Impacts of weather-related road closures on daily habitual travel in North Carolina

Julia Cardwell, Paul L. Delamater and Charles E. Konrad

Journal of Transport Geography, 2024, vol. 121, issue C

Abstract: Weather-related road closures have the potential to cause serious impacts to society by disrupting road network function. Impacts to the population are variable based on the temporal and spatial extent of the closures, as well as the ability of the road network to absorb the impacts of closures by offering suitable alternative routes. In general, analyses of the impacts of weather-related road closures have focused on short-term, major events, such as hurricanes. There has been little focus on the ability for weather-related disruptions of varying size and severity (from localized tree fall to major hurricanes) to cause cumulative impacts to the population over longer time scales. This analysis considers daily impacts to free-flow travel time by employing an adjusted graph theory approach that also considers demand to more effectively analyze travel time impacts. In particular, this study uses mobility data to determine “habitual travel” for each census block group in the state, which allows for consideration of weather-related travel time impacts based on regularly occurring trips. We conduct a case study in North Carolina over the period of 2016–2023. Results indicate that although major events (such as Hurricane Matthew and Florence) represent the days with the most intense travel time disruptions, much of the state has experienced more than 30 days of travel-time disruption due to weather-related closures. Ultimately, rural areas of the state, especially the southeast coastal plain and the far western area of the state, emerge as the most impacted regions, which exposes potential vulnerabilities, especially considering the expected increase of weather-related road closures due to climate change.

Keywords: Extreme weather; Graph theory; Road network disruption (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jotrge:v:121:y:2024:i:c:s0966692324002527

DOI: 10.1016/j.jtrangeo.2024.104043

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