MobRISK: A Model for Assessing the Dynamic Exposure and Behavioral Responses of Road Users to Flash Flood Events

Flash floods are responsible for a majority of natural disaster fatalities in the USA and Europe and most of them are vehicle-related. If human exposure to flood is generally assessed through the number of inhabitants per buildings located in flood prone zone, it is clear that this number varies dramatically throughout the day as people move from place to place to follow their daily program of activities. Knowing the number of motorists exposed to low water crossings or the factors determining their exposure would allow providing a more realistic evaluation of the degree of exposure, hence the potential vehicle-related human impacts for a given rainfall-runoff scenario. In order to bridge this gap and provide emergency managers with methods to assess the risk level for motorists, this paper describes the development of MobRISK microsimulation system: a model for assessing the exposure of road users to hydro-meteorological events.

Recent advances in transportation research provide an appropriate framework for simulating individual travel-activity patterns using activity-based approach. These activity-based mobility models enable prediction of the sequence of activities performed by individuals and locating them with a high spatial-temporal resolution. MobRISK aims at providing an accurate spatiotemporal exposure assessment by integrating travel-activity behaviors and mobility adaptation with respect to weather disruptions. The model is applied in a flash flood prone area in Southern France to assess motorists' exposure to September 2002 flash flood event. The results show that risk of flooding mainly occurs in principal road links with considerable traffic load. However, a lag time between the timing of the road submersion and persons crossing these roads contributes to reduce the potential vehicle-related fatal accidents. It is also found that socio-demographic variables have significant effect on individual exposure. Thus, the proposed model demonstrates the benefits of considering spatiotemporal dynamics of population exposure to flash floods and presents an important improvement in exposure assessment methods. Such improved characterization of road user exposures can present valuable information for flood risk management services and emergency planning.