湖北农业科学 ›› 2021, Vol. 60 ›› Issue (2): 66-71.doi: 10.14088/j.cnki.issn0439-8114.2021.02.012

• 资源·环境 • 上一篇    下一篇

基于道路交通的石家庄市强降水内涝风险评估

魏军, 陈笑娟, 胡会芳, 张静, 李婷   

  1. 河北省气象灾害防御中心,石家庄 050021
  • 收稿日期:2020-12-20 出版日期:2021-01-25 发布日期:2021-02-07
  • 通讯作者: 陈笑娟,女,高级工程师,(电子信箱)juan2044335@163.com。
  • 作者简介:魏 军(1987-),男,江苏泗阳人,工程师,硕士,主要从事城市气象灾害研究,(电话)18333109359(电子信箱)weijun052700@126.com。
  • 基金资助:
    河北省气象局科研项目(20ky27; 17ky05)

Risk assessment of heavy rainfall and waterlogging in Shijiazhuang based on road traffic

WEI Jun, CHEN Xiao-juan, HU Hui-fang, ZHANG Jing, LI Ting   

  1. Hebei Meteorological Disaster Prevention Center,Shijiazhuang 050021,China
  • Received:2020-12-20 Online:2021-01-25 Published:2021-02-07

摘要: 基于构建的石家庄市强降水内涝数学模型,选取2、5、10、30、50、100年一遇小时降水对2017年石家庄市道路积涝水深进行情景模拟,同时以道路交通的车流、车速表征城市内涝的承载体脆弱性,利用GIS空间分析功能完成强降水内涝灾害对道路交通的风险评估。结果表明,随着小时降水重现期的增大,城市道路积水面积和积水深度呈不同程度增加趋势;在2年一遇的降水强度下,城区25.8%的道路有积水,平均积水深度为8.6 cm,而在100年一遇的降水强度下,积水网格数量超过70%,单元网格内部积水明显增加,平均积水深度为56.3 cm;道路交通内涝风险评估表现出低风险区网格数量在30年一遇时最高,而中高风险区的网格数量随着重现期变大不断增多。

关键词: 道路交通, 城市内涝, 风险评估, 情景模拟

Abstract: Based on the mathematical model of heavy precipitation and waterlogging in Shijiazhuang city, 2, 5, 10, 30, 50, and 100 years for one hour of precipitation are selected to simulate the road waterlogging depth in Shijiazhuang city in 2017. The traffic flow and speed of the vehicle are used to characterize the vulnerability of the waterlogged carrier, and the GIS spatial analysis function is used to complete the risk assessment of road traffic caused by the heavy rainfall waterlogging disaster. The results show that with the increase of the hourly precipitation recurrence period, the area and depth of water accumulation on urban roads increase in varying degrees; Under the rainfall intensity of 2 years, 25.8% of the roads in the urban area have accumulated water, and the average accumulation of water. The water depth is 8.6 cm, and under a rainfall intensity of 100 years, the number of accumulated water grids exceeds 70%, and the accumulated water in the unit grid increases significantly, with an average accumulated water depth of 56.3 cm. The risk assessment of road waterlogging shows that the number of grids in the low-risk area is the highest at 30 years, and the number of grids in the middle-high-risk area increases with the recurrence period.

Key words: road traffic, urban waterlogging, risk assessment, scenario simulation

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