4.7 Article

A Simulation-Based Framework for Earthquake Risk-Informed and People-Centered Decision Making on Future Urban Planning

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EARTHS FUTURE
卷 10, 期 1, 页码 -

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AMER GEOPHYSICAL UNION
DOI: 10.1029/2021EF002388

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  1. UKRI GCRF [NE/S009000/1]
  2. NERC [NE/S009000/1] Funding Source: UKRI

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Numerous approaches to earthquake risk modeling have been proposed, but most focus on current static exposure and vulnerability, limiting their use in decision-making for future urban landscapes. We present an end-to-end risk modeling framework that addresses this challenge by considering future earthquake risks using a simulation-based approach. The framework also advances the state-of-practice in risk modeling by integrating physical and social impacts and incorporating a participatory approach to decision-making.
Numerous approaches to earthquake risk modeling and quantification have already been proposed in the literature and/or are well established in practice. However, most of these procedures are designed to focus on risk in the context of current static exposure and vulnerability, and are therefore limited in their ability to support decisions related to the future, as yet partially unbuilt, urban landscape. We propose an end-toend risk modeling framework that explicitly addresses this specific challenge. The framework is designed to consider the earthquake (ground-shaking) risks of tomorrow's urban environment, using a simulation-based approach to rigorously capture the uncertainties inherent in future projections of exposure as well as physical and social vulnerability. The framework also advances the state-of-practice in future disaster risk modeling by additionally: (a) providing a harmonized methodology for integrating physical and social impacts of disasters that facilitates flexible characterization of risk metrics beyond physical damage/asset losses; and (b) incorporating a participatory, people-centered approach to risk-informed decision making. The framework is showcased using the physical and social environment of an expanding synthetic city. This example application demonstrates how the framework may be used to make policy decisions related to future urban areas, based on multiple, uncertain risk drivers.

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