Accurately estimating the spatial and temporal distribution of precipitation is crucial for hydrological modeling. However, precipitation products based on a single source have their advantages and disadvantages. How to effectively combine the advantages of different precipitation datasets has become an important topic in developing high-quality precipitation products internationally in recent years. This paper uses the measured precipitation data of Multi-Source Weighted-Ensemble Precipitation (MSWEP) and in situ rainfall observation in the Taihu Lake Basin, as well as the longitude, latitude, elevation, slope, aspect, surface roughness, distance to the coastline, and land use and land cover data, and adopts a two-step method to achieve precipitation fusion: (1) downscaling the MSWEP source precipitation field using the bilinear interpolation method and (2) using the geographically weighted regression (GWR) method and tri-cube function weighting method to achieve fusion. Considering geographical and human activities factors, the spatial and temporal distribution of precipitation errors in MSWEP is detected. The fusion of MSWEP and gauge observation precipitation is realized. The results show that the method in this paper significantly improves the spatial resolution and accuracy of precipitation data in the Taihu Lake Basin.

Urban point source pollution has been effectively controlled in recent years; however, rainfall-driven non-point source (NPS) pollution has become a major contributor to the deterioration of urban water environments. This study focuses on the plain river network region of Wuxi City in the Taihu Basin, China. By integrating field monitoring with coupled model simulations, this study upscaled results from the experimental plot to the urban-scale river network, enabling analysis of the full processes of pollutant inflow and transport and evaluation of the role of rainfall in regulating these dynamics. Field monitoring in the experimental plot demonstrated a strong correlation between the temporal dynamics of NPS pollutant inflows and rainfall characteristics. Further analysis using model simulations in the river network area revealed that rainfall, maximum 1 h rainfall, and rainfall duration were identified as the primary drivers of pollutant inflows, while early drought duration, rainfall intensity, and variance between rainfall per unit time exerted non-linear effects. Specifically, when early drought duration was approximately 6–7 days or when rainfall intensity ranged from 2.1 to 2.6 mm/h, riverine nitrogen (N) and phosphorus (P) concentrations and pollutant loadings reached their peaks. In addition, when the deviation of unit-time rainfall from the event mean was between 1.8 and 2 mm, the duration of increase in pollutants entering the river was the longest. This study provides quantitative evidence highlighting the influence of rainfall characteristics on nitrogen and phosphorus dynamics in plain river network urban rivers. The findings offer valuable insights into the remediation of urban black-odor water bodies.