System Coordination, Dynamic Drivers, and Spatiotemporal Evolution of Water Resources Carrying Capacity: A Case Study in Jiangsu, China

Water resources carrying capacity (WRCC) includes the relationships between water resources utilizations and economic development, social demand, and ecological protection. Most previous studies lack WRCC analyses of regions experiencing economic development and industrial development. Therefore, this study takes Jiangsu Province in China as a typical case which includes 13 prefecture-level cities from 2012 to 2021. To provide a comprehensive and nuanced assessment, this study proposes an integrated analytical paradigm for WRCC that explicitly incorporates system coordination, dynamic drivers, and spatiotemporal evolution. First, the entropy-weighted Chebyshev–TOPSIS method is applied to calculate WRCC. Second, the coupling coordination degree model (CCD) is introduced to assess coordination among the four subsystems. Third, the Panel Vector Autoregression model (PVAR) is used to examine dynamic interactions. Fourth, the geographically and temporally weighted regression model (GTWR) is considered to identify spatiotemporal trends with a certain degree of endogeneity. The results indicate that WRCC generally improved across Jiangsu Province over the study period, although marked differences persist among its 13 prefecture-level cities. Suzhou and Nanjing presented relatively high WRCC levels, whereas Huai’an and Suqian showed weaker coordination. The economic subsystem is strongly constrained by water resources and ecological conditions. The impact of the ecological environment on WRCC continues to intensify, which indicates its increasing role in regional water resource management. These findings show that WRCC is jointly shaped by interactions among subsystems and by drivers that vary across space and time. The proposed framework can support water allocation, ecological protection, and development planning tailored to the conditions of individual cities.