Abstract. Accurate quantification of global groundwater storage anomaly (GWSA) is imperative for global water security and socio-economic sustainability. The Gravity Recovery and Climate Experiment (GRACE) satellite has emerged as a prevailing methodology for estimating GWSA. However, oversimplification of non-groundwater components potentially compromised its accuracy in most previous studies. Here we present an improved GRACE-derived GWSA dataset at the global scale, namely igGWSA, with full consideration of non-groundwater components including glaciers, snow, permafrost, lakes, reservoirs, surface runoff, profile soil moisture (PSM), and plant canopy water based on current new datasets. In particular, PSM was generated based on Catchment Land Surface Model and random forest algorithm. igGWSA demonstrated strong agreement with well-observed groundwater level and model-simulated GWSA in five globally recognized hotspots of groundwater depletion. Compared to igGWSA with full consideration, simplified estimation would lead to misinterpretations of groundwater storage variations in glacier-covered regions, giant lakes, and deep-soil areas, highlighting the necessity of comprehensively accounting for non-groundwater components in estimating GWSA, especially under a changing environment. igGWSA dataset is publicly available on Zenodo through https://doi.org/10.5281/zenodo.16871689 (Wang et al., 2025).
Wang et al. (Mon,) studied this question.