Integrating Complex Climate Hazard Modeling and Travel Demand Modeling

Keywords: Climate Resilience, Resiliency, Hazards, Modeling, Transportation Networks, Extreme Events, Flooding
Abstract Type: Paper Abstract

Abstract

Embedding climate resilience into transportation networks is an utmost priority, given the speed and stochasticity in which extreme hazard events are occurring. Increasingly, transportation planners and engineers are attempting to best understand how hazards affect their networks. Traditional approaches that focus on one hazard independently from others often have been found lacking during analyses of extreme events, which tax transportation networks in often unanticipated ways. Thus, there is an emerging sense that a useful analytical climate resilience framework needs to include two complex considerations: 1) Multiple simultaneous extreme events which cascade through a network; and 2) advanced modeling which estimates how these events disrupt interconnected transportation networks.

For a coastal state transportation agency, we have developed a pilot project which seeks to model both multiple, simultaneously occurring extreme hazard events and integrates these outcomes with the agency’s travel demand model (TDM) and other new models, which then provides resilience intelligence on how such compounding events affect the transportation networks. Broadly, our approach in this pilot focuses on three flooding hazards: Sea level rise (SLR), high tide flooding (HTF), and extreme rainfall events. Importantly, our approach also considers the transportation networks as several interlocking, related networks. Our criticality analysis treats the pilot study area’s transportation system as a network comprised of hubs and corridors comprised as a traditional TDM, a freight network, a rail and transit network, related infrastructure (e.g., electrical grid) networks, emergency routes, and evacuation routes.