Abstract
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. Moreover, the impact of recurrent flooding on populations living in the affected areas is also not clear. To address this problem, this dissertation develops a comprehensive framework that can assess the impact of recurrent flooding on transportation accessibility and investigate the social vulnerability of the population living in the areas with significant impact. This dissertation contains three parts. In the first two parts, the impact of recurrent flooding on auto and transit accessibility are investigated. In the last part, the shifting impact of recurrent flooding on auto accessibility with multiple years of data is examined. This dissertation contributes to the existing literature in the following aspects: 1) develops a comprehensive framework that can assess the impact of recurrent flooding on transportation accessibility at a spatially and temporally disaggregated level, with the aid of crowdsourced data, 2) identifies the affected “hotspot” areas and enables the computation of a social vulnerability index for the populations living in the most affected areas, 3) examines the shift of recurrent flooding impacts across multiple years, including changes in social vulnerability of the highly impacted populations.
Using crowdsourced WAZE flood incident data from the Hampton Roads region in Virginia, the first part of the dissertation examines changes in auto accessibility for travelers residing in 1,113 traffic analysis zones (TAZs) across five time-of-day periods with the gravity model. Furthermore, a social vulnerability index (SVI) framework is developed to understand the socioeconomic characteristics of TAZs that experience high accessibility reduction under recurrent flooding. Results show that individual TAZs experience the most accessibility reduction under recurrent flooding during the morning peak period, ranging from 0% to 49.6% for work trips (with population weighted mean reduction of 1.71%) and 0% to 87.9% for non-work trips (with population weighted mean reduction of 0.81%). 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 flooding’s impacts on accessibility. Furthermore, the social vulnerability analysis showed that zones with higher percentages of lower socio-economic status, unemployed, less educated, and limited English proficiency residents experience higher accessibility reduction for work trips. These results highlight 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.
The second part of the dissertation considers the impact of recurrent flooding on transit service accessibility, also using spatially and temporally disaggregated crowdsourced flood incident data from WAZE. Ten fixed route transit networks are built for five time-of-day periods for 710 traffic analysis zones (TAZs) served by transit in the Hampton Roads region, to capture the spatial and temporal variation of transit accessibility reduction due to recurrent flooding. Study results show that the greatest transit accessibility reduction occurs during the morning peak hour, with individual TAZ transit accessibility reduction ranging from 0 to 88.2% for work trips (with an average of 6.4%) and ranging from 0 to 99.9% for non-work trips (with an average of 3.7%). Furthermore, social vulnerability analysis indicates that TAZs with a greater share of people with higher vulnerability in transportation and socio-economic status are more likely to experience recurrent flooding-induced transit accessibility reduction. Results from this second part of the study reinforce the notion that transportation impacts under recurrent flooding are not uniformly experienced throughout a region, and this spatial and temporal variation translates to different impacts borne by various population groups. In the case study region, populations are reliant on transit are experiencing the worst impacts of transit accessibility reduction under recurrent flooding. Disaggregate impact analysis like this study can support transportation engineers and planners to prioritize resources to ensure equitable transit accessibility under increasing climate disruptions.
The last part of the dissertation examines the shifting impacts of recurrent flooding on auto accessibility using crowdsourced WAZE flood report data during the month of August from 2018 to 2022, to identify “hotspots” in the Hampton Roads region with high frequency of significant accessibility reduction for both work and non-work travel purposes. Results show that 12% and 3% of the region’s population live in hotspots experiencing significant accessibility reduction from recurrent flooding for work and non-work trips, respectively. The city of Norfolk is a common “hotspot” for residents who experience both work and non-work accessibility reduction. Social vulnerability analysis revealed that populations more vulnerable in socio-economic status and transportation are more susceptible to recurrent flooding-induced accessibility impacts in terms of both extent and frequency. The comparison of social vulnerability indices (SVIs) indicates between 2016 and 2021, the situation is deteriorating where socially vulnerable groups (particularly those with low income) have limited ability to relocate away from the highly impacted areas. This study reinforces the importance of spatially and temporally disaggregated studies of climate event impacts, and provide evidence that social inequities of climate events need to be assessed dynamically and over time.
Overall, this dissertation develops a framework to assess the spatially and temporally heterogeneous impacts of recurrent flooding on transportation system accessibility with the aid of crowdsourced data. The dissertation also investigates the accessibility impact of recurrent flooding on local socially vulnerable populations and the changing demographics over time. The framework can be applied to other cities and regions as crowdsourced WAZE data is easily accessible. Furthermore, the framework can be integrated into a greater system for smart city management. The output of the framework can support city planners and policymakers for both short-term decisions making or long-term infrastructure planning, and enhance transportation system resilience under climate change.
