To solve the flood drainage conflict among different regions of the water basin when the flood occurs, it is of great significance to study the allocation of flood drainage rights. The allocation of flood drainage rights requires flood management departments to consider the influences of socioeconomic differences among different regions on flood control operations to realize sustainable development. Under the pattern of the total amount allocation of “watershed–administrative regions”, the evaluation index system of flood drainage rights allocation incorporated four aspects: natural conditions, level of social development, level of economic development, and technology and management. The fuzzy analytic hierarchy process (FAHP) was used to calculate the weight coefficient of each allocation index and the initial distribution’s proportion of the total amount in each region. Land area, population, gross domestic product (GDP), and sewage treatment capacity were selected as the evaluation indexes of the environmental Gini coefficient, and the environmental Gini coefficient method was used to evaluate and adjust the initial allocation of each region. Taking the allocation of flood drainage rights in the Taihu Basin as a case study, the final allocation results were obtained after initial allocation and feedback optimization. By evaluating the environmental Gini coefficient of each evaluation index, it is concluded that the final allocation could meet the requirements of fair allocation in each administrative region and be effectively implemented. Optimal allocation of the flood drainage rights in the Taihu Basin can contribute to overall flood control management, the reduction of flood disasters, and the stable development of society in the basin.

Rapid economic growth and social development in China have led to serious water pollution problems and water resource shortages, limiting the sustainable development that could support both the socio-economy and water resources carrying capacity (WRECC). However, the spatial heterogeneity and evolutionary characteristics of the coordination between the WRECC and economic development have not been adequately explored in China. In this study, we developed the support and pressure indicators of China’s 30 provinces and then analyzed the spatiotemporal distribution and evolution characteristics of their WRECC by using the geographically and temporally weighted regression (GTWR) model. The main findings are shown in the following: (i) From a temporal perspective, there has been an overall upward trend in the WRECC to support human activities; however, the WRECC level is not high. Approximately 63.7% of provinces remain in an overloaded state, indicating that the support indicator of most provinces is smaller than the pressure indicator imposed by human social activities. (ii) There are significant spatial differences in the WRECC indicators across provinces. Provinces with low-level WRECCs are concentrated in central China but decrease significantly from the country’s borders to its center. Eastern regions have a medium-level of WRECC with the greatest degree of regional difference, while western regions have a high-level of WRECC with the smallest degree of regional difference. The variation of WRECC is attributed to within-group differences in the three geographical regions in China. (iii) The factors that significantly impact the WRECC include population density, gross domestic product (GDP), temperature, urbanization, the added value of tertiary industry within the GDP, and R&D expenditures. GDP and R&D expenditures positively impact the WRECC, while the other four factors have different influences on the WRECC. (iv) The spatial distributions of driving factors show significant aggregation characteristics, with decreasing trends from the eastern to western regions and from the southern to northern regions. These findings present a comprehensive understanding of the current WRECC in China’s provinces which can be used as a reference for realizing environmentally sustainable water development strategies under high-quality economic development.