Collaborative Research: Modeling Post-Disaster Housing Recovery Integrating Performance Based Engineering and Urban Simulation

点击翻译按钮获取中文摘要

Following natural disasters in the United States, federal, state and local government officials must facilitate the recovery of the functionality and well-being of the affected communities. The housing sector plays a vital role in recovery because schools, businesses, neighborhoods and community-based organizations all rely on residents having healthy living conditions so that they can remain in the affected region. Existing disaster risk modeling methods are not able to adequately represent the housing recovery process and its long-term impacts to communities. This project will address this problem by developing and applying new data and computer model methods to simulate post-disaster housing recovery. The computer model will enable policy-makers and planners to quantify the benefits and tradeoffs associated with possible pre- and post-disaster housing interventions. They will be able to explore potential scenarios for various future hazard events towards the goal of enhancing housing recovery after disasters in the United States. To facilitate technology transfer to other researchers and disaster risk managers, the computer model and data from this project will be free, open source, and available over the World Wide Web. The research will provide training for a doctoral student and an opportunity to teach undergraduate students from different backgrounds about the role of science and engineering in improving the resilience of communities to natural disasters.We will investigate key questions related to housing recovery using a post-disaster recovery simulation model that integrates building performance information and homeowner decision making over space and time. The three main components of the research are (1) a probabilistic model that computes building damage using data about loss of functionality, habitability, and repairability (2) a model that quantifies the influences and uncertainty associated with homeowners' decisions whether to repair, reoccupy, sell, or abandon damaged homes based on the extent of damage, demographics, neighborhood conditions, and utility services and (3) a simulation of post-disaster housing recovery, that accounts for the influences of building, homeowner, and resource attributes, such as housing stock and population movement. We will apply the simulation model to a large urban jurisdiction for the purposes of (a) evaluation, (b) hypothesis testing, (c) and assessing potential policies and other interventions for enhancing recovery. The project will further the science in performance-based engineering and urban modeling to facilitate experiments for examining the geographic effects of post-disaster residential building functionality and housing occupancy.