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
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Pragnaditya Malakar, Abhijit Mukherjee, Soumendra N. Bhanja, Dipankar Saha, Ranjan Kumar Ray, Sudeshna Sarkar, and Anwar Zahid
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-208, https://doi.org/10.5194/hess-2020-208, 2020
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Groundwater withdrawals and population are the primary influencing factors affecting groundwater level change in most of the Indus-Ganges-Brahmaputra-Meghna basin aquifer of South-Asia. Machine learning-based methods can be used to model groundwater level efficiently in the basin. However, in areas where human influence dominates, these methods have limitations in modeling groundwater level due to insufficient knowledge of spatial and depth-dependent groundwater withdrawals.
Soumendra N. Bhanja, Abhijit Mukherjee, R. Rangarajan, Bridget R. Scanlon, Pragnaditya Malakar, and Shubha Verma
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Groundwater depletion in India has been a much-debated issue in recent years. Here we investigate long-term, spatiotemporal variation in prevailing groundwater recharge rates across India. Groundwater recharge rates have been estimated based on field-scale groundwater-level measurements and the tracer injection approach; recharge rates from the two estimates compared favorably. The role of precipitation in controlling groundwater recharge is studied.
Soheil Radfar, Georgios Boumis, Hamed R. Moftakhari, Wanyun Shao, Larisa Lee, and Alison N. Rellinger
Geosci. Commun. Discuss., https://doi.org/10.5194/gc-2024-7, https://doi.org/10.5194/gc-2024-7, 2024
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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.
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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.
Pragnaditya Malakar, Abhijit Mukherjee, Soumendra N. Bhanja, Dipankar Saha, Ranjan Kumar Ray, Sudeshna Sarkar, and Anwar Zahid
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Revised manuscript not accepted
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Hydrol. Earth Syst. Sci., 23, 711–722, https://doi.org/10.5194/hess-23-711-2019, https://doi.org/10.5194/hess-23-711-2019, 2019
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Groundwater depletion in India has been a much-debated issue in recent years. Here we investigate long-term, spatiotemporal variation in prevailing groundwater recharge rates across India. Groundwater recharge rates have been estimated based on field-scale groundwater-level measurements and the tracer injection approach; recharge rates from the two estimates compared favorably. The role of precipitation in controlling groundwater recharge is studied.
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Haiguang Cheng, Kaiheng Hu, Shuang Liu, Xiaopeng Zhang, Hao Li, Qiyuan Zhang, Lan Ning, Manish Raj Gouli, Pu Li, Anna Yang, and Peng Zhao
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After reviewing 2,519 literature and media reports, we compiled the first comprehensive global dataset of 555 debris flow barrier dams (DFBDs) from 1800 to 2023. Our dataset meticulously documents 36 attributes of DFBDs, and we have utilized Google Earth for validation. Additionally, we discussed the applicability of landslide dam stability and peak discharge models to DFBDs. This dataset offers a rich foundation of data for future studies on DFBDs.
Karl Nicolaus van Zweel, Laurent Gourdol, Jean François Iffly, Loïc Léonard, François Barnich, Laurent Pfister, Erwin Zehe, and Christophe Hissler
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Our study monitored groundwater in a Luxembourg forest over a year to understand water and chemical changes. We found seasonal variations in water chemistry, influenced by rainfall and soil interactions. This data helps predict environmental responses and manage water resources better. By measuring key parameters like pH and dissolved oxygen, our research provides valuable insights into groundwater behavior and serves as a resource for future environmental studies.
Rohit Mukherjee, Frederick Policelli, Ruixue Wang, Elise Arellano-Thompson, Beth Tellman, Prashanti Sharma, Zhijie Zhang, and Jonathan Giezendanner
Earth Syst. Sci. Data, 16, 4311–4323, https://doi.org/10.5194/essd-16-4311-2024, https://doi.org/10.5194/essd-16-4311-2024, 2024
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Lei Huang, Yong Luo, Jing M. Chen, Qiuhong Tang, Tammo Steenhuis, Wei Cheng, and Wen Shi
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Timely global terrestrial evapotranspiration (ET) data are crucial for water resource management and drought forecasting. This study introduces the VISEA algorithm, which integrates satellite data and shortwave radiation to provide daily 0.05° gridded near-real-time ET estimates. By employing a vegetation index–temperature method, this algorithm can estimate ET without requiring additional data. Evaluation results demonstrate VISEA's comparable accuracy with accelerated data availability.
Sibylle Kathrin Hassler, Rafael Bohn Reckziegel, Ben du Toit, Svenja Hoffmeister, Florian Kestel, Anton Kunneke, Rebekka Maier, and Jonathan Paul Sheppard
Earth Syst. Sci. Data, 16, 3935–3948, https://doi.org/10.5194/essd-16-3935-2024, https://doi.org/10.5194/essd-16-3935-2024, 2024
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Agroforestry systems (AFSs) combine trees and crops within the same land unit, providing a sustainable land use option which protects natural resources and biodiversity. Introducing trees into agricultural systems can positively affect water resources, soil characteristics, biomass and microclimate. We studied an AFS in South Africa in a multidisciplinary approach to assess the different influences and present the resulting dataset consisting of water, soil, tree and meteorological variables.
Keirnan J. A. Fowler, Ziqi Zhang, and Xue Hou
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-263, https://doi.org/10.5194/essd-2024-263, 2024
Revised manuscript accepted for ESSD
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This paper presents Version 2 of the Australian edition of the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS v2 comprises data for an increased number (561) of catchments, each with with long-term monitoring, combining hydrometeorological time series with attributes related to geology, soil, topography, land cover, anthropogenic influence and hydroclimatology. It is freely downloadable from https://zenodo.org/doi/10.5281/zenodo.12575680.
Kaihao Zheng, Peirong Lin, and Ziyun Yin
Earth Syst. Sci. Data, 16, 3873–3891, https://doi.org/10.5194/essd-16-3873-2024, https://doi.org/10.5194/essd-16-3873-2024, 2024
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We develop a globally applicable thresholding scheme for DEM-based floodplain delineation to improve the representation of spatial heterogeneity. It involves a stepwise approach to estimate the basin-level floodplain hydraulic geometry parameters that best respect the scaling law while approximating the global hydrodynamic flood maps. A ~90 m resolution global floodplain map, the Spatial Heterogeneity Improved Floodplain by Terrain analysis (SHIFT), is delineated with demonstrated superiority.
Yuzhong Yang, Qingbai Wu, Xiaoyan Guo, Lu Zhou, Helin Yao, Dandan Zhang, Zhongqiong Zhang, Ji Chen, and Guojun Liu
Earth Syst. Sci. Data, 16, 3755–3770, https://doi.org/10.5194/essd-16-3755-2024, https://doi.org/10.5194/essd-16-3755-2024, 2024
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We present the temporal data of stable isotopes in different waterbodies in the Beiluhe Basin in the hinterland of the Qinghai–Tibet Plateau (QTP) produced between 2017 and 2022. In this article, the first detailed stable isotope data of 359 ground ice samples are presented. This first data set provides a new basis for understanding the hydrological effects of permafrost degradation on the QTP.
Jun Liu, Julian Koch, Simon Stisen, Lars Troldborg, Anker Lajer Højberg, Hans Thodsen, Mark F. T. Hansen, and Raphael J. M. Schneider
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-292, https://doi.org/10.5194/essd-2024-292, 2024
Revised manuscript accepted for ESSD
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We developed a CAMELS-style dataset in Denmark, which contains hydrometeorological time series and landscape attributes for 3,330 catchments. Many of the catchments in CAMELS-DK are small and located at low elevations. The dataset provides information on groundwater characteristics and dynamics, as well as quantities related to human impact on the hydrological system in Denmark. The dataset is especially relevant for developing data-driven and hybrid physically-informed modeling frameworks.
Bernhard Lehner, Mira Anand, Etienne Fluet-Chouinard, Florence Tan, Filipe Aires, George H. Allen, Pilippe Bousquet, Josep G. Canadell, Nick Davidson, C. Max Finlayson, Thomas Gumbricht, Lammert Hilarides, Gustaf Hugelius, Robert B. Jackson, Maartje C. Korver, Peter B. McIntyre, Szabolcs Nagy, David Olefeldt, Tamlin M. Pavelsky, Jean-Francois Pekel, Benjamin Poulter, Catherine Prigent, Jida Wang, Thomas A. Worthington, Dai Yamazaki, and Michele Thieme
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-204, https://doi.org/10.5194/essd-2024-204, 2024
Revised manuscript accepted for ESSD
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The Global Lakes and Wetlands Database (GLWD) version 2 distinguishes a total of 33 non-overlapping wetland classes, providing a static map of the world’s inland surface waters. It contains cell fractions of wetland extents per class at a grid cell resolution of ~500 m. The total combined extent of all classes including all inland and coastal waterbodies and wetlands of all inundation frequencies—that is, the maximum extent—covers 18.2 million km2, equivalent to 13.4 % of total global land area.
Hordur Bragi Helgason and Bart Nijssen
Earth Syst. Sci. Data, 16, 2741–2771, https://doi.org/10.5194/essd-16-2741-2024, https://doi.org/10.5194/essd-16-2741-2024, 2024
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LamaH-Ice is a large-sample hydrology (LSH) dataset for Iceland. The dataset includes daily and hourly hydro-meteorological time series, including observed streamflow and basin characteristics, for 107 basins. LamaH-Ice offers most variables that are included in existing LSH datasets and additional information relevant to cold-region hydrology such as annual time series of glacier extent and mass balance. A large majority of the basins in LamaH-Ice are unaffected by human activities.
Chengcheng Hou, Yan Li, Shan Sang, Xu Zhao, Yanxu Liu, Yinglu Liu, and Fang Zhao
Earth Syst. Sci. Data, 16, 2449–2464, https://doi.org/10.5194/essd-16-2449-2024, https://doi.org/10.5194/essd-16-2449-2024, 2024
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To fill the gap in the gridded industrial water withdrawal (IWW) data in China, we developed the China Industrial Water Withdrawal (CIWW) dataset, which provides monthly IWWs from 1965 to 2020 at a spatial resolution of 0.1°/0.25° and auxiliary data including subsectoral IWW and industrial output value in 2008. This dataset can help understand the human water use dynamics and support studies in hydrology, geography, sustainability sciences, and water resource management and allocation in China.
Nehar Mandal, Prabal Das, and Kironmala Chanda
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-109, https://doi.org/10.5194/essd-2024-109, 2024
Revised manuscript accepted for ESSD
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Optimal features among hydroclimatic variables and land surface model (LSM) outputs are selected using a novel Bayesian network (BN) approach for simulating Terrestrial Water Storage Anomalies (TWSA). TWSA is simulated using ML models (CNN, SVR, ETR, and Stacking Ensemble Regression), and gridwise leader models are identified globally. TWSA is reconstructed (BNML_TWSA) with the selected leader models from January 1960 to December 2022 to generate a continuous global gridded dataset.
Pierre-Antoine Versini, Leydy Alejandra Castellanos-Diaz, David Ramier, and Ioulia Tchiguirinskaia
Earth Syst. Sci. Data, 16, 2351–2366, https://doi.org/10.5194/essd-16-2351-2024, https://doi.org/10.5194/essd-16-2351-2024, 2024
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Nature-based solutions (NBSs), such as green roofs, have appeared as relevant solutions to mitigate urban heat islands. The evapotranspiration (ET) process allows NBSs to cool the air. To improve our knowledge about ET assessment, this paper presents some experimental measurement campaigns carried out during three consecutive summers. Data are available for three different (large, small, and point-based) spatial scales.
Ralph Bathelemy, Pierre Brigode, Vazken Andréassian, Charles Perrin, Vincent Moron, Cédric Gaucherel, Emmanuel Tric, and Dominique Boisson
Earth Syst. Sci. Data, 16, 2073–2098, https://doi.org/10.5194/essd-16-2073-2024, https://doi.org/10.5194/essd-16-2073-2024, 2024
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The aim of this work is to provide the first hydroclimatic database for Haiti, a Caribbean country particularly vulnerable to meteorological and hydrological hazards. The resulting database, named Simbi, provides hydroclimatic time series for around 150 stations and 24 catchment areas.
Changming Li, Ziwei Liu, Wencong Yang, Zhuoyi Tu, Juntai Han, Sien Li, and Hanbo Yang
Earth Syst. Sci. Data, 16, 1811–1846, https://doi.org/10.5194/essd-16-1811-2024, https://doi.org/10.5194/essd-16-1811-2024, 2024
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Using a collocation-based approach, we developed a reliable global land evapotranspiration product (CAMELE) by merging multi-source datasets. The CAMELE product outperformed individual input datasets and showed satisfactory performance compared to reference data. It also demonstrated superiority for different plant functional types. Our study provides a promising solution for data fusion. The CAMELE dataset allows for detailed research and a better understanding of land–atmosphere interactions.
Yuhan Guo, Hongxing Zheng, Yuting Yang, Yanfang Sang, and Congcong Wen
Earth Syst. Sci. Data, 16, 1651–1665, https://doi.org/10.5194/essd-16-1651-2024, https://doi.org/10.5194/essd-16-1651-2024, 2024
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We have provided an inaugural version of the hydrogeomorphic dataset for catchments over the Tibetan Plateau. We first provide the width-function-based instantaneous unit hydrograph (WFIUH) for each HydroBASINS catchment, which can be used to investigate the spatial heterogeneity of hydrological behavior across the Tibetan Plateau. It is expected to facilitate hydrological modeling across the Tibetan Plateau.
Chang Liao, Darren Engwirda, Matthew Cooper, Mingke Li, and Yilin Fang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-398, https://doi.org/10.5194/essd-2023-398, 2024
Revised manuscript accepted for ESSD
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Discrete Global Grid systems, or DGGs, are digital frameworks that help us organize information about our planet. Although scientists have used DGGs in areas like weather and nature, using them in the water cycle has been challenging because some core datasets are missing. We created a way to generate these datasets. We then developed the datasets in the Amazon Basin, which plays an important role in our planet's climate. These datasets may help us improve our water cycle models.
Lingbo Li, Hong-Yi Li, Guta Abeshu, Jinyun Tang, L. Ruby Leung, Chang Liao, Zeli Tan, Hanqin Tian, Peter Thornton, and Xiaojuan Yang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-43, https://doi.org/10.5194/essd-2024-43, 2024
Revised manuscript accepted for ESSD
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We have developed a new map that reveals how organic carbon from soil leaches into headwater streams over the contiguous United States. We use advanced artificial intelligence techniques and a massive amount of data, including observations at over 2,500 gauges and a wealth of climate and environmental information. The map is a critical step in understanding and predicting how carbon moves through our environment, hence a useful tool for tackling climate challenges.
Ziyun Yin, Peirong Lin, Ryan Riggs, George H. Allen, Xiangyong Lei, Ziyan Zheng, and Siyu Cai
Earth Syst. Sci. Data, 16, 1559–1587, https://doi.org/10.5194/essd-16-1559-2024, https://doi.org/10.5194/essd-16-1559-2024, 2024
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Large-sample hydrology (LSH) datasets have been the backbone of hydrological model parameter estimation and data-driven machine learning models for hydrological processes. This study complements existing LSH studies by creating a dataset with improved sample coverage, uncertainty estimates, and dynamic descriptions of human activities, which are all crucial to hydrological understanding and modeling.
Pierluigi Claps, Giulia Evangelista, Daniele Ganora, Paola Mazzoglio, and Irene Monforte
Earth Syst. Sci. Data, 16, 1503–1522, https://doi.org/10.5194/essd-16-1503-2024, https://doi.org/10.5194/essd-16-1503-2024, 2024
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FOCA (Italian FlOod and Catchment Atlas) is the first systematic collection of data on Italian river catchments. It comprises geomorphological, soil, land cover, NDVI, climatological and extreme rainfall catchment attributes. FOCA also contains 631 peak and daily discharge time series covering the 1911–2016 period. Using this first nationwide data collection, a wide range of applications, in particular flood studies, can be undertaken within the Italian territory.
Wei Jing Ang, Edward Park, Yadu Pokhrel, Dung Duc Tran, and Ho Huu Loc
Earth Syst. Sci. Data, 16, 1209–1228, https://doi.org/10.5194/essd-16-1209-2024, https://doi.org/10.5194/essd-16-1209-2024, 2024
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Dams have burgeoned in the Mekong, but information on dams is scattered and inconsistent. Up-to-date evaluation of dams is unavailable, and basin-wide hydropower potential has yet to be systematically assessed. We present a comprehensive database of 1055 dams, a spatiotemporal analysis of the dams, and a total hydropower potential of 1 334 683 MW. Considering projected dam development and hydropower potential, the vulnerability and the need for better dam management may be highest in Laos.
Chuanqi He, Ci-Jian Yang, Jens M. Turowski, Richard F. Ott, Jean Braun, Hui Tang, Shadi Ghantous, Xiaoping Yuan, and Gaia Stucky de Quay
Earth Syst. Sci. Data, 16, 1151–1166, https://doi.org/10.5194/essd-16-1151-2024, https://doi.org/10.5194/essd-16-1151-2024, 2024
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The shape of drainage basins and rivers holds significant implications for landscape evolution processes and dynamics. We used a global 90 m resolution topography to obtain ~0.7 million drainage basins with sizes over 50 km2. Our dataset contains the spatial distribution of drainage systems and their morphological parameters, supporting fields such as geomorphology, climatology, biology, ecology, hydrology, and natural hazards.
Jingyu Lin, Peng Wang, Jinzhu Wang, Youping Zhou, Xudong Zhou, Pan Yang, Hao Zhang, Yanpeng Cai, and Zhifeng Yang
Earth Syst. Sci. Data, 16, 1137–1149, https://doi.org/10.5194/essd-16-1137-2024, https://doi.org/10.5194/essd-16-1137-2024, 2024
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Our paper provides a repository comprising over 330 000 observations encompassing daily, weekly, and monthly records of surface water quality spanning the period 1980–2022. It included 18 distinct indicators, meticulously gathered at 2384 monitoring sites, ranging from inland locations to coastal and oceanic areas. This dataset will be very useful for researchers and decision-makers in the fields of hydrology, ecological studies, climate change, policy development, and oceanography.
Ana M. Ricardo, Rui M. L. Ferreira, Alberto Rodrigues da Silva, Jacinto Estima, Jorge Marques, Ivo Gamito, and Alexandre Serra
Earth Syst. Sci. Data, 16, 375–385, https://doi.org/10.5194/essd-16-375-2024, https://doi.org/10.5194/essd-16-375-2024, 2024
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Floods are among the most common natural disasters responsible for severe damages and human losses. Agueda.2016Flood, a synthesis of locally sensed data and numerically produced data, allows complete characterization of the flood event that occurred in February 2016 in the Portuguese Águeda River. The dataset was managed through the RiverCure Portal, a collaborative web platform connected to a validated shallow-water model.
Jiawei Hou, Albert I. J. M. Van Dijk, Luigi J. Renzullo, and Pablo R. Larraondo
Earth Syst. Sci. Data, 16, 201–218, https://doi.org/10.5194/essd-16-201-2024, https://doi.org/10.5194/essd-16-201-2024, 2024
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The GloLakes dataset provides historical and near-real-time time series of relative (i.e. storage change) and absolute (i.e. total stored volume) storage for more than 27 000 lakes worldwide using multiple sources of satellite data, including laser and radar altimetry and optical remote sensing. These data can help us understand the influence of climate variability and anthropogenic activities on water availability and system ecology over the last 4 decades.
Menaka Revel, Xudong Zhou, Prakat Modi, Jean-François Cretaux, Stephane Calmant, and Dai Yamazaki
Earth Syst. Sci. Data, 16, 75–88, https://doi.org/10.5194/essd-16-75-2024, https://doi.org/10.5194/essd-16-75-2024, 2024
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As satellite technology advances, there is an incredible amount of remotely sensed data for observing terrestrial water. Satellite altimetry observations of water heights can be utilized to calibrate and validate large-scale hydrodynamic models. However, because large-scale models are discontinuous, comparing satellite altimetry to predicted water surface elevation is difficult. We developed a satellite altimetry mapping procedure for high-resolution river network data.
Marvin Höge, Martina Kauzlaric, Rosi Siber, Ursula Schönenberger, Pascal Horton, Jan Schwanbeck, Marius Günter Floriancic, Daniel Viviroli, Sibylle Wilhelm, Anna E. Sikorska-Senoner, Nans Addor, Manuela Brunner, Sandra Pool, Massimiliano Zappa, and Fabrizio Fenicia
Earth Syst. Sci. Data, 15, 5755–5784, https://doi.org/10.5194/essd-15-5755-2023, https://doi.org/10.5194/essd-15-5755-2023, 2023
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CAMELS-CH is an open large-sample hydro-meteorological data set that covers 331 catchments in hydrologic Switzerland from 1 January 1981 to 31 December 2020. It comprises (a) daily data of river discharge and water level as well as meteorologic variables like precipitation and temperature; (b) yearly glacier and land cover data; (c) static attributes of, e.g, topography or human impact; and (d) catchment delineations. CAMELS-CH enables water and climate research and modeling at catchment level.
Peter Burek and Mikhail Smilovic
Earth Syst. Sci. Data, 15, 5617–5629, https://doi.org/10.5194/essd-15-5617-2023, https://doi.org/10.5194/essd-15-5617-2023, 2023
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We address an annoying problem every grid-based hydrological model must solve to compare simulated and observed river discharge. First, station locations do not fit the high-resolution river network. We update the database with stations based on a new high-resolution network. Second, station locations do not work with a coarser grid-based network. We use a new basin shape similarity concept for station locations on a coarser grid, reducing the error of assigning stations to the wrong basin.
Najwa Sharaf, Jordi Prats, Nathalie Reynaud, Thierry Tormos, Rosalie Bruel, Tiphaine Peroux, and Pierre-Alain Danis
Earth Syst. Sci. Data, 15, 5631–5650, https://doi.org/10.5194/essd-15-5631-2023, https://doi.org/10.5194/essd-15-5631-2023, 2023
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We present a regional long-term (1959–2020) dataset (LakeTSim) of daily epilimnion and hypolimnion water temperature simulations in 401 French lakes. Overall, less uncertainty is associated with the epilimnion compared to the hypolimnion. LakeTSim is valuable for providing new insights into lake water temperature for assessing the impact of climate change, which is often hindered by the lack of observations, and for decision-making by stakeholders.
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...
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