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

Abstract

Study region: The west bank of Dianchi Lake, China. Study focus: The 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.

Keywords

• SCS-CN model
• Mountain floods
• Rainfall runoff
• CN
• Vegetation interception rainfall