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High-Resolution Flood Numerical Model and Dijkstra Algorithm Based Risk Avoidance Routes Planning

Author

Listed:
  • Bingyao Li

    (Xi’an University of Technology)

  • Jingming Hou

    (Xi’an University of Technology)

  • Xinghua Wang

    (Xi’an University of Technology)

  • Yongyong Ma

    (Xi’an University of Technology)

  • Donglai Li

    (Xi’an University of Technology)

  • Tian Wang

    (Xi’an University of Technology)

  • Guangzhao Chen

    (Xi’an University of Technology)

Abstract

Flooding is the most pervasive risk globally among natural hazards, efficient and reliable emergency evacuation path planning scheme is of great significance for improving the emergency rescue efficiency. To this end, a systematic framework for determining the risk avoidance path under flood disasters is proposed, which adopts the high-resolution 2-D hydrodynamic model, the road section weight value module, and the classic Dijkstra algorithm. Then Fengxi New City is applied as a case study in which four different rainfall condition scenarios (50a, 100a, 200a, 500a) are created to verify the applicability of the framework. The simulation results show that the increase of rainfall return period changes the rescue scenario shortest path, and the planned path distance and travel time under 500a rainfall conditions are 33.17% and 28.85% higher than those under no rainfall conditions respectively, and the algorithm time consumption takes an average of 0.012s, which can fully meet the popular acceptance of path planning time. This paper provides a novel and promising method for evaluating the planning and decision-making of the risk avoidance routes under flood disaster scenarios.

Suggested Citation

  • Bingyao Li & Jingming Hou & Xinghua Wang & Yongyong Ma & Donglai Li & Tian Wang & Guangzhao Chen, 2023. "High-Resolution Flood Numerical Model and Dijkstra Algorithm Based Risk Avoidance Routes Planning," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(8), pages 3243-3258, June.
    • Handle: RePEc:spr:waterr:v:37:y:2023:i:8:d:10.1007_s11269-023-03500-5
    DOI: 10.1007/s11269-023-03500-5
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    References listed on IDEAS

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    1. Porta, Sergio & Crucitti, Paolo & Latora, Vito, 2006. "The network analysis of urban streets: A dual approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 369(2), pages 853-866.
    2. Bingyao Li & Jingming Hou & Donglai Li & Dong Yang & Hao Han & Xu Bi & Xinghua Wang & Reinhard Hinkelmann & Junqiang Xia, 2021. "Application of LiDAR UAV for High-Resolution Flood Modelling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(5), pages 1433-1447, March.
    3. Jun Rentschler & Melda Salhab & Bramka Arga Jafino, 2022. "Flood exposure and poverty in 188 countries," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
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