Consideration of vegetation interception of rainfall within the SCS-CN model: Application to the west bank of Dianchi Lake

Abstract

Study regionThe west bank of Dianchi Lake, China. Study focusThe Soil Conservation Service Curve Number (SCS-CN) model is widely used to simulate rainfall runoff of mountain floods. The determination of the CN parameter within the SCS-CN model is key to accurately simulating runoff. CN is closely related to regional land use, soil type, antecedent moisture conditions and slope. Therefore, this study established an optimized SCS-CN model by comprehensively considering the above factors, particularly the interception of rainfall by vegetation. New hydrological insights for the region(1) The original CN value resulted in underestimation of surface runoff in the study area [Nash-Sutcliffe Efficiency Coefficient (NSE) = 0.2260], indicating that regional differences reduce the applicability of the original CN value; (2) the optimized model considering the slope, antecedent rainfall, and other single or combined factors generated simulations of runoff that were closer to observations (NSE = 0.6811); the accuracy of the CN value can be effectively improved by combining various factors; however, since the CN had not yet reached the optimal value, simulations remained inaccurate; (3) consideration of interception of rainfall by vegetation in the model greatly improved the accuracy of simulated runoff [NSE = 0.8620]; indicating that the impact of vegetation interception of rainfall on surface runoff cannot be ignored. The results demonstrated that the SCS-CN model can provide more accurate simulations of mountain flood runoff in the study area after considering multiple factors, such as vegetation interception of rainfall.