Global gridded (0.5° × 0.5°) groundwater storage from a physics-constrained neural network (PCNN)-based data assimilation framework

This dataset presents a global, gridded (0.5° × 0.5°) monthly groundwater product from Apr 2002 to Dec 2023 derived through the integration of WGHM-2.2e and GRACE observations within a physics-constrained neural network (PCNN)-based data assimilation framework. Validation against in situ groundwater observations from 27,602 wells demonstrates that PCNN-GWS exhibits improved correlation relative to WGHM-2.2e. The dataset further demonstrates advantages over existing global groundwater products derived from traditional hydrologic data assimilation techniques and GRACE–land surface model (LSM) residual methods.