Data, information, and tools needed for community resilience planning and decision-making

McAllister, Therese P.; Clavin, Christopher; Ellingwood, Bruce R.; Lindt, John van de; Mizzen, David R.; Lavelle, Francis M.

doi:10.6028/nist.sp.1240

Cited by 14 publications

(4 citation statements)

References 5 publications

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“…These natural hazards models have become increasingly data-driven, requiring comprehensive data sets to capture complex, system-level responses. Examples of such models include performance-based earthquake engineering (PBEE) design methods and resilience-based design methods (e.g., FEMA, 2018;McAllister et al, 2019), which require fragility data to relate structural, non-structural, and infrastructure systems performance to engineering demand parameters, and stochastic wind hazard loss models (Hamid et al, 2011;Pita et al, 2015) that require field data to better calibrate and validate the hazard, infrastructure vulnerability, costing components, and economic impacts of preparedness and mitigation policies.…”

Section: Reconnaissance Instrumentation and Natural Hazard Simulationmentioning

confidence: 99%

Research Needs, Challenges, and Strategic Approaches for Natural Hazards and Disaster Reconnaissance

Wartman

Berman

Bostrom

et al. 2020

Front. Built Environ.

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Section: Reconnaissance Instrumentation and Natural Hazard Simulationmentioning

confidence: 99%

Research Needs, Challenges, and Strategic Approaches for Natural Hazards and Disaster Reconnaissance

Wartman

Berman

Bostrom

et al. 2020

Front. Built Environ.

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“…An important step toward effective community resilience planning is developing the decision-making tools required to evaluate mitigation strategies for reducing the direct and indirect losses and accelerate the recovery. McAllister et al (2019) discussed data, information, and tools that are necessary for community resilience planning and decision-making identifying current advancements as well as research gaps and path forward addressing them. An important note from this report relates to the existing analytical tools for resilience planning and the fact that they largely focus on mitigation plans, while recovery models that account for the interdependencies between different systems in a community are needed.…”

Section: Introductionmentioning

confidence: 99%

“…McAllister et al. (2019) also pointed out that analytical tools are needed to assess the effect of resilience improvement plans and their impact on the built environment, businesses, organizations, and population, as well as risks and benefits for community resilience. There exist various studies in the literature connecting resilience to sustainability, which indicates the importance of decisions made for the community (Rafiei & Adeli, 2016; Zavadskas et al., 2017).…”

Section: Introductionmentioning

confidence: 99%

Community resilience assessment via agent‐based modeling approach

Aghababaei

Koliou

2022

Computer aided Civil Eng

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In this paper, a comprehensive community-level model is developed advancing the use of agent-based modeling for the purpose of community resilience planning. Agents to simulate businesses, healthcare system, and people are introduced, which are utilized along with a set of developed agents for the education system, utilities, and households to create an agent-based model of the Centerville testbed subjected to tornado hazards. Resilience measures are also introduced to quantify the resilience of the community and its systems and make it possible to assess various strategies related to pre-disaster preparedness for informed decision-making. The results show the capability of the proposed computational model to capture the complex behaviors and dynamics of interdependent systems within a community and to evaluate the impact of disruptions on the community as well as a series of resilience measures (mitigation strategies) for the purposes of community planning. Therefore, the proposed model and its findings could provide a new tool for interested community stakeholders and decision-makers assessing mitigation strategies to enhance the recovery time and resilience of the community.

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“…Community disaster resilience has to be quantified so that different strategies for its improvement can be compared and evaluated (McAllister et al, 2019). Researchers affiliated with the Multidisciplinary Centre for Earthquake Engineering Research (MCEER) proposed a framework to quantify seismic resilience of a community using a measure of community's function provision over time after an earthquake (Bruneau et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Quantifying Disaster Resilience of a Community with Interdependent Civil Infrastructure Systems

Blagojević¹,

Hefti²,

Henken³

et al. 2021

Preprint

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Disaster resilient civil infrastructure systems are essential for disaster resilient communities. Measuring the resilience of these systems is the first step towards their improvement. This, however, is not easy: civil infrastructure systems are highly complex, operate in different ways, and are affected differently in different disasters. Adding to the complexity are the interdependencies among different systems. The Re-CoDeS framework for quantifying disaster resilience measures the lack of resilience of a system (e.g., a community) as the amount of the system’s unmet demand for a considered resource or service over the resilience assessment interval. This paper extends the Re-CoDeS framework by considering component interdependencies using a demand/supply approach: whenever the demand of a component is not met by the currently available supply capacity of the system, that component ceases to operate and its supply capacity decreases. Interdependency relations among components can change during the resilience assessment interval as the components’ functionality recovers following a disaster. The proposed iRe-CoDeS framework is demonstrated on a virtual community served by three interdependent civil infrastructure systems producing five types of resources and services.

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Data, information, and tools needed for community resilience planning and decision-making

Cited by 14 publications

References 5 publications

Research Needs, Challenges, and Strategic Approaches for Natural Hazards and Disaster Reconnaissance

Research Needs, Challenges, and Strategic Approaches for Natural Hazards and Disaster Reconnaissance

Community resilience assessment via agent‐based modeling approach

Quantifying Disaster Resilience of a Community with Interdependent Civil Infrastructure Systems

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