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Integrated simulation method for waterlogging and traffic congestion under urban rainstorms

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  • Boni Su
  • Hong Huang
  • Yuntao Li

Abstract

Heavy rainstorms are increasingly frequent events in urban areas. Urban rainstorms lead to road waterlogging and low visibility, which affect drivers’ behavior and can thus cause traffic congestion and potential accidents. It is important to study the mechanisms of waterlogging and traffic congestion caused by rainstorms to more effectively predict them and reduce losses. In this paper, an integrated simulation method to analyze the influence of urban rainstorms on waterlogging and traffic congestion was developed. Firstly, waterlogging simulation was conducted to predict the spatiotemporal distribution of water depth on roads based on an urban storm water model. Secondly, psychological questionnaires were distributed to study the drivers’ behavior during a rainstorm. Based on the psychological questionnaires’ results, the vehicles’ speed was estimated under different water depth and visibility conditions. Finally, a microscopic traffic simulation was carried out to predict the traffic condition using the results of the previous two parts. Case studies were conducted on a simplified road model. The effects of different parameters on waterlogging and traffic congestion were analyzed. Then the method was applied to an actual urban area in Beijing, and a detailed waterlogging situation and traffic situation were obtained. Alternate future scenarios of adding drains to mitigate waterlogging and traffic congestion during heavy rainstorms were simulated, and the method’s potential to assist in decision making for urban drainage system design was shown. The integrated simulation method is helpful for early warning and risk management of urban rainstorms on waterlogging and traffic congestion. Copyright Springer Science+Business Media Dordrecht 2016

Suggested Citation

  • Boni Su & Hong Huang & Yuntao Li, 2016. "Integrated simulation method for waterlogging and traffic congestion under urban rainstorms," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(1), pages 23-40, March.
  • Handle: RePEc:spr:nathaz:v:81:y:2016:i:1:p:23-40
    DOI: 10.1007/s11069-015-2064-4
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    References listed on IDEAS

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    1. Joy Sanyal & X. Lu, 2004. "Application of Remote Sensing in Flood Management with Special Reference to Monsoon Asia: A Review," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 33(2), pages 283-301, October.
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    Citations

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    Cited by:

    1. Zipeng Chen & Kun Li & Jianhua Du & Yi Chen & Ronggang Liu & Yi Wang, 2021. "Three-dimensional simulation of regional urban waterlogging based on high-precision DEM model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(3), pages 2653-2677, September.
    2. Jingyi Gao & Osamu Murao & Xuanda Pei & Yitong Dong, 2022. "Identifying Evacuation Needs and Resources Based on Volunteered Geographic Information: A Case of the Rainstorm in July 2021, Zhengzhou, China," IJERPH, MDPI, vol. 19(23), pages 1-21, November.
    3. Luoyang Wang & Yao Li & Hao Hou & Yan Chen & Jinjin Fan & Pin Wang & Tangao Hu, 2022. "Analyzing spatial variance of urban waterlogging disaster at multiple scales based on a hydrological and hydrodynamic model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(2), pages 1915-1938, November.
    4. Xianhua Wu & Yaru Cao & Yang Xiao & Ji Guo, 2020. "Finding of urban rainstorm and waterlogging disasters based on microblogging data and the location-routing problem model of urban emergency logistics," Annals of Operations Research, Springer, vol. 290(1), pages 865-896, July.
    5. Qing Yang & Ying Sun & Xingxing Liu & Jinmei Wang, 2020. "MAS-Based Evacuation Simulation of an Urban Community during an Urban Rainstorm Disaster in China," Sustainability, MDPI, vol. 12(2), pages 1-19, January.

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