Marlon Vieira Passos, Karina Barquet, Jung-Ching Kan, Georgia Destouni, Zahra Kalantari

Undertaking systemic risk assessments of critical infrastructures (CIs) is necessary to improve understanding, mitigate impacts, and increase resilience to cascading effects of intensifying hydrometeorological hazards. This paper presents a novel quantitative approach for simulating local physical interdependencies between multiple infrastructure sectors that may be disrupted by floods. Open-source
infrastructure datasets and proximity-based rules were used to generate a network graph of interdependencies, directed from critical service providers to users. The infrastructure model comprised five subnetworks: power, water, telecommunications, emergency, and transport. Stakeholder participation was incorporated in the model to assign interdependency weights according to perceived critical sector importance. Local
(node-edge) resilience metrics were computed to identify critical, vulnerable, and non-redundant CIs in the network. For infrastructures located in areas under risk of floods, global resilience metrics (for whole-network degradation) evaluated failure propagation. The approach was tested in a case study of Halmstad municipality, Sweden, with a
history of extreme hydrometeorological events. Results identified key power, water, and communication infrastructures with high disruption potential under flood exposure, as well as specific residential and industrial areas near hazard zones being the most vulnerable due to their extensive dependencies. Implications, limitations, and recommendations for further research for local climate adaptation planning are provided.