Abstract
Regional hurricane risk is often assessed assuming a static housing inventory, yet a region’s housing inventory changes continually. Failing to include changes in the built environment in hurricane risk modeling can substantially underestimate expected losses. This study uses publicly available data and a long short-term memory (LSTM) neural network model to forecast the annual number of housing units for each of 1,000 individual counties in the southeastern United States over the next 20 years. When evaluated using testing data, the estimated number of housing units was almost always (97.3 % of the time), no more than one percentage point different than the observed number, predictive errors that are acceptable for most practical purposes. Comparisons suggest the LSTM outperforms ARIMA and simpler linear trend models. The housing unit projections can help facilitate a quantification of changes in future expected losses and other impacts caused by hurricanes. For example, this study finds that if a hurricane with similar characteristics as Hurricane Harvey were to impact southeast Texas in 20 years, the residential property and flood losses would be nearly US$4 billion (38 %) greater due to the expected increase of 1.3 million new housing units (41 %) in the region.
Highlights
Probabilistic regional hurricane risk assessments typically have been static, where the hazard is modeled as stationary and the built environment is considered to be unchanging
The projected changes in housing units assume that past housing development behavior will carry into the future
7.2 Conclusions The recommended REACH20 model advances the field of hurricane risk modeling by producing the first known dataset of county-level annual housing inventory projections over a multi-decade period and multi-state region
Summary
Probabilistic regional hurricane risk assessments typically have been static, where the hazard is modeled as stationary and the built environment is considered to be unchanging. The number, locations, and types of buildings exposed to hurricanes change continually over time in ways that can alter risk. In Harris County, Texas, home to Houston, for example, the population grew 36 % from 2000 to 2020 (U.S Census Bureau, 2020a). Such a transformation could have a large effect on hurricane risk.
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