Hydrogeology Journal

, Volume 24, Issue 8, pp 2017–2033 | Cite as

Characterization of mean transit time at large springs in the Upper Colorado River Basin, USA: a tool for assessing groundwater discharge vulnerability

  • John E. Solder
  • Bernard J. Stolp
  • Victor M. Heilweil
  • David D. Susong
Paper

Abstract

Environmental tracers (noble gases, tritium, industrial gases, stable isotopes, and radio-carbon) and hydrogeology were interpreted to determine groundwater transit-time distribution and calculate mean transit time (MTT) with lumped parameter modeling at 19 large springs distributed throughout the Upper Colorado River Basin (UCRB), USA. The predictive value of the MTT to evaluate the pattern and timing of groundwater response to hydraulic stress (i.e., vulnerability) is examined by a statistical analysis of MTT, historical spring discharge records, and the Palmer Hydrological Drought Index. MTTs of the springs range from 10 to 15,000 years and 90 % of the cumulative discharge-weighted travel-time distribution falls within the range of 2−10,000 years. Historical variability in discharge was assessed as the ratio of 10–90 % flow-exceedance (R10/90%) and ranged from 2.8 to 1.1 for select springs with available discharge data. The lag-time (i.e., delay in discharge response to drought conditions) was determined by cross-correlation analysis and ranged from 0.5 to 6 years for the same select springs. Springs with shorter MTTs (<80 years) statistically correlate with larger discharge variations and faster responses to drought, indicating MTT can be used for estimating the relative magnitude and timing of groundwater response. Results indicate that groundwater discharge to streams in the UCRB will likely respond on the order of years to climate variation and increasing groundwater withdrawals.

Keywords

Environmental tracers Groundwater age Climate change Groundwater vulnerability USA 

Caractérisation du temps de transit moyen pour de grandes sources du bassin versant du Colorado supérieur, Etats-Unis d’Amérique: un outil pour évaluer la vulnérabilité de la décharge des eaux souterraines

Résumé

Les traceurs environnementaux (gaz nobles, tritium, gaz industriels, isotopes stables, et carbone radioactif) et l’hydrogéologie ont été interprétés pour déterminer la répartition du temps de transit des eaux souterraines et calculer le temps de transit moyen (TTM) à l’aide d’une modélisation globale à paramètres pour 19 grandes sources réparties sur l’ensemble du bassin versant du Colorado supérieur (UCRB), Etats-Unis d’Amérique. La valeur prédictive du TTM pour évaluer le schéma et le temps de réponse des eaux souterraines au stress hydraulique ( à savoir, la vulnérabilité) est examinée à l’aide d’une analyse statistique des TTM, des débits historiques enregistrés des sources, et de l’indice de sécheresse hydrologique de Palmer. Les TTM des sources est compris entre 10 à 15,000 ans et 90 % de la distribution du débit cumulé pondéré par le temps de transit se situent dans la fourchette comprise entre 2 à 10,000 ans. La variabilité historique du débit a été évaluée comme étant le rapport de 10–90 % du flux excédentaire (R10/90%) et variait de 2.8 à 1 .1 pour certaines sources à partir de données de débit disponibles. Le temps de latence (à savoir, le retard dans la réponse du débit par rapport aux conditions de sécheresse) a été déterminé par une analyse de corrélation croisée et variait de 0.5–6 ans pour la même sélection de sources. Les sources avec des TTM plus courtes (<80 ans) sont corrélées statistiquement avec de plus grandes variations de débit et des réponses plus rapides à la sécheresse, indiquant que le TTM peut être utilisé pour estimer l’importance relative et le temps de réponse des eaux souterraines. Les résultats indiquent que la décharge des eaux souterraines vers les cours d’eau dans le UCRB répondra probablement à la variation climatique et à l’augmentation des prélèvements d’eaux souterraines dans un laps de temps correspondant à l’ordre de grandeur des années.

Caracterización del tiempo de tránsito medio en grandes manantiales de la cuenca superior del río Colorado, EEUU: una herramienta para evaluar la vulnerabilidad de la descarga del agua subterránea

Resumen

Se interpretaron los trazadores ambientales (gases nobles, tritio y gases industriales, isótopos estables y radio-carbono) y la hidrogeología para determinar la distribución de los tiempos de tránsito y calcular el tiempo de tránsito medio (MTT) del agua subterránea con el modelado de parámetros concentrados en 19 grandes manantiales distribuidos a través de la cuenca alta del río Colorado (UCRB), EEUU. Se examina el valor predictivo del MTT para evaluar el patrón y el tiempo de respuesta del agua subterránea al estrés hídrico (es decir, la vulnerabilidad) a través de un análisis estadístico de MTT, registros históricos de descarga de manantiales, y el Índice de Sequía Hidrológica de Palmer. Los MTTs de los manantiales abarcan un intervalo de 10–15,000 años y el 90 % de la distribución de tiempo de tránsito de la descarga ponderada acumulativa cae dentro del rango de 2–10,000 años. Se evaluó la variabilidad histórica de la descarga como una relación del 10 al 90 % del flujo de excedencia (R10/90%) y variaba desde 2.8 a 1.1 para los manantiales con datos disponibles de descarga. El tiempo de retardo (es decir, el retardo en la respuesta de descarga en condiciones de sequía) se determinó mediante análisis de una correlación cruzada con un rango entre 0.5 a 6 años para los mismos manantiales seleccionados. Los manantiales con MTT más cortos (<80 años) se correlacionan estadísticamente con las variaciones de descarga más grandes y las respuestas más rápidas a la sequía, lo que indica el MTT se puede utilizar para la estimación de la magnitud relativa y el tiempo de respuesta del agua subterránea. Los resultados indican que la descarga de agua subterránea a los arroyos en el UCRB es probable que respondan en el orden de años a la variación del clima y al aumento de extracción de agua subterránea.

美国上科罗拉多河流域大泉地区地下水的平均通过时间描述:评价地下水排泄脆弱性的工具

摘要

利用分布在美国上科罗拉多河流域19个大泉的集中参数模拟解译了环境示踪剂(惰性气体、氚、工业气体、稳定同位素及放射性碳)和水文地质状况,以确定地下水通过时间分布和计算平均通过时间。利用平均通过时间统计分析、泉排泄历史记录和Palmer水文干旱指数检查了评估地下水对水力应力(即脆弱性)响应的模式和时间选择的平均通过时间预测值。泉的平均通过时间从10年到15,000年不等,90%累计排泄-加权通过时间分布范围2–10,000年。以10到90%的流量超过数比值(R10/90%)评价了排泄量的历史变异性,根据现有的排泄数据,所选的泉范围可变性为2.8到1.1。通过交叉对比分析确定了延迟时间(即排泄对干旱条件的响应延迟),同样所选的泉延迟时间为0.5 到6年。平均通过时间较短的泉( < 80年)统计上和较大的排泄变化相对应,对干旱的响应更快,表明平均通过时间可用来估算地下水响应的相对值和时间选择。结果表明,上科罗拉多河流域地下水排泄到河流很可能对气候变化的年度顺序和增加的地下水抽取量做出响应。

Caracterização do tempo médio de trânsito nas grandes nascentes da Bacia do Alto Rio Colorado, EUA: uma ferramenta para avaliar a vulnerabilidade da vazão da água subterrânea

Resumo

Traçadores ambientais (gases nobres, trítio, gases industriais, isótopos estáveis, e radiocarbono) e a hidrogeologia foram interpretados para determinar a distribuição do tempo de trânsito da água subterrânea e calcular o tempo médio de trânsito (TMT) utilizando modelagem de parâmetros concentrados em 19 grandes nascentes distribuídas pela Bacia do Alto Rio Colorado (BARC), EUA. O valor predito do TMT para avaliar o padrão e o tempo de resposta da água subterrânea após um estresse hidráulico (p.ex., vulnerabilidade) é examinado através da análise estatística do TMT, dos registros históricos da vazão das nascentes, e do Índice Hidrológico de Sêca de Palmer. Os TMTs das nascentes variam de 10 a 15,000 anos e 90 % da distribuição acumulada do tempo de trânsito ponderado pela descarga recai entre 2 e 10,000 anos. A variabilidade histórica da descarga foi avaliada através da razão entre 10 e 90 % do fluxo-limite (R10/90%) e variou de 2.8–1.1 para as nascentes selecionadas com dados de vazão disponíveis. O tempo de atraso (tempo decorrido entre o início das condições de sêca e a resposta da vazão) foi determinado através de análise de correlação cruzada e variou de 0.5–6 anos para as mesmas nascentes selecionadas. Nascente com TMTs mais curtos (<80 anos) correlacionam-se estatisticamente com variações de vazão maiores e respostas à sêca mais rápidas, indicando que o TMT pode ser utilizado para estimar a magnitude relativa e o tempo de resposta da água subterrânea. Os resultados indicam que a descarga de água subterrânea nos rios da BARC provavelmente responderão às variações climáticas e ao aumento da explotação da água subetrrânea na ordem de anos.

Supplementary material

10040_2016_1440_MOESM1_ESM.pdf (10.2 mb)
ESM 1(PDF 10428 kb)
10040_2016_1440_MOESM2_ESM.pdf (535 kb)
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10040_2016_1440_MOESM3_ESM.pdf (752 kb)
ESM 3(PDF 752 kb)

References

  1. Aeschbach-Hertig W, Peeters F, Beyerle U, Kipfer R (2000) Palaeotemperature reconstruction from noble gases in ground water taking into account equilibration with entrapped air. Nature 405:1040–1044. doi:10.1038/35016542 CrossRefGoogle Scholar
  2. Andrews JN (1985) The isotopic composition of radiogenic helium and its use to study groundwater movement in confined aquifers. Chem Geol 49:339–351. doi:10.1016/0009-2541(85)90166-4 CrossRefGoogle Scholar
  3. Borsa AA, Agnew DC, Cayan DR (2014) Ongoing drought-induced uplift in the western United States. Science 26(345):1587–1590. doi:10.1126/science.1260279 CrossRefGoogle Scholar
  4. Brauch NJ, Apodaca LE (1995) Bibliography, indices, and data sources of water-related studies, Upper Colorado River Basin, Colorado and Utah, 1872–1995, US Geol Surv Open File Rep 95-450Google Scholar
  5. Bredehoeft JD (2010) Monitoring regional groundwater extraction: the problem. Groundwater 49(6):808–814. doi:10.1111/j.1745-6584.2011.00799 CrossRefGoogle Scholar
  6. Busenberg E, Plummer LN (2000) Dating young groundwater with sulfur hexafluoride: natural and anthropogenic sources of sulfur hexafluoride. Water Resour Res 36(10):3011–3030. doi:10.1029/2000WR900151 CrossRefGoogle Scholar
  7. Busenberg E, Plummer LN (2014) A 17-year record of environmental tracers in spring discharge, Shenandoah National Park, Virginia, USA: use of climatic data and environmental conditions to interpret discharge, dissolved solutes, and tracer concentrations. Aquat Geochem 20(2–3):267–290Google Scholar
  8. Castle SL, Thomas BF, Reager JT, Rodell M, Swenson SC, Famiglietti JS (2014) Groundwater depletion during drought threatens future water security of the Colorado River Basin. Geophys Res Lett 41(16):5904–5911. doi:10.1002/2014GL061055 CrossRefGoogle Scholar
  9. Christensen NS, Lettenmeier DP (2007) A multimodel ensemble approach to assessment of climate change impacts on the hydrology and water resources of the Colorado River Basin. Hydrol Earth Syst Sci 11(4):1417–1434CrossRefGoogle Scholar
  10. Cook BI, Ault TR, Smerdon JE (2015) Unprecedented 21st-century drought risk in the American Southwest and Central Plains. Sci Adv (1)1, e1400082. doi:10.1126/sciadv.1400082
  11. Cook PG, Böhlke JK (2000) Determining the timescales for groundwater flow and solute transport. In: Cook PG, Herczeg AL (eds) Environmental tracers in subsurface hydrology. Kluwer, Boston, pp 1–30CrossRefGoogle Scholar
  12. Davis PJ (1972) Gamma and related functions. In: Abramowitz M, Stegun IA (eds) Handbook of mathematical functions. Dover, New York, pp 253–295Google Scholar
  13. Dunn SM, Birkel C, Tetzlaff D, Soulsby C (2010) Transit time distributions of a conceptual model: their characteristics and sensitivities. Hydrol Process 24(12):1719–1729. doi:10.1002/hyp.7560 CrossRefGoogle Scholar
  14. Engdahl NB, Maxwell RM (2015) Quantifying changes in age distributions and the hydrologic balance of a high-mountain watershed from climate induced variations in recharge. J Hydrol 522:152–162CrossRefGoogle Scholar
  15. Flora SP (2004) Hydrogeological characterization and discharge variability of springs in the Middle Verde River Watershed, Central Arizona. MSc Thesis, Univ. Arizona. https://nau.edu/uploadedFiles/Academic/CEFNS/NatSci/SESES/Research/Geology/flora04.pdf. Accessed 25 July 2015
  16. Freethey GW, Cordy GE (1991) Geohydrology of Mesozoic rocks in the Upper Colorado River Basin in Arizona, Colorado, New Mexico, Utah, and Wyoming, excluding the San Juan Basin. US Geol Surv Prof Pap 1411-CGoogle Scholar
  17. Frisbee MD, Phillips FM, Campbell AR, Liu F, Sanchez SA (2011) Streamflow generation in a large alpine watershed in the southern Rocky Mountains of Colorado: is streamflow generation simply an aggregation of hillslope runoff responses? Water Resour Res 47(6)Google Scholar
  18. Gardner PM, Heilweil VM (2014) A multiple-tracer approach to understanding regional groundwater flow in the Snake Valley area of the eastern Great Basin, USA. Appl Geochem 45:33–49CrossRefGoogle Scholar
  19. Geldon AL (1991) Hydrologic properties and ground-water flow systems of Paleozoic rocks in the Upper Colorado River Basin in Arizona, Colorado, New Mexico, Utah, and Wyoming, excluding the San Juan Basin, US Geol Surv Prof Pap 1411-BGoogle Scholar
  20. Glover KC, Naftz DL, Martin LJ (1996) Geohydrology of Tertiary rocks in the Upper Colorado River Basin in Colorado, Utah, and Wyoming, excluding the San Juan Basin, US Geol Surv Water Resour Invest Rep 96-4105Google Scholar
  21. Green CT, Zhang Y, Jurgens BC, Starn JJ, Landon MK (2014) Accuracy of travel time distribution (TTD) models as affected by TTD complexity, observation errors, and model and tracer selection. Water Resour Res 50(7):6191–6213. doi:10.1002/2014WR015625 CrossRefGoogle Scholar
  22. Harnish J, Eisenhauer A (1998) Natural CF4 and SF6 on Earth. Geophys Res Lett 25(13):2401–2404CrossRefGoogle Scholar
  23. Harnisch J, Frische M, Borchers R, Eisenhauer A, Jordan A (2000) Natural fluorinated organics in fluorite and rocks. Geophys Res Lett 27(13):1883–1886CrossRefGoogle Scholar
  24. Heilweil VM, Sweetkind DS, Gerner SJ (2014) Innovative environmental tracer techniques for evaluating sources of spring discharge from a carbonate aquifer bisected by a river. Groundwater 52(1):71–83CrossRefGoogle Scholar
  25. Heim RR (2002) A review of twentieth-century drought indices used in the United States. Bull Am Meteorol Soc 83:1149–1165. doi:10.1175/1520-0477 CrossRefGoogle Scholar
  26. Hrachowitz M, Soulsby C, Tetzlaff D, Malcolm IA, Schoups G (2010) Gamma distribution models for transit time estimation in catchments: physical interpretation of parameters and implications for time-variant transit time assessment. Water Resour Res 46(10). doi:10.1029/2010WR009148
  27. Johnson NL, Kotz S, Balakrishnan N (1994) Continuous univariate distributions-1, 2nd edn. Wiley, New YorkGoogle Scholar
  28. Jurgens BC, Böhlke JK,Eberts SM (2012) TracerLPM (Version 1): an Excel® workbook for interpreting groundwater age distributions from environmental tracer data. US Geol Surv Tech Methods Rep 4-F3, 60 ppGoogle Scholar
  29. Kipfer R, Aeschbach-Hertig W, Peeters F, Stute M (2002) Noble gases in lakes and ground waters. In: Porcelli D, Ballentine CJ, Wieler R (eds) Noble gases in geochemistry and cosmochemistry. Mineralogical Society of America, Chantilly, VA, pp 615–700Google Scholar
  30. Land L, Huff GF (2010) Multi-tracer investigation of groundwater residence time in a karstic aquifer: Bitter Lakes National Wildlife Refuge, New Mexico, USA. Hydrogeol J 18(2):455–472CrossRefGoogle Scholar
  31. Liu F, Williams MW, Caine N (2004) Source waters and flow paths in an alpine catchment, Colorado Front Range, United States. Water Resour Res 40, W09401. doi:10.1029/2004WR003076 Google Scholar
  32. Maloszewski P, Zuber A (1996) Lumped parameter models for interpretation of environmental tracer data, In: Manual on mathematical models in isotope hydrology. IAEA, Austria, pp 9–58Google Scholar
  33. Manga M (1996) Hydrology of spring-dominated streams in the Oregon Cascades. Water Resour Res 32, W01238CrossRefGoogle Scholar
  34. Manga M (1999) On the timescales characterizing groundwater discharge at springs. J Hydrol 219(1–2):56–69CrossRefGoogle Scholar
  35. Manning AH, Clark JF, Diaz SH, Rademacher LK, Earman S, Plummer LN (2012) Evolution of groundwater age in a mountain watershed over a period of thirteen years. J Hydrol 460:13–28, doi:10.1016/j.jhydrol.2012.06.030
  36. Massoudieh A (2013) Inference of long-term groundwater flow transience using environmental tracers: a theoretical approach. Water Resour Res 49(12):8039–8052. doi:10.1002/2013WR014548 CrossRefGoogle Scholar
  37. Massoudieh A, Leray S, de Dreuzy JR (2014a) Assessment of the value of groundwater age time-series for characterizing complex steady-state flow systems using a Bayesian approach. Appl Geochem 50:240–251Google Scholar
  38. Massoudieh A, Visser A, Sharifi S, Broers HP (2014b) A Bayesian modeling approach for estimation of a shape-free groundwater age distribution using multiple tracers. Appl Geochem 50:252–264Google Scholar
  39. McGuire KJ, McDonnell JJ (2006) A review and evaluation of catchment transit time modeling. J Hydrol 330(3–4):543–563. doi:10.1016/j.jhydrol.2006.04.020 CrossRefGoogle Scholar
  40. McMahon PB, Thomas JC, Hunt AG (2013) Groundwater ages and mixing in the Piceance Basin Natural Gas Province, Colorado. Environ Sci Technol 47(23):13250–13257. doi:10.1021/es402473c CrossRefGoogle Scholar
  41. Meinzer OE (1927) Large springs in the United States. US Geol Surv Water Supp Pap. http://pubs.er.usgs.gov/publication/wsp557. Accessed June 2016
  42. Miller MP, Susong DD, Shope CL, Heilweil VM, Stolp BJ (2014) Continuous estimation of baseflow in snowmelt-dominated streams and rivers in the Upper Colorado River Basin: a chemical hydrograph separation approach. Water Resour Res 50(8):6986–6999. doi:10.1002/2013WR014939 CrossRefGoogle Scholar
  43. National Climatic Data Center (2016) www.ncdc.noaa.gov. Accessed June 2016
  44. Netopil R (1971) Ke Klasifikaci pramenu podle variability vydatnasti [The classification of water springs on the basis of the variability of yields]. Sbornik-Hydrological Conference, Papers. Stud Geogr. In: Alfaro C, Wallace M (1994) Origin and classification of springs and historical review with current applications. Environ Geol 24(2):112–124. doi:10.1007/BF00767884
  45. Pearson FJ, Balderer W, Loosli HH, Lehman BE, Matter A, Peters T, Schmassman H, Gautschi A (1991) Applied isotope hydrology: a case study in northern Switzerland. Elsevier, AmsterdamGoogle Scholar
  46. Plummer LN, Busenberg E (2000) Chlorofluorcarbons. In: Cook P, Herczeg AL (eds) Environmental tracers in subsurface hydrology. Kluwer, Boston, pp 441–478Google Scholar
  47. Porporato A, Calabrese S (2015) On the probabilistic structure of water age. Water Resour Res 51(5):3588–3600. doi:10.1002/2015WR017027 CrossRefGoogle Scholar
  48. Pulwarty R, Jacobs K, Dole R (2005) The hardest working river: drought and critical water problems on the Colorado. In: Wilhite D (ed) Drought and water crises: science, technology and management. Taylor and Francis, New York, pp 249–285Google Scholar
  49. R Core Team (2014). R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/. Accessed 14 September 2013
  50. Rumsey CA, Miller MP, Susong DD, Tillman FD, Anning DW (2015) Regional scale estimates of baseflow and factors influencing baseflow in the Upper Colorado River Basin. J Hydrol Reg Stud 4:91–107. doi:10.1016/j.ejrh.2015.04.008 CrossRefGoogle Scholar
  51. Schlosser P, Stute M, Dorr H, Sonntag C, Munnich KO (1988) Tritium/3He dating of shallow groundwater. Earth Planet Sci Lett 89:353–362CrossRefGoogle Scholar
  52. Schlosser P, Stute M, Sonntag C, Munnich KO (1989) Tritiogenic 3He in shallow groundwater. Earth Planet Sci Lett 94:245–256CrossRefGoogle Scholar
  53. Seager R, Ting M, Held I, Kushnir Y, Lu J, Vecchi G, Huang H, Harnik N, Leetmaa A, Lau N, Li C, Velez J, Naik N (2007) Model predictions of an imminent transition to a more arid climate in southwestern North America. Science 316:1181–1184CrossRefGoogle Scholar
  54. Solomon DK (2000) 4He in groundwater. In: Cook PG, Herczeg AL (eds) Environmental tracers in subsurface hydrology. Kluwer, Boston, pp 397–424Google Scholar
  55. Suckow A (2014) The age of groundwater: definitions, models and why we do not need this term. Appl Geochem 50:222–230CrossRefGoogle Scholar
  56. Sultana Z, Coulibaly P (2011) Distributed modeling of future changes in hydrological processes of Spencer Creek watershed. Hydrol Process 25(8):1254–1270. doi:10.1002/hyp.7891
  57. Sun RJ, Weeks JB, Grubb HF (1997) Bibliography of the Regional Aquifer-System Analysis (RASA) Program of the US Geological Survey, 1978–96. US Geol Sur Water Resour Invest Rep 97-4074Google Scholar
  58. Tague C, Grant GE (2009) Groundwater dynamics mediate low-flow response to global warming in snow-dominated alpine regions, Water Resour Res 45. doi:10.1029/2008WR007179
  59. Uhlenbrook S, Frey M, Leibundgut C, Maloszewski P (2002) Hydrograph separations in a mesoscale mountainous basin at event and seasonal timescales. Water Resour Res 38(6). doi 10.1029/2001WR000938
  60. US Bureau of Reclamation (2012) Colorado River basin water supply and demand study. http://www.usbr.gov/lc/region/programs/crbstudy/finalreport/. Accessed 12 July 2014
  61. USGS (2015) Reston Groundwater Dating Laboratory water equilibrated tracer concentrations. http://water.usgs.gov/lab/software/air_curve/. Accessed 10 June 2014
  62. Vogel JC (1967) Investigation of groundwater flow with radiocarbon. In: Isotopes in hydrology. IAEA, Austria, pp 355–368Google Scholar
  63. Wilberg DE (1995) Origin of water that discharges from Calf Creek Spring, Garfield County, Utah. US Geol Surv Open-File Rep 95-340. http://pubs.er.usgs.gov/publication/ofr95340. Accessed 20 September 2014
  64. Yager RM, Plummer LN, Kauffman LJ, Doctor DH, Nelms DL, Schlosser P (2013) Comparison of age distributions estimated from environmental tracers by using binary-dilution and numerical models of fractured and folded karst: Shenandoah Valley of Virginia and West Virginia, USA. Hydrogeol J 21(6):1193–1217CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg (outside the USA) 2016

Authors and Affiliations

  • John E. Solder
    • 1
  • Bernard J. Stolp
    • 1
  • Victor M. Heilweil
    • 1
  • David D. Susong
    • 1
  1. 1.US Geological SurveySalt Lake CityUSA

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