Modeling wildfires in the Alpine context: Lessons learnt from real case studies

In the Alpine region, climate change is altering the predisposing factors of wildfires, leading to an increase in their frequency and intensity. This trend, combined with the inherent vulnerability of Alpine forest stands, underscores the growing importance of fire modeling as a fundamental tool to support both prevention strategies and emergency response. This study compares two wildfire simulation models — FlamMap and PROPAGATOR — which, although both widely used in Italy, are based on fundamentally different modeling approaches. The models are applied to three significant case studies in Lombardia’s Alpine area that took place in the period 2017–2022 (Tirano, Campolaro, and Sonico Wildfires), allowing a comparison of their performance in reproducing fire spread, rate of spread, and fireline intensity under varying topographic, vegetational, and meteorological conditions. Results indicate that both models reasonably captured the propagation of the three wildfires, although substantial differences emerged in fireline intensity and rate of spread, reflecting their distinct modeling assumptions. A closer examination of the outputs, combined with the specific input data required by each model, suggests that FlamMap is more suitable for planning contexts due to its ability to capture fine-scale fuel-topography interactions, while PROPAGATOR is better suited for operational scenarios thanks to its flexibility, fast implementation and computation, and capacity to incorporate time-varying wind. The analysis benefited from detailed information provided by local managers directly involved in the events, which helped reconstruct the actual fire dynamics and evaluate model outputs against real-world cases. These findings emphasize the critical role of accurate wind and fuel data, as well as the need for a structured database of past wildfires in the Alpine context to improve model calibration and reliability. Overall, this study provides practical insights to support stakeholders in selecting appropriate modeling tools across different phases of wildfire risk management and underscores the need for further refinement of simulation systems tailored to complex mountain landscapes.