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<p>Frequent extreme rainfall events have intensified urban inundation, and the prolonged recession of accumulated water has become increasingly prominent, severely undermining urban flood resilience. Existing real-time assessment methods for urban inundation recession are inefficient and incapable of accurately supporting emergency drainage operations and post-disaster recovery. To address this gap, this study develops a dynamic assessment framework aimed at clarifying the inundation recession mechanisms, evaluating urban flood resilience, and providing scientific guidance for emergency dispatch strategies. The framework centers on multidimensional assessment indices and systematically considers the impact of rainfall structure. Using a typical flood-prone comprehensive urban area as a case study, this research quantitatively analyzes the spatiotemporal characteristics of the water recession process and the urban resilience. The results show that: (1) When the rainfall return period exceeds 50&#xa0;years, the capacity of pipe network tends to saturate, and urban inundation recession relies more on surface runoff. Beyond a 100-year return period, the system’s recession response slows down nonlinearly, requiring emergency surface drainage pathways and measures to alleviate inundation. (2) Rainfall peak structure critically controls the recession rhythm. Rainfall with rear-peak and lower concentration significantly delay the high-pressure drainage window of the urban system. (3) The recession of pipe network generally lags behind that of area-wide surface by 0.3–0.5&#xa0;h. Although spatial non-uniform rainfall mitigates overall drainage loads, it exacerbates local drainage bottlenecks. (4) Taking A3, A8 and A13 for examples, the highest node overflow densities occur at 1.15&#xa0;h, 1.42&#xa0;h, and 1.82&#xa0;h, respectively, consistently between the corresponding recession start time of area-wide surface and pipe network. This spatiotemporal clustering precisely diagnoses the transition from surface-water recession to system-wide drainage recovery, while also pinpointing the pipe network nodes that hinder recession. It suggests that node overflow density can serve as an effective indicator for identifying critical recession points and resilience weaknesses within the urban system. These findings provide new quantitative evidence for urban drainage systems’ resilience assessment and intervention.</p>

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Dynamic Recession Mechanisms Identification and Resilience Assessment Framework of Inundation in Typical Comprehensive Urban Areas

  • 期刊论文

  • 发表日期：

    2026年6月24日

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  • Bingxue Li,
  • Jingming Hou,
  • Xia Zhou,
  • Donglai Li,
  • Guangzhao Chen,
  • Chenchen Fan,
  • Jiahao Lv,
  • Jing Jing,
  • Yanhong Wang,
  • Xinxin Pan,
  • Yuhan Wang,
  • Qingshi Zhou

摘要

Frequent extreme rainfall events have intensified urban inundation, and the prolonged recession of accumulated water has become increasingly prominent, severely undermining urban flood resilience. Existing real-time assessment methods for urban inundation recession are inefficient and incapable of accurately supporting emergency drainage operations and post-disaster recovery. To address this gap, this study develops a dynamic assessment framework aimed at clarifying the inundation recession mechanisms, evaluating urban flood resilience, and providing scientific guidance for emergency dispatch strategies. The framework centers on multidimensional assessment indices and systematically considers the impact of rainfall structure. Using a typical flood-prone comprehensive urban area as a case study, this research quantitatively analyzes the spatiotemporal characteristics of the water recession process and the urban resilience. The results show that: (1) When the rainfall return period exceeds 50 years, the capacity of pipe network tends to saturate, and urban inundation recession relies more on surface runoff. Beyond a 100-year return period, the system’s recession response slows down nonlinearly, requiring emergency surface drainage pathways and measures to alleviate inundation. (2) Rainfall peak structure critically controls the recession rhythm. Rainfall with rear-peak and lower concentration significantly delay the high-pressure drainage window of the urban system. (3) The recession of pipe network generally lags behind that of area-wide surface by 0.3–0.5 h. Although spatial non-uniform rainfall mitigates overall drainage loads, it exacerbates local drainage bottlenecks. (4) Taking A3, A8 and A13 for examples, the highest node overflow densities occur at 1.15 h, 1.42 h, and 1.82 h, respectively, consistently between the corresponding recession start time of area-wide surface and pipe network. This spatiotemporal clustering precisely diagnoses the transition from surface-water recession to system-wide drainage recovery, while also pinpointing the pipe network nodes that hinder recession. It suggests that node overflow density can serve as an effective indicator for identifying critical recession points and resilience weaknesses within the urban system. These findings provide new quantitative evidence for urban drainage systems’ resilience assessment and intervention.