城市雨水管网模型的水文参数灵敏度分析  

Analysis on Hydrological Parameters Sensitivity in Urban Rainwater Pipe Network Model

作　　者：王荫茵 陶涛[1] 吕永鹏[2,3] 

机构地区：[1]同济大学环境科学与工程学院,上海市200092 [2]上海城市排水系统工程技术研究中心,上海市200092 [3]上海市政工程设计研究总院(集团)有限公司,上海市200092

出　　处：《城市道桥与防洪》2016年第2期159-162,17-18,共4页Urban Roads Bridges & Flood Control

基　　金：公益性行业科研专项(201306102);国家自然科学基金资助(51408225);国家重大水专项(2013ZX07304002)

摘　　要：为定量分析上海某区域的SWMM模型输出的总径流量和峰值流量对输入水文参数的变化响应的灵敏度,使用修正的Morris灵敏度分析法分析了3场降雨中SWMM模型中总径流量和峰值流量对水文参数不渗透性洼地蓄水(Destore-Imperv)、渗透性洼地蓄水(Destore-perv)、不渗透性粗糙系数曼宁值(Manning-Imperv)、渗透性粗糙系数曼宁值(Manning-perv)等参数的局部灵敏度。模拟结果证明,总降雨量变大,峰值流量对于参数Manning-Imperv、Destore-Imperv响应的灵敏度程度变大,并且峰值降雨强度越大,总径流量对于参数Max.Infiltration Rate、Decay Constant、Min.Infiltration Rate响应的灵敏度随之变大。To quantitatively analyze of the sensitivity of the total runoff volume and peak flow from the stormwater management model(SWMM) of an area in Shanghai to the change respond of input hydrological parameter, the modified Morris sensitivity analysis method is used to analyze the local sensitivity of the total runoff volume and peak flow in SWMM model to the hydrological parameters of impervious depression storage water(Destore-Imperv), pervious depression storage water(Destore-perv), impervious roughness coefficient(Manning-Imperv) pervious roughness coefficient(Manning-perv) and etc. in three times of rainfalls. The simulation result shows that the sensitivity of peak flow to the respond of the parameters Manning-Imperv and Destore-Imperv goes up with the variation of total rainfall volume, and the more increasing is peak rainfall strength, the higher is sensitivity of the total runoff volume to the respond of the parameters Max. Infiltration Rate, Decay Constant and Min. Infiltration Rate.

关 键 词：SWMM 修正的Morris筛选法 灵敏度 水文参数率定 

分 类 号：TU99[建筑科学—市政工程]