Robustness of road systems to extreme flooding: using elements of GIS, travel demand, and network science

The main objective of this article is to study the robustness of road networks to extreme flooding events that can negatively affect entire regional systems in a relatively unpredictable way. Here, we adopt a deterministic approach to simulate extreme flooding events in two cities, New York City and Chicago, by removing entire sections of road systems using U.S. FEMA floodplains. We then measure changes in the number of real trips that can be completed (using travel demand data), Geographical Information Systems properties, and network topological indicators. We notably measure and discuss how betweenness centrality is being redistributed after flooding. Broadly, robustness in spatial systems like road networks is dependent on many factors, including system size (number of nodes and links) and topological structure of the network. Expectedly, robustness also depends on geography, and cities that are naturally more at risk will tend to be less robust, and therefore the notion of robustness rapidly becomes sensitive to individual contexts.