A Dynamic Assessment Framework for Water Resource Spatial Equilibrium: Structural Imbalances and Convergence Patterns in Anhui Province of China

Existing water resource spatial equilibrium (WRSE) evaluations face persistent limitations in identifying structural sources of imbalance and characterizing their dynamic evolutionary trajectories. To address this gap, this study aims to develop a diagnostic framework that quantifies spatial inequity, pinpoints its structural origins, and depicts temporal convergence patterns. Methodologically, we adopt statistical analytical approaches, specifically Dagum Gini coefficient decomposition and kernel density estimation (KDE), and construct a four-subsystem evaluation framework covering water–city, water–land, water–population, and water–industry dimensions. We apply this framework to WRSE analysis in Anhui Province, China, using balanced panel data from 2012 to 2023. Results indicate continuous WRSE improvement, with the overall Gini coefficient declining from 0.644 to 0.535, though the water–land subsystem remains the most imbalanced and slowest-improving bottleneck. Nearly 60% of the total imbalance stems from inter-zonal disparities among three geographically distinct functional zones, while intra-zone differentiation accounts for only 14%. KDE reveals a convergence across all subsystems with heterogeneous rates: the water–industry subsystem converges fastest driven by efficiency gains, whereas the water–land subsystem converges slowest constrained by rigid irrigation demand. This work advances WRSE research from imbalance description to root-cause diagnosis, featuring four-subsystem disaggregation, coupled decomposition–density analysis, and a generalizable inter-zone dominance pattern for climatic transition zones.