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投稿时间:2016-01-27 修订日期:2017-02-23
投稿时间:2016-01-27 修订日期:2017-02-23
中文摘要: 随着城市化的推进,暴雨内涝逐渐成为许多城市的主要自然灾害,但当前暴雨内涝模型大多基于水动力学方法,需要大量的输入参数,不便于推广和应用。研究采用概化方法针对外环内中心城区构建上海暴雨内涝评估模型(Shanghai Urban Flooding Assessment Model, SUM),通过对接逐时次的降雨量,实现了对城市内涝的逐小时连续模拟。在此基础上,利用报警灾情资料和区内积水监测数据对模型模拟结果进行了评估。结果表明,该模型可以较好地模拟本市中心城区的内涝积水状况,且随着降雨量的增大,积水面积的增幅也逐渐变大;致灾阈值的分析表明浦西地区的内涝致灾雨量总体上低于浦东,其中本市黄浦、徐汇、虹口、闸北等中心城区以及宝山区部分街道的致灾雨量相对较低。
中文关键词: 暴雨,内涝,致灾阈值
Abstract:Urban flooding has gradually become a major natural disaster in many cities with the development of the urbanization, but the current urban flooding models are mostly based on hydrodynamic methods, requiring a lot of input parameters, so they are inconvenient in popularization and application. In this paper, Shanghai Urban Flooding Assessment Model (SUM) was established aiming at the downtown inside the outer ring with the generalized method. Through inputting the hourly rainfall, hourly continuous simulation to urban flooding was achieved. On this basis, using the disaster situation data and ponding monitoring data, we assessed the simulation results. The results indicate that the SUM can simulate the urban flooding situation in the downtown of Shanghai better. The catchment area increases with the increase of precipitation amount. Analysis of disaster threshold shows that the rainfall causing water logging disaster in Puxi of Shanghai is generally lower than that in Pudong. The disaster rainfall is less relatively in the central part of the city including Huangpu District, Xuhui District, Hongkou District, Zhabei District and some streets in Baoshan District.
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基金项目:上海市科学技术委员会民生科技项目(15dz1207801)和国家重点基础研究发展计划(973计划)(2015CB452806)共同资助
引用文本:
杨辰,王强,顾宇丹,2017.上海市城市暴雨内涝评估建模及模拟研究[J].气象,43(7):879-886.
YANG Chen,WANG Qiang,GU Yudan,2017.Study of Shanghai Urban Flooding Assessment Modeling and Simulation[J].Meteor Mon,43(7):879-886.
杨辰,王强,顾宇丹,2017.上海市城市暴雨内涝评估建模及模拟研究[J].气象,43(7):879-886.
YANG Chen,WANG Qiang,GU Yudan,2017.Study of Shanghai Urban Flooding Assessment Modeling and Simulation[J].Meteor Mon,43(7):879-886.