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Simulation of an Agricultural Watershed Using an Improved Curve Number Method in SWAT

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Transactions of the ASABE. 51(4): 1323-1339. (doi: 10.13031/2013.25248) @2008
Authors:   X. Wang, S. Shang, W. Yang, A. M. Melesse
Keywords:   Hydrologic modeling, Infiltration excess, Precipitation, Runoff, Saturation excess.

The USDA Soil Conservation Service (SCS) curve number (CN) method has been the foundation of the hydrology algorithms in commonly used continuous simulation models, including the Soil and Water Assessment Tool (SWAT). This expanded use of the SCS-CN method has proven successful for many applications. However, because the SCS-CN method was originally developed to determine design peak discharges of synthetic storm events under an average antecedent moisture condition, research is needed to address the controversy over the use of this method to represent continuous precipitation runoff processes. In addition, poor results obtained for some conditions indicate the necessity to improve the method to provide a more realistic and accurate representation of water flow amounts, paths, and source areas upon which erosion and water quality predictions depend. Thus, the objectives of this study were to: (1) propose a modified curve number (MCN) method, and (2) assess the MCN method relative to the existing SWAT method with an Ia/S value either equal to 0.2 or 0.05. The equations that formulate the MCN method were coded into the SWAT 2005 framework. A SWAT model implementing the MCN method was evaluated along with the models implementing the existing SWAT method with Ia/S values of 0.2 and 0.05. The evaluation was conducted in the 870 km2 upper portion of the Forest River watershed located in northeastern North Dakota. The results revealed that the total streamflows predicted by the three models were comparable, as indicated by similar values for the Nash-Sutcliffe coefficient. However, the MCN approach resulted in the most accurate prediction of the streamflow components (i.e., baseflow versus direct flow) as well as water yields. For the study area, the MCN method was judged to be superior to the existing commonly used curve number methods in terms of mimicking the precipitation runoff processes.

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