This PhD thesis is the result of the four-year work and research in the theme of wildfire modeling and its operational use. As described in the Introduction, all the researches were strongly conditioned by the hiring in the Corpo Nazionale dei Vigili del Fuoco (the National Fire Brigade) during the second year of the PhD. Starting from the experience in the wildfire management that has been developed during the entry course to the National Fire Brigade and, in particular, during real events, the wildfire risk management in the Liguria Region is described in this thesis, as the common thread of the implementations ad analysis performed during the PhD research. In Liguria region the operational preparedness to the wildfire risk is based on the SPIRL model, which forecasts the wildfire danger at municipal level. Basing on the outputs of the model, tactical and operative actions are performed, as the improvement of the ready-to-go firefighting units, and monitoring actions on the field. The real case of the Albenga wildfire, occurred in 2022, gives the chance to analyze the real benefits derived from the application of this type of preparedness, comparing the improvement of the units of National Fire Brigade, the forecasted wildfire danger and the number of wildfires occurred. In the operative management of a wildfire event, decision-makers in Liguria region have the possibility to simulate the possible wildfire spread by the use of the PROPAGATOR model, an empirical stochastic model developed by CIMA Foundation. The model has been implemented during the PhD research, introducing new firefighting activities that can be simulated, and evaluating and producing the maps of the Rate of Spread and the Fireline Intensity. The spatial resolution of the model can now vary, enlarging the possible applications of the model in the simulation of large wildfires, which last for entire days or weeks, or very detailed wildfires of small dimension (as the prescribed fires).
The Importance of Predictive Models in Forest Fire Risk Management: the example of Liguria Region
BAGHINO, FRANCESCO
2025
Abstract
This PhD thesis is the result of the four-year work and research in the theme of wildfire modeling and its operational use. As described in the Introduction, all the researches were strongly conditioned by the hiring in the Corpo Nazionale dei Vigili del Fuoco (the National Fire Brigade) during the second year of the PhD. Starting from the experience in the wildfire management that has been developed during the entry course to the National Fire Brigade and, in particular, during real events, the wildfire risk management in the Liguria Region is described in this thesis, as the common thread of the implementations ad analysis performed during the PhD research. In Liguria region the operational preparedness to the wildfire risk is based on the SPIRL model, which forecasts the wildfire danger at municipal level. Basing on the outputs of the model, tactical and operative actions are performed, as the improvement of the ready-to-go firefighting units, and monitoring actions on the field. The real case of the Albenga wildfire, occurred in 2022, gives the chance to analyze the real benefits derived from the application of this type of preparedness, comparing the improvement of the units of National Fire Brigade, the forecasted wildfire danger and the number of wildfires occurred. In the operative management of a wildfire event, decision-makers in Liguria region have the possibility to simulate the possible wildfire spread by the use of the PROPAGATOR model, an empirical stochastic model developed by CIMA Foundation. The model has been implemented during the PhD research, introducing new firefighting activities that can be simulated, and evaluating and producing the maps of the Rate of Spread and the Fireline Intensity. The spatial resolution of the model can now vary, enlarging the possible applications of the model in the simulation of large wildfires, which last for entire days or weeks, or very detailed wildfires of small dimension (as the prescribed fires).File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/217995
URN:NBN:IT:UNIGE-217995