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 Niño 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.

Natural hazards have always shaped our planet, but global climate change alters the nature of the risk they pose. Climate change is expected to both intensify existing hazards and create new, previously unknown types of hazards (Oppenheimer et al., 2014). Even when the nature of the new threat is known, such as in the case of rising sea level, there is deep uncertainty associated with the overall magnitude of the hazard

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As sea levels rise, urban traffic networks in low-lying coastal areas face an increasing risk offlood disruption and commute delays. We hypothesize that road network connectivity rather than flood exposure governs commute delays. We integrate an existing traffic model with flood maps to identify inundated roads, simulate traffic patterns, and quantify commute delays. When identifying inundated roads, we demonstrate potential biases arising from the model integration and propose appropriate refinements, such as incorporating road geometry and elevation data, and identifying small-scale topographical features like road-creek crossings. Our results for the San Francisco Bay Area show commute delays propagate far inland, creating longer commute delays for inland communities with low road network connectivity than for communities near the flood zone. We show that metric reach, a measure of road network connectivity, is a better proxy for quantifying the resilience of a community to flood-related commute delays than flood exposure.