Rainfall-Driven Nonlinear Sediment Resuspension Improves SWAT Simulation of Endogenous Pollution in the Songhua River Basin

Endogenous pollution released by riverbed sediments has become a key limiting factor for the sustainable improvement of river water quality. In this study, endogenous pollution specifically refers to the pollutants released into the overlying water by the resuspension process of riverbed sediments after hydrodynamic disturbances caused by rainfall runoff. To quantify this process, we modified the nutrient module of SWAT_2012 by introducing a rainfall-driven nonlinear resuspension term. Studies have shown that due to the gradual increase in disturbance, the release of pollutants in sediment exhibits a process from weak release to threshold activation and then to release saturation. In this study, two S-shaped response functions, Sigmoid and Gompertz, were selected to characterize this process. Model performance was evaluated using the Nash–Sutcliffe efficiency (NSE) and percent bias (PBIAS) against observed runoff and CBOD flux. Runoff simulation remained essentially unaffected, whereas CBOD simulation improved substantially: NSE increased from 0.607 in SWAT_2012 to 0.815 in SWAT_ZS and 0.744 in SWAT_ZG, with corresponding PBIAS values improving from −41.19% to 11.49% and 15.81%, respectively. Overall, SWAT_ZS performed the best in the Songhua River Basin. The results further indicate that rainfall-induced sediment resuspension may represent an important contribution of CBOD variability during wet periods, highlighting the substantial role of endogenous pollution under strong hydrological disturbance. By explicitly incorporating rainfall-driven nonlinear sediment resuspension into the SWAT nutrient module, this study provides a framework for representing episodic endogenous pollution and offers a transferable approach for quantifying sediment-derived pollution at the watershed scale.