Scholarlink

<p>Climate change and sea-level rise are escalating the threat of hurricane-induced coastal flooding, demanding new approaches for long-term risk assessment. A linked statistical–deterministic modeling framework for evaluating future hurricane surge hazards with future climate conditions is detailed. The methodology combines a synthetic hurricane track simulator with a high-resolution hydrodynamic model to simulate thousands of potential hurricanes. The model includes scenarios with sea-level rise (SLR) and hurricane climatology change (HCC) factors in the next century. This framework was applied to St. Mary Parish in south Louisiana. The contribution of HCC and SLR to potential surges are assessed. Statistical analyses of the results reveal that sea-level rise is a dominant driver of increased flooding: surge heights in the study area grow significantly under even modest SLR. In contrast, the effects of the projected changes in hurricane frequency/intensity are more subtle – any surge increases due to HCC are relatively minor and not consistently significant across the six city case studies. These findings suggest that rising ocean base levels amplify flood risk more uniformly than shifts in hurricane climatology in the coming 100 years. The study also quantifies local sensitivity to SLR. The results highlight the critical importance of accounting for sea-level rise in coastal flood mitigation strategies. The demonstrated modeling approach offers a flexible, scalable tool for coastal engineers and planners, capable of producing granular surge risk estimates under future scenarios with climate change.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Hurricane surge prediction using a statistical–deterministic modeling framework: application to St Mary Parish, Louisiana, USA

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月18日

查看全文
  • Xuan Ma,
  • James M. Kaihatu

摘要

Climate change and sea-level rise are escalating the threat of hurricane-induced coastal flooding, demanding new approaches for long-term risk assessment. A linked statistical–deterministic modeling framework for evaluating future hurricane surge hazards with future climate conditions is detailed. The methodology combines a synthetic hurricane track simulator with a high-resolution hydrodynamic model to simulate thousands of potential hurricanes. The model includes scenarios with sea-level rise (SLR) and hurricane climatology change (HCC) factors in the next century. This framework was applied to St. Mary Parish in south Louisiana. The contribution of HCC and SLR to potential surges are assessed. Statistical analyses of the results reveal that sea-level rise is a dominant driver of increased flooding: surge heights in the study area grow significantly under even modest SLR. In contrast, the effects of the projected changes in hurricane frequency/intensity are more subtle – any surge increases due to HCC are relatively minor and not consistently significant across the six city case studies. These findings suggest that rising ocean base levels amplify flood risk more uniformly than shifts in hurricane climatology in the coming 100 years. The study also quantifies local sensitivity to SLR. The results highlight the critical importance of accounting for sea-level rise in coastal flood mitigation strategies. The demonstrated modeling approach offers a flexible, scalable tool for coastal engineers and planners, capable of producing granular surge risk estimates under future scenarios with climate change.