Transportation infrastructure networks are increasingly exposed to multiple natural hazards, thus demanding sophisticated assessment methodologies for evaluating compound threats and supporting decision-making. This paper presents an operational multi-hazard assessment framework integrating the Analytical Hierarchy Process (AHP) with Weighted Linear Combination (WLC) within a GIS-based decision support system. The methodology is implemented as a plugin for CI-RES (critical infrastructure resilience), a web-based geospatial platform developed by ENEA for integrated analysis and resilience assessment of critical infrastructure systems, enabling automated evaluation of infrastructure elements against six natural hazards: seismic, flood, landslide, volcanic, wildfire, and tsunami. The approach combines spatial analysis with multi-criteria decision-making techniques, allowing users to define hazard priorities through pairwise comparison matrices while ensuring consistency through automatic validation procedures. A comprehensive case study covering the Italian national territory demonstrates the framework’s ability to process large-scale infrastructure datasets, generating spatially explicit hazard maps and statistical summaries. Our results reveal significant variations in multi-hazard exposure across different infrastructure types and geographic regions, with approximately 48% of the analysed road network falling within medium-to-high multi-hazard zones, 58% of road bridges and viaducts, 46% of railways, and 66% of railway bridges. The integration within the CI-RES platform provides stakeholders with an accessible web-based interface for conducting multi-hazard assessments, supporting evidence-based infrastructure planning and emergency management decisions. This work contributes both methodologically, through the AHP–WLC integration, and practically, through its implementation in an operational decision support system.
Pollino et al. (Sat,) studied this question.