Probabilistic resilience model for management of road infrastructure systems subject to flood events

Abstract

Road infrastructure systems play a critical role in economic development by facilitating access to markets, jobs, and social services. However, they are vulnerable to various natural hazards and threats, which have caused infrastructure failures and significant economic losses in the past. As a result, there is an increasing awareness of building more resilient transportation systems. This paper addresses the challenge of modeling and assessing the risk and resilience of road infrastructure systems for optimal decision-making. This is facilitated by the generic system modeling framework for decision analysis proposed in Faber et al. (2017), which accounts for both the generation of benefits and losses. By utilizing this scenario-based modeling approach, it is possible to gain a thorough understanding of the infrastructure failures that have the most significant impact on the expected total consequences at the road network level. Moreover, the application of the modeling framework enables the comparison of different decision alternatives, such as decisions on the level of preparedness and decisions on the percentage of benefit to be saved as reserves. The modeling approach is illustrated for a roadway network with bridges as the most vulnerable assets. The effect of climate change on the probabilistic life-cycle performance of the bridge network is investigated, and the probability of resilience failure is assessed through the event where reserves are insufficient for re-establishing the functionality of the transportation systems after a flood event.