The stability of modern economies relies on the uninterrupted supply of electricity, heat, and transport fuels, making the energy sector highly exposed to various risks and disruptions, including floods, which are among the major natural hazards affecting energy infrastructure in Poland. Despite risks, a scalable and integrated modelling framework for operational flood risk management in energy infrastructure is still lacking. Such a framework should account for increasing climate-related hazard dynamics, integrate robust fragility and damage models with comprehensive flood risk assessments at both asset and system levels, and explicitly consider interdependencies among energy system components and associated critical infrastructure. This integration is essential for analyzing cascading failures and their consequences, while complying with the EU CER Directive requirements for resilience and continuity of critical infrastructure services. An original three-stage spatial vulnerability analysis method was developed, involving GIS data preparation, classification of asset importance, and flood scenario modelling, demonstrated on selected rivers in the Odra River basin. The Expected Damage Factor (EDF) metric was applied to combine flood probability with infrastructure significance. The analysis enabled spatial identification of the most vulnerable components of the energy system and illustrated the dynamics of threats in time and space. The EDF coefficient allowed for quantitative vulnerability assessment, supporting more precise adaptive planning. The approach innovatively combines infrastructure criticality assessment with probabilistic flood scenarios and explicitly incorporates systemic interdependencies in accordance with the CER Directive, enhancing operational flood risk management capabilities. The method provides a practical tool for critical infrastructure protection, operational planning, and the development of adaptive strategies, thereby increasing the flood resilience of the energy system and supporting stakeholders responsible for risk management.
Duda et al. (Wed,) studied this question.