Identifying determinants of groundwater storage using a geocomplexity-heterogeneity model

Groundwater is a vital component of the global water cycle and plays a critical role in ecological security and sustainable development. Groundwater storage anomalies (GWSA) are jointly driven by climate change and human activities. However, existing studies on GWSA mainly rely on the quantitative characteristics of explanatory variables, while the investigation of spatial data patterns remains limited despite their increasing importance. This study develops a geocomplexity-heterogeneity model to identify spatial drivers of GWSA by integrating spatially local complexity with robust stratified heterogeneity. The geocomplexity-heterogeneity model was used to identify both national-scale patterns of GWSA and the dominant climatic and anthropogenic explanatory factors in two representative regions, including the Huang-Huai-Hai Plain and the southeastern Tibetan Plateau, over the period 2002–2022. The results indicate that national GWSA in China decreased at a rate of 1.89 mm yr−1 during 2002–2022. The most significant decline occurred in the Huang-Huai-Hai Plain (10.68 mm yr−1), while the Sichuan Basin and surrounding regions showed moderate recovery. In the Huang-Huai-Hai Plain, GWSA variability reflects the combined effects of climatic water processes and intensive human water use, with temperature playing a leading role and irrigation exerting a strong influence primarily through its interaction with climatic conditions. In contrast, GWSA in the southeastern Tibetan Plateau was primarily shaped by natural climate processes, particularly precipitation and vegetation dynamics. The geocomplexity-heterogeneity model enhances the spatial interpretation of GWSA by combining local complexity with stratified heterogeneity, thereby improving the robustness of region-specific driver identification.