<p>In order to explore the spatiotemporal variation patterns and driving mechanisms of water pollution in China and to support the sustainable use of water resources and water environment governance, the study quantifies the water pollution loads of the agricultural, industrial, and domestic sectors by constructing a gray water footprint accounting model. It decomposes the driving factors of gray water footprint changes using the logarithmic mean Divisia index model and tracks the gray water footprint transfer effects in cross-regional trade based on the multi-regional input-output model. The results show that from 2010 to 2024, the gray water footprint and the degree of water pollution in the 31 provinces of China both showed a significant downward trend, with an average decline of 30%. Spatially, there is a difference characteristic of high in the southeast and low in the northwest. The population effect and the economic level effect are the main driving factors of the gray water footprint changes. The impact of gray water footprint transfer on the degree of water pollution ranges from 16.67% to 29.31%, with the provinces in North China and the southeast coastal areas being more significantly affected by cross-regional trade transfer. The study results provide a scientific basis for formulating water pollution control policies that are nationally coordinated and regionally collaborative, clarifying the need to address cross-border pollution transfer issues through provincial coordination mechanisms and to differentially advance pollution control and efficiency improvement in different regions.</p>