<p>Urban rainstorm-induced flooding poses a severe threat to the structural integrity and functionality of road networks. This study quantitatively evaluates the structural resilience of the urban road network in Hangzhou by integrating multi-source spatial data. Flooding scenarios across five rainfall recurrence intervals (10- to 200-year events) were simulated using the SCS-CN model. Subsequently, a complex network topology model was applied to assess resilience variations from both global and local perspectives. The results demonstrate that: (1) road failures are predominantly concentrated in low-lying areas and lower-grade branch roads, expanding progressively with increased recurrence intervals; (2) global network resilience experiences significant degradation, evidenced by diminished connectivity and network efficiency; (3) locally, betweenness centrality serves as the dominant metric for identifying critical vulnerable nodes, which exhibit a spatial tendency to cluster toward the city center under intensifying flood stress; and (4) disruption simulations reveal that the removal of high-betweenness nodes drastically accelerates structural fragmentation. Based on these findings, targeted optimization strategies are proposed, encompassing elevation upgrades for critical segments, the deployment of high-capacity drainage systems at high-centrality underpasses, and the establishment of redundant micro-circulation pathways. This global-local analytical framework provides scientific insights and actionable planning interventions for enhancing infrastructure resilience in comparable flood-prone cities.</p>

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Multi-scenario flooding impacts on urban road network structural resilience: a global-local complex network analysis

  • Yijun Shi,
  • Yifan Shen,
  • Ou Bai,
  • Lihua Xu

摘要

Urban rainstorm-induced flooding poses a severe threat to the structural integrity and functionality of road networks. This study quantitatively evaluates the structural resilience of the urban road network in Hangzhou by integrating multi-source spatial data. Flooding scenarios across five rainfall recurrence intervals (10- to 200-year events) were simulated using the SCS-CN model. Subsequently, a complex network topology model was applied to assess resilience variations from both global and local perspectives. The results demonstrate that: (1) road failures are predominantly concentrated in low-lying areas and lower-grade branch roads, expanding progressively with increased recurrence intervals; (2) global network resilience experiences significant degradation, evidenced by diminished connectivity and network efficiency; (3) locally, betweenness centrality serves as the dominant metric for identifying critical vulnerable nodes, which exhibit a spatial tendency to cluster toward the city center under intensifying flood stress; and (4) disruption simulations reveal that the removal of high-betweenness nodes drastically accelerates structural fragmentation. Based on these findings, targeted optimization strategies are proposed, encompassing elevation upgrades for critical segments, the deployment of high-capacity drainage systems at high-centrality underpasses, and the establishment of redundant micro-circulation pathways. This global-local analytical framework provides scientific insights and actionable planning interventions for enhancing infrastructure resilience in comparable flood-prone cities.