Journal
SCIENCE ADVANCES
Volume 6, Issue 32, Pages -Publisher
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/sciadv.aba2423
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Funding
- UPS Endowment Fund
- NSF through the Office of Polar Programs [PLR-1744758, PLR-1739027]
- Stanford Graduate Fellowship
- Haas Center for Public Service
- School of Earth, Energy and Environmental Sciences
- Department of Civil and Environmental Engineering
- Institute for Computational and Mathematical Engineering
- Center for Sustainable Development and Global Competitiveness
- Stanford Professionals in Real Estate
- Dawe family
- Woods Institute for the Environment
- Stanford's Bill Lane Center for the American West
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As sea level rises, urban traffic networks in low-lying coastal areas face increasing risks of flood disruptions. Closure of flooded roads causes employee absences and delays, creating cascading impacts to communities. We integrate a traffic model with flood maps that represent potential combinations of storm surges, tides, seasonal cycles, interannual anomalies driven by large-scale climate variability such as the El Nino Southern Oscillation, and sea level rise. When identifying inundated roads, we propose corrections for potential biases arising from model integration. Our results for the San Francisco Bay Area show that employee absences are limited to the homes and workplaces within the areas of inundation, while delays propagate far inland. Communities with limited availability of alternate roads experience long delays irrespective of their proximity to the areas of inundation. We show that metric reach, a measure of road network density, is a better proxy for delays than flood exposure.
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