Advertisement

Variation in groundwater recharge and surface-water quality due to climatic extremes in semi-arid mountainous watersheds

  • Connor P. NewmanEmail author
Paper
  • 93 Downloads

Abstract

Climate change has the potential to substantially impact groundwater recharge, groundwater/surface-water dynamics, and surface-water quality. Changes in climate could be manifested as decreasing overall snowpack or an increase in the variability of snowpack year-to-year, and may affect wildfire occurrence and severity. Observed climatic extremes, including abnormal seasonal snowfall (both drought and extreme precipitation) and wildfires, have occurred in recent years in a semi-arid region of the Great Basin in the western United States. These climatic extremes have caused focused groundwater recharge following winters with elevated snowfall (2011 and 2017). Groundwater recharge calculated using the water-table fluctuation method, for periods following the elevated snowfall, was more than 10 times greater than previous studies in the basin that utilized distributed recharge calculation methods. Caution must be exercised when using results of these calculations in subsequent analyses such as groundwater flow modeling, to assure that all required assumptions are met and that calculated recharge rates are spatially applicable. Although water-quality changes due to the elevated snowfall were not evident in the surface-water data, several geochemical constituents (Ba, Ca, K, Mg, Na, pH, and specific conductance) indicated statistically significant concentration differences following a downstream wildfire in the watershed (representing the climatic extreme of drought). Both recharge calculations and statistical evaluations of water chemistry were completed using an easily modified Python script, which could be utilized by water managers to aid in water-resource planning under potentially variable future climatic conditions.

Keywords

Climate change Groundwater hydraulics Groundwater recharge USA Water table fluctuations 

Variation de la recharge des eaux souterraines et de la qualité de l’eau de surface en raison des extrêmes climatiques dans les bassins versants montagneux semi-arides

Résumé

Le changement climatique peut peotentiellement impacter de manière substantielle la recharge des eaux souterraines, la dynamique entre les eaux souterraines et les eaux de surface, et la qualité des eaux de surface. Les changements climatiques pourraient se manifester par une diminution globale du manteau neigeux ou par une augmentation de sa variabilité d’une année à l’autre, et peut affecter la gravité et l’occurrence des incendies de forêt. Les extrêmes climatiques observés, y compris les chutes de neige saisonnières anormales (sécheresse et précipitations extrêmes) et les incendies de forêt, se sont produits ces dernières années dans une région semi-aride du Grand Bassin dans l’ouest des États-Unis. Ces extrêmes climatiques ont provoqué une recharge concentrée des eaux souterraines après les hivers caractérisés par des chutes de neige importantes (2011 et 2017). La recharge des eaux souterraines calculée à l’aide de la méthode de fluctuation de la nappe phréatique, pour les périodes suivant les chutes de neige élevées, était plus de 10 fois plus importante que les études antérieures dans le bassin qui utilisaient des méthodes de calcul de la recharge distribuée. Il faut faire preuve de prudence lors de l’utilisation des résultats de ces calculs dans les analyses ultérieures telles que la modélisation des écoulements d’eaux souterraines, afin de s’assurer que toutes les hypothèses requises sont remplies et que les taux de recharge calculés sont spatialement applicables. Bien que les changements de qualité de l’eau dus aux chutes de neige élevées n’aient pas été évidents dans les données concernant les eaux de surface, plusieurs éléments géochimiques (Ba, Ca, K, Mg, Na, pH et conductivité spécifique) ont indiqué des différences de concentration statistiquement significatives après un feu de forêt en aval dans le bassin versant (représentant l’extrême climatique de la sécheresse). Les calculs de recharge et les évaluations statistiques de la chimie de l’eau ont été réalisés à l’aide d’un script Python facilement modifié, qui pourrait être utilisé par les gestionnaires de l’eau pour faciliter la planification des ressources en eau pour des conditions climatiques futures potentiellement variables.

Variación en la recarga de aguas subterráneas y en la calidad de las aguas superficiales debido a los extremos climáticos en las cuencas montañosas semiáridas

Resumen

El cambio climático tiene el potencial de afectar sustancialmente la recarga de las aguas subterráneas, la dinámica de la relación agua subterránea/agua superficial y la calidad de las aguas superficiales. Los cambios en el clima podrían manifestarse como una disminución general de la acumulación de nieve o un aumento en la variabilidad de la acumulación de nieve de un año a otro, y podrían afectar la ocurrencia y severidad de los incendios forestales. En los últimos años, en una región semiárida de la Great Basin, en el oeste de los Estados Unidos, se han producido fenómenos climáticos extremos, como nevadas estacionales anormales (sequías y precipitaciones extremas) e incendios forestales. Estos extremos climáticos han causado una recarga focalizada de las aguas subterráneas después de los inviernos con nevadas elevadas (2011 y 2017). La recarga de aguas subterráneas calculada por el método de fluctuación de la capa freática, para los períodos posteriores a la nevada elevada, fue más de 10 veces mayor que los estudios previos en la cuenca que utilizaron métodos de cálculo de recarga distribuida. Se debe tener precaución al utilizar los resultados de estos cálculos en análisis posteriores, como la modelación del flujo de agua subterránea, para asegurar que se cumplan todas las suposiciones requeridas y que las tasas de recarga calculadas sean aplicables espacialmente. Aunque los cambios en la calidad del agua debido a una elevada nevada no fueron evidentes en los datos de aguas superficiales, varios componentes geoquímicos (Ba, Ca, K, Mg, Na, pH y conductividad específica) indicaron diferencias de concentración estadísticamente significativas después de un incendio forestal río abajo en la cuenca (que representa el extremo climático de la sequía). Tanto los cálculos de recarga como las evaluaciones estadísticas de la química del agua se completaron utilizando un Python script fácilmente modificable, que podría ser utilizado por los administradores del agua para ayudar en la planificación de los recursos hídricos en condiciones climáticas futuras potencialmente variables.

半干旱山区流域极端气候引起的地下水补给和地表水水质变化

摘要

气候变化有可能对地下水补给、地下水-地表水动力学和地表水水质产生重要影响。气候变化可能表现为整个积雪减少或积雪变化逐年增加,并可能影响野火的发生和加重。近年来,在美国西部大盆地的半干旱地区观测到气候极端事件,包括异常的季节性降雪 (干旱和极端降水)和野火。这些气候极端事件导致冬季降雪量增加(2011年和2017年)后地下水补给增加。在降雪量升高之后的时期,利用地下水位波动法计算的地下水补给量是先前使用分布式补给计算方法的10倍以上。在后续分析 (如地下水流量建模)中引用这些结果时必须谨慎,以确保满足所有的假设条件并且计算的补给率在空间上可应用。虽然由于降雪量升高引起的水质变化在地表水数据中并不明显,但是流域 (有极端干旱气候)下游野火后,几种地球化学成分(Ba,Ca,K,Mg,Na,pH和特定电导率)的浓度差异存在统计学意义。水化学的补给计算和统计评价是使用易于修改的Python脚本实现的,水资源管理者可利用这些脚本制定未来潜在变化的气候条件下的水资源规划。

Variações na recarga das águas subterrâneas e na qualidade das águas superficiais devido a extremos climáticos em bacias montanhosas semiáridas

Resumo

As mudanças climáticas têm o potencial de impactar substancialmente a recarga das águas subterrâneas, a dinâmica das águas superficiais/subterrâneas e a qualidade das águas superficiais. Mudanças no clima podem se manifestar como um decréscimo global de mantos de gelo ou um aumento na variabilidade de mantos de gelo ano a ano e pode afetar a ocorrência e severidade de incêndios florestais. Extremos climáticos observados, incluindo nevascas sazonais anormais (tanto secas quanto precipitações extremas) e incêndios florestais, ocorreram nos últimos anos em uma região semiárida da Grande Bacia no oeste dos Estados Unidos. Esses extremos climáticos provocaram uma recarga concentrada das águas subterrâneas após invernos com elevadas nevascas (2011 e 2017). A recarga das águas subterrâneas calculada usando o método de flutuação do lençol freático, para períodos após nevascas elevadas, foi mais de 10 vezes maior do que em estudos anteriores que utilizaram métodos de cálculo da recarga distribuída na bacia. Deve-se ter cuidado ao usar os resultados desses cálculos em analises subsequentes, como modelagem do fluxo das águas subterrâneas, para assegurar que todas as premissas necessárias sejam atendidas e que as taxas de recarga calculadas sejam espacialmente aplicáveis. Embora mudanças na qualidade da água devido a nevascas elevadas não foram evidentes na água superficial, diversos constituintes geoquímicos (Ba, Ca, K, Mg, Na, pH, e condutância especifica) indicaram diferenças de concentração estatisticamente significativas após um incêndio florestal a jusante da bacia hidrográfica (representando o extremo climático da seca). Ambos os cálculos de recarga e avaliações estatísticas da química da água foram concluídos usando um script Python facilmente modificado, que poderia ser utilizado pelos gerestores hídricos para auxiliar no planejamento dos recursos hídricos sob condições climáticas futuras potencialmente variáveis.

Notes

Acknowledgements

The author claims no real or perceived financial conflicts or conflicts of interest. The reader is referred to ESM1, which is provided with this paper for a link to the Python script for completion of analyses, and all additional statistical evaluations. The data are provided in ESM2. Helpful comments were offered on the original draft by Dr. Moutaz Al-Dabbas, Dr. Sadeq Aljawad, and two anonymous reviewers.

Supplementary material

10040_2019_1967_MOESM1_ESM.pdf (2 mb)
ESM 1 (PDF 2094 kb)
10040_2019_1967_MOESM2_ESM.xlsx (2.6 mb)
ESM 2 (XLSX 2699 kb)

References

  1. Avon L, Durbin TJ (1994) Evaluation of the Maxey-Eakin method for estimating recharge to ground-water basins in Nevada. Water Resour Bull 30(1):99–111CrossRefGoogle Scholar
  2. Bakker M (2014) Python scripting: the return to programming. Groundwater 52(6):821–822.  https://doi.org/10.1111/gwat.12269 CrossRefGoogle Scholar
  3. Berger DL, Halford KJ, Belcher WR, Lico MS (2008) Technical review of water-resources investigations of the Tule Desert, Lincoln County, southern Nevada. US Geol Surv Open-File Rep 2008-1354, 19 ppGoogle Scholar
  4. Chowdhury AH, Uliana M, Wade S (2008) Ground water recharge and flow characterization using multiple isotopes. Groundwater 46(3):426–436.  https://doi.org/10.1111/j.1745-6584.2008.00443.x CrossRefGoogle Scholar
  5. Cuthbert MO (2010) An improved time series approach for estimating groundwater recharge from groundwater level fluctuations. Water Resour Res 46:W09515.  https://doi.org/10.1029/2009WR008572 CrossRefGoogle Scholar
  6. Cuthbert MO, Acworth RI, Andersen MS, Larsen JR, McCallum AM, Rau GC, Tellam JH (2016) Understanding and quantifying focused, indirect groundwater recharge from ephemeral streams using water table fluctuations. Water Resour Res 52:827–840.  https://doi.org/10.1002/2015WR017503 CrossRefGoogle Scholar
  7. Daly C, Neilson RP, Phillips DL (1994) A statistical-topographic model for mapping climatological precipitation over mountainous terrain. J Appl Meteorol 33(2):140–158.  https://doi.org/10.1175/1520-0450(1994)033%3C0140:ASTMFM%3E2.0.CO;2 CrossRefGoogle Scholar
  8. Dettinger MD (1989) Reconnaissance estimates of natural recharge to desert basins in Nevada, U.S.A., by using chloride-balance calculations. J Hydrol 106:55–78CrossRefGoogle Scholar
  9. Garfin G, Franco G, Blanco H, Comrie A, Gonzalez P, Piechota T, Smyth R, Waskom R (2014) Southwest, chap 20. In: Melillo JM, Richmond TC, Yohe GW (eds) Climate change impacts in the United States: the third National Climate Assessment, pp 462–486.  https://doi.org/10.7930/J08G8HMN
  10. Garrels RM, Mackenzie FT (1967) Origin of the chemical compositions of some springs and lakes. In: Stumm W (ed) Equilibrium concepts in natural water systems. American Chemical Society, Washington, DC, pp 222–242CrossRefGoogle Scholar
  11. Glynn PD, Plummer LN (2005) Geochemistry and the understanding of ground-water systems. Hydrogeol J 13:263–287.  https://doi.org/10.1007/s10040-004-0429-y CrossRefGoogle Scholar
  12. Godsey SE, Kirchner JW, Clow DW (2009) Concentration-discharge relationships reflect chemostatic characteristics of US catchments. Hydrol Process 23:1844–1864.  https://doi.org/10.1002/hyp.7315 CrossRefGoogle Scholar
  13. Healy RW, Cook PG (2002) Using groundwater levels to estimate recharge. Hydrogeol J 10:91–109.  https://doi.org/10.1007/s10040-001-0178-0 CrossRefGoogle Scholar
  14. Healy RW, Winter TC, LaBaugh JW, Franke OL (2007) Water budgets: foundations for effective water-resources and environmental management. US Geol Surv Circ 1308, 90 ppGoogle Scholar
  15. Helsel DR, Hirsch RM (2002) Statistical methods in water resources. Techniques Water Resources Invest, book 4, chap A3. US Geological Survey, Reston, VA, 522 ppGoogle Scholar
  16. Huntington JM (2010) Conceptual understanding and groundwater quality of the basin-fill aquifers in eagle and Carson valleys, Nevada. In: Thiros SA, Bexfield LM, Anning DW, Huntington JM (eds) Conceptual understanding and groundwater quality of selected basin-fill aquifers in the southwestern United States. US Geol Surv Prof Pap 1781, pp 49–69Google Scholar
  17. Huntington JM, Savard CS (2015) Discharge, suspended sediment, bedload, and water quality in Clear Creek, western Nevada, water years 2010–12. US Geol Surv Sci Invest Rep 2015-5124, 39 pp.  https://doi.org/10.3133/sir20155124
  18. Huntington JM, Riddle DJ, Paul AP (2018) Discharge, sediment, and water chemistry in Clear Creek, western Nevada, water years 2013–16. US Geol Surv Sci Invest Rep 2018–5050, 55 pp.  https://doi.org/10.3133/sir20185050
  19. Leduc C, Bromley J, Schroeter P (1997) Water table fluctuation and recharge in semi-arid climate: some results of the HAPEX-Sahel hydrodynamic survey (Niger). J Hydrol 188–189:123–138.  https://doi.org/10.1016/S0022-1694(96)03156-3 CrossRefGoogle Scholar
  20. Lute AC, Abatzoglou JT (2014) Role of extreme snowfall events in interannual variability of snowfall accumulation in the western United States. Water Resour Res 50:2874–2888.  https://doi.org/10.1002/2013WR014465 CrossRefGoogle Scholar
  21. Lute AC, Abatzoglou JT, Hegewisch KC (2015) Projected changes in snowfall extremes and interannual variability of snowfall in the western United States. Water Resour Res 51:960–972.  https://doi.org/10.1002/2014WR016267 CrossRefGoogle Scholar
  22. Mast MA, Murphy SF, Clow DW, Penn CA, Sexstone GA (2016) Water-quality response to a high-elevation wildfire in the Colorado Front Range. Hydrol Process 30:1811–1823.  https://doi.org/10.1002/hyp.10755 CrossRefGoogle Scholar
  23. Maurer DK, Berger DL (1997) Subsurface flow and water yield from watersheds tributary to Eagle Valley hydrographic area, west-central Nevada. US Geol Surv Water Resour Invest Rep 97-4191, 56 ppGoogle Scholar
  24. Maurer DK, Thodal CE (2000) Quantity and chemical quality of recharge, and updated water budgets, for the basin-fill aquifer in Eagle Valley, western Nevada. US Geol Surv Sci Invest Rep 99-4289, 46 ppGoogle Scholar
  25. Maurer DK, Berger DL, Prudic DE (1996) Subsurface flow to Eagle Valley from Vicee, Ash, and Kings canyons, Carson City, Nevada, estimated from Darcy’s law and the chloride-balance method. US Geol Surv Water Resour Invest Rep 96-4088, 74 ppGoogle Scholar
  26. Maurer DK, Paul AP, Berger DL, Mayers CJ (2009) Analysis of streamflow trends, ground-water and surface-water interactions, and water quality in the upper Carson River basin, Nevada and California. US Geol Surv Sci Invest Rep 2008-5238, 192 ppGoogle Scholar
  27. Maxey GB, Eakin TE (1949) Ground water in White River Valley, White Pine, Nye, and Lincoln counties, Nevada. Nevada State Eng Water Resour Bull 8:53Google Scholar
  28. Meixner T, Manning AH, Stonestrom DA, Allen DM, Ajami H, Blasch KW et al (2016) Implications of projected climate change for groundwater recharge in the western United States. J Hydrol 534:124–138.  https://doi.org/10.1016/j.jhydrol.2015.12.027 CrossRefGoogle Scholar
  29. Nagorski SA, Moore JN, McKinnon TE, Smith DB (2003) Scale-dependent temporal variations in stream water geochemistry. Environ Sci Tech 37(5):859–864CrossRefGoogle Scholar
  30. Nimmo JR, Horowitz C, Mitchell L (2015) Discrete-storm water-table fluctuation method to estimate episodic recharge. Groundwater 53(2):282–292.  https://doi.org/10.1111/gwat.12177 CrossRefGoogle Scholar
  31. Ramsahoye LE, Lang SM (1961) A simple method for determining specific yield from pumping tests. US Geol Surv Water Suppl Pap 1536-CGoogle Scholar
  32. Reimann C, Filzmoser P (2000) Normal and lognormal data distribution in geochemistry: death of a myth—consequences for the statistical treatment of geochemical and environmental data. Environ Geol 39(9):1001–1014.  https://doi.org/10.1007/s002549900081 CrossRefGoogle Scholar
  33. Rhoades AM, Ullrich PA, Zarzyski CM (2017) Projecting 21st century snowpack trends in western USA mountains using variable-resolution CESM. Clim Dyn 50(1–2):261–288.  https://doi.org/10.1007/s00382-017-3606-0 Google Scholar
  34. Scanlon BR, Healy RW, Cook PG (2002) Choosing appropriate techniques for quantifying groundwater recharge. Hydrogeol J 10:18–39.  https://doi.org/10.1007/s10040-001-0176-2 CrossRefGoogle Scholar
  35. Schaefer DH, Green JM, Rosen MR (2007) Hydrogeologic settings and ground-water flow simulations of the Eagle Valley and Spanish Springs regional study areas, Nevada. In: Paschke SS (ed) Hydrogeologic settings and ground-water flow simulations for regional studies of the transport of anthropogenic and natural contaminants to public-supply wells—studies begun in 2001. US Geol Surv Prof Pap 1737Google Scholar
  36. Stewart JH (1980) Geology of Nevada: a discussion to accompany the geologic map of Nevada. Nevada Bureau of Mines and Geology Map no. 50, Nev. Bur. Mines Geol., Reno, NVGoogle Scholar
  37. Stone DB, Moomaw CL, Davis A (2001) Estimating recharge distribution by incorporating runoff from mountainous areas in an alluvial basin in the Great Basin region of the southwestern United States. Groundwater 39(6):807–818.  https://doi.org/10.1111/j.1745-6584.2001.tb02469.x CrossRefGoogle Scholar
  38. Sweetkind DS, Masbruch MD, Heilweil VM, Buto SG (2011) Groundwater flow, chapter C. In: Heilweil VM, Brooks LE (eds) Conceptual model of the Great Basin carbonate and alluvial aquifer system. US Geol Surv Sci Invest Rep 2010-5193, pp 51–72Google Scholar
  39. Todd AS, Manning AH, Verplanck PL, Crouch C, McKnight DM, Dunham R (2012) Climate-change-driven deterioration of water quality in a mineralized watershed. Envi Sci Tech 46:9324–9332.  https://doi.org/10.1021/es3020056 CrossRefGoogle Scholar
  40. USGS (2018) Aquifer testing results. https://nevada.usgs.gov/aquifertests/. Accessed 10 September 2018
  41. Walton DB, Hall A, Berg N, Schwartz M, Sun F (2017) Incorporating snow albedo feedback into downscaled temperatures and snow cover projections for California’s Sierra Nevada. J Clim 30:1417–1438.  https://doi.org/10.1175/JCLI-D-16-0168.1 CrossRefGoogle Scholar
  42. Weider W, Boutt DF (2010) Heterogeneous water table response to climate revealed by 60 years of ground water data. Geophys Res Lett 37:L24405.  https://doi.org/10.1029/2010GL045561 CrossRefGoogle Scholar
  43. Weston BD, Watters RJ, Vikre PG (2009) Pervasively-altered rocks in the Glenbrook Creek watershed: effects of slope stability, erosion, and sediment composition on Lake Tahoe’s water quality. Poster presented at the annual meeting of the Association of Environmental and Engineering Geologists, Stateline, Nevada, September 2009Google Scholar
  44. Winter TC, Harvey JW, Franke OL, Alley WM (1999) Ground water and surface water: a single resource. US Geol Surv Circ 1139, 79 ppGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Nevada Division of Environmental ProtectionCarson CityUSA
  2. 2.Colorado Water Science Center, USGS, Denver Federal CenterDenverUSA

Personalised recommendations