• New Soil and Water Assessment Tool (SWAT) algorithms for simulation of stormwater best management practices (BMPs) such as detention basins, wet ponds, sedimentation filtration ponds, and retention irrigation systems are under development for modeling small/urban watersheds. Modeling stormwater BMPs often requires time steps as small as minutes to realistically capture the instantaneous flow and sediment load coming from upland areas. SWAT2005 uses the Modified Universal Soil Loss Equation (MUSLE) for modeling upland erosion and sediment load. The MUSLE model is an empirical soil loss equation, which was formulated based on field observations rather than theoretically derived relationships to predict long-term average soil loss. This article presents modified physically based erosion models in SWAT for seamless modeling of erosion processes with the recently developed sub-hourly flow models. In the new algorithms, splash erosion is calculated based on the kinetic energy delivered by raindrops, adapted from the European Soil Erosion Model, and overland flow erosion is estimated using a physically based equation adapted from the Areal Nonpoint-Source Watershed Environment Response Simulation (ANSWERS) model. The Yang model and the Brownlie model were also modified for in-stream sediment routing. The SWAT model with the modified sub-daily sediment algorithms was calibrated and validated each for a one-year period at 15 min intervals with measured data from the USDA-ARS Riesel watersheds in Texas. Results show that SWAT with the sub-daily algorithms performed as well or better in terms of sediment yield prediction than SWAT with the current daily output structure. In addition, SWAT (sub-daily) was able to adequately represent the timing, peak, and duration of sediment transport events. Thus, this initial evaluation indicates that the new sub-daily flow and sediment structure in SWAT is a promising tool for water quality assessment studies in small watersheds or urban watersheds where sub-daily process are so important to quantify. © 2011 American Society of Agricultural and Biological Engineers ISSN 2151-0032.

author list (cited authors)

  • Jeong, J., Kannan, N., Arnold, J. G., Glick, R., Gosselink, L., Srinivasan, R., & Harmel, R. D.

publication date

  • September 2011