In Portugal, the 2017 fire season was particularly extreme, leading to an unprecedented large number of fatalities, injured people, destruction of houses and infrastructures. These dramatic outcomes have contributed to raise awareness regarding the importance of ensuring the safety of people and assets from high intensity uncontrollable wildfires. It is crucial to identify the settlements at higher risk and the most suitable mitigation actions that can maximize the protection of people and assets.
We developed a simple methodology that combines exposure and vulnerability to estimate wildfire risk at the local level. Exposure was estimated using a fire spread simulation approach that was used to determine the probability of (i) a wildfire generating firebrands that could affect a settlement and (ii) a high intensity wildfire occurring adjacent to a settlement. Exposure was estimated using two fuel scenarios created to represent the current year of 2023 (short-term scenario) and 2030, assuming that no fuel management nor large fires occur in the meantime (medium-term worst-case scenario). Vulnerability was determined by the (i) Index of Total Dependence (IDT), and (ii) evacuation difficulty. Exposure and vulnerability metrics were normalized in percentiles, distributed into quadrants and combined to provide six levels of wildfire risk. For each vulnerability\exposure combination, we proposed a set of priority mitigation actions. The methodology was applied to three areas in Portugal where the risk estimates were analyzed and compared with the implementation rate of two risk mitigation programs already in place.
Results showed that 8.7% of the settlements had “very high” wildfire risk and about 19.5% had “high” wildfire risk, potentially affecting 8,403 and 34,762 inhabitants, respectively. The spatial distribution of settlements at higher risk was very heterogeneous across the study areas and the total fraction ranged between 14% in Coimbra to 36% in Barlavento Algarvio. The overall implementation of mitigation programs in the study areas is very low, with only around 1% of the settlements in “very high” risk having any of the mitigation programs implemented. Conversely, our results also suggest that the implementation rate in settlements classified in lower risk classes is disproportionately high.
The application of this risk analysis methodology can be used to assess the implementation status of mitigation actions, and contribute to tailor the actions that maximize the protection of people and assets according to the specific conditions found in each targeted area.