Abstract
The groundwater recharge produced by discrete precipitation events in unconfined aquifers is often estimated from water-table fluctuations (WTFs) recorded in shallow wells. This recharge estimate is prone to uncertainties when recharge is not instantaneous, when there is groundwater drainage, and when there are other processes producing WTFs. A numerical analysis of these uncertainties is presented, which accounts for noninstantaneous recharge and the changes in the stage of a river connected to the unconfined aquifer. This analysis is performed for idealized synthetic unconfined aquifers with one-dimensional (1-D) and 2-D numerical flow models which account for the anisotropy and the spatial heterogeneity of the hydraulic conductivity (K). The logarithm of K is assumed to be a Gaussian random field with a spherical semivariogram. Groundwater recharge may be grossly underestimated with the WTF data when the recharge is not instantaneous. Estimation errors are especially important near the river. On the other hand, the recharge may be largely overestimated when the river stage rises simultaneously during the recharge episode. The errors increase with the variance of the Ln K value and depend on the main direction of anisotropy and the spatial connectivity of the most permeable areas near the river. The errors are large along the most permeable zones connected to the river in the main direction of anisotropy. The recharge estimation errors are largest when the main direction of anisotropy is perpendicular to the river and are smallest when the main direction of anisotropy is parallel to the river.
Résumé
La recharge des eaux souterraines produite par des événements discrets de précipitation dans des aquifères libres est souvent estimée à partir des fluctuations de niveau de nappe (WTFs) enregistrées dans les puits peu profonds. Cette évaluation de recharge est encline aux incertitudes lorsque la recharge n’est pas instantanée, lorsqu’il y a drainage d’eaux souterraines, et lorsqu’il y a d’autres processus produisant des fluctuations de nappe. Une analyse numérique de ces incertitudes est présentée, qui prend en compte une recharge non-instantanée et les changements de niveau d’un cours d’eau en connexion avec l’aquifère libre. Cette analyse est réalisée pour un aquifère libre synthétique idéalisé, à l’aide de modèles numériques unidimensionnels (1-D) et 2-D d’écoulement prenant en compte l’anisotropie et l’hétérogénéité spatiale de la conductivité hydraulique K. On pose l’hypothèse que le logarithme de K est un champ aléatoire gaussien avec un semi-variogramme sphérique. La recharge des eaux souterraines peut être largement sous-estimée avec les données de niveau de nappe quand la recharge n’est pas instantanée. Les erreurs d’évaluation sont particulièrement importantes à proximité du cours d’eau. D’autre part, la recharge peut-être largement surestimée quand le niveau du cours d’eau monte simultanément pendant l’épisode de recharge. Les erreurs augmentent avec la variance de la valeur du Ln K et dépendent de la direction principale de l’anisotropie et de la connectivité spatiale des zones les plus perméables à proximité du cours d’eau. Les erreurs sont grandes le long des zones les plus perméables en relation avec le cours d’eau, dans la direction principale de l’anisotropie. Les erreurs d’évaluation de la recharge sont les plus grandes quand la direction principale de l’anisotropie est perpendiculaire au cours d’eau et les plus petites quand la direction principale de l’anisotropie est parallèle au cours d’eau.
Resumen
La recarga subterránea que se produce en acuíferos libres en episodios discretos de precipitación se suele estimar a partir de las fluctuaciones de la superficie freática (FSF) medidas en pozos someros. La recarga que se obtiene con este método tiene incertidumbres cuando la recarga no es instantánea, existe drenaje subterráneo e intervienen otros procesos que producen fluctuaciones de la superficie freática. En este artículo se presenta un análisis numérico de estas incertidumbres que tiene en cuenta la existencia de una recarga no instantánea y los cambios en el nivel de un río conectado al acuífero libre. El análisis se realiza para acuíferos libres, sintéticos e idealizados mediante modelos numéricos en una (1-D) y dos (2-D) dimensiones que tienen en cuenta la anisotropía y la heterogeneidad espacial de la conductividad hidráulica, K. Se supone que el logaritmo de K es una función aleatoria Gaussiana con un semivariograma esférico. La recarga subterránea puede ser ampliamente subestimada con el método FSF cuando la recarga no es instantánea. Los errores de estimación son especialmente importantes cerca del río. Por otro lado, la recarga puede ser sobreestimada en gran medida si el nivel del río asciende durante el episodio de recarga. Los errores de estimación aumentan con la varianza del Ln K y dependen de la dirección principal de anisotropía y de la conectividad espacial de las zonas más permeables cerca del río. Los errores son grandes a lo largo de las zonas más permeables conectadas al río a lo largo de la dirección principal de anisotropía. Los errores en la estimación de la recarga son máximos cuando la dirección principal de anisotropía es perpendicular al río y son mínimos cuando la dirección principal de anisotropía es paralela al río.
摘要
非承压含水层中离散降水事件产生的地下水补给往往是根据浅井记录的地下水位波动(WTF)来估算的。当补给不是瞬时的,当有地下水排水时,以及当有其他过程产生地下水位波动时,这种补给估计很容易产生不确定性。对这些不确定因素进行了数值分析,解释了非瞬时补给和与无承压含水层相连的河流阶段的变化。本文采用一维(1-D)和二维数值流模型,考虑了导水率的各向异性和空间异质性,对理想的合成无侧限含水层进行了数值分析。K的对数是一个具有球面半变异函数的高斯随机场。当补给不是瞬时,WTF数据可能会严重低估地下水补给。估计误差在河流附近尤为重要。另一方面,在补给过程中,当河段同时上升时,补给可能被大大高估。误差随LnK值的变化而增大,主要取决于各向异性的主方向和河流附近最易渗透的区域的空间连通性。沿主要各向异性方向与河流相连的最渗透带的误差较大。当主各向异性方向垂直于河流时,补给量估计误差最大,当主各向异性方向与河流平行时,计算误差最小。
Resumo
A recarga das águas subterrâneas produzida por eventos pontuais de precipitação em aquíferos livres é frequentemente estimada a partir das flutuações do nível freático (water table fluctuations - WTFs) registadas em poços pouco profundos. Essa estimativa de recarga está sujeita a incertezas quando a recarga não é instantânea, quando há drenagem de águas subterrâneas e quando há outros processos que produzem flutuações no nível freático. É apresentada uma análise numérica dessas incertezas considerando a recarga não instantânea e as mudanças no nível de um rio conectado ao aquífero livre. Esta análise é realizada para aquíferos livres sintéticos idealizados com modelos numéricos de fluxo unidimensional (1-D) e 2-D, que representam a anisotropia e a heterogeneidade espacial da condutividade hidráulica, K. Presume-se que o logaritmo de K seja um campo aleatório gaussiano com um semivariograma esférico. A recarga das águas subterrâneas pode ser subestimada grosseiramente com os dados da WTF quando a recarga não é instantânea. Erros de estimativa são especialmente importantes perto do rio. Por outro lado, a recarga pode ser superestimada quando o nível do rio sobe simultaneamente durante o episódio de recarga. Os erros aumentam com a variância do valor de Ln K e dependem da direção principal da anisotropia e da conectividade espacial das áreas mais permeáveis próximas ao rio. Os erros são grandes ao longo das zonas mais permeáveis conectadas ao rio na direção principal da anisotropia. Os erros de estimativa de recarga são maiores quando a direção principal da anisotropia é perpendicular ao rio e são menores quando a direção principal da anisotropia é paralela ao rio.
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References
Abdulrazzak MJ, Sorman AU, Alhames AS (1989) Water balance approach under extreme arid conditions: a case study of Tabalah Basin, Saudi Arabia. Hydrol Process 3:107–122. https://doi.org/10.1002/hyp.3360030202
Águila JF (2017) Reactive transport models of low permeability structured porous and fractured media. PhD Thesis, University de Coruña, A Coruña, Spain, 531 pp. http://hdl.handle.net/2183/20232. Accessed December 2018
Ahrens J, Geveci B, Law C (2005) ParaView: an end-user tool for large data visualization. ReportLA-UR-03-1560, Los Alamos National Laboratory, Los Alamos, NM. https://datascience.lanl.gov/data/papers/ParaView.pdf. Accessed December 2018
Athavale RN, Rangarajan R (1988) Natural recharge measurements in the hard rock regions of semi-arid India using tritium injection: a review. In: Simmers I (ed) Estimation of natural groundwater recharge. NATO ASI Series, Series C: mathematical and physical sciences, vol 222. Springer, Dordrecht, The Netherlands
Arnold JG, Muttiah RS, Srinivasan R, Allen PM (2000) Regional estimation of base flow and groundwater recharge in the upper Mississippi River basin. J Hydrol 227(1–4):21–40. https://doi.org/10.1016/S0022-1694(99)00139-0
Ayachit U (2015) The ParaView guide: a parallel visualization application. Kitware, Clifton, NY
Bierkens MFP (1998) Modeling water table fluctuations by means of a stochastic differential equation. Water Resour Res 34(10):2485–2499
Bierkens MFP, Knotters M, Hoogland T (2001) Space-time modeling of water table depth using a regionalized time series model and the Kalman filter. Water Resour Res 37:1277–1290
Brunner P, Simmons CT, Cook PG (2009) Spatial and temporal aspects of the transition from connection to disconnection between rivers, lakes and groundwater. J Hydrol 376(1–2):159–169. https://doi.org/10.1016/j.jhydrol.2009.07.023.
Cai Z, Ofterdinger U (2016) Analysis of groundwater-level response to rainfall and estimation of annual recharge in fractured hard rock aquifers, NW Ireland. J Hydrol 535:71–84. https://doi.org/10.1016/j.jhydrol.2016.01.066
Callahan TJ, Vulava VM, Passarello MC, Garrett CG (2012) Estimating groundwater recharge in lowland watersheds. Hydrol Process 26(19):2845–2855. https://doi.org/10.1002/hyp.8356
Chenini I, Mammou AB (2010) Groundwater recharge study in arid region: an approach using GIS techniques and numerical modeling. Comput Geosci 36(6):801–817. https://doi.org/10.1016/j.cageo.2009.06.014
Crosbie RS, Binning P, Kalma JD (2005) A time series approach to inferring groundwater recharge using the water table fluctuation method. Water Resour Res 41(1):W01008. https://doi.org/10.1029/2004WR003077
Cuthbert MO (2010) An improved time series approach for estimating groundwater recharge from groundwater level fluctuations. Water Resour Res 46(9):W09515. https://doi.org/10.1029/2009WR008572
Delin GN, Healy RW, Lorenz DL, Nimmo JR (2007) Comparison of local- to regional-scale estimates of ground-water recharge in Minnesota, USA. J Hydrol 334(1–2):231–249. https://doi.org/10.1016/j.jhydrol.2006.10.010
Dennehy KF, Reilly TE, Cunningham WL (2015) Groundwater availability in the United States: the value of quantitative regional assessments. Hydrogeol J 23(8):1629–1632. https://doi.org/10.1007/s10040-015-1307-5
Ebrahimi H, Ghazavi R, Karimi H (2016) Estimation of groundwater recharge from the rainfall and irrigation in an arid environment using inverse modeling approach and RS. Water Resour Manag 30(6):1939–1951. https://doi.org/10.1007/s11269-016-1261-6
Egboka BCE, Cherry JA, Farvolden RN, Frind EO (1983) Migration of contaminants in groundwater at a landfill: a case study: 3. tritium as an indicator of dispersion and recharge. J Hydrol 63(1–2):51–80. https://doi.org/10.1016/0022-1694(83)90223-8.
Flint LE (2003) Physical and hydraulic properties of volcanic rocks from Yucca Mountain, Nevada. Water Resour Res 39(5):1119. https://doi.org/10.1029/2001WR001010.
Flury M, Flühler H, Jury WA, Leuenberger J (1994) Susceptibility of soils to preferential flow of water: a field study. Water Resour Res 30(7):1945–1954. https://doi.org/10.1029/94WR00871
Freeze RA, Cherry JA (1979) Groundwater. Prentice-Hall, Englewood Cliffs, NJ
Gómez-Hernández JJ, Journel AG (1993) Joint simulation of multi-Gaussian random variables. In: Soares A (ed) Geostatistics Tróia’ 92. Quantitative geology and geostatistics, vol 5. Springer, Dordrecht, The Netherlands
Hagedorn B, El-Kadi AI, Mair A, Whittier B, Ha K (2011) Estimating recharge in fractured aquifers of a temperate humid to semiarid volcanic island (Jeju, Korea) from water table fluctuations, and Cl, CFC-12 and 3H chemistry. J Hydrol 409(3–4):650–662. https://doi.org/10.1016/j.jhydrol.2011.08.060
Hameed AS, Resmi TR, Suraj S, Warrier CU, Sudheesh M, Deshpande RD (2015) Isotopic characterization and mass balance reveals groundwater recharge pattern in Chaliyar River basin, Kerala, India. J Hydrol 4:48–58. https://doi.org/10.1016/j.ejrh.2015.01.003.
Healy RW, Cook PG (2002) Using groundwater levels to estimate recharge. Hydrogeol J 10(1):91–109. https://doi.org/10.1007/s10040-001-0178-0
Heppner CS, Nimmo JR (2005) A computer program for predicting recharge with a master recession curve. United States Geological Survey, Reston, VA
Huang FK, Chuang MH, Wang GS, Yeh HD (2015) Tide-induced groundwater level fluctuation in a U-shaped coastal aquifer. J Hydrol 530:291–305 https://doi.org/10.1016/j.jhydrol.2015.09.032
Hussain Y, Ullah SF, Hussain MB, Aslam AQ, Akhter G, Martinez-Carvajal H, Cárdenas-Soto M (2017) Modelling the vulnerability of groundwater to contamination in an unconfined alluvial aquifer in Pakistan. Environ Earth Sci 76:84. https://doi.org/10.1007/s12665-017-6391-5
Jassas H, Merkel B (2014) Estimating groundwater recharge in the semiarid Al-Khazir Gomal Basin, North Iraq. Water 6:2467–2481. https://doi.org/10.3390/w6082467
Jie Z, van Heyden J, Bendel D, Barthel R (2011) Combination of soil-water balance models and water-table fluctuation methods for evaluation and improvement of groundwater recharge calculations. Hydrogeol J 19(8):1487–1502. https://doi.org/10.1007/s10040-011-0772-8
Knowling MJ, Werner AD (2016) Estimability of recharge through groundwater model calibration: insights from a field-scale steady-state example. J Hydrol 540:973–987. https://doi.org/10.1016/j.jhydrol.2016.07.003
Kumar CP, Seethapathi PV (2002) Assessment of natural ground water recharge in Upper Ganga Canal command area. J Appl Hydrol 15(4):13–20
Lautz LK (2008) Estimating groundwater evapotranspiration rates using diurnal water-table fluctuations in a semi-arid riparian zone. Hydrogeol J 16(3):483–497. https://doi.org/10.1007/s10040-007-0239-0
Lee CH, Yeh HF, Chen JF (2008) Estimation of groundwater recharge using the soil moisture budget method and the base-flow model. Environ Geol 54(8):1787–1797. https://doi.org/10.1007/s00254-007-0956-7
Lerner DN, Issar A, Simmers Is (1990) Groundwater recharge: a guide to understanding and estimating natural recharge. IAH, Heise, Hannover, Germany
Levanon E, Shalev E, Yechieli Y, Gvirtzman H (2016) Fluctuations of fresh-saline water interface and of water table induced by sea tides in unconfined aquifers. Adv Water Resour 96:34–42. https://doi.org/10.1016/j.advwatres.2016.06.013
Liang X, Zhang YK (2012) A new analytical method for groundwater recharge and discharge estimation. J Hydrol 450-451:17–24. https://doi.org/10.1016/j.jhydrol.2012.05.036
Lu C, Samper J, Fritz B, Clement A, Montenegro L (2011) Interactions of corrosion products and bentonite: an extended multicomponent reactive transport model. Phys Chem Earth, Parts A/B/C 36:1661–1668
Lott RB, Hunt RJ (2001) Estimating evapotranspiration in natural and constructed wetlands. Wetlands 21(4):614–628. https://doi.org/10.1672/0277-5212(2001)021[0614:EEINAC]2.0.CO;2
Manghi F, Mortazavi B, Crother C, Hamdi MR (2009) Estimating regional groundwater recharge using a hydrological budget method. Water Resour Manag 23(12):2475–2489. https://doi.org/10.1007/s11269-008-9391-0
Mazur MLC, Wiley MJ, Wilcox DA (2014) Estimating evapotranspiration and groundwater flow from water-table fluctuations for a general wetland scenario. Ecohydrology 7:378–390. https://doi.org/10.1002/eco.1356
Mehl S, Hill MC (2010) Grid-size dependence of Cauchy boundary conditions used to simulate stream–aquifer interaction. Adv Water Resour 33:430–442. https://doi.org/10.1016/j.advwatres.2010.01.008.
Molinero J, Samper J (2004) Groundwater flow and solute transport in fracture zones: an improved model for a large-scale field experiment at Äspö (Sweden). J Hydraul Res 42(Spec Issue):157–172. https://doi.org/10.1080/00221680409500059
Mon A, Samper J, Montenegro L, Naves A, Fernández J (2017) Long-term non-isothermal reactive transport model of compacted bentonite, concrete and corrosion products in a HLW repository in clay. J Contam Hydrol 197:1–16. https://doi.org/10.1016/j.jconhyd.2016.12.006.
Mould DJ, Frahm E, Salzmann T, Miegel K, Acreman MC (2010) Evaluating the use of diurnal groundwater fluctuations for estimating evapotranspiration in wetland environments: case studies in southeast England and northeast Germany. Ecohydrology 3:294–305. https://doi.org/10.1002/eco.108
Neshat A, Pradhan B, Pirasteh S, Shafri HZM (2014) Estimating groundwater vulnerability to pollution using a modified DRASTIC model in the Kerman agricultural area, Iran. Environ Earth Sci 71(7):3119–3131. https://doi.org/10.1007/s12665-013-2690-7
Neuman SP (1987) On methods of determining specific yield. Ground Water 25:679–684. https://doi.org/10.1111/j.1745-6584.1987.tb02208.x
Nimmo JR, Healy RW, Stonestrom DA (2005) Aquifer recharge. In: Anderson MG, Bear J, (eds) Encyclopedia of hydrological sciences, vol 4. Wiley, Chichester, UK, pp 2229–2246
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
Nwankwor GI, Cherry JA, Gillham RW (1984) A comparative study of specific yield determinations for a shallow sand aquifer. Ground Water 22:764–772. https://doi.org/10.1111/j.1745-6584.1984.tb01445.x
Park E (2012) Delineation of recharge rate from a hybrid water table fluctuation method. Water Resour Res 48(7):W07503. https://doi.org/10.1029/2011WR011696
Park E, Parker JC (2008) A simple model for water table fluctuations in response to precipitation. J Hydrol 356(3–4):344–349. https://doi.org/10.1016/j.jhydrol.2008.04.022
Prada S, Cruz JV, Figueira C (2016) Using stable isotopes to characterize groundwater recharge sources in the volcanic island of Madeira, Portugal. J Hydrol 536:409–425. https://doi.org/10.1016/j.jhydrol.2016.03.009
Rasmussen TC, Crawford LA (1997) Identifying and removing barometric pressure effects in confined and unconfined aquifers. Ground Water 35(3):502–511. https://doi.org/10.1111/j.1745-6584.1997.tb00111.x
Rasmussen WC, Andreasen GE (1959) Hydrologic budget of the Beaverdam Creek basin, Maryland. US Geol Surv Water Suppl Pap 1472
Razavi S, Gupta HV (2015) What do we mean by sensitivity analysis? The need for comprehensive characterization of “global” sensitivity in earth and environmental systems models. WRR Publ Cover Image 51(5):3070–3092
Saghravani SR, Yusoff I, Mustapha S, Saghravani SF (2013) Estimating groundwater recharge using empirical method: a case study in the tropical zone. Sains Malaysiana 42(5):553–560
Samper J, Lu C, Montenegro L (2008a) Coupled hydrogeochemical calculations of the interactions of corrosion products and bentonite. Phys Chem Earth 33:S306–S316. https://doi.org/10.1016/j.pce.2008.10.009
Samper J, Lu C, Montenegro L (2008b) Reactive transport model of interactions of corrosion products and bentonite. Phys Chem Earth 33(Supplement 1):S306–S316
Samper J, Pisani B (2009) Aquifer recharge evaluation by a combination of soil water balance and groundwater flow models. In: Silva et al. (eds) IX Jornadas sobre Investigación de la Zona no Saturada del Suelo - ZNS’09, vol IX. Barcelona, November 18–20, 2009
Samper J, Xu T, Yang C (2009) A sequential partly iterative approach for multicomponent reactive transport with CORE2D. Comput Geosci 13:301–316. https://doi.org/10.1007/s10596-008-9119-5
Samper J, Yang C, Zheng L, Montenegro L, Xu T, Dai Z, Zhang G, Lu C, Moreira S (2011) CORE2D V4: a code for water flow, heat and solute transport, geochemical reactions, and microbial processes. In: Groundwater reactive transport models. Bentham , pp 160–185. https://doi.org/10.2174/978160805306311201010160
Samper J, Naves A, Montenegro L, Mon A (2016) Reactive transport modelling of the long-term interactions of corrosion products and compacted bentonite in a HLW repository in granite: uncertainties and relevance for performance assessment. Appl Geochem 67:42–51. https://doi.org/10.1016/j.apgeochem.2016.02.001
Sanford W (2002) Recharge and groundwater models: an overview. Hydrogeol J 10(1):110–120. https://doi.org/10.1007/s10040-001-0173-5
Scanlon BR, Goldsmith RS (1997) Field study of spatial variability in unsaturated flow beneath and adjacent to playas. Water Resour Res 33(10):2239–2252. https://doi.org/10.1029/97WR01332
Scanlon BR, Healy RW, Cook PG (2002) Choosing appropriate techniques for quantifying groundwater recharge. Hydrogeol J 10(1):18–39. https://doi.org/10.1007/s10040-001-0176-2
Scanlon BR, Keese KE, Flint AL, Flint LE, Gaye CB, Edmunds WM, Simmers I (2006) Global synthesis of groundwater recharge in semiarid and arid regions. Hydrol Process 20:3335–3370
Schilling KE, Jacobson PJ, Libra RD, Gannon JM, Langel RJ, Peate DW (2017) Estimating groundwater age in the Cambrian-Ordovician aquifer in Iowa: implications for biofuel production and other water uses. Environ Earth Sci 76(2):1–9. https://doi.org/10.1007/S12665-016-6321-Y.
Sharda VN, Kurothe RS, Sena DR, Pande VC, Tiwari SP (2006) Estimation of groundwater recharge from water storage structures in a semi-arid climate of India. J Hydrol 329(1–2):224–243. https://doi.org/10.1016/j.jhydrol.2006.02.015
Sibanda T, Nonner JC, Uhlenbrook S (2009) Comparison of groundwater recharge estimation methods for the semi-arid Nyamandhlovu area, Zimbabwe. Hydrogeol J 17(6):1427–1441. https://doi.org/10.1007/s10040-009-0445-z
Soler JM, Samper J, Yllera A, Hernández A, Quejido A, Fernández M, Yang C, Naves A, Hernán P, Wersin P (2008) The DI-B in-situ diffusion experiment at Mont Terri: results and modelling, physics and chemistry of the earth, vol 33. Phys Chem Earth, Parts A/B/C 33:S196–S207
Song Z, Li L, Kong J, Zhang H (2007) A new analytical solution of tidal water table fluctuations in a coastal unconfined aquifer. J Hydrol 340(3–4):256–260. https://doi.org/10.1016/j.jhydrol.2007.04.015
Sophocleous MA (1991) Combining the soil-water balance and water-level fluctuation methods to estimate natural groundwater recharge: practical aspects. J Hydrol 124(3–4):229–241. https://doi.org/10.1016/0022-1694(91)90016-B
Spane FA (2002) Considering barometric pressure in groundwater flow investigations. Water Resour Res 38(6), 1078. https://doi.org/10.1029/2001WR000701
Tashie AM, Mirus BB, Pavelsky TM (2016) Identifying long-term empirical relationships between storm characteristics and episodic groundwater recharge. Water Resour Res 52:21–35. https://doi.org/10.1002/2015WR017876
Todd DK, Mays LW (2005) Groundwater hydrology. Wiley, Hoboken, NJ
Toll NJ, Rasmussen TC (2007) Removal of barometric pressure effects and earth tides from observed water levels. Ground Water 45(1):101–105. https://doi.org/10.1111/j.1745-6584.2006.00254.x
Uribe J, Muñoz JF, Gironás J, Oyarzún R, Aguirre E, Aravena R (2015) Assessing groundwater recharge in an Andean closed basin using isotopic characterization and a rainfall-runoff model: Salar del Huasco basin, Chile. Hydrogeol J 23:1535–1551. https://doi.org/10.1007/s10040-015-1300-z
Varni M, Comas R, Weinzettel P, Dietrich S (2013) Application of water table fluctuation method to characterize the groundwater recharge in the Pampa plain. Argentina Hydrol Sci J 58(7):1445–1455
von Freyberg J, Moeck C, Schirmer M (2015) Estimation of groundwater recharge and drought severity with varying model complexity. J Hydrol 527:844–857. https://doi.org/10.1016/j.jhydrol.2015.05.025
Wang C, Li H, Wan L, Wang X, Jiang X (2014) Closed-form analytical solutions incorporating pumping and tidal effects in various coastal aquifer systems. Adv Water Resour 69:1–12. https://doi.org/10.1016/j.advwatres.2014.03.003
Weeks EP (2002) The Lisse effect revisited. Ground Water 40(6):652–656. https://doi.org/10.1111/j.1745-6584.2002.tb02552.x
Yang C, Samper J, Molinero M (2008) Inverse microbial and geochemical reactive transport models in porous media. Phys Chem Earth 2008 33(14–16):1026–1034
Yang L, Qi Y, Zheng C, Andrews CB, Yue S, Lin S, Li Y, Wang C, Xu Y, Li H (2018) A modified water-table fluctuation method to characterize regional groundwater discharge. Water 10(4):503. https://doi.org/10.3390/w10040503
Yin L, Hu G, Huang J, Wen D, Dong J, Wang X, Li H (2011) Groundwater-recharge estimation in the Ordos plateau, China: comparison of methods. Hydrogeol J 19(8):1563–1575. https://doi.org/10.1007/s10040-011-0777-3
Zang YG, Sun DM, Feng P, Semprich S (2017) Effects of airflow induced by rainfall on shallow groundwater table fluctuations. Groundwater 55(3):375–386. https://doi.org/10.1111/gwat.12486
Zheng L, Samper J, Montenegro L, Fernández AM (2010) A coupled THMC model of a heating and hydration laboratory experiment in unsaturated compacted FEBEX bentonite. J Hydrol 386(1–4):80–94. https://doi.org/10.1016/j.jhydrol.2010.03.009
Zheng L, Samper J, Montenegro L (2011) A coupled THC model of the FEBEX in situ test with bentonite swelling and chemical and thermal osmosis. J Contam Hydrol 126(1–2):45–60
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The comments and corrections of the two anonymous reviewers are greatly acknowledged.
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The research leading to this work has received funding from ENRESA, the Spanish Ministry of Economy and Competitiveness (Project CGL2016-78281), the FEDER funds and the Galician Regional Government (Ref: ED431C 2017/67 from “Consolidación e estruturación de unidades de investigación competitivas”). The first author had a contract from the FPI Program of the Spanish Ministry of Economy and Competitiveness.
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Águila, J.F., Samper, J. & Pisani, B. Parametric and numerical analysis of the estimation of groundwater recharge from water-table fluctuations in heterogeneous unconfined aquifers. Hydrogeol J 27, 1309–1328 (2019). https://doi.org/10.1007/s10040-018-1908-x
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DOI: https://doi.org/10.1007/s10040-018-1908-x