An improved process-based representation of stream solute transport in the soil and water assessment tools

Hydrological models have long been used to study the interactions between land, surface and groundwater systems, and to predict and manage water quantity and quality. The soil and water assessment tool (SWAT), a widely used hydrological model, can simulate various ecohydrological processes on land and subsequently route the water quality constituents through surface and subsurface waters. So far, in-stream solute transport algorithms of the SWAT model have only been minimally revised, even though it has been acknowledged that an improvement of in-stream process representation can contribute to better model performance with respect to water quality. In this study, we aim to incorporate a new and improved solute transport model into the SWAT model framework. The new process-based model was developed using in-stream process equations from two well established models—the One-dimensional Transport with Inflow and Storage model and the Enhanced Stream Water Quality Model. The modified SWAT model (Mir-SWAT) was tested for water quality predictions in a study watershed in Germany. Compared to the standard SWAT model, Mir-SWAT improved dissolved oxygen (DO) predictions by removing extreme low values of DO (<6 mg/L) simulated by SWAT. Phosphate concentration peaks were reduced during high flows and a better match of daily predicted and measured values was attained using the Mir-SWAT model (R2 = 0.17, NSE = −0.65, RSR = 1.29 with SWAT; R2 = 0.28, NSE = −0.04, RSR = 1.02 with Mir-SWAT). In addition, Mir-SWAT performed better than the SWAT model in terms of Chlorophyll-a content particularly during winter months, improving the NSE and RSR for monthly average Chl-a by 74 and 42%, respectively. With the new model improvements, we aim to increase confidence in the stream solute transport component of the model, improve the understanding of nutrient dynamics in the stream, and to extend the applicability of SWAT for reach-scale analysis and management.