Abstract
The common challenge currently faced by critical infrastructure (CI) asset owners and operators is the lack of an integrated and robust resilience-informed business planning and management approach in response to interdependent assets’ failures, in particular due to low-probability/high-impact environmental hazards.
Interdependencies among CI can cause cascading failures and hence, amplify impacts due to these failures. This can also affect CI’s service restoration rate and consequently, reducing their resilience in coping with these hazardous events. As infrastructures are becoming more interdependent in some sectors, there is an increasing need for better management of the interactions and interdependencies.
To reduce these impacts, an integrated resilience and vulnerability- informed Decision Support System (DSS) is required to identify interdependent network’s vulnerable components and introduce adaptive capacities accordingly. This is of particular importance given ever growing investments in asset management across different sectors in order to improve the resilience of the networks in response to extreme environmental hazards.
This study presents a novel framework for building a resilience and vulnerability-informed decision support system (RV-DSS). This framework provides potential means of communicating challenges induced due to interdependencies and quantifies benefits of considering interdependencies in streamlining intervention strategies for systems. It also proposes a measure of network resilience in response to hazardous events, in addition to the commonly used measures of vulnerability for assessment of the network performance. The framework can be used in initiating the interdependency-based communications among different CI network owners and managers, leading to shared knowledge and common understanding of their connected assets, hidden failure propagation mechanisms and collective recovery process. The application of the framework is then demonstrated using a case study in North Argyll, Scotland. It is quantitatively demonstrated that although infrastructures with a higher level of interdependency, can impose the network to higher vulnerability, it provides a greater opportunity for an integrated recovery