Predicting saturation‐excess runoff distribution with a lumped hillslope model: SWAT‐HS. Issue 12 (9th May 2017) - Hoang, Linh
Abstract: Saturation‐excess runoff is the major runoff mechanism in humid well‐vegetated areas where infiltration rates often exceed rainfall intensity. Although the Soil and Water Assessment Tool (SWAT) is one of the most widely used models, it predicts runoff based mainly on soil and land use characteristics, and is implicitly an infiltration‐excess runoff type of model. Previous attempts to incorporate the saturation‐excess runoff mechanism in SWAT fell short due to the inability to distribute water from one hydrological response unit to another. This paper introduces a modified version of SWAT, referred to as SWAT‐Hillslope (SWAT‐HS). This modification improves the simulation of saturation‐excess runoff by redefining hydrological response units based on wetness classes and by introducing a surface aquifer with the ability to route interflow from "drier" to "wetter" wetness classes. Mathematically, the surface aquifer is a nonlinear reservoir that generates rapid subsurface stormflow as the water table in the surface aquifer rises. The SWAT‐HS model was tested in the Town Brook watershed in the upper reaches of the West Branch Delaware River in the Catskill region of New York, USA. SWAT‐HS predicted discharge well with a Nash‐Sutcliffe Efficiency of 0.68 and 0.87 for daily and monthly time steps. Compared to the original SWAT model, SWAT‐HS predicted less surface runoff and groundwater flow and more lateral flow. The saturated areas predicted by SWAT‐HS were concentrated in locations with a high topographic index and were in agreement with field observations. With the incorporation of topographic characteristics and the addition of the surface aquifer, SWAT‐HS improved streamflow simulation and gave a good representation of saturated areas on the dates that measurements were available. SWAT‐HS is expected to improve water quality model predictions where the location of the surface runoff matters.