Print Email Facebook Twitter Effectiveness Assessment of Adaptation Measures to Build Wildfire Resilience of Road Networks Title Effectiveness Assessment of Adaptation Measures to Build Wildfire Resilience of Road Networks Author Arango, Erica (University of Minho) Nogal Macho, M. (TU Delft Integral Design & Management) Yang, M. (TU Delft Safety and Security Science) Sousa, Hélder S. (University of Minho) Stewart, Mark G. (University of Technology Sydney) Matos, José C. (University of Minho) Date 2023 Abstract Wildfires have become a source of concern for society due to the increase in frequency, intensity, and unpredictability. This has caused serious impacts all over the world, even in areas where this type of problem did not occur before. Studies on the adaptation of critical infrastructure have been conducted to reduce the impacts of this type of hazard influenced by climate change. However, there are currently no tools to evaluate adaptation measures and their influence on the resilience of transport infrastructure to wildfires. Therefore, this paper proposes the application of a simplified methodology to assess the priority level in interventions on bridge networks and the effectiveness of different adaptation measures. The methodology is applied to a case study in Portugal. In that sense, the results show that adaptation measures such as changing vegetation management policy and implementing wildfire spread barriers effectively reduce the exposure of bridges. Therefore, this tool can be very useful for stakeholders and practitioners supporting wildfire management in terms of adaptation measures. To reference this document use: http://resolver.tudelft.nl/uuid:22633ffb-e7b0-4ce2-af31-a48f7d171c7f Event 14th International Conference on Applications of Statistics and Probability in Civil Engineering 2023, 2023-07-09 → 2023-07-13, Trinity College Dublin, Dublin, Ireland Part of collection Institutional Repository Document type conference paper Rights © 2023 Erica Arango, M. Nogal Macho, M. Yang, Hélder S. Sousa, Mark G. Stewart, José C. Matos Files PDF submission_51.pdf 794.91 KB Close viewer /islandora/object/uuid:22633ffb-e7b0-4ce2-af31-a48f7d171c7f/datastream/OBJ/view