U017-07
When Floods Hit the Road: Resilience to Flood-Related Traffic Disruption in the San Francisco Bay Area and Beyond

Tuesday, 15 December 2020: 05:53
Indraneel Kasmalkar1, Katherine Serafin2,3, Yufei Miao4, Ian Avery Bick4, Derek Ouyang3, Leonard Ortolano4 and Jenny Suckale3,4, (1)Stanford University, Institute of Computational and Mathematical Engineering, Stanford, CA, United States, (2)University of Florida, Department of Geography, Ft Walton Beach, FL, United States, (3)Stanford University, Department of Geophysics, Stanford, CA, United States, (4)Stanford University, Department of Civil and Environmental Engineering, Stanford, CA, United States
Abstract:
The San Francisco Bay Area is known for its high levels of traffic congestion. Extreme flood events have the added potential to inundate low-lying coastal roads, causing further disruption to traffic networks. Flood-induced traffic disruption in this region can cause loss of wages and jobs for individuals, economic costs for businesses, and increases to road accidents and loss of life. A rising sea level will continue to increase the frequency and intensity of coastal flood events over the coming decades.

The goal of our study is to understand changes in traffic patterns in the San Francisco Bay Area caused by coastal flooding and sea level rise, and to quantify the traffic disruption in the form of employee absences and travel time delays. We integrate a traffic model with a set of regional flood maps to simulate Bay Area morning peak hour traffic patterns under flood conditions. The flood maps represent extreme water levels resulting from potential combinations of storm surges, tides, seasonal cycles, interannual anomalies driven by large-scale climate variability such as the El Niño Southern Oscillation, and sea level rise. Our work details the requirements and challenges of integrating flood maps with traffic models, especially the importance of representing roads with accurate geometry and elevation to avoid overestimation of flooding.

Our results highlight the spatially extensive impacts of coastal flooding, where inundated roadways in the immediate vicinity of the Bay can disrupt traffic patterns far inland, even in communities with no direct flood exposure. We show that regions with high availability of alternate roads are resilient to flood-related traffic disruption because the alternate roads can offset road closures and mitigate the resulting increases in congestion. We propose a simple graph-theoretic metric, metric reach, to estimate the availability of alternate roads and thus quantify the resilience of regions to flood-related traffic disruption.

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