Revised runoff curve number for runoff prediction in the Loess Plateau of China

Abstract

AbstractThe soil conservation service (now Natural Resources Conservation Service) Curve Number (SCS‐CN), one of the most commonly used methods for surface runoff prediction. The runoff calculated by this method was very sensitive to CN values. In this study, CN values were calculated by both arithmetic mean (CN_C) and least square fit method (CN_F) using observed rainfall‐runoff data from 43 sites in the Loess Plateau region, which are considerably different from the CN2 values obtained from the USDA‐SCS handbook table (CN_T). The results showed that using CN_C instead of CN_T for each watershed produce little improvement, while replacing CN_T with CN_F improves the performance of the original SCS‐CN method, but still performs poorly in most study sites. This is mainly due to the SCS‐CN method using a constant CN value and discounting of the temporal variation in rainfall‐runoff process. Therefore, three factors—soil moisture, rainfall depth and intensity—affecting the surface runoff variability are considered to reflect the variation of CN in each watershed, and a new CN value was developed. The reliability of the proposed method was tested with data from 38 watersheds, and then applied to the remaining five typical watersheds using the optimized parameters. The results indicated that the proposed method, which boosted the model efficiencies to 81.83% and 74.23% during calibration and validation cases, respectively, performed better than the original SCS‐CN and the Shi and Wang (2020b) method, a modified SCS‐CN method based on tabulated CN value. Thus, the proposed method incorporating the influence of the temporal variability of soil moisture, rainfall depth, and intensity factors suggests an accurate runoff prediction for general applications under different hydrological and climatic conditions on the Loess Plateau region.