| 城市降雨径流模拟的参数不确定性分析 |
| 摘要点击 2960 全文点击 1183 投稿时间：2011-07-18 修订日期：2012-01-11 |
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| 中文关键词 参数识别 SWMM模型 RSA方法 不确定性分析 城市降雨径流 |
| 英文关键词 parameter identifiability storm water management model(SWMM) regionalized sensitivity analysis (RSA) uncertainty analysis urban rainfall runoff |
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| 中文摘要 |
| 以厦门城市小流域为例,基于蒙特卡洛随机采样和区域灵敏度分析(RSA)方法,从参数的可识别性和灵敏度分析2个方面来分析城市降雨径流SWMM模型参数的不确定性.结果表明,水文水力模块中汇水单元不透水区贮水深度(Dstore-Imperv)、汇水单元透水区贮水深度(Dstore-Perv)和CN特征曲线(Curve Number)这3个参数可识别性较好,区域灵敏度高; 水文水力模块的区域灵敏度的排序为:Dstore-Imperv＞CN＞Dstore-Perv＞汇水单元透水区曼宁糙率(N-Perv)＞传导系数(Conductivity)＞管道曼宁糙率(Con-Mann)＞汇水单元不透水区曼宁糙率(N-Imperv).水质模块冲刷函数中地表冲刷系数(Coefficient)和地表径流幂指数(Exponent)这2个参数以及累积函数中的地表最大可累积的污染物量(Max.Buildup)的识别性较高,区域灵敏度较大.而从区域灵敏度的排序来看, 3种用地类型的地表累积速率(Rate Constant)参数K-S距离最小,Max.Buildup、Coefficient和Exponent参数的K-S距离相对较大. |
| 英文摘要 |
| An urban watershed in Xiamen was selected to perform the parameter uncertainty analysis for urban stormwater runoff modeling in terms of identification and sensitivity analysis based on storm water management model(SWMM) using Monte-Carlo sampling and regionalized sensitivity analysis(RSA) algorithm. Results show that Dstore-Imperv, Dstore-Perv and Curve Number (CN) are the identifiable parameters with larger K-S values in hydrological and hydraulic module, and the rank of K-S values in hydrological and hydraulic module is Dstore-Imperv＞CN＞Dstore-Perv＞N-Perv＞conductivity＞Con-Mann＞N-Imperv. With regards to water quality module, the parameters in exponent washoff model including Coefficient and Exponent and the Max.Buildup parameter of saturation buildup model in three land cover types are the identifiable parameters with the larger K-S values. In comparison, the K-S value of rate constant in three landuse/cover types is smaller than that of Max.Buildup, Coefficient and Exponent. |
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