Bao Ning

Areas with high intensity of human activity tend to face more severe water environment quality challenges, and the spatial layout of water environment monitoring cross sections in watersheds needs to take this characteristic into full consideration. This study proposes a new approach to optimizing the layout of surface water quality monitoring cross sections from the perspective of the impacts of human activity on water quality. Using the Ganjiang River Basin as a case study, we construct an optimization model based on the spatial distribution of human activity intensity and the locations of existing monitoring cross sections, with the objective of maximizing the coverage of human activity intensity. The results show that, under the constraint of a fixed number of monitoring cross sections, the optimized monitoring network can increase the coverage of human activity intensity in the study area from 30.58% to 36.81%. In the scenario of adding new monitoring cross sections, a cost–benefit analysis based on the relationship between the number of additional cross sections and the resulting maximum coverage reveals distinct phases and diminishing marginal returns in the optimized layout. The methodology proposed in this study supports the optimization of surface water quality monitoring networks in the basins. It offers a novel perspective for optimizing the layout of surface water quality monitoring cross sections, and the resulting optimization outcomes can serve as a reference for environmental planning and regulatory departments in decision-making.