Statistical and Spatial Analysis of Hurricane-induced Roadway Closures and Power Outages

Mahyar Ghorbanzadeh,Reza Arghandeh Jouneghani,Mohammadreza Koloushani,Mehmet Baran Ulak,Eren Erman Ozguven

doi:10.3390/en13051098

Abstract

Hurricanes lead to substantial infrastructure system damages, such as roadway closures and power outages, in the US annually, especially in states like Florida. As such, this paper aimed to assess the impacts of Hurricane Hermine (2016) and Hurricane Michael (2018) on the City of Tallahassee, the capital of Florida, via exploratory spatial and statistical analyses on power outages and roadway closures. First, a geographical information systems (GIS)-based spatial analysis was conducted to explore the power outages and roadway closure patterns in the city including kernel density estimation (KDE) and density ratio difference (DRD) methods. In order to provide a more detailed assessment on which population segments were more affected, a second step included a statistical analysis to identify the relationships between demographic- and socioeconomic-related variables and the magnitude of power outages and roadway closures caused by these hurricanes. The results indicate that the high-risk locations for roadway closures showed different patterns, whereas power outages seemed to have similar spatial patterns for the hurricanes. The findings of this study can provide useful insights and information for city officials to identify the most vulnerable regions which are under the risk of disruption. This can lead to better infrastructure plans and policies.

Highlights

The United States is among the five countries hit the hardest by natural disasters over the last decade [1]
In order to understand how the impacts of Hermine and Michael were different for the city and to assess the differences in the areas affected by roadway closures and power outages, density ratio difference (DRD) metric to assess the differences in the areas affected by roadway closures and power outages, DRD metric values were obtained for both closures andand outages
Spatial analysis was conducted via a series of spatial analytic methods to explore the power outages and roadway closures patterns including the kernel density estimation (KDE) and the DRD methods

Summary

Introduction

The United States is among the five countries hit the hardest by natural disasters over the last decade [1]. According to the Federal Emergency Management Agency (FEMA), there have been 3728 nationally declared disasters between 1953 and 2018 in the US, including fires (1054), severe storms (923), floods (786), hurricanes (341), and tornadoes (164) [2]. FEMA suggests that, without considering efficient plans, these disasters will have more long-term impacts on communities as well as the economy [2]. Among these hazards, hurricanes, such as the Hurricane Hermine (2016), Hurricane. The State of Florida has been exposed to 39 hurricanes, 22 severe storms, and 13 flooding cases since Irma (2017), and Hurricane Michael (2018), have caused substantial infrastructure system damages, such as roadway closures and power outages, in the US, especially in the State of Florida [5,6].

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