Construction and Application of Distributed Non-Point Source Pollution Model in Watersheds Based on Time-Varying Gain and Stormwater Runoff Response at the Watershed Scale

Characterizing surface runoff and the transport process of non-point source pollutants (NSPs) carried by this runoff is crucial for identifying key source areas, estimating pollution loads entering water bodies, and implementing pollution control, which is particularly important in regions dominated by smallholder farming in China. Currently, most of the commonly used NSP models originated from international countries and have shortcomings such as high data requirements, high generalization degrees, and requiring the calibration of numerous parameters in the application process. Therefore, a distributed non-point source pollution model based on the time-varying gain and stormwater runoff response was constructed, designed for application at the watershed scale. This study describes the construction of the model, introducing its principles and structure through three key modules: a rainfall–runoff module, a soil erosion module, and a pollutant migration and transformation module. The proposed model was used to simulate the rainfall–runoff, soil erosion, and nutrient migration and transformation processes at different spatiotemporal scales. Although it achieved the best performance at the monthly and annual scales, its simulation results at the daily and hourly scales still met the relevant requirements, with relative errors within 20% and Nash–Sutcliffe Efficiency (NSE) coefficients of approximately 0.7. The annual sediment delivery ratios for the Yangliu Small Watershed and the basin above the Ankang section in 2022 were determined to be 0.445 and 0.36, respectively. The pollutant processes corresponding to different runoff events in the Yangliu Small Watershed were simulated, and the average NSE for total nitrogen (TN), ammonia nitrogen (NH3-N), nitrate nitrogen (NO3-N), total phosphorus (TP), and soluble reactive phosphorus (SRP) were determined to be 0.69, 0.74, 0.79, 0.71, and 0.71, respectively. For the basin above the Ankang section, the NSE coefficients for the simulation of NH3-N and TP pollutant processes were 0.78 and 0.83, respectively. The model demonstrated robust applicability across various spatial (ranging from small to large watersheds) and temporal (hourly−daily−monthly−annual) scales, and exhibited stability across different basins in a semi-humid region of China. The model is characterized by a parsimonious parameter set, ease of calibration, and strong spatiotemporal versatility, thus providing an efficient and reliable tool for non-point source pollution simulation.