| Sumario: | Flooding can affect every aspect of our lives and road transportation is not an exception. However, the interaction between floods and transportation was not investigated closely in the past. As transportation is the lifeline of any economy, it is essential to analyse potential dangers and threads that can lead to network capacity restraints. Considering the potential of flooding to affect large areas for long durations, disruptions to transportation can result in extensive knock-on effects. To examine how flooding can impact road transportation a novel methodology was developed into a software tool which integrates flood and traffic models. The flood is simulated with InfoWorks flood model and the traffic is represented by a detailed microscopic model (SUMO), which simulates individual vehicles and their interactions. Comparing normal (dry) traffic scenario with a flooded one yields the impacts of flooding on traffic (travelled distance and time, fuel consumption and CO 2 emissions, maps of speed changes on the roads). The results indicated that delays persist long after the perturbations of flooding have subsided and that durations of trip delays are extremely long in some cases whereas distance impacts are typically negligible. Major knock-on effects on the system indicated that even not flooded critical infrastructure should be considered in flood analysis, as their services may be indirectly impacted by the flood conditions. Although substantial, the impacts proved challenging to monetise as time delays are spread around many drivers and some trips (such as delay to a doctor's trip to the hospital) can have significant, but intangible consequences. • Performed a dynamic integration between flood and road transportation models. • Impacts on the traffic system are estimated as the difference between normal and flooded conditions. • The impacts are assessed as the additional travel delays, travel distance, fuel consumptions and greenhouse gas emissions. • Maps of average speed reductions during flooding highlights the most vulnerable areas in a study area. • Results suggest that the knock-on effect of the capacity reductions is overarching in both time and space.
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