收录期刊

    HUANG Xuan, LIU Guoqing, LIU Sien, YANG Fan, WU Jingxiu, FAN Ziwu. Study on numerical simulation method of extreme rain flood risk in plain river network cities[J]. China Flood & Drought Management, 2023, 33(7): 21-27,33. DOI: 10.16867/j.issn.1673-9264.2022494
    Citation: HUANG Xuan, LIU Guoqing, LIU Sien, YANG Fan, WU Jingxiu, FAN Ziwu. Study on numerical simulation method of extreme rain flood risk in plain river network cities[J]. China Flood & Drought Management, 2023, 33(7): 21-27,33. DOI: 10.16867/j.issn.1673-9264.2022494

    Study on numerical simulation method of extreme rain flood risk in plain river network cities

    • Under the influence of global climate change and human activities, extreme rainstorm events occur frequently. Especially,Zhengzhou "July 20" extreme rainstorm alarmed people about the urban flood risk. In order to solve the problem of the extreme rainstrom flood simulation in plain river network cities, a modeling method, which is refined urban scale model coupled with basinal scale model, was purposed, and the boundary condition considered the combination of the precipitation process of Zhengzhou and local Characteristics of rainfall and water level. Based on the simulation method, a one-dimensional and two-dimensional coupled hydrological and hydrodynamic flood analysis model was constructed. Taking Wuxi city as the research object, the flood process under different times of the extreme rainstrom event of Zhengzhou city was simulated. Flood disaster characteristics of cities in plain river network under the extreme rainstrom was revealed based on the analysis of the distribution of inundation risks and variation law of river network water level. The research results can provide method support for numerical simulation of the urban extreme flood disaster, and provide theoretical basis for urban flood control and development planning, reducing disaster losses to the greatest extent.
    • loading

    Catalog

      Turn off MathJax
      Article Contents

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return