A multiplex network-based framework to assess interdependent infrastructure asset criticality and priority under natural hazard scenarios

Critical infrastructure, such as energy, telecommunication and healthcare systems face increasing risks from natural hazards. At the same time, their resilience management is becoming increasingly challenging due to their complexity, the existence of interdependencies between them and resource constraints, which necessitate asset-level prioritization approaches. This study addresses these challenges by introducing a decision-support framework for ranking assets in interdependent infrastructure systems according to their criticality and priority to natural hazard scenarios. Criticality considers the extent of impacts across multiple dimensions, while priority additionally considers the exposure of assets to hazard scenarios and their vulnerability, assessed through functionality thresholds. We introduce a node-weighted directed multiplex network model of the interdependent infrastructure system, where nodes represent infrastructure assets, links their interactions, and layers different types of these interactions. Accordingly, potential cascading effects across systems, different types of infrastructure interdependencies and multiple criticality dimensions are considered. The application of the framework is demonstrated in a semi-hypothetical case study of flood hazard in Torbay, UK. Five infrastructure systems, three interdependency types and three criticality dimensions were considered. Accordingly, the highest-ranked assets according to the introduced indices belong predominantly to the electricity and telecommunications networks, which have the potential to cause the widest systemic effects. The introduced framework is intended as an adaptable decision-support heuristic, providing a structured approach for infrastructure asset criticality assessment and scenario-based prioritization.