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Water resources management (<i>WRM</i>) is a global strategic issue. Effectively evaluating <i>WRM</i> performance and analyzing its influencing factors have strong practical significance for improving regional <i>WRM</i> performance. Data envelopment analysis (DEA) is one of the most popular models to measure the efficiency of decision-making units (DMUs). Taking regional <i>WRM</i> performance as efficiency DMUs, this paper proposes the indicator system to quantify <i>WRM</i> performance from the perspectives of resource endowments, economic and technological development, and ecosystem protection. The <i>WRM</i> performance of 31 provincial administrative regions in mainland China from 2013 to 2019 are measured, and the temporal and spatial changes are explored using the window DEA model and the Malmquist index model. Finally, the Tobit model is used to quantitatively analyze the affecting factors. The results indicate that: (1) in 2015 and 2019, <i>WRM</i> performance of Sichuan, Shaanxi, Xinjiang, Inner Mongolia, and Guangxi were slightly higher than that in other years, and the areas with more room for <i>WRM</i> performance improvements were areas with abundant water resources; (2) from 2013 to 2019, China’s overall <i>WRM</i> performance showed a slow rise, and there were obvious fluctuations in 2018; (3) the improvement in <i>WRM</i> performance was primarily the result of an improvement to comprehensive technical efficiency changes (EC), whereas technological progress changes (TC) have largely restricted China’s <i>WRM</i> performance; (4) the main influencing factors of <i>WRM</i> performance in China were as follows: industrial development level, water resources utilization rate, and urban sewage discharge per capita.