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    次降雨条件下紫色土坡耕地SCS-CN模型参数优化与径流模拟

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

    • 摘要: 摘要:紫色土丘陵区降雨分布不均,季节性干旱频发,精准模拟降雨径流是实现耕地降雨资源化利用的前提。目的为提升SCS-CN模型在紫色土坡耕地的径流模拟精度,方法本研究基于标准径流小区监测的降雨径流数据,分析紫色土坡耕地入渗及降雨径流特征,并引入坡度修正径流曲线数(CN),结合降雨特征修正初损系数(λ),构建适用于紫色土坡耕地的SCS-CN改进模型。结果1)紫色土坡耕地土壤入渗速率随坡度增大呈降低趋势,5 °坡耕地土壤入渗速率整体高于10 °、15 °;10 °和15 °初始入渗率较5 °减少13.75 %、50.09 %,稳定入渗率减少21.58 %,57.58 %,平均入渗率减少23.03 %,58.99 %。2)次降雨事件根据降雨量分为三类雨型:I雨型为大雨量、低频率,II雨型为中雨量、中频率,III雨型为小雨量、高频率。三类雨型下坡面径流深表现为:I雨型>II雨型>III雨型;3)引入坡度公式修正后5 °~15 ° CNⅡ 取值分别为78.14、78.45、78.77;结合雨型特征将I雨型中P > 70 mm的次降雨事件 λ 值最优为0.35,III雨型中 λ 值最优为0.14。4)验证组模拟结果与率定组一致,坡度结合雨型修正模型纳什效率系数提升31%,百分比偏差减少97%,均方根误差降低了33%,R2 = 0.98.。结论引入坡度并结合雨型修正的SCS-CN模型在次降雨下的紫色土坡耕地径流模拟精度最高。研究结果可为紫色土丘陵区坡耕地径流调控及季节性干旱下的降雨资源化利用提供科学依据。

       

      Abstract: 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.

       

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