基于SWMM的城市社区尺度管网排水模拟--以福州市某排水小区为例  

Simulation of pipeline network drainage at urban community scales based on SWMM:A case study in Fuzhou City

作　　者：叶陈雷 徐宗学 雷晓辉[2] 陈阳[3] 李鹏 王京晶 YE Chenlei;XU Zongxue;LEI Xiaohui;CHEN Yang;LI Peng;WANG Jingjing(Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology,College of Water Sciences,Beijing Normal University,Beijing 100875,China;China Institute of Water Resources and Hydropower Research,Beijing 100038,China;College of Resources and Civil Engineering,Northeastern University,Shenyang 110819,China)

机构地区：[1]北京师范大学水科学研究院城市水循环与海绵城市技术北京市重点实验室,北京100875 [2]中国水利水电科学研究院水资源研究所,北京100038 [3]东北大学资源与土木工程学院,沈阳110819

出　　处：《南水北调与水利科技（中英文）》2022年第2期271-280,共10页South-to-North Water Transfers and Water Science & Technology

基　　金：国家自然科学基金项目(52079005);北京师范大学学科交叉项目(BNUXKJC1927)。

摘　　要：基于福州市晋安区某典型居民区实测的管道液位数据,利用遗传算法对SWMM(storm water management model)参数进行优化率定,并利用Morris法对影响产汇流计算的主要参数敏感性进行分析。在此基础上,利用不同重现期的降雨驱动模型,比较分析在不同情景下小区排水管网的排水能力。结果表明:基于遗传算法对研究小区SWMM的参数率定取得了较好的效果,模型参数的拟合度较高;20180531场次降雨计算得到纳什效率系数0.82,20180620场次降雨计算得到纳什效率系数为0.81,实测最大水位、峰现时间等参数误差均在2%以内。通过对参数进行Morris敏感性分析,该居民小区SWMM的最大下渗率、最小下渗率、衰减系数以及管道糙率是比较敏感的模型参数。在不同重现期降雨情景下对排水管网排水能力分析可知,在降雨历时增加时,流量、节点平均超载时长、节点溢流数、满管时间等指标受降雨重现期的影响较大,节点超载数、满流管道数受降雨历时影响相对较小。研究结果可以为城市社区尺度下的管网排水系统模拟及评估提供一定的借鉴。Under the joint influence of climate change and rapid urbanization,China's cities are facing increasingly severe flood problems.SWMM(storm water management model)is an important tool for calculating and analyzing the urban rainstorm,which has been widely used in urban drainage analysis,urban flood simulation,evaluation of sponge city building,water quality change,etc.Although lots of work have been done in this domain,the analysis of the whole process of pipe network drainage at the scale of the urban community still needs to be further improved.Based on the measured rainfall data and measured pipeline water level data,the main parameters of the SWMM are optimized and cablibrated through a genetic algorithm,and the Morris method is used to analyze the sensitivity of each parameter.On this basis,using rainfall-driven models with different return periods,the drainage capacity of community drainage networks under different scenarios is compared and analyzed.The results show that the parameter calibration of the SWMM based on a genetic algorithm has obtained good results.The Nash efficiency coefficient(E_(NS))calculated for 20180531 rainfall event is 0.82,and for the 20180620 rainfall event is 0.81,respectively.The errors of measured maximum water level,peak time,and other parameters are within 2%.Through the Morris sensitivity analysis of the parameters,the maximum infiltration rate,minimum infiltration rate,decay constant,and pipeline roughness of the SWMM of the residential area are more sensitive model parameters.Using different combined scenarios to drive the SWMM,taking a typical drainage community in Jin′an District,Fuzhou asan example,a relatively complete urban drainage waterlogging analysis system is proposed.Based on analysis of the drainage capacity of the drainage pipe network under the rainfall scenarios of different return periods,when the rainfall duration increases,the flow,average overload duration of nodes,overflow number of nodes,full pipe time,and other indicators are greatly affected by the ra

关 键 词：雨洪模拟 SWMM 遗传算法 敏感性分析 管网排水分析 

分 类 号：TV125[水利工程—水文学及水资源] TU992[建筑科学—市政工程]