Improved SCS-CN Method Based on Storage and Depletion of Antecedent Daily Precipitation

Abstract

The accurate simulation or prediction of storm runoff is one of the most important bases of water resource management and environmental quality assessment of water and soil. The soil conservation service-curve number (SCS-CN) method cannot effectively determine the effect of antecedent precipitation storage and depletion on runoff, which limits the accuracy of the method’s runoff prediction. Thus, potential initial abstraction and decay constant were developed in this study to improve the SCS-CN method. Potential initial abstraction determined the maximum rainfall storage before runoff and the threshold of daily effective rainfall, and the decay constant was used to describe the dynamic depletion of antecedent daily effective rainfall induced by evapotranspiration and seepage. The improved SCS-CN method was evaluated withthe runoff data observed in four cropping systems and three drainage areas, and it proved that the improved SCS-CN method predicted runoff more accurately than the original SCS-CN method. The inproved SCS-CN method increased both NSE and R2 values by more than 20 % for the four cropping systems, and increased R2 values by 11.9, 13.9 and 9.6 % for the plot, field, and catchment, respectively, compared with the original SCS-CN method. The decay constant did not vary with cropping systems and drainage areas.