Evaluating resilience enhancing interventions for transport networks subjected to floods using simulations: example of flood protection wall

Abstract

This paper presents a high-resolution simulation approach for evaluating the effects of interventions to improve the resilience of transport infrastructure against climate-related hazards. This simulation approach facilitates modeling and evaluation of a broad range of interventions, such as constructing floodwalls to reduce the exposure of road sections to inundation or retrofitting bridge piers to decrease scouring vulnerability. This is achieved through a risk simulation tool which comprises a library of interacting probabilistic models that simulate the: (1) initiation of source events, e.g., heavy rainfall; (2) formation of hazard events, e.g., floods and landslides; (3) physical and functional impacts on individual infrastructure components, as well as their collective performance as a network; and (4) restoration of infrastructure components. The risk is quantified in terms of the ensuing economic consequences, such as restoration costs, and socio-economic consequences, such as costs of increased travel time and loss of connectivity. Finally, through a host of simulated scenarios, resilience improvement interventions are evaluated based on their contribution to reducing the considered risk measures. The probabilistic modeling capability of this tool captures the spatiotemporal uncertainty in source events and its propagation throughout the entire risk estimation, which is unprecedented in literature. This approach is showcased through an application to a transport network located in Switzerland subject to heavy rainfall, flooding, and landslides. The application demonstrates the evaluation of three flood protection wall interventions through multiple scenarios of hazard events. The proposed approach can serve as a decision support tool for infrastructure managers by providing them with a thorough and quantitative evaluation of interventions to better plan and allocate resources.