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21 results for “groundwater recharge”
Global groundwater recharge estimates
<p>Groundwater recharge estimates have been presented in Berghuijs et al. (2022). The estimates exclude regions with mean temperatures below −2°C and regions with aridity below 1. The estimates consist of total groundwater recharge (units mm per year) and the fraction of precipitation becoming groundwater recharge (dimensionless).</p> <p> </p> <p> </p>
Figure 1 in The nematode fauna from the top soil to the vadose zone in a forested groundwater recharge area
Figure 1. Population density of nematodes (ind./10 g DW soil ± SD) at Hintere Stellimatten (HST) and Verbindungsweg (VW). The decline in density was significant at both sites (Kruskall-Wallis rank sum test), but showed no significant differences after Dunn's post hoc test.
River-groundwater Interaction and Recharge Effects on Microplastics Contamination of Groundwater in Confined Alluvial Aquifers: Original dataset
<p>The dataset includes all the microplastics analysed for the manuscript "River–Groundwater Interaction and Recharge Effects on Microplastics Contamination of Groundwater in Confined Alluvial Aquifers" by Edoardo Severini, Laura Ducci, Alessandra Sutti, Stuart Robottom, Sandro Sutti and Fulvio Celico (https://doi.org/10.3390/w14121913). The dataset "MP (ctrl and sample).txt" contains the raw data of environmental and ctrl samples. The values of the ctrl samples were used to analyse the statistical differences between ctrl and environmental samples and subsequently used to define the identification parameters (threshold) for the microplastics identification in surface water and groundwater, contained in the file "MP (after ctrl sample).txt".</p>
An in-situ daily dataset for benchmarking temporal variability of groundwater recharge
<p>A newly developed benchmark dataset of groundwater recharge per unit specific yield (RpSy, n meters) at daily temporal resolution is presented. The data has been obtained through the application of the Water table Fluctuation (WTF) method at groundwater wells within the continental US. To ensure high-fidelity estimates, only wells that meet a set of stringent criteria have been considered. The RpSy dataset may serve as a benchmark for validating the temporal consistency of recharge products and daily simulation results from land surface and integrated hydrologic models.</p> <p>The resulting product is a continuous daily RpSy (n meters) time series data for 485 groundwater wells. The data files are provided in the .csv format and consist of three columns for each observation well. The first column lists the local time, while the second and third columns provide the RpSy and RpSyu (considering a groundwater depth-dependent specific yield) time series in meters per day. Additionally, a file containing site information for all the selected wells is included. It contains four columns that detail the USGS ID of the groundwater well, its latitude (Lat), longitude (Long), and screen depth (depth, in meters). The data file can be accessed in most text editors and spreadsheets.</p>
The observed data used in paper titled "A hydrographic method to identify groundwater net recharge, barometric effect, and evapotranspiration from a complicated semidiurnal water table fluctuation"
<p>The water level and atmospheric pressure within the monitoring well located the semi-arid loess hilly-gully region on the piedmont of western Shaanxi Province, China (34°18′36″ N, 107°07′55″ E), were automatically monitored at 20-min intervals by the Levelogger and Barologger, respectively. These data were used as a case example to state a method of estimating groundwater net recharge rate, barometric efficiency and hourly-scaled groundwater evapotranspiration rate.</p>
Characterizing the groundwater flow pathways and recharge sources of a desert inter-dune aquifer system by geophysical approaches and multiple isotopes (B, H and O)
<p>Major cations and anions, and H, O, and B isotope data of South Sumujaran Lake of Badain Jaran Desert, China</p>
Dataset used in "Catchment landforms predict groundwater-dependent wetland sensitivity to recharge changes".
<p>Dataset in the form of text files, all 60 presented catchments are identified by the HydroATLAS database ID in each file. Catchment topography figures are available following their HydroATLAS ID. For the seepage distribution, one text file is presented for each catchment named with the corresponding catchment ID. Code to generate desaturation parameters (lambda and n) and ML models are saved in a common directory (catchment_desaturation_estimator), code is commented to facilitate reproducibility. </p>
Data - Quantifying dynamic linkages between precipitation, groundwater recharge, and streamflow using ensemble rainfall‐runoff analysis
<p>The data support the analysis conducted in "Quantifying Dynamic Linkages Between Precipitation, Groundwater Recharge, and Streamflow Using Ensemble Rainfall‐Runoff Analysis", accepted for publication in Water Resources Research (https://doi.org/10.1029/2024WR037821) by Huibin Gao, Qin Ju, Dawei Zhang, Zhenlong Wang, Zhenchun Hao, and James Kirchner.</p> <p> </p>
Monthly water storage anomalies, precipitation, and groundwater recharge in two karstic basins, southwest China (2003-2014)
<p>This dataset includes the regionally-averaged monthly hydrological data in two karstic basins, southwest China which are processed or estimated for the manuscript entitled "A novel approach for assessing groundwater recharge by combining GRACE and baseflow with case studies in karst areas of southwest China" by Huang et al., 2022 (submitted to Water Resources Research, Major Revision).</p> <p><strong>Basin description:</strong></p> <p>The Wujiang River Basin (WRB, ~87,900 km<sup>2</sup>, ~70% karstification) and Xijiang River Basin (XRB, ~360,000 km<sup>2</sup>, ~44% karstification) are two typical karstic basins in southwest China. The Wujiang River is the largest tributary in the southern part of the upper Yangtze River. It is originated from the Wumeng Mountain in the Yunnan-Guizhou Plateau and flows from Guizhou to Chongqing. The Xijiang River is the largest tributary of the Pearl River (the largest river in southern China). It is originated from the mountains in eastern Yunnan and flows to Guangxi, Guangdong, and finally into the South China Sea.</p> <p><strong>Data description:</strong></p> <p>1. TWSA (unit: mm in equivalent water thickness) is the average terrestrial water storage anomaly data obtained from three release 6 GRACE (Gravity Recovery and Climate Experiment) mascon solutions, i.e., the Center for Space Research (CSR) at the University of Texas (<a href="http://www2.csr.utexas.edu/grace/RL06_mascons.html">http://www2.csr.utexas.edu/grace/RL06_mascons.html</a>), Jet Propulsion Laboratory (JPL, <a href="https://podaac.jpl.nasa.gov/dataset/TELLUS_GRAC-GRFO_MASCON_CRI_GRID_RL06_V2">https://podaac.jpl.nasa.gov/dataset/TELLUS_GRAC-GRFO_MASCON_CRI_GRID_RL06_V2</a>), and Goddard Space Flight Center (GSFC, <a href="https://earth.gsfc.nasa.gov/geo/data/grace-mascons">https://earth.gsfc.nasa.gov/geo/data/grace-mascons</a>). The anomalies were estimated by removing a mean background value during 2006-2012.</p> <p>2. SMSA and SWSA (unit: mm in equivalent water thickness) are the soil moisture storage anomaly and surface water storage anomaly data based on the model simulations by WGHM (v2.2d) provided by Dr. Hannes Müller Schmied (email: hannes.mueller.schmied@em.uni-frankfurt.de) at Institute of Physical Geography, Goethe-University Frankfurt. The anomalies were estimated by removing a mean background value during 2006-2012.</p> <p>3. Precipitation data (unit: mm/month) were based on the monthly gridded (0.5×0.5 degree) data product obtained from China Meteorological Administration (CMA, https://data.cma.cn/) which was interpolated from ground-based data measured by meteorological stations.</p> <p>4. Groundwater recharge (unit: mm/month) was estimated based on the groundwater budget method, i.e., the summation of groundwater storage change (GWSC) and baseflow. GRACE-based recharge was estimated using the GWSC derived from GRACE TWSA, WGHM-simulated SMSA and SWSA and in situ-based reservoir storage data. Observation-based recharge was estimated using the GWSC based on in situ groundwater-level data and specific yield (or storage coefficient). Both GRACE- and observation-based recharge were estimated using the baseflow separated by a multiple linear regression using the in situ streamflow as predictand, and precipitation and water table depth data as predictors.</p> <p>Time span: 2003-2014. The time lable like "200301" means January, 2003. "200312" means December, 2003.</p>
Estimation of average diffuse aquifer recharge using time series modeling of groundwater heads
<p>This map contains the data used in the study 'Estimation of average diffuse aquifer recharge using time series modeling of groundwater heads'. In this study a new method is presented to estimate average diffuse aquifer recharge of water table aquifers in temperate climates using time series analysis of water table level fluctuations. Recharge is estimated from time series models fitted to observed heads under the additional constraint that the seasonal harmonic of the observed head is reproduced as the sum of the transformed seasonal harmonics present in precipitation, evaporation, and pumping. The method is applied to measured heads obtained from piezometers situated on and around the ice-pushed sand ridge of Salland in the Netherlands. Results are compared with recharge estimates based on the saturated zone chloride mass balance.</p> <p>The data are ascii text files saved in the following compressed maps:<br> - Groundwater_chloride_concentration.zip<br> - Groundwater_head_time_series.zip<br> - Makkink_reference_evaporation_time_series.zip<br> - Measured_precipitation_time_series.zip<br> - Precipitation_chloride_concentrations.zip<br> - Pumping_time_series.zip</p> <p>For further details, please refer to the readme files contained in each submap.</p>
Regional-scale assessment of groundwater recharge and the water balance for Austria
<p><strong>Version 1.0 - This version is the final revised one. <br></strong></p> <p>This dataset accompanies the paper: Zeitfogel et al. (2025), Regional-scale assessmentof groundwater recharge and the water balance for Austria, published at Journal of Hydrology: Regional Studies.</p> <p>The dataset includes spatially distributed maps of groundwater recharge rates, precipitation, runoff, and actual evapotranspiration for Austria, resulting from an Austria-wide implementation of the rainfall-runoff model COSERO. By downloading these datasets, you acknowledge that neither the authors nor the providers of the source datasets can be held liable for the accuracy or completeness of the data.</p> <p>The model parameterization of soil information was based on regionalized soil hydraulic property maps.</p> <p>The basins_info file provides spatial information about the delinated model basins, the corresponding gauges, and the calibration stages. </p> <p>This study was funded by the Austrian Academy of Science (Project RechAUT), the Austrian Federal Ministry of Agriculture, Regions and Tourism (Project InfCapAT), and by the Austrian Climate Research Program (ACRP) - 14th call, under grant agreement No. KR21KB0K00001 (HyMELT-CC).</p>
Proposed managed aquifer recharge projects in California groundwater sustainability plans
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Time-series of groundwater recharge, Tiber Riber Basin, Italy from 801 CE to the present day
<p>Groundwater, essential for water availability, sanitation, and achieving Sustainable Development Goals, is shaped by climate dynamics and complex hydrogeological structures. Here, we provide a time-series of groundwater recharge from 801 CE to the present day in the Tiber River Basin, Italy, using historical records and hydrological modelling. Groundwater drought occurred in 36% of the Medieval Climatic Anomaly (801-1249) years, 12% of the Little Ice Age (1250-1849) years, and 26% of the Modern Warming Period (1850-2020) years. Importantly, a predominant warm phase of the Atlantic Multidecadal Oscillation, aligned with solar maxima, coincided with prolonged dry spells during both the medieval and modern periods, inducing a reduction in recharge rates due to hydrological memory effects. This study enhances understanding of climate-water interactions, offering a comprehensive view of groundwater dynamics in central Mediterranean and highlighting the importance of the past for sustainable future strategies. Leveraging this understanding can address water scarcity and enhance basin resilience.</p>
Disturbance on the Groundwater Recharge from Precipitation by a Near Earthquake
<p>该数据是手稿《近震降水对地下水补给的扰动》中的水位和降水的原始数据。</p>
Dataset to the article 'Redox-zoning in high-energy subterranean estuaries as a function of storm floods, temperatures, seasonal groundwater recharge and morphodynamics'
<p>This repository contains model input files, and pre- and post-processing scripts for the research article:</p> <p>Janek Greskowiak, Stephan L. Seibert, Vincent E.A. Post, Gudrun Massmann (2023), Redox-zoning in high-energy subterranean estuaries as a function of storm floods, temperatures, seasonal groundwater recharge and morphodynamics, Estuarine, Coastal and Shelf Science, https://doi.org/10.1016/j.ecss.2023.108418</p> <p><br> Data:</p> <p>The folder Laserascannerdata_top_and_hydr_heads contains five cross-shore topography profiles of a high energy beach on Spiekeroog Island, Germany, including a python-script that assembles them to a daily times-series over one year and that calculates the tide-averaged hydraulic heads in the intertidal zone as detailed in Greskowiak and Massmann (2021), The impact of morphodynamics and storm floods on pore water flow and transport in the subterranean estuary, Hydrological Processes, 35:e14050, https://doi.org/10.1002/hyp.14050</p> <p><br> Model input:</p> <p>The file Dynamod_1_redox_basecase.zip contains a folder with the model input textfiles (SEAWAT and PHT3D) for the case that considers all dynamic influence factors investigated in the paper, i.e., seasonal meteoric groundwater recharge, stormfloods, temperature-dependence of reaction rates and morphodynamics.</p> <p>The files pht3d_ph.dat and pht3d_datab.dat are PHT3D model specific files defining the reacants and reactions, and have to be copied into the model folder before PHT3D is started.</p> <p><br> Run models:</p> <p>First the SEAWAT model needs to be run with the name file 'Dynamod_1_redox_basecase.nam'. This creates the mt3d link file 'mt3d_link.ftl'. After that, PHT3D has to be started with the name file 'pht3d.nam'</p> <p>Note that running the models will generate 22 Gybte output.</p> <p><br> Pre-processing:</p> <p>All model input files were generated with the python-script Dynamod_1_redox_basebase.py using Flopy, a python-based groundwater modelling user-interface:<br> https://www.usgs.gov/software/flopy-python-package-creating-running-and-post-processing-modflow-based-models</p> <p><br> Post-processing:</p> <p>For the figures 3,4 and S1, S2 in the paper, the corresponding python scripts are provided in this database. Note that with respect to Figures 5 and S3, only the results for the case with all dynamic influence factors (Figure S3_h) are being plotted.</p> <p> </p> <p>Other model output:<br> Animation_A1_Dynamod_redox.mp4 is a video animation showing the dynamic modelled salinity and temperature distribution, and redox zoning in the subterranean estuary all dynamic influence factors investigated in the paper, i.e., seasonal meteoric groundwater recharge, stormfloods, temperature-dependence of reaction rates and morphodynamics.</p>
Data from: A coupled soil water balance model for simulating depression-focused groundwater recharge
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Time-series of groundwater recharge, Tiber Riber Basin, Italy from 801 CE to the present day
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Decline in Iran's Groundwater Recharge
<p>Iran's groundwater data</p>
Dataset for "A Numerical Investigation of Bedrock Groundwater Recharge and Exfiltration on Soil Mantled Hillslopes."
<p>Model input and output data used to produce the results in the publication.</p>
Complementary Data of Groundwater model for the Publication: "Comparison of methods to calculate groundwater recharge for karst aquifers under Mediterranean climate"
<p>This repository provides the resources related to the publication "Comparison of methods to calculate groundwater recharge for karst aquifers under Mediterranean climate." It includes the groundwater model data sets.</p>
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