted values, to account for fractionation during analysis.Analysis date 18O ()Internal precision (2 ) Berkeley Tap Water prinary lab standard 10/29/03 12.90 0.006 10/29/03 12.82 0.009 11/6/03 12.85 0.015 11/6/03 12.84 0.011 1/23/05 12.70 0.014 1/23/05 12.69 0.011 1/26/05 12.71 0.004 1/26/05 12.69 0.007 BEVO secondary lab standard 10/29/03 2.64 0.011 10/29/03 2.67 0.008 10/29/03 2.61 0.007 10/29/03 2.57 0.016 1/23/05 2.66 0.008 1/23/05 2.66 0.006 1/23/05 2.64 0.008 1/23/05 2.62 0.009 1/23/05 2.64 0.009 1/23/05 2.63 0.006 1/23/05 2.61 0.005 1/23/05 2.63 0.007 1/23/05 2.66 0.007 1/26/05 2.65 0.011 1/26/05 2.64 0.006 1/26/05 2.67 0.007 1/26/05 2.62 0.006 1/26/05 2.65 0.007 1/26/05 2.69 0.01 1/26/05 2.66 0.008 1/26/05 2.62 0.009 1/26/05 2.62 0.008

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Table D 4. Replicate analysis results for hydrogen isotope samples, analyzed at Southern Methodist University. Site IDSample date Sample time 2H () 2H Repeat ()Difference () M SP9/3/20038:00 25.2 26.51.3 ESP9/25/20039:30 22.9 22.70.2 ALB9/29/20039:30 24.2 22.51.7 ESP8/25/200410:30 26.1 26.10.1 BPS5/24/200511:30 23.0 24.31.3 SV W 5/23/200512:00 20.6 19.70.9 FO W 5/26/200511:30 27.4 25.81.6 SV N 6/14/200510:00 21.4 21.60.2 SVE6/15/200512:00 28.7 27.31.3 USP5/11/20057:30 22.7 22.30.4 M SP 10/25/2004 1 10:30 29.6 29.6 1 0.0 1 The first repeat analysis of this sample measured 27.8. A third repeat analysis resulted in the reported value.

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APPENDIX E. Methods for isotopic analysis E.1. ISOTOPE SAMPLING EQUIPMENT CLEANING Prior to collecting a sample, some the following cleaning procedures were carried out on plastic sample bottles: 1) 24 hour soak in distilled water + soap solution (Micro) 2) Thorough rise of each bottle, 5 times 3) 24 hour soak in distilled water 4) Brief rinse of each bottle 5) 48 hour soak in 20 percent nitric acid solution 6) Thorough rinse of each bottle, 3 times 7) 24 hour soak in deionized (not distilled) water 8) Drying in laminar flow vent hood For glass sample containers (oxygen and hydrogen isotopes), these procedures are the same, except for the omission of steps involving acid rinsing (steps 5 and 6). E.2. SAMPLE COLLECTION To collect a sample from a springs, the following steps were performed: (1) rinse the bottle once with water from the collection site; (2) immerse the bottle into

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the sample source, filling completely with water; (3) cap and remove the bottle from the sample source; (4) wrap bottle cap with ParaFilm; (5) store in dark, refrigerated conditions. E.3. SAMPLE STORAGE AND DATA MANAGEMENT I was responsible for collecting water samples for isotopic analysis (i.e., Chapters 3 and 4). While these samples were collected concurrently with USGS water quality samples, they were not tracked by the USGS National Water Information System (NWIS). At the outset of my graduate education, I issued this challenge to myself: Never lose track of a sample bottle, and never ambiguously identify a sample bottle or its analytical results. Traditionally, scientists use spreadsheets to track water samples and results, but spreadsheets present data management problems. The potential for human error, plus subtle errors arising from manually copying and pasting data in spreadsheets can lead to lost and misidentified samples. Also, spreadsheets have limited data summarizing and manipulation abilities. To keep track of these samples and their analysis results, I designed a relational database. Broadly speaking, the database consisted of four tables: Site, Sample, Result, and Parameter. Additional tables were added to track batches of samples as they were analyzed in the laboratory. For a thorough introduction to the

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subject of relational databases, consider an introductory level database textbook such as Silberschatz et al. (2002). Despite having a digital database with all sample information, sample bottles had self explanatory labels that contained all of the information needed to positively identify a sample, in the event of catastrophic digital data loss. The sample label contained (1) site name; (2) sampling date and time; (3) typical analysis for this container; (4) whether the sample was filtered and acidified; (5) whether the sample has been analyzed or not; (6) whether the sample has been placed into archival storage; and (7) a unique numeric sample identifier that cross referenced to the relational database. E.4. HOLDING TIME CONSIDERATIONS Some isotope samples were stored for up to 23 months before being analyzed. When water is removed from its original environment and placed in a sample container, it can undergo alterations to its chemical and isotopic composition. Therefore, it is important to consider whether isotopic ratio being measured could have changed in the sample bottle during this time. Strontium isotope ratios for samples in this thesis were unlikely to change measurably while the water was stored in its sample container. Decay of 87Rb to 87Sr is very slow (t1/2 = 48.8 Ga), and ratios will not change measurably during our

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lifetime (McNutt, 2000). There are natural processes that can fractionate Sr isotopes (thus altering the 87Sr/86Sr ratio), but the effects are negligible (Banner and Kaufman, 1994). Thus, Sr isotope analyses of water samples are not measurably affected by processes such as evaporation, biological activity, and mineral precipitation. However, Sr isotopic ratios of waters can be significantly (i.e., measurably) affected by mineral dissolution, ion exchange with clays, and leaching from sample containers. Mineral dissolution and ion exchange are not significant post collection processes for this thesis samples, as the sample waters either had low turbidity (< 2 NTU) or were filtered to remove particulates. Leaching from the sample container was minimized by pre cleaning the containers with a strong, trace element grade HNO3 nitric acid solution. Oxygen and hydrogen isotope ratios are unlikely to measurably change while water is held in a sample container. Evaporation is the most significant concern for fractionation in these samples, and was prevented by using glass containers wrapped with ParaFilm and ensuring there was zero headspace (no air) in the container after sampling. Oxygen and hydrogen also can be modified by exchange with solid minerals including silicate clays, carbonate minerals, and even the glass walls of a sample container. This is because of the hydrolosis reaction

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2H2O + SiO2 < > H4SiO4(aq) where there is an exchange of oxygen atoms between water molecules and quartz. However, the amount of oxygen in water (56 mol/L) which is much larger than the typical molarity of all dissolved ions in most natural waters (say, 0.001 to 0.010 mol/L). Furthermore, the kinetics of isotope exchange between quartz and water are very slow; a study by Longinelli et al. (2004) found that glass from a sunken ship had only developed a 900 nanometer zone of alteration after 1800 years of exposure to an infinite reservoir of seawater. E.5. SAMPLE ANALYSIS Strontium isotope samples were analyzed at The University of Texas at Austin. Each sample was evaporated and then redissolved in 3N HNO3. This solution was passed through a Sr spec resin column to selectively sequester dissolved Sr2+. Sr2+ was eluted from the column using 0.1N HNO3. The eluted solution was evaporated, redissolved in 0.01N phosphoric acid, and dispensed onto a tantalum filament. The filament was placed into a Finnigan MAT 261 thermal ionization mass spectrometer. The heated, ionized sample was analyzed in dynamic collection mode. To correct for strontium fractionation during ionization, the measured 84Sr/88Sr ratio was corrected to a value of 0.1194, and the other ratios (namely, 87Sr/86Sr) were corrected using an exponential fractionation law (Banner and

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Kaufman, 1994). Standard samples, blank water samples, and a replicate sample were analyzed in order to ensure precision and accuracy (see Appendix D). Oxygen isotope samples were analyzed at The University of Texas at Austin. Samples were dispensed into glass vials filled with carbon dioxide gas, and were allowed to equilibrate with this gas for 8 hours at 40C. The carbon dioxide gas was fed into a light isotope mass spectrometer alternately with a reference gas of known isotopic composition (Epstein and Mayeda, 1953). Approximately one third of analyzed samples were internal lab standards, and external precision was estimated to be 0.1 or better (see Appendix D). Hydrogen isotope samples were analyzed at Southern Methodist University. Samples were passed over depleted uranium metal at 800C (Bigeleisen et al., 1952), which reduced the hydrogen in the water molecule to H2 gas. The H2 gas was collected onto activated carbon, and then analyzed by mass spectrometer. Internal laboratory standards were analyzed frequently, but not reported by the lab. The lab reports that results from standard and duplicate analyses define an analytical precision of 1.2 or better (see Appendix D)

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E.6. RESULTS REPORTING Strontium isotope ratios are reported as the ratio of 87Sr to 86Sr (87Sr/86Sr). Oxygen and hydrogen isotopes are reported using delta notation (Gonfiantini, 1981; Coplen, 1994), and are referenced to standard mean ocean water (SMOW).

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Figure E 1 Samples that required filtration were pumped through a 0.45 m cellulose filter that was placed in a polycarbonate housing. Tygontubing and a peristaltic pump was used to pump water, typically from a 3 liter Teflon bottle or a 1 liter polypropylene bottle.

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VITA Brad Garner was born on February 28, 1977 in Irving, Texas, the first child of Steve and Ann Garner. He graduated from Arlington High School in May 1995. Beginning in August 1995, he attended the University of Texas at Austin. Despite majoring in computer science, he spent his carefree collegiate summers as a seasonal park ranger at Great Sand Dunes National Park. In August 1999, he received his Bachelor of Science. After spending three and a half years as a professional software engineer in Austin, he discovered that software engineering was neither suited to him nor sustainable as a career path. He survived this quarter life crisis, began working part time at the United States Geological Survey, and enrolled in the University of Texas Jackson School of Geosciences in August 2003. Permanent Address: 209 Mill Creek Drive Arlington, TX 76010 This thesis was typed by the author.