徐美, 刘舒, 孙杨, 姚永慧. 利用洪涝模型进行城市内涝风险快速识别与预警[J]. 武汉大学学报 ( 信息科学版), 2020, 45(8): 1185-1194. DOI: 10.13203/j.whugis20200122
引用本文: 徐美, 刘舒, 孙杨, 姚永慧. 利用洪涝模型进行城市内涝风险快速识别与预警[J]. 武汉大学学报 ( 信息科学版), 2020, 45(8): 1185-1194. DOI: 10.13203/j.whugis20200122
XU Mei, LIU Shu, SUN Yang, YAO Yonghui. Rapid Identification and Early Warning of Urban Waterlogging Risk Using Flooding Model[J]. Geomatics and Information Science of Wuhan University, 2020, 45(8): 1185-1194. DOI: 10.13203/j.whugis20200122
Citation: XU Mei, LIU Shu, SUN Yang, YAO Yonghui. Rapid Identification and Early Warning of Urban Waterlogging Risk Using Flooding Model[J]. Geomatics and Information Science of Wuhan University, 2020, 45(8): 1185-1194. DOI: 10.13203/j.whugis20200122

利用洪涝模型进行城市内涝风险快速识别与预警

Rapid Identification and Early Warning of Urban Waterlogging Risk Using Flooding Model

  • 摘要: 中国越来越多的城市面临暴雨内涝问题,如能提前发布内涝预警,可防患于未然。基于水力学的精细化洪涝模型可对城区暴雨、洪水在河道、地表、管网的流动过程进行全程模拟,获得地表内涝积水过程、范围、水深等信息,为实现内涝识别和预警提供数据支撑。在利用精细化洪涝模型构建暴雨-内涝情景库的基础上,提出了利用情景匹配模式针对预报降雨发布城市内涝预警的方法。城市地表复杂,排水设施数据质量参差不齐,采用多模式概化方法尽可能详细地刻画决定内涝模拟效果的局部微地形,地表模型与管网模型采用多种耦合方式,实现了城区内涝的精细化模拟,能够进行内涝风险的精准化快速识别。以中国北京市城区为例,通过城区精细化洪涝模型对多种降雨条件下的暴雨情景进行模拟与分析,构建了北京城区的暴雨-内涝情景库。以道路和桥区为重点关注对象,在暴雨预报之际,结合暴雨与情景库特征参数快速识别有内涝风险的道路、桥区及其他区域并依此进行内涝风险预警,可指导相关部门合理安排交通管制、有效部署排涝力量。

     

    Abstract:
      Objectives   Duty of flood prevention is becoming more urgent in recent years because of more frequent waterlogging caused by extreme weather and rapid urbanization. Advanced early warning of waterlogging can help people taking preventive measures to guard against possible trouble. Identification of waterlogging risk is the premise for early warning.
      Methods   The urban hydraulic flood model can simulate the process of waterlogging based on rainstorm forecast and it is a kind of effective method for prevention of loss caused by waterlogging. The method of waterlogging risk identification and warning using detailed hydraulic flooding model of Beijing main city will be introduced. An advanced rainstorm-waterlogging library is formed based on the simulation results of many rainfall scenario for quick identification of a forecast rainfall. The early warning of possible waterlogging in main roads and bridges can be issued after the rainfall forecast through the quick parameters matching of the forecast rainfall and the scenario library. Urban surface is complex and the data quality of drainage facilities is not perfect but they are important factors for model’s simulation results. In this research, multi-mode generalization of spatial data is used to describe the local microtopography as detailed as possible for improving simulation effect. And the surface model and pipe network model are coupled together via various mode according to the quality of drainage data.
      Results   The discharge process calculated by the model is similar to the main peak trend of the measured process. The simulation result of the 1D model was therefore considered to be reasonable. As for the verification of the surface result, the verification effect cannot be measured accurately because the reference data is not ideal. However, the simulation results of all the important bridges were checked one by one according to the familiar departments and personnel, and the simulated waterlogging situation was basically similar to actual situation. The Beijing’s urban flooding model has been put into used during flood season from the year 2018 and served for the flood prevention task of the Beijing main city.
      Conclusions   The urban detailed flooding model can simulate the whole process of rainfall-runoff-convergence and it is suitable for integrated simulation of internal and external flood and waterlogging.

     

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