如何精细量化降雨径流污染负荷是流域尺度实现面源精准治污全过程控制的重要前提.本研究以水污染较为严重的望虞河西岸综合示范区为例,通过开展不同土地利用类型的降雨观测实验,修正SCS-CN模型中的初损率,并基于土地利用类型遥感解译和降雨径流污染物浓度测定,精细刻画降雨径流中总磷(TP)、总氮(TN)、氨氮(NH<sub>3</sub>-N)、化学需氧量(COD)4类主要污染物的时空分布格局.结果表明:研究区绿地和农田、硬质地表的降雨初损率分别为0.3和0.9;径流深、污染负荷与降雨深之间存在显著的正相关性.随着降雨量逐年递减,研究区降雨径流中TP、TN、NH<sub>3</sub>-N、COD四类污染物的负荷量分别从2017年的190、1359、445和16041 t减少至2019年的118、949、314和11250 t;单位面积TN和COD负荷最高的用地类型是农村住宅用地,草地的四种污染物单位面积负荷均最低,林地次之.相关研究结果为望虞河流域水污染控制提供了基础数据,也为定量测算平原河网区面源污染负荷提供了方法参考.;Quantifying the pollutant loads in rainfall-runoff plays a critical role in non-point water pollution control at the watershed level. In this study, rainfall-runoff experiments were conducted on various land use types in the western bank area of Wangyu River to localize the initial abstraction ratio in the SCS-CN model. Then, by incorporating the remote sensing interpretation of land use types and the measurement of pollutant concentration in the rainfall-runoff, this study explored the temporal and spatial patterns of four kinds of pollutants, namely total phosphorus (TP), total nitrogen (TN), ammonia nitrogen (NH<sub>3</sub>-N) and chemical oxygen demand (COD). The results indicate that the recommended initial abstraction ratios for grassland/forest/farmland and impervious surface in the study area are 0.3 and 0.9, respectively. Besides, the rainfall-runoff depths and pollutant loads are found to be significantly and positively correlated with the rainfall depths. Along with the decrease of annual rainfall in this region, the annual amount of TP, TN, NH<sub>3</sub>-N and COD loads in rainfall-runoff have reduced from 190, 1359, 445 and 16041 t in 2017 to 118, 949, 314 and 11250 t in 2019, respectively. Rural resident land, among all the land use types, has the highest TN and COD loads per area, while grassland and forest rank the bottom. This study provides precise information about pollutants in rainfall-runoff to facilitate the development of water pollution control strategies in Wangyu River watershed and can be used as a methodological reference for future quantification of non-point source pollution practices in plain areas with dense river networks.