Rail2Flood: A nationwide classification of floodhazard exposure along the Italian Railway Network

In a climate-changing world, flood events represent one of the most impactful natural hazards, causing severe damage to people and infrastructures. Railway systems are critical infrastructures, susceptible to both structural damage and service disruptions. This study leverages a methodology capable of identifying and classifying paths along the railway system that are vulnerable to fluvial flood hazard and debris-flows. The methodology adopted is DEM-based and suitable for large-scale applications. We hereby focus on Italian Railway Network (IRN) and we consider three flood hazard scenarios, H1 (return period, Tr, up to 500 years), H2 (Tr = 100-200 years) and H3 (Tr = 20-50 years), as defined by the EU Flood Directive and the National Flood Risk Management Plans (FRMP). More specifically, the official FRMP data with national coverage and updated to 2020 are here employed. Across Italy, 26%, 19% and 10% of the IRN is exposed to low, medium and high hazard scenarios (H1, H2 and H3, respectively). To analyze this exposure, we discretize the railway system into sections (average length of 2.53 km) and assess their interaction with flood hazard maps. For each flooded stretch, we characterize the upstream basin using key hydrological parameters, including time of concentration, sub-basin area, river slope, and the presence of debris-flows, as influenced by topography-related triggering thresholds. Based on these parameters, we identified three distinct flood types affecting railroad segments: Very Steep River (VSR) portions characterized by steep slopes and fast hydrological response, Rapid River (RR) stretches with fast-responding watercourses, and Slow River (SR) sections. Each type includes a debris-flow classification determined by the contributing basin's morphological characteristics. The analysis of these flood types reveals that RR floods are predominant, representing 67% of the analyzed flood-prone sections, while SR and VSR floods account for 20% and 13%, respectively. A nationwide dataset is compiled, processed and analyzed in order to provide a comprehensive overview of the IRN affected by floods. This analysis represents a significant step forward in enhancing our understanding of flood dynamics and exposure analysis of railway infrastructure, thereby contributing to more informed decision-making processes in flood risk management and disaster mitigation efforts.