Evaluation of Water Resources Carrying Capacity Based on Fuzzy Matter-Element Model in Jinhua City, Southeastern China

Regional water systems in rapidly urbanizing hilly basin cities are affected by hydrological variability, population concentration, industrial water demand, and water-use efficiency. This study evaluated the water resources carrying capacity (WRCC) of Jinhua City, southeastern China, from 2011 to 2023 using an integrated 15-indicator system covering water resources support, water-use and population pressure, economic structure and water-use efficiency, and ecological and environmental support. Indicator definitions, units, directions, and data sources were harmonized using official water resources bulletins and statistical records. A combined weighting method integrating the modified Analytic Hierarchy Process and the entropy weight method was coupled with a fuzzy matter-element model and the Hamming closeness measure. WRCC grades were assigned using standard-derived Hamming closeness thresholds based on pooled-reference membership transformation. Obstacle degree, leave-one-indicator-out sensitivity, and redundancy diagnostics were further used for interpretation and robustness assessment. The combined weights were mainly concentrated in water-use and population pressure (35.85%), water resources support (26.77%), and economic structure and water-use efficiency (26.10%). Industrial water use, per capita comprehensive water use, population density, water consumption per 10,000 yuan industrial value added, and water consumption per 10,000 yuan GDP had the highest indicator weights. Annual Hamming closeness ranged from 0.2621 to 0.6391. Jinhua’s WRCC reached Grade II in 2015, 2019, 2020, and 2021, while the remaining years were classified as Grade III. The highest closeness occurred in 2019, whereas 2022 and 2023 declined to Grade III and were close to the II/III threshold. Obstacle diagnosis showed that water-use and population pressure were the dominant subsystem obstacles. Sensitivity analysis showed that the peak year and the lowest year remained unchanged across all leave-one-indicator-out scenarios, whereas the boundary years showed grade sensitivity. The results provide a transparent annual assessment and diagnostic evidence for WRCC management.