Probabilistic Resilience-Guided Infrastructure Risk Management

Abstract

The increased frequency and magnitude of natural and anthropogenic hazard events that affected infrastructure systems over the past two decades have highlighted the need for more effective risk management strategies. Such strategies are expected to not only manage the immediate disruption to system's functionality following hazard realization, but to also mitigate the latter's extended-term consequences (e.g., recovery cost and restoration time), which would otherwise be disastrous. To yield realistic managerial insights, such resilience-guided risk management necessitates accounting for the different sources of uncertainties associated with both the hazard quantification and the response of the infrastructure being considered. Through considering such uncertainties, the probabilistic resilience quantification framework developed in this study is expected to provide valuable managerial insights to guide resource allocations for both pre-and posthazard realization. The applicability of the framework is demonstrated on a simplified system subjected to different anthropogenic hazard scenarios. Beyond the presented case study, the developed framework lays the foundation for adopting probabilistic resilience quantification to guide the next-generation risk management processes of infrastructure systems under different forms of natural and anthropogenic hazards.

Revealing indirect risks in complex socioeconomic systems: A highly detailed multi‐model analysis of flood events in Austria

“…This reduces the need for policy interventions and costs in the long-term. Examples of the application of the concept of resilience are Kurth et al (2020), who demonstrate how the lack of resilience of transport network translates into economy-wide losses, Salem et al (2020), who develop a probabilistic resilience quantification framework for infrastructure management or De Bruijn (2004), who develops indicators for the resilience of flood risk management.…”

Data-Driven Community Flood Resilience Prediction

“…However, flood risk needs first to be quantified in order to efficiently develop better mitigation strategies and eventually enhance resilience. In this respect, flood risk is identified as the expected damage (i.e., consequence), resulting from a hazard's probability of occurrence, coupled with the atrisk-community's exposure and vulnerabilities, considering different uncertainties [11][12][13].…”

“…Flood risk is a result from the simultaneous realization of three aspects: (i) flood hazard: the potential, or probability, of a flood event of certain characteristics occurring at a given location, (ii) flood vulnerability: a measure of the susceptibility, and the adaptability, of the exposed community to the flood hazard, and finally (iii) flood exposure: the assets, humans, and otherwise (i.e., infrastructure systems) that are located in a flood-prone area [11,13,15]. This indicates that a severe flood hazard does not necessarily yield a high-risk flood, as it can occur in an area with a low number of exposed elements, but flood risk can be quantified only when the exposed and vulnerable community prone to said hazard is coupled with the hazard realization [12,15]. As an extension, resilience analysis evaluates the extended functionality loss and recovery trajectory of communities prone to flood hazards, taking into account the direct and indirect losses as well as restoration costs [5,12].…”

“…This indicates that a severe flood hazard does not necessarily yield a high-risk flood, as it can occur in an area with a low number of exposed elements, but flood risk can be quantified only when the exposed and vulnerable community prone to said hazard is coupled with the hazard realization [12,15]. As an extension, resilience analysis evaluates the extended functionality loss and recovery trajectory of communities prone to flood hazards, taking into account the direct and indirect losses as well as restoration costs [5,12].…”

Management of Resilience in Civil Infrastructure Systems: An Interdisciplinary Approach

“…Seven articles accepted for this special collection focus on the assessment of resilience to support decision-making processes for infrastructure planning and management. Salem et al (2020) proposed a probabilistic resilience assessment framework to incorporate uncertainties related to both disruptive events and the response of an infrastructure system to quantify its resilience. Within this framework, the authors used probabilistic variables to consider the uncertain nature of the functionality loss of an infrastructure system and its recovery time in different postdisaster scenarios.…”