Developing a Modeling Framework for Integrated Wildfire Management Strategies: Preventing, Forecasting and Managing Extreme Wildfires

Wildfires reflect the complex human-environment relationship, with humans shaping fire regimes through wildfire ignitions, suppression efforts, and fuel availability. Wildfires mirror ongoing socio-economic and climate changes: extreme fire weather combines with fire-prone landscapes and growing human exposure in wildland-urban areas, driving changes in fire regimes and an increase in extreme wildfires. Thus, a shift in wildfire management is crucial, by adopting a holistic approach to mitigate these events and build resilient landscapes and societies. This dissertation explores the wildfire problem from a Civil Protection perspective, proposing a modeling framework to assess fire danger and develop propagation scenarios. It supports integrated strategies in mitigation, preparedness, and response phases. This research, focused on Italy, was conducted at the CIMA Foundation, a Competence Centre of the Italian Civil Protection Department for wildfire risk management. The first part of this research developed a model to simulate hourly fuel moisture dynamics considering different fuel types. By integrating topography, fuel characteristics, and wind conditions, the RISICO system was consequently developed to generate dynamic hourly fire danger maps, supporting preparedness, response, and mitigation efforts. Machine Learning enhanced fire danger assessment through a simplified fuel classification method and a model linking RISICO outputs to potential wildfire activity and the needs of the national firefighting fleet, aiding resource management. Lastly, the wildfire propagation model PROPAGATOR was used to design and optimize prescribed fires, highlighting the role of mitigation in preventing extreme wildfires. The modeling solutions were designed for operational use, to be integrated as tools in wildfire risk management systems. Thus, a balance between modeling complexity and ease of use was sought. This framework offers an innovative decision-support tool for implementing integrated strategies in the context of Civil Protection, enabling the prevention, forecasting, and management of extreme wildfires.