A novel framework to study community-level social and physical impacts of hurricane-induced winds through synthetic scenario analysis
A novel framework to study community-level social and physical impacts of hurricane-induced winds through synthetic scenario analysis
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DOI：
10.3389/fbuil.2023.1005264
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发表时间：
2023-02
期刊：
影响因子：
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通讯作者：
R. K. Mazumder;S. A. Enderami;E. Sutley
中科院分区：
文献类型：
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作者：
R. K. Mazumder;S. A. Enderami;E. Sutley
强烈的飓风经常造成严重的基础设施破坏，并对沿海社区造成社会和经济后果。在社区复原力规划的背景下，对这种影响进行评估可以促进为社区利益制定更了解风险的缓解计划。本研究提出了一个利用参数风场模型综合模拟场景飓风的新框架，用于预测社区级建筑破坏、直接经济损失和社会后果。提出的综合场景方法使用历史飓风数据并调整其原始轨迹来创建综合变化场景，并估计每个建筑物所在位置的峰值阵风风速。本研究采用随机损伤模拟算法对建筑物的物理损伤进行评估。该算法使用相应的基于损伤的脆弱性函数，预测建筑物所在位置的最大阵风速度，以及随机生成的数字，为每个建筑物分配一个损伤级别。由于建筑物的物理损坏而造成的货币损失是使用联邦应急管理局的直接损失率和考虑不确定性的建筑物重置成本来确定的。为了评估物理损害暴露的社会影响，测量了三种可能的灾后社会破坏，包括家庭流离失所、就业中断和学校关闭。该框架通过其在北卡罗来纳州Onslow县飓风多发社区的应用得到了验证。开发的框架的新贡献，除了引入了飓风引起的风危害的空间预测方法外，还在于它能够阐明飓风引起的风对沿海社区建筑库存造成重大物理损害的社会后果的某些方面。这些进步使社区规划者和决策者能够做出更明智的风险决策，以提高沿海社区的抵御能力。
Strong hurricane winds often cause severe infrastructure damage and pose social and economic consequences in coastal communities. In the context of community resilience planning, estimating such impacts can facilitate developing more risk-informed mitigation plans in the community of interest. This study presents a new framework for synthetically simulating scenario-hurricane winds using a parametric wind field model for predicting community-level building damage, direct economic loss, and social consequences. The proposed synthetic scenario approach uses historical hurricane data and adjusts its original trajectory to create synthetic change scenarios and estimates peak gust wind speed at the location of each building. In this research, a stochastic damage simulation algorithm is applied to assess the buildings’ physical damage. The algorithm assigns a damage level to each building using the corresponding damage-based fragility functions, predicted maximum gust speed at the building’s location, and a randomly generated number. The monetary loss to the building inventory due to its physical damage is determined using FEMA’s direct loss ratios and buildings’ replacement costs considering uncertainty. To assess the social impacts of the physical damage exposure, three likely post-disaster social disruptions are measured, including household dislocation, employment disruption, and school closures. The framework is demonstrated by its application to the hurricane-prone community of Onslow County, North Carolina. The novel contribution of the developed framework, aside from the introduced approach for spatial predicting hurricane-induced wind hazards, is its ability to illuminate some aspects of the social consequences of substantial physical damages to the building inventory in a coastal community due to the hurricane-induced winds. These advancements enable community planners and decision-makers to make more risk-informed decisions for improving coastal community resilience.