SCS-CN model parameters and run off simulation for sloping farmlandon purple soilunder repeated rainfall conditions

Abstract : Background The rainfall distribution in the purple soil hilly region is uneven, and seasonal droughts occur frequently. Accurately simulating rainfall-runoff processes is a prerequisite for realizing the utilization of rainfall resources in cultivated land. Methods Based on rainfall-runoff data monitored in standard runoff plots, this study analyzed the infiltration and rainfall-runoff characteristics of purple soil sloping farmland. The slope factor was introduced to modify the Curve Number （CN）, and the initial abstraction coefficient （λ） was optimized in conjunction with rainfall characteristics, thereby constructing an improved SCS-CN model suitable for purple soil sloping farmland. Results 1） The soil infiltration rate in purple soil sloping farmland decreased with increasing slope. The infiltration rate of 5 ° sloping farmland was generally higher than that of 10 ° and 15 ° slopes. Compared to the 5 ° slope, the initial infiltration rates on 10 ° and 15 ° slopes decreased by 13.75 % and 50.09 %, the steady infiltration rates decreased by 21.58% and 57.58%, and the average infiltration rates decreased by 23.03% and 58.99%, respectively. 2） Individual rainfall events were classified into three types based on rainfall amount: Type I （high rainfall amount, low frequency）, Type II （moderate rainfall amount, moderate frequency）, and Type III （low rainfall amount, high frequency）. The runoff depth for the three rainfall types followed the order: Type I > Type II > Type III. 3） After applying the slope correction formula, the calibrated CNII values for 5°, 10°, and 15° slopes were 78.14, 78.45, and 78.77, respectively. Based on rainfall type characteristics, the optimal λ value for Type I events （P > 70 mm） was 0.35, and for Type III events, it was 0.14. 4） Validation results were consistent with the calibration set. Compared to the standard model, the slope-rainfall type coupled modified model improved the Nash-Sutcliffe efficiency coefficient （NSE） by 31%, reduced the percent bias （PBIAS） by 97%, decreased the root mean square error （RMSE） by 33%, and achieved an R² of 0.98. Conclusions The SCS-CN model incorporating both slope and rainfall type modifications demonstrated the highest accuracy in simulating runoff from individual rainfall events on purple soil sloping farmland. The results provide a scientific basis for runoff control and the utilization of rainfall resources during seasonal droughts in the purple soil hilly region.