GRACE Downscaling-Based Dataset of Groundwater Storage Anomalies in China’s Oases (2002-2023)
CUI Bochao1,5XUE Dongping1GUI Dongwei2LIU Qi3ABD-ELMABOD Sameh Kotb1,4CHEN Xiaonan1,5GOETHALS Peter5DE MAEYER Philippe6
1 State Key Laboratory of Desert and Oasis Ecology，Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands，Xinjiang Institute of Ecology and Geography，Chinese Academy of Sciences，Urumqi 830011，China2 Xinjiang Technical Institute of Physics and Chemistry，Chinese Academy of Sciences，Urumqi 830011，China3 Biological and Environmental Science and Engineering Division，King Abdullah University of Science and Technology，Thuwal 23955，Saudi Arabia4 Department of Soil and Water Use，Agricultural and Biological Research Institute，National Research Centre，Cairo 12622，Egypt5 Department of Animal Sciences and Aquatic Ecology，Ghent University，Ghent 9000，Belgium6 Department of Geography，Ghent University，Ghent 9000，Belgium
DOI:10.3974/geodb.2026.05.04.V1
Published:May. 2026
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Key Words：
Chinese oases,GRACE,groundwater storage anomaly,downscaling,machine learning
Abstract：
The GRACE Downscaling-Based Dataset of Groundwater Storage Anomalies in China’s Oases (2002-2023) was developed based on GRACE/GRACE-FO satellite gravimetry data, the mean of the Mascon products released by CSR, JPL, and GSFC, in combination with multisource remote sensing and land surface model data, including MODIS land surface temperature (LST), GPM precipitation, ERA5-Land evapotranspiration, FLDAS soil moisture and runoff, SRTM topography, and NDVI. A random forest downscaling model with spatiotemporal encoding (RFst) was applied to enhance the spatial resolution of total water storage anomalies (TWSA) from 0.5° to 0.1°. Groundwater storage anomalies were then retrieved by subtracting soil moisture, snow water equivalent, and surface water storage anomalies from the downscaled TWSA. The dataset includes the longitude and latitude of 0.1° grid cells across oasis regions in arid China, as well as monthly GWSA values (mm) for 254 months from April 2002 to April 2023. The dataset is archived in .xlsx format, and consists of one data file with data size of 11 MB.
Foundation Item：
Xinjiang Uygur Autonomous Region (2023TSYCLJ0049); National Natural Science Foundation of China (42361144792)
Data Citation：
CUI Bochao, XUE Dongping, GUI Dongwei, LIU Qi, AB, CHEN Xiaonan, GOETHALS Peter, DE MAEYER Philippe. GRACE Downscaling-Based Dataset of Groundwater Storage Anomalies in China’s Oases (2002-2023)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2026. https://doi.org/10.3974/geodb.2026.05.04.V1. .
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Data Product:
| ID |
Data Name |
Data Size |
Operation |
| 1 |
Oasis_GWSA_0.1deg2002-2023.xlsx |
11269.27KB |
|