This research is aimed at developing a quantitative model for measuring regional economic resilience to hurricane hazards. Resilience, being described as a dynamic and complex process, requires measurements at multiple timescales of relevant indicators that include infrastructure reconstruction, mitigation activities, public disaster expenditures, local employment, housing permits, retail sales, and personal income. By integrating atmospheric properties of storms, physical attributes of a region?s built environment and economic characteristics, the proposed model is capable of forecasting the rate of recovery in a local economy at multiple timescales. Key resilience indicators are identified and their effects are estimated with data collected from past events. Because these data are quantifiable and verifiable, we are able to produce a model with enhanced reliability and robustness. Two primary objectives are pursued: 1) model the progress in built environment recovery using remotely sensed image archives; 2) model the rate of economic recovery using time-series data at the Metropolitan Statistical Area level. We are exploring a potentially transformative concept by developing a quantitative model in both economic and physical dimensions of recovery. As the result, a critical knowledge gap between assessing the immediate damage of hurricanes and understanding its broader and lasting impacts could be bridged. The result will afford further numerical evidence for both complementing and strengthening existing theories in urban redevelopment and disaster recovery.
The success of this research has the potential to greatly improve the long term economic well-being of communities in hurricane-prone regions with better designed public policies and investment. The outcomes and methodologies will be introduced as part of graduate curriculum as well as through websites and other academic outlets at both Texas Tech and East Carolina Universities. The project will support doctoral students in Wind Science and Engineering and Coastal Resource Management at two collaborating institutions. These activities will provide valuable training opportunities for graduate and undergraduate students, nurture the next generation of experts in multidisciplinary disaster-focused research, and contribute to the knowledgebase of hazard mitigation. It could also catalyze fundamental changes to help communities become more physically, socially and economically resilient in facing future disasters.
The research project accomplished its goals by proposing a new scale to infer ground building damage more accurately from remote sensing images, developing a method for reconstructing near-surface wind field with building damage survey data; analyzing economic indicators (employment and building permit) following major wind disasters; and tracking the rate of housing reconstruction using remote sensed imagery. The outcomes of the project includes a new scale with 36 states to rate the level of building damage as observed on remote sensing images. Regression models were calibrated and validated and the analysis of goodness-of-fit indicated the new scale outperformed the existing Remote Sensing (RS) and revised RS Scales. A Rankine vortex model was fitted with post-tornado damage survey data to produce a numerical wind field. The result showed consistent agreement between simulated peak wind speeds and observed building damages. In the subsequent months following the windstorms, local communities (metropolitan statistical areas, or MSAs) experienced an increase in building permits to replace buildings that were destroyed. However, the magnitude of increase was fairly small because of a large building inventory not affected by the storm. Meanwhile, employments dropped after the tornado before returning to their long-term trend. As house's damage severity (as measured in Degree of Damage) increased the probability of it being repaired decreased. The same was true if it didn't get repaired quickly after the storm. Factors such demographics, income, and neighboring properties would be further examined through telephone survey. The results from the project can help reducing the impact of future disasters by 1) providing timely and accurate damage assessment in support of response and relief activities; 2) informing structural engineers about near-surface wind characteristics of tornadoes and hurricanes for cost-effective design and safety protection; and 3) advise communities and businesses in wind-prone regions about their risk to windstorms and mitigation strategies. The project provided opportunities to both doctoral students and faculty for performing interdisciplinary research involving engineering, atmospheric science, and economics. It helped to prepare them to take on complex, large-scale problems in the future.
