Articles | Volume 17, issue 4
https://doi.org/10.5194/essd-17-1515-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-1515-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
14 Apr 2025
Data description paper |
| 14 Apr 2025
| 14 Apr 2025
An in situ daily dataset for benchmarking temporal variability of groundwater recharge
Pragnaditya Malakar
CORRESPONDING AUTHOR
Department of Civil, Construction, and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USA
Department of Geological Sciences, Jadavpur University, Kolkata, India
Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Berhampur, Berhampur, Odisha, India
Aatish Anshuman
Department of Civil, Construction, and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USA
Mukesh Kumar
CORRESPONDING AUTHOR
Department of Civil, Construction, and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USA
Georgios Boumis
Department of Civil, Construction, and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USA
T. Prabhakar Clement
Department of Civil, Construction, and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USA
Arik Tashie
Department of Civil, Construction, and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USA
Hitesh Thakur
Department of Civil, Construction, and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USA
Nagaraj Bhat
Department of Civil, Construction, and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USA
Shri Madhwa Vadiraja Institute of Technology and Management, Bantakal, Karnataka, India
Lokendra Rathore
Department of Civil, Construction, and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USA
Related authors
No articles found.
Soheil Radfar, Georgios Boumis, Hamed R. Moftakhari, Wanyun Shao, Larisa Lee, and Alison N. Rellinger
Geosci. Commun., 8, 237–250, https://doi.org/10.5194/gc-8-237-2025, https://doi.org/10.5194/gc-8-237-2025, 2025
Short summary
Short summary
Our study presents a method to visualize how variations in the relationship of flood drivers like discharge and surge evolve over time. This method simplifies complex relationships, making it easier to understand evolving flood risks, especially as climate change increases these threats. By surveying a diverse group, we found that this visual approach could improve communication between scientists and non-experts, helping communities better prepare for compound flooding in a changing climate.
Elias C. Massoud, Nathan Collier, Yaoping Wang, Jiafu Mao, Adrian Harpold, Steven A. Kannenberg, Gerbrand Koren, Mukesh Kumar, Pushpendra Raghav, Pallav Ray, Mingjie Shi, Jing Tao, Sreedevi P. Vasu, Huiqi Wang, Qing Zhu, and Forrest M. Hoffman
EGUsphere, https://doi.org/10.5194/egusphere-2025-3517, https://doi.org/10.5194/egusphere-2025-3517, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
We studied how well Earth System Models simulate soil moisture and its connection to plant growth and water use. Using a model evaluation tool and real-world data, we found that models generally perform well at the surface but struggle deeper in the soil. These issues vary by region, especially in colder regions. Our results can help improve future model development and support better predictions of how ecosystems respond to a changing environment.
Wouter J. M. Knoben, Ashwin Raman, Gaby J. Gründemann, Mukesh Kumar, Alain Pietroniro, Chaopeng Shen, Yalan Song, Cyril Thébault, Katie van Werkhoven, Andrew W. Wood, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 29, 2361–2375, https://doi.org/10.5194/hess-29-2361-2025, https://doi.org/10.5194/hess-29-2361-2025, 2025
Short summary
Short summary
Hydrologic models are needed to provide simulations of water availability, floods, and droughts. The accuracy of these simulations is often quantified with so-called performance scores. A common thought is that different models are more or less applicable to different landscapes, depending on how the model works. We show that performance scores are not helpful in distinguishing between different models and thus cannot easily be used to select an appropriate model for a specific place.
Cited articles
Ala-aho, P., Rossi, P. M., and Kløve, B.: Estimation of temporal and spatial variations in groundwater recharge in unconfined sand aquifers using Scots pine inventories, Hydrol. Earth Syst. Sci., 19, 1961–1976, https://doi.org/10.5194/hess-19-1961-2015, 2015
Alley, W. M., Reilly, T. E., and Franke, O. L.: Sustainability of ground-water resources, US Department of the Interior, US Geological Survey, 1186, Denver, Colorado, USA, 1999.
Anurag, H. and Ng, G. H. C.: Assessing future climate change impacts on groundwater recharge in Minnesota, J. Hydrol., 612, 128112, https://doi.org/10.1016/J.JHYDROL.2022.128112, 2022.
Asoka, A., Wada, Y., Fishman, R., and Mishra, V.: Strong linkage between precipitation intensity and monsoon season groundwater recharge in India, Geophys. Res. Lett., 45, 5536–5544, https://doi.org/10.1029/2018GL078466, 2018.
Barnett, L. and Seth, A. K.: The MVGC multivariate Granger causality toolbox: A new approach to Granger-causal inference, J. Neurosci. Meth., 223, 50–68, https://doi.org/10.1016/j.jneumeth.2013.10.018, 2014.
Berghuijs, W. R., Luijendijk, E., Moeck, C., van der Velde, Y., and Allen, S. T.: Global Recharge Data Set Indicates Strengthened Groundwater Connection to Surface Fluxes, Geophys. Res. Lett., 49, e2022GL099010, https://doi.org/10.1029/2022GL099010, 2022.
Bhanja, S. N., Mukherjee, A., Rangarajan, R., Scanlon, B. R., Malakar, P., and Verma, S.: Long-term groundwater recharge rates across India by in situ measurements, Hydrol. Earth Syst. Sci., 23, 711–722, https://doi.org/10.5194/hess-23-711-2019, 2019.
Blasch, K. W., Constantz, J., and Stonestrom, D. A.: Thermal Methods for Investigating Groundwater Recharge, Prof. Pap., USGS, https://doi.org/10.3133/PP17031, 2007.
Boumis, G., Kumar, M., Nimmo, J. R., and Clement, T. P.: Influence of Shallow Groundwater Evapotranspiration on Recharge Estimation Using the Water Table Fluctuation Method, Water Resour. Res., 58, e2022WR032073, https://doi.org/10.1029/2022WR032073, 2022.
Chaney, N. W., Minasny, B., Herman, J. D., Nauman, T. W., Brungard, C. W., Morgan, C. L. S., McBratney, A. B., Wood, E. F., and Yimam, Y.: POLARIS Soil Properties: 30 m Probabilistic Maps of Soil Properties Over the Contiguous United States, Water Resour. Res., 55, 2916–2938, https://doi.org/10.1029/2018WR022797, 2019.
Chen, X., Kumar, M., deB Richter, D., and Mau, Y.: Impact of gully incision on hillslope hydrology, Hydrol. Process., 34, 3848–3866, https://doi.org/10.1002/HYP.13845, 2020.
Condon, L. E., Atchley, A. L., and Maxwell, R. M.: Evapotranspiration depletes groundwater under warming over the contiguous United States, Nat. Commun., 11, 1–8, https://doi.org/10.1038/s41467-020-14688-0, 2020.
Crosbie, R. S., Binning, P., and Kalma, J. D.: A time series approach to inferring groundwater recharge using the water table fluctuation method, Water Resour. Res., 41, 1–9, https://doi.org/10.1029/2004WR003077, 2005.
Crosbie, R. S., Davies, P., Harrington, N., and Lamontagne, S.: Ground truthing groundwater-recharge estimates derived from remotely sensed evapotranspiration: a case in South Australia, Hydrogeol. J., 23, 335–350, https://doi.org/10.1007/s10040-014-1200-7, 2015.
Crosbie, R. S., Doble, R. C., Turnadge, C., and Taylor, A. R.: Constraining the Magnitude and Uncertainty of Specific Yield for Use in the Water Table Fluctuation Method of Estimating Recharge, Water Resour. Res., 55, 7343–7361, https://doi.org/10.1029/2019WR025285, 2019.
Cunningham, W. L., Geiger, L. H., and Karavatis, G. A.: US Geological Survey Groundwater Climate Response Network, US Department of the Interior, US Geological Survey Fact Sheet 2007–3003, 4, https://doi.org/10.3133/fs20073003, 2007.
Cuthbert, M. O.: An improved time series approach for estimating groundwater recharge from groundwater level fluctuations, Water Resour. Res., 46, 9515, https://doi.org/10.1029/2009WR008572, 2010.
Cuthbert, M. O., Taylor, R. G., Favreau, G., Todd, M. C., Shamsudduha, M., Villholth, K. G., MacDonald, A. M., Scanlon, B. R., Kotchoni, D. O. V., Vouillamoz, J. M., Lawson, F. M. A., Adjomayi, P. A., Kashaigili, J., Seddon, D., Sorensen, J. P. R., Ebrahim, G. Y., Owor, M., Nyenje, P. M., Nazoumou, Y., Goni, I., Ousmane, B. I., Sibanda, T., Ascott, M. J., Macdonald, D. M. J., Agyekum, W., Koussoubé, Y., Wanke, H., Kim, H., Wada, Y., Lo, M. H., Oki, T., and Kukuric, N.: Observed controls on resilience of groundwater to climate variability in sub-Saharan Africa, Nature, 572, 230–234, https://doi.org/10.1038/s41586-019-1441-7, 2019.
Dai, Y., Xin, Q., Wei, N., Zhang, Y., Shangguan, W., Yuan, H., Zhang, S., Liu, S., and Lu, X.: A Global High-Resolution Data Set of Soil Hydraulic and Thermal Properties for Land Surface Modeling, J. Adv. Model. Earth Sy., 11, 2996–3023, https://doi.org/10.1029/2019MS001784, 2019.
Daly, C., Halbleib, M., Smith, J. I., Gibson, W. P., Doggett, M. K., Taylor, G. H., Curtis, J., and Pasteris, P. P.: Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States, Int. J. Climatol., 28, 2031–2064, https://doi.org/10.1002/JOC.1688, 2008.
Delin, G. N., Healy, R. W., Lorenz, D. L., and Nimmo, J. R.: Comparison of local- to regional-scale estimates of groundwater recharge in Minnesota, USA, J. Hydrol., 334, 231–249, https://doi.org/10.1016/J.JHYDROL.2006.10.010, 2007.
Famiglietti, J. S.: The global groundwater crisis, Nat. Clim. Change, 4, 945–948, https://doi.org/10.1038/nclimate2425, 2014.
Fan, Y., Clark, M., Lawrence, D. M., Swenson, S., Band, L. E., Brantley, S. L., Brooks, P. D., Dietrich, W. E., Flores, A., Grant, G., Kirchner, J. W., Mackay, D. S., McDonnell, J. J., Milly, P. C. D., Sullivan, P. L., Tague, C., Ajami, H., Chaney, N., Hartmann, A., Hazenberg, P., McNamara, J., Pelletier, J., Perket, J., Rouholahnejad-Freund, E., Wagener, T., Zeng, X., Beighley, E., Buzan, J., Huang, M., Livneh, B., Mohanty, B. P., Nijssen, B., Safeeq, M., Shen, C., van Verseveld, W., Volk, J., and Yamazaki, D.: Hillslope Hydrology in Global Change Research and Earth System Modeling, Water Resour. Res., 55, 1737–1772, https://doi.org/10.1029/2018WR023903, 2019.
Gehman, C. L., Harry, D. L., Sanford, W. E., Stednick, J. D., and Beckman, N. A.: Estimating specific yield and storage change in an unconfined aquifer using temporal gravity surveys, Water Resour. Res., 45, W00D21, https://doi.org/10.1029/2007WR006096, 2009.
Ghannam, K., Nakai, T., Paschalis, A., Oishi, C. A., Kotani, A., Igarashi, Y., Kumagai, T., and Katul, G. G.: Persistence and memory timescales in root-zone soil moisture dynamics, Water Resour. Res., 52, 1427–1445, https://doi.org/10.1002/2015WR017983, 2016.
Gnann, S., Reinecke, R., Stein, L., Wada, Y., Thiery, W., Müller Schmied, H., Satoh, Y., Pokhrel, Y., Ostberg, S., Koutroulis, A., Hanasaki, N., Grillakis, M., Gosling, S. N., Burek, P., Bierkens, M. F. P., and Wagener, T.: Functional relationships reveal differences in the water cycle representation of global water models, Nat. Water 112, 1079–1090, https://doi.org/10.1038/s44221-023-00160-y, 2023.
Gong, C., Zhang, Z., Wang, W., Duan, L., and Wang, Z.: An assessment of different methods to determine specific yield for estimating groundwater recharge using lysimeters, Sci. Total Environ., 788, 147799, https://doi.org/10.1016/J.SCITOTENV.2021.147799, 2021.
Gonzalez, M. O., Preetha, P., Kumar, M., and Clement, T. P.: Comparison of Data-Driven Groundwater Recharge Estimates with a Process-Based Model for a River Basin in the Southeastern USA, J. Hydrol. Eng., 28, 04023019, https://doi.org/10.1061/JHYEFF.HEENG-5882, 2023.
Gumuła-Kawęcka, A., Jaworska-Szulc, B., Szymkiewicz, A., Gorczewska-Langner, W., Pruszkowska-Caceres, M., Angulo-Jaramillo, R., and Šimůnek, J.: Estimation of groundwater recharge in a shallow sandy aquifer using unsaturated zone modeling and water table fluctuation method, J. Hydrol., 605, 127283, https://doi.org/10.1016/j.jhydrol.2021.127283, 2022.
Gupta, S., Papritz, A., Lehmann, P., Hengl, T., Bonetti, S., and Or, D.: Global Soil Hydraulic Properties dataset based on legacy site observations and robust parameterization, Sci. Data, 9, 444, https://doi.org/10.1038/s41597-022-01481-5, 2022.
Healy, R. W.: Estimating groundwater recharge, Cambridge University Press, 245 pp., https://doi.org/10.1017/CBO9780511780745, 2010.
Healy, R. W. and Cook, P. G.: Using groundwater levels to estimate recharge, Hydrogeol. J., 101, 91–109, https://doi.org/10.1007/S10040-001-0178-0, 2002.
Heppner, C. S. and Nimmo, J. R.: A Computer Program for Predicting Recharge with a Master Recession Curve, US Geol. Surv. Sci. Invest. Rep. 2005-5172, US Geological Survey, p. 8, https://pubs.er.usgs.gov/publication/sir2005517 (last access: 3 April 2025), 2005.
Hung Vu, V. and Merkel, B. J.: Estimating groundwater recharge for Hanoi, Vietnam, Sci. Total Environ., 651, 1047–1057, https://doi.org/10.1016/J.SCITOTENV.2018.09.225, 2019.
Jasechko, S., Seybold, H., Perrone, D., Fan, Y., and Kirchner, J. W.: Widespread potential loss of streamflow into underlying aquifers across the USA, Nature, 591, 391–395, https://doi.org/10.1038/s41586-021-03311-x, 2021.
Kim, N. W., Chung, I. M., Won, Y. S., and Arnold, J. G.: Development and application of the integrated SWAT–MODFLOW model, J. Hydrol., 356, 1–16, https://doi.org/10.1016/J.JHYDROL.2008.02.024, 2008.
Kollet, S. J. and Maxwell, R. M.: Integrated surface-groundwater flow modeling: A free-surface overland flow boundary condition in a parallel groundwater flow model, Adv. Water Resour., 29, 945–958, https://doi.org/10.1016/j.advwatres.2005.08.006, 2006.
Konikow, L. F.: Long-Term Groundwater Depletion in the United States, Groundwater, 53, 2–9, https://doi.org/10.1111/gwat.12306, 2015.
Kumar, M. and Duffy, C. J.: Exploring the Role of Domain Partitioning on Efficiency of Parallel Distributed Hydrologic Model Simulations, J. Hydrogeol. Hydrol. Eng., 12, 2, https://doi.org/10.4172/2325-9647.1000119, 2015.
Kumar, M., Duffy, C. J., and Salvage, K. M.: A Second-Order Accurate, Finite Volume-Based, Integrated Hydrologic Modeling (FIHM) Framework for Simulation of Surface and Subsurface Flow, Vadose Zone J., 8, 873–890, https://doi.org/10.2136/vzj2009.0014, 2009.
Lapworth, D. J., MacDonald, A. M., Krishan, G., Rao, M. S., Gooddy, D. C., and Darling, W. G.: Groundwater recharge and age-depth profiles of intensively exploited groundwater resources in northwest India, Geophys. Res. Lett., 42, 7554–7562, https://doi.org/10.1002/2015GL065798, 2015.
Li, B. and Rodell, M.: Evaluation of a model-based groundwater drought indicator in the conterminous U. S., J. Hydrol., 526, 78–88, https://doi.org/10.1016/J.JHYDROL.2014.09.027, 2015.
Li, B., Rodell, M., Peters-Lidard, C., Erlingis, J., Kumar, S., and Mocko, D.: Groundwater recharge estimated by land surface models: An evaluation in the conterminous United States, J. Hydrometeorol., 22, 499–522, https://doi.org/10.1175/JHM-D-20-0130.1, 2021.
Liu, Y., Parolari, A. J., Kumar, M., Huang, C. W., Katul, G. G., and Porporato, A.: Increasing atmospheric humidity and CO2 concentration alleviate forest mortality risk, P. Natl. Acad. Sci. USA, 114, 9918–9923, https://doi.org/10.1073/pnas.1704811114, 2017.
Liu, Y., Kumar, M., Katul, G. G., Feng, X., and Konings, A. G.: Plant hydraulics accentuates the effect of atmospheric moisture stress on transpiration, Nat. Clim. Change, 107, 10, 691–695, https://doi.org/10.1038/s41558-020-0781-5, 2020.
Lv, M., Xu, Z., Yang, Z. L., Lu, H., and Lv, M.: A Comprehensive Review of Specific Yield in Land Surface and Groundwater Studies, J. Adv. Model. Earth Sy., 13, e2020MS00227, https://doi.org/10.1029/2020MS002270, 2021.
Malakar, P., Mukherjee, A., Bhanja, S. N., Ganguly, A. R., Ray, R. K., Zahid, A., Sarkar, S., Saha, D., and Chattopadhyay, S.: Three decades of depth-dependent groundwater response to climate variability and human regime in the transboundary Indus-Ganges-Brahmaputra-Meghna mega river basin aquifers, Adv. Water Resour., 149, 103856, https://doi.org/10.1016/J.ADVWATRES.2021.103856, 2021a.
Malakar, P., Mukherjee, A., Bhanja, S. N., Ray, R. K., Sarkar, S., and Zahid, A.: Machine-learning-based regional-scale groundwater level prediction using GRACE, Hydrogeol. J., 29, 1027–1042, https://doi.org/10.1007/s10040-021-02306-2, 2021b.
Malakar, P., Mukherjee, A., Bhanja, S. N., Sarkar, S., Saha, D., and Ray, R. K.: Deep Learning-Based Forecasting of Groundwater Level Trends in India: Implications for Crop Production and Drinking Water Supply, ACS ES&T Eng., 1, 965–977, https://doi.org/10.1021/ACSESTENGG.0C00238, 2021c.
Malakar, P., Anshuman, A., Boumis, G., Kumar, M., Clement, P., Tashie, A., Thakur, H., and Rathore, L.: An in-situ daily dataset for benchmarking temporal variability of groundwater recharge, Zenodo [code and data set], https://doi.org/10.5281/zenodo.13323242, 2024.
Maréchal, J. C., Dewandel, B., Ahmed, S., Galeazzi, L., and Zaidi, F. K.: Combined estimation of specific yield and natural recharge in a semi-arid groundwater basin with irrigated agriculture, J. Hydrol., 329, 281–293, https://doi.org/10.1016/j.jhydrol.2006.02.022, 2006.
Martens, B., Miralles, D. G., Lievens, H., van der Schalie, R., de Jeu, R. A. M., Fernández-Prieto, D., Beck, H. E., Dorigo, W. A., and Verhoest, N. E. C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, 2017.
McMahon, P. B., Plummer, L. N., Böhlke, J. K., Shapiro, S. D., and Hinkle, S. R.: A comparison of recharge rates in aquifers of the United States based on groundwater-age data, Hydrogeol. J., 19, 779–800, https://doi.org/10.1007/s10040-011-0722-5, 2011.
Meyboom, P.: Estimating groundwater recharge from stream hydrographs, J. Geophys. Res., 66, 1203–1214, https://doi.org/10.1029/JZ066I004P01203, 1961.
Milly, P. C. D. and Dunne, K. A.: Potential evapotranspiration and continental drying, Nat. Clim. Change, 6, 946–949, https://doi.org/10.1038/nclimate3046, 2016.
Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453–469, https://doi.org/10.5194/hess-15-453-2011, 2011.
Moeck, C., Grech-Cumbo, N., Podgorski, J., Bretzler, A., Gurdak, J. J., Berg, M., and Schirmer, M.: A global-scale dataset of direct natural groundwater recharge rates: A review of variables, processes and relationships, Sci. Total Environ., 717, https://doi.org/10.1016/j.scitotenv.2020.137042, 2020.
Mueller, B. and Seneviratne, S. I.: Systematic land climate and evapotranspiration biases in CMIP5 simulations, Geophys. Res. Lett., 41, 128–134, https://doi.org/10.1002/2013GL058055, 2014.
National Snow and Ice Data Center: Snow Data Assimilation System (SNODAS) Data Products at NSIDC, Version 1, National Snow and Ice Data Center, https://nsidc.org/data/G02158/versions/1 (last access: 15 January 2024), 2022.
Nimmo, J. R. and Perkins, K. S.: Episodic Master Recession Evaluation of Groundwater and Streamflow Hydrographs for Water-Resource Estimation, Vadose Zone J., 17, 180050, https://doi.org/10.2136/vzj2018.03.0050, 2018.
Nimmo, J. R., Horowitz, C., and Mitchell, L.: Discrete-storm water-table fluctuation method to estimate episodic recharge, Groundwater, 53, 282–292, https://doi.org/10.1111/gwat.12177, 2015.
Niraula, R., Meixner, T., Ajami, H., Rodell, M., Gochis, D., and Castro, C. L.: Comparing potential recharge estimates from three Land Surface Models across the western US, J. Hydrol., 545, 410–423, https://doi.org/10.1016/j.jhydrol.2016.12.028, 2017.
Raghav, P. and Kumar, M.: Retrieving gap-free daily root zone soil moisture using surface flux equilibrium theory, Environ. Res. Lett., 16, 104007, https://doi.org/10.1088/1748-9326/AC2441, 2021.
Raghav, P., Wagle, P., Kumar, M., Banerjee, T., and Neel, J. P. S.: Vegetation Index-Based Partitioning of Evapotranspiration Is Deficient in Grazed Systems, Water Resour. Res., 58, e2022WR032067, https://doi.org/10.1029/2022WR032067, 2022.
Reitz, M. and Sanford, W.: Modern monthly effective recharge maps for the conterminous US, 2003–2015, USGS Science Data Catalog, https://data.usgs.gov/datacatalog/data/USGS:5cd0a1b1e4b09b8c0b79a51c (last access: 15 January 2024), 2019a.
Reitz, M. and Sanford, W. E.: Estimating quick-flow runoff at the monthly timescale for the conterminous United States, J. Hydrol., 573, 841–854, https://doi.org/10.1016/j.jhydrol.2019.04.010, 2019b.
Reitz, M., Sanford, W. E., Senay, G. B., and Cazenas, J.: Annual Estimates of Recharge, Quick-Flow Runoff, and Evapotranspiration for the Contiguous U. S. Using Empirical Regression Equations, J. Am. Water Resour. As., 53, 961–983, https://doi.org/10.1111/1752-1688.12546, 2017a.
Reitz, M., Senay, G. B., and Sanford, W. E.: Combining remote sensing and water-balance evapotranspiration estimates for the conterminous United States, Remote Sens.-Basel, 9, https://doi.org/10.3390/rs9121181, 2017b.
Ruddell, B. L., Drewry, D. T., and Nearing, G. S.: Information Theory for Model Diagnostics: Structural Error is Indicated by Trade-Off Between Functional and Predictive Performance, Water Resour. Res., 55, 6534–6554, https://doi.org/10.1029/2018WR023692, 2019.
Runge, J.: Causal network reconstruction from time series: From theoretical assumptions to practical estimation, Chaos, 28, 075310, https://doi.org/10.1063/1.5025050, 2018.
Runge, J., Bathiany, S., Bollt, E., Camps-Valls, G., Coumou, D., Deyle, E., Glymour, C., Kretschmer, M., Mahecha, M. D., Muñoz-Marí, J., van Nes, E. H., Peters, J., Quax, R., Reichstein, M., Scheffer, M., Schölkopf, B., Spirtes, P., Sugihara, G., Sun, J., Zhang, K., and Zscheischler, J.: Inferring causation from time series in Earth system sciences, Nat. Commun., 101, 1–13, https://doi.org/10.1038/s41467-019-10105-3, 2019.
Russo, T. A. and Lall, U.: Depletion and response of deep groundwater to climate-induced pumping variability, Nat. Geosci., 10, 105–108, https://doi.org/10.1038/ngeo2883, 2017.
Scanlon, B. R., Healy, R. W., and Cook, P. G.: Choosing appropriate techniques for quantifying groundwater recharge, Hydrogeol. J., 101, 18–39, https://doi.org/10.1007/S10040-001-0176-2, 2002.
Scanlon, B. R., Keese, K. E., Flint, A. L., Flint, L. E., Gaye, C. B., Edmunds, W. M., and Simmers, I.: Global synthesis of groundwater recharge in semiarid and arid regions, Hydrol. Process., 20, 3335–3370, https://doi.org/10.1002/hyp.6335, 2006.
Scanlon, B. R., Mukherjee, A., Gates, J., Reedy, R. C., and Sinha, A. K.: Groundwater recharge in natural dune systems and agricultural ecosystems in the Thar Desert region, Rajasthan, India, Hydrogeol. J., 18, 959–972, https://doi.org/10.1007/s10040-009-0555-7, 2010.
Seo, S. B., Mahinthakumar, G., Sankarasubramanian, A., and Kumar, M.: Conjunctive Management of Surface Water and Groundwater Resources under Drought Conditions Using a Fully Coupled Hydrological Model, J. Water Res. Pl., 144, 04018060, https://doi.org/10.1061/(ASCE)WR.1943-5452.0000978, 2018.
Shah, N. and Ross, M.: Variability in Specific Yield under Shallow Water Table Conditions, J. Hydrol. Eng., 14, 1290–1298, https://doi.org/10.1061/(asce)he.1943-5584.0000121, 2009.
Singh, N. K. and Borrok, D. M.: A Granger causality analysis of groundwater patterns over a half-century, Sci. Rep.-UK, 91, 1–8, https://doi.org/10.1038/s41598-019-49278-8, 2019.
Squeo, F. A., Aravena, R., Aguirre, E., Pollastri, A., Jorquera, C. B., and Ehleringer, J. R.: Groundwater dynamics in a coastal aquifer in north-central Chile: Implications for groundwater recharge in an arid ecosystem, J. Arid Environ., 67, 240–254, https://doi.org/10.1016/j.jaridenv.2006.02.012, 2006.
Tashie, A. M., Mirus, B. B., and Pavelsky, T. M.: Identifying long-term empirical relationships between storm characteristics and episodic groundwater recharge, Water Resour. Res., 52, 21–35, https://doi.org/10.1002/2015WR017876, 2016.
Taylor, R. G., Scanlon, B., Döll, P., Rodell, M., Van Beek, R., Wada, Y., Longuevergne, L., Leblanc, M., Famiglietti, J. S., Edmunds, M., Konikow, L., Green, T. R., Chen, J., Taniguchi, M., Bierkens, M. F. P., Macdonald, A., Fan, Y., Maxwell, R. M., Yechieli, Y., Gurdak, J. J., Allen, D. M., Shamsudduha, M., Hiscock, K., Yeh, P. J. F., Holman, I., and Treidel, H.: Ground water and climate change, Nat. Clim. Change, 3, 322–329, https://doi.org/10.1038/nclimate1744, 2013a.
Taylor, R. G., Todd, M. C., Kongola, L., Maurice, L., Nahozya, E., Sanga, H., and Macdonald, A. M.: Evidence of the dependence of groundwater resources on extreme rainfall in East Africa, Nat. Clim. Change, 3, 374–378, https://doi.org/10.1038/nclimate1731, 2013b.
Therrien, R., McLaren, R. G. G., Sudicky, E. A. A., and Panday, S. M. M.: HydroGeoSphere: a three-dimensional numerical model describing fully-integrated subsurface and surface flow and solute transport, Groundw. Simulations Group, Univ. Waterloo, Waterloo, 322 pp., https://www.ggl.ulaval.ca/fileadmin/ggl/documents/rtherrien/hydrogeosphere.pdf (last access: 15 January 2024), 2010.
Thomas, B. F., Behrangi, A., and Famiglietti, J. S.: Precipitation intensity effects on groundwater recharge in the southwestern United States, Water-Sui., 8, 90, https://doi.org/10.3390/w8030090, 2016.
Valois, R., MacDonell, S., Núñez Cobo, J. H., and Maureira-Cortés, H.: Groundwater level trends and recharge event characterization using historical observed data in semi-arid Chile, Hydrolog. Sci. J., 65, 597–609, https://doi.org/10.1080/02626667.2020.1711912, 2020.
Varni, M., Comas, R., Weinzettel, P., and Dietrich, S.: Application of the water table fluctuation method to characterize groundwater recharge in the Pampa plain, Argentina, Hydrol. Sci. J., 58, 1445–1455, https://doi.org/10.1080/02626667.2013.833663, 2013.
Wu, J., Cao, M., Tong, D., Finkelstein, Z., and Hoek, E. M. V.: A critical review of point-of-use drinking water treatment in the United States, npj Clean Water, 4, 40, https://doi.org/10.1038/s41545-021-00128-z, 2021.
Xu, C. Y. and Chen, D.: Comparison of seven models for estimation of evapotranspiration and groundwater recharge using lysimeter measurement data in Germany, Hydrol. Process., 19, 3717–3734, https://doi.org/10.1002/HYP.5853, 2005.
Ye, H., Deyle, E. R., Gilarranz, L. J., and Sugihara, G.: Distinguishing time-delayed causal interactions using convergent cross mapping, Sci. Rep.-UK, 5, 14750, https://doi.org/10.1038/srep14750, 2015.
Zhang, J., Felzer, B. S., and Troy, T. J.: Extreme precipitation drives groundwater recharge: the Northern High Plains Aquifer, central United States, 1950–2010, Hydrol. Process., 30, 2533–2545, https://doi.org/10.1002/hyp.10809, 2016.
Short summary
Groundwater dynamics depend on groundwater recharge, but daily benchmark data of recharge are scarce. Here we present a daily groundwater recharge per unit specified yield (RpSy) data at 485 US groundwater monitoring wells. RpSy can be used to validate the temporal consistency of recharge products from land surface and hydrologic models and facilitate assessment of recharge-driver functional relationships in them.
Groundwater dynamics depend on groundwater recharge, but daily benchmark data of recharge are...
Altmetrics
Final-revised paper
Preprint