Railway Infrastructure Resilience Analysis in Case of Flooding: Case Study in Italy

This study seeks to assess the flooding impacts on Italy's railway infrastructure, to establish a model based on which the system vulnerability can be measured, and the mitigation strategy can be evaluated. Using Python libraries, exposed railway sections are determined by intersecting flood risk map with Italy's railway network. In addition, Eurostat's dataset provides traffic statistics for weighing network sections. The whole project comprises three phases: i) identifying flood-exposed railway elements, ii) transferring traffic data to the real-path link dataset and assigning weights to nodes according to traffic. Key Performance Indicators (KPIs), focusing on system resilience to flooding, are using Degree Centrality (DC) and Betweenness Centrality (BC). These outcome related KPIs aid in understanding and mitigating the impact of disruptions, enhancing railway system resilience.