Spatial and temporal variations in resilience to tropical cyclones along the United States coastline as determined by the multi-hazard hurricane impact level model

Stephanie Pilkington and Hussam Mahmoud ()
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Stephanie Pilkington: Colorado State University
Hussam Mahmoud: Colorado State University

Palgrave Communications, 2017, vol. 3, issue 1, 1-8

Abstract: Abstract The United States coastline, where over 50% the population lives, is vulnerable to hurricanes along the East and Gulf coasts. However, the question remains as to whether these two areas are equally resilient to a landfalling hurricane. In addition, while it is assumed that improvements in building codes, infrastructure protections, and changing policy over the past century have been effective in reducing the impacts to a community from historically extreme hurricane events, such an assumption is still to be validated. Here, a multi-hazard artificial neural network model is used to address these questions. The Hurricane Impact Level Model is the first prediction model to utilize machine-learning techniques (artificial neural networks) to established complex connections between all meteorological factors (wind, pressure, storm surge, and precipitation resulting in inland flooding) of a tropical cyclone and how those interact with the location of landfall to produce a certain level of economic damage. This model allows for a more all-encompassing assessment of how the impacts of tropical cyclones vary along the coastline. The Hurricane Impact Level Model was trained with historical tropical cyclone events from 1998 to present day, resulting in established locational associations to modern relevant building codes and mitigation practices. Simulating the meteorological factors from historical events allows for a new assessment of economic impact changes due to infrastructure improvements and policy adaptations over time. In essence, if Hurricane Sandy hit Florida instead of New York, it would have a lower economic impact due to lower population density and more stringent building codes, which the artificial neural network has associated with the latitudes and longitudes within the state of Florida. If the Galveston hurricane were to hit today, the seawall would not succeed in lowering the economic impact to the Texas coastline. Over the years, significant effort has been put in to improving the resiliency of the United States coastline, mainly in the southern states, but it has not been enough to counteract the effects of population growth within coastal counties.

Date: 2017
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DOI: 10.1057/s41599-017-0016-1

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