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Real-time urban flood modeling: exploring the sub-grid approach for accurate simulation and hazard analysis

Author

Listed:
  • R. Reshma

    (Indian Institute of Technology Madras)

  • N. Nithila Devi

    (Indian Institute of Technology Madras)

  • Soumendra Nath Kuiry

    (Indian Institute of Technology Madras)

Abstract

The increasing magnitude of monetary and life losses caused by urban floods worldwide has sparked a deeper interest among researchers in comprehending these phenomena. Accurate modeling and forecasting of floods play a pivotal role in developing effective strategies for flood damage mitigation and management, thereby reducing associated hazards. A critical concern in this endeavor is optimizing the trade-off between computation time and accuracy when simulating real-time flood events. This paper aims to establish the superiority of the sub-grid approach in achieving accurate simulation results of real-time flood events within minimal computational time. By conducting simulations of one experimental test and two real-world flood events using the HEC-RAS flow simulation model, we demonstrate that the sub-grid approach significantly reduces computation time by approximately 90% while faithfully capturing the dynamics of urban flood. In contrast, the non-sub-grid approach often over-predicts flow dynamics in urban areas and fails to effectively trace building footprints, resulting in unrealistic flow patterns and under or overstating the hazard maps. In a nutshell, the sub-grid hydraulic modeling approach enables better hazard analysis and mapping. The outcomes of this research provide valuable guidance to modelers and authorities, suggesting the adoption of the sub-grid approach for accurate and reliable real-time urban flood modeling, inundation forecasting, and hazard zoning in the context of urban flood hazard analysis.

Suggested Citation

  • R. Reshma & N. Nithila Devi & Soumendra Nath Kuiry, 2024. "Real-time urban flood modeling: exploring the sub-grid approach for accurate simulation and hazard analysis," 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. 120(11), pages 9609-9647, September.
  • Handle: RePEc:spr:nathaz:v:120:y:2024:i:11:d:10.1007_s11069-024-06579-0
    DOI: 10.1007/s11069-024-06579-0
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    References listed on IDEAS

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    1. Yun Xing & Qiuhua Liang & Gang Wang & Xiaodong Ming & Xilin Xia, 2019. "City-scale hydrodynamic modelling of urban flash floods: the issues of scale and resolution," 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. 96(1), pages 473-496, March.
    2. Jingming Hou & Nie Zhou & Guangzhao Chen & Miansong Huang & Guangbi Bai, 2021. "Rapid forecasting of urban flood inundation using multiple machine learning models," 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(2), pages 2335-2356, September.
    3. Ismail Haltas & Sebnem Elçi & Gokmen Tayfur, 2016. "Numerical Simulation of Flood Wave Propagation in Two-Dimensions in Densely Populated Urban Areas due to Dam Break," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(15), pages 5699-5721, December.
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