A Demand-Supply Framework for Evaluating the Effect of Resource and Service Constraints on Community Disaster Resilience
A Demand-Supply Framework for Evaluating the Effect of Resource and Service Constraints on Community Disaster Resilience
复制标题
用于评估资源和服务限制对社区抗灾能力影响的供需框架
DOI：
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
B. Stojadinović
中科院分区：
文献类型：
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作者：
N. Blagojević;B. Stojadinović
量化社区抗灾能力的工具对于就社区抗灾能力改进措施作出明智决策至关重要。在量化社区灾难恢复能力方面的主要研究空白之一是社区灾难恢复模拟。这样的模拟使人们能够深入了解实现快速有效的社区灾难恢复的因素，反之亦然。本文提出的IRE-CODES框架将社区灾难恢复模拟为一个时步循环，在每个时间步，社区组件对各种资源和服务的需求和供应的相互作用决定了组件的操作和恢复能力。然后，使用多维度量来量化社区的灾难恢复能力，其中每个维度表示社区对特定资源或服务的未满足需求，被标记为缺乏恢复能力(LOR)。本文介绍了如何应用这种需求/供应方法来考虑资源和服务限制，即阻碍因素，这些因素延长了部件恢复，从而降低了社区的灾难恢复能力。对圣安德烈亚斯断层上发生Mw7.2级地震的旧金山东北部地区的住房恢复力进行了量化，以说明所提出的方法。R最近在NHERI模拟中心开发的鲸鱼应用程序框架用于这一目的，介绍了如何使用IRE-CODE框架扩展这种关于自然灾害对社区影响的区域模拟，以模拟社区灾难恢复和量化社区灾难复原力。结果表明，以旧金山部分地区为研究对象的案例研究得到的住宅复原力量化结果与现有的住宅复原力估计值基本一致。获得了灾后社区一级对恢复资源和服务的供求演变情况，查明了对这些资源和服务的未得到满足的需求如何以及何时阻碍了社区恢复。最后，研究了社区动员恢复所需资源和服务的能力对其抗灾能力的影响。
Tools that quantify community disaster resilience are essential for informed decision-making on community disaster resilience improvement measures. One of the major research gaps in quantifying community disaster resilience are community disaster recovery simulations. Such simulations enable an insight into factors that enable a rapid and efficient community disaster recovery and vice versa. The iRe-CoDeS framework presented in this paper, simulates community disaster recovery as a time-stepping loop, where at each time step the interplay of demand and supply of community components for various resources and services dictates components’ ability to operate and recover. Disaster resilience of a community is then quantified using a multi-dimensional metric, where each dimension represents the unmet demand of a community regarding a certain resource or a service, labelled as Lack of Resilience (LoR). This paper presents how such a demand/supply approach can be applied to account for resource and service constraints, impeding factors, that prolong component recovery and thus decrease community disaster resilience. Housing resilience of north-east San Francisco exposed to a Mw7.2 earthquake on the San Andreas Fault is quantified to illustrate the proposed approach. rWhale application framework recently developed at the NHERI SimCenter is used for this purpose, presenting how such a regional simulation on the effect of natural disasters on communities can be extended using the iRe-CoDeS framework to simulate community disaster recovery and quantify community disaster resilience. It is shown that housing resilience quantification results obtained in the Case Study focused on a part of San Francisco are in accordance with the existing estimates of housing resilience. The evolution of the post-disaster community-level supply and demand for recovery resources and services is obtained, identifying how and when the unmet demand for these resources and services impedes community recovery. Lastly, the effect of community’s ability to mobilize resources and services needed for its recovery on its disaster resilience is investigated.