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<p>As climate change and urbanization intensify, urban infrastructures face escalating flood risks, necessitating robust assessment methods for effective prevention and control measures. The complexity of large-scale urban infrastructures, with their numerous entrances and exits, demands comprehensive flood risk modeling that can balance computational efficiency with simulation accuracy. However, traditional high-fidelity flood simulations at the urban basin scale are often constrained by data limitations and computational demands. This study proposed a hybrid-fidelity modeling approach to address these challenges. At the basin scale, the method integrates rainfall-runoff hydrological modeling with one-dimensional river hydrodynamics. At the neighborhood scale, where infrastructure entrances are concentrated, it couples one-dimensional sewer hydrodynamics with two-dimensional flood propagation modeling. This multi-scale approach enables the lower-fidelity basin models to provide boundary conditions for higher-fidelity neighborhood simulations, optimizing computational efficiency while maintaining assessment accuracy. The hybrid-fidelity modeling approach was applied to flood risk assessment of urban infrastructures in a planned region. Model simulations determined maximum inundation depths at infrastructure entrances under various rainfall scenarios, establishing a scientific foundation for developing targeted flood prevention and control strategies. This hybrid-fidelity approach offers a practical solution for comprehensive urban flood risk assessment in large infrastructures, balancing model complexity with computational feasibility.</p>

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A Hybrid-fidelity Modeling Approach for Evaluating Flooding Risk in Large Urban Infrastructures

  • 期刊论文

  • 发表日期：

    2025年4月9日

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  • Xuan Wang,
  • Jiaxin Yan,
  • Yong Liu,
  • Zhipeng Liu,
  • Shixiang Kuang,
  • Jinsuo Lu

摘要

As climate change and urbanization intensify, urban infrastructures face escalating flood risks, necessitating robust assessment methods for effective prevention and control measures. The complexity of large-scale urban infrastructures, with their numerous entrances and exits, demands comprehensive flood risk modeling that can balance computational efficiency with simulation accuracy. However, traditional high-fidelity flood simulations at the urban basin scale are often constrained by data limitations and computational demands. This study proposed a hybrid-fidelity modeling approach to address these challenges. At the basin scale, the method integrates rainfall-runoff hydrological modeling with one-dimensional river hydrodynamics. At the neighborhood scale, where infrastructure entrances are concentrated, it couples one-dimensional sewer hydrodynamics with two-dimensional flood propagation modeling. This multi-scale approach enables the lower-fidelity basin models to provide boundary conditions for higher-fidelity neighborhood simulations, optimizing computational efficiency while maintaining assessment accuracy. The hybrid-fidelity modeling approach was applied to flood risk assessment of urban infrastructures in a planned region. Model simulations determined maximum inundation depths at infrastructure entrances under various rainfall scenarios, establishing a scientific foundation for developing targeted flood prevention and control strategies. This hybrid-fidelity approach offers a practical solution for comprehensive urban flood risk assessment in large infrastructures, balancing model complexity with computational feasibility.