[Estimation and Critical Source Area Identification of Non-point Source Pollution Based on Improved Export...

Non-point source pollution(NSP) poses a great threat to water ecosystem health. The quantitative estimation of spatial distribution characteristics and accurate identification of critical source areas(CSAs) of NSP are the basis for its efficient and accurate control. The export coefficient model(ECM) has been widely used to assess NSP, but this model should be improved because it ignores pollutant loss in transport processes. In this study, the ECM, which refines the physical transport processes of pollutants through quantifying the loss rate of pollutants in runoff, sediment, and infiltration, was improved to assess NSP and identify CSAs. The simulation accuracy among Johnes ECM, frequent ECM, and improved ECM were analyzed, and the effects of the three models on the simulation results of both spatial distribution characteristics and CSAs were explored. The study showed that:① the simulation error of the improved ECM(-6.79%) was significantly lower than that of the Johnes ECM(50.44%) and the frequent ECM(-84.01%), and this improved ECM increased the simulation accuracy of NSP. ② The spatial distribution characteristics and CSAs of NSP obtained from Johnes, frequent, and improved ECMs were significantly different, and the simulation results of improved ECM were more consistent with the spatial characteristics of NSP in the watershed. The NSP was high in the southeast and low in the northwest of the basin, and the NSP mainly came from urban and cultivated land. ③ Based on the improved ECM, the CSAs of NSP in the basin were mainly distributed in Changping, Shahe, Shigezhuang, the north of Wenquan, and the west of Malianwa Street, accounting for 6.71% of the area. This study can provide an effective tool and scientific reference for the assessment and control of NSP in data-limited regions.