A novel end-user-oriented approach to dynamic post-disaster resilience quantification for individual facilities

Abstract

Community recovery from a disaster is a complex process, in which the importance of different types of infrastructure functionality can change over time. For instance, sheltering facilities can be critical in the immediate post-disaster phase, but play a declining role over the longer-term recovery period. On the other hand, the successful functionality of educational institutions may become important only at the end of any emergency response period. Most of the myriad of metrics available for measuring disaster resilience do not capture the dynamic importance of functionality explicitly, however. This means that very different recovery trajectories of a given infrastructure can correspond to the same resilience value, regardless of variations in its utility over time. While some efforts have been made to integrate features of time dependency into individual facility (i.e., component-level) resilience quantification, the resulting metrics either capture only a limited set of temporal instances throughout the post-disaster response and recovery process or do not offer a way to prioritize time steps in line with variations in the importance of facility functionality. This study proposes a novel yet straightforward metric for component-level post-disaster resilience quantification that overcomes the aforementioned limitations. The metric involves a dynamic weighting component that allows stakeholders to place varying emphasis on different temporal points throughout the recovery process. The end-user-centered approach to resilience quantification facilitated by the metric allows for flexible, context-specific interpretations of infrastructure functionality importance that may vary across different communities. After presenting the metric, we demonstrate it through a hypothetical case study of infrastructure facilities with varying degrees of importance across the post-disaster recovery period, and showcase its versatility relative to a previously well-established measurement of component-level resilience. As the case-study demonstration underlines, the proposed metric has significant potential for use in stakeholder-driven approaches to decision making on critical infrastructure (as well as other types of built environment) recovery and resilience.