SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Verification of a new spatial distribution function of soil water storage capacity using conceptual and SWAT models 
Authors:Xie, K., P. Liu, J. Zhang, D.A. Libera, G. Wang, Z. Li and D. Wang 
Year:2020 
Journal:Journal of Hydrologic Engineering 
Volume (Issue):25(3) 
Pages: 
Article ID:04020001 
DOI:10.1061/(ASCE)HE.1943-5584.0001887 
URL (non-DOI journals): 
Model:SWAT (modified) 
Broad Application Category:hydrologic only 
Primary Application Category:modified runoff curve number approach 
Secondary Application Category:model comparison 
Watershed Description:6,448 km^2 Xunhe River, located in Shaanxi Province, China; and nine watersheds ranging in size from 179.74 to 9,435.15 km^2 distributed across nine states in the northwest, midwest, southeast, and eastern U.S. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:The Soil Conservation Service Curve Number (SCS-CN) method is widely used in conceptual rainfall-runoff models for describing the runoff response with a curve, which is a function of the cumulative storm rainfall and antecedent wetness conditions. To improve the SCS-CN method, a new distribution function was recently proposed to unify the surface runoff modeling of the SCS-CN method and probability-distributed functions in the variable infiltration capacity (VIC) and Xin’anjiang models. This study aims to verify the new distribution function in a conceptual rainfall-runoff model and in the Soil and Water Assessment Tool (SWAT) by using real catchments. The Xunhe River basin in China and other basins in the United States were used as case studies. Results show that more observed variability in streamflow is captured when using the new spatial distribution function of soil water storage capacity in the con- ceptual runoff model. Specifically, there is a 9.8% average increase in the Nash-Sutcliffe efficiency (NSE), while simultaneously reducing the bias and mean relative absolute error (MRAE). When using the new distribution in SWAT, the model is able to better estimate the observed streamflow as indicated by higher NSE values for most of the basins. Akaike information criterion (AIC) is used for validating the goodness-of-fit when the number of parameters and model structure change. Further findings suggest that the estimated variance is more sensitive to the value of the new shape parameter a when soil water content is low in the early stage of rainfall. Therefore, the proposed new distribution function is shown to be effective in improving the accuracy of simulating streamflow for both conceptual and SWAT models. 
Language:English 
Keywords:Soil conservation service curve number (SCS-CN) model; Soil and water assessment tool (SWAT) model; Distribution function; Akaike information criterion