Assessing The Spatially Heterogeneous Transportation Impacts of Recurrent Flooding in The Hampton Roads Region: Part 1 Auto Accessibility

arxiv(2024)

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摘要
Recurrent flooding has increased rapidly in coastal regions due to sea level rise and climate change. A key metric for evaluating transportation system degradation is accessibility, yet the lack of temporally and spatially disaggregate data means that the impact of recurrent flooding on accessibility, and hence transportation system performance: is not well understood. Using crowdsourced WAZE flood incident data from the Hampton Roads region in Virginia, this study (Part 1) examines changes in the roadway network accessibility for travelers residing in 1,113 traffic analysis zones (TAZs) across five time of day periods. Additionally, a social vulnerability index framework is developed to understand the socioeconomic characteristics of TAZs that experience high accessibility reduction under recurrent flooding. Results show that TAZs experience the most accessibility reduction under recurrent flooding during the morning peak period (6 to 9am) with large differences across different zones, ranging from 0 to 49.6 (percentage) for work trips (with population weighted mean reduction of 1.71 percent) and 0 to 87.9 (percentage) for nonwork trips (with population weighted mean reduction of 0.81 percent). Furthermore, the social vulnerability analysis showed that zones with higher percentages of lower socioeconomic status, unemployed, less educated, and limited English proficiency residents experience greater accessibility reduction for work trips. In contrast to previous studies that aggregate the effects of recurrent flooding across a city, these results demonstrate that there exists large spatial and temporal variation in recurrent floodings impacts on accessibility. This study also highlights the need to include social vulnerability analysis in assessing impacts of climate events, to ensure equitable outcomes as investments are made to create resilient transportation infrastructure.
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