Probabilistic framework for quantifying infrastructure systems’ resilience against floods

Abstract

ABSTRACT This manuscript proposes a probabilistic framework to quantitatively assess communities’ resilience by simulating the state and serviceability of their infrastructure systems from the onset of a flood until the end of recovery. It comprises multiple interconnected models. Hazard model characterizes flood parameters (e.g., depth and velocity). Depth-damage curves estimate the damage to infrastructure systems’ components. The HEC-FIA mortality model characterizes the flood-induced casualties. Serviceability models determine the ability of interdependent infrastructure systems to meet the demand during the recovery process. The recovery models estimate the recovery duration and cost of damaged components probabilistically. The Monte Carlo analysis is employed to consider multiple relevant uncertainties, generating distributions of the flood-induced losses under various scenarios. The ratio of total losses to the gross regional product characterizes the community’s resilience. This framework facilitates the assessment of the impact of various resilience enhancement measures, guiding the selection of appropriate measures through a cost-benefit analysis.