径流曲线数模型在湖南省山区小流域的优化与应用
Optimization and application of SCS-CN model in small mountain basins of Hunan Province
投稿时间:2023-11-12  修订日期:2024-04-16
DOI:
中文关键词:  SCS-CN模型  产流预报  纳什效率系数  相对误差  径流曲线数
英文关键词:SCS-CN model  Runoff forecast  Nash efficiency coefficient  Pbias  Curve number
基金项目:国家重点基础研究发展计划(2023YFC3008502)
作者单位邮编
杨娜娜 中国水利水电科学研究院 100038
刘舒* 中国水利水电科学研究院 100038
刘正风 水利部 水利水电规划设计总院 
陈伯文 湖南省水利水电勘测设计规划研究总院有限公司 
沈豪 中国水利水电科学研究院 
南永天 北京市智慧水务发展研究院 
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中文摘要:
      径流曲线数模型(Soil Conservation Service Curve Number Model)可以利用降雨资料估算径流,对水资源合理配置和山洪灾害预警具有重要意义,因为其方便计算、参数简单,而被广泛应用。目前标准SCS-CN模型在山区小流域的适用性欠佳,因此需要对模型参数进行优化以提高预测精度。本文以湖南省螺岭桥流域为例,根据实测降雨径流资料优化径流曲线数CN(Curve Number)查算表,并利用步长优化参数算法研究初损率对模型精度的影响,将优化模型的方法应用于湖南省凤凰小流域,验证该优化方法的可靠性。结果分析表明:与标准SCS-CN模型相比,优化后的SCS-CN模型效率系数NSE从0.576提升至0.813,决定系数R2为0.858。将模型优化方法验证于气候地形条件相似的凤凰流域,模型NSE值提高117%。通过预测径流深与实测径流深比较,优化模型模拟精度较为理想,对湖南省山区小流域场次降雨产流预报有一定的参考意义。
英文摘要:
      The Soil Conservation Service Curve Number (SCS-CN) model can use rainfall data to estimate runoff, which is of great significance for rational allocation of water resources and flash flood disaster warning. Because of its convenient calculation and simple parameters, it is widely used. At present, the standard SCS-CN model is not suitable for small mountain basins, so it is necessary to optimize the model parameters to improve the prediction accuracy. With its convenient calculation and simple parameters, it is widely used in areas lacking or without data. Taking Luolingqiao Basin in Hunan Province as an example, this paper optimized the runoff Curve CN(Curve Number) calculation table based on the measured rainfall runoff data, and studied the impact of initial loss rate on the model accuracy by using the step size optimization parameter algorithm. The optimization model method was applied to Fenghuang small Basin in Hunan Province to verify the reliability of the optimization method. The results show that compared with the standard SCS-CN model, the efficiency coefficient NSE of the optimized SCS-CN model is increased from 0.576 to 0.813, and the determination coefficient R2 is 0.858. The model optimization method was verified in Fenghuang basin with similar climatic and topographical conditions, and the NSE value of the model was increased by 117%. By comparing the predicted runoff depth with the measured runoff depth, the simulation accuracy of the optimized model is ideal, and it has certain reference significance for the forecast of rainfall runoff production in small mountain basins in Hunan Province.
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