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<p>Design rainstorm patterns significantly alter urban flood evolution, while large-scale hydrodynamic simulations face severe computational inefficiency—especially in narrow valley cities with complex terrain. To address these challenges, this study employs a hydrodynamic–hydrological coupling model to simulate flood processes under eight typical design rainstorm patterns in a narrow valley city, and proposes a novel Dynamic Active Grid (DAG) algorithm that dynamically activates only hydraulically relevant grids and freezes dry/inactive areas to accelerate simulations. Results show that rainstorm patterns dominate flood characteristics: (1) Compared with uniform rainfall, delayed single-peak rainfall increases flood peaks by 8.04%–153.62%, while double-peak rainfall generally reduces peaks with small positional variations (within ± 5%). (2) Single-peak rainfall enlarges inundation areas by up to 204.31%, and peak delay exacerbates inundation; single-peak rainfall causes more severe inundation under small return periods, while double-peak rainfall risks rise for large return periods. (3) The DAG algorithm reduces redundant computation and improves efficiency by over 30% for small-return-period floods, though acceleration weakens for large floods due to expanded active grids. This study clarifies rainstorm pattern effects on floods in narrow valley cities, providing direct support for rainstorm-pattern-based flood risk assessment and targeted urban flood management. The DAG algorithm offers an efficient tool for large-scale, long-term flood simulations.</p>

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The Impact of Designed Rainstorms on River Flood Evolution Process Based on Dynamic Active Grid Hydrodynamic Model

  • 期刊论文

  • 发表日期：

    2026年6月25日

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  • Donglai Li,
  • Jiahao Lv,
  • Jingming Hou,
  • Tian Wang,
  • Wei Zhou,
  • Xinxin Pan,
  • Yu Tong,
  • Qingshi Zhou,
  • Xinghua Wang,
  • Guangzhao Chen,
  • Liping Ma

摘要

Design rainstorm patterns significantly alter urban flood evolution, while large-scale hydrodynamic simulations face severe computational inefficiency—especially in narrow valley cities with complex terrain. To address these challenges, this study employs a hydrodynamic–hydrological coupling model to simulate flood processes under eight typical design rainstorm patterns in a narrow valley city, and proposes a novel Dynamic Active Grid (DAG) algorithm that dynamically activates only hydraulically relevant grids and freezes dry/inactive areas to accelerate simulations. Results show that rainstorm patterns dominate flood characteristics: (1) Compared with uniform rainfall, delayed single-peak rainfall increases flood peaks by 8.04%–153.62%, while double-peak rainfall generally reduces peaks with small positional variations (within ± 5%). (2) Single-peak rainfall enlarges inundation areas by up to 204.31%, and peak delay exacerbates inundation; single-peak rainfall causes more severe inundation under small return periods, while double-peak rainfall risks rise for large return periods. (3) The DAG algorithm reduces redundant computation and improves efficiency by over 30% for small-return-period floods, though acceleration weakens for large floods due to expanded active grids. This study clarifies rainstorm pattern effects on floods in narrow valley cities, providing direct support for rainstorm-pattern-based flood risk assessment and targeted urban flood management. The DAG algorithm offers an efficient tool for large-scale, long-term flood simulations.