Abstract
The impacts of wildfires have been increasing in the Mediterranean Basin, and Portugal recently experienced some of the most extreme fire seasons on record. It is urgent to shift wildfire management goals by re-balancing wildfire suppression and mitigation efforts, to reduce fire intensity and increase the effectiveness of suppression operations. Our study aims at assessing wildfire hazard in Serra da Cabreira (NW Portugal) by combining landscape-scale wildfire modelling and landscape wildfire connectivity analysis. The impact of two levels of landscape treatment in wildfire hazard decrease was also assessed. We used the 95th percentile historical weather conditions (2001–2019) to simulate fireline intensity (FLI), burn probability (BP) and fire size (FS), using the Minimum Travel Time (MTT) algorithm implemented in FlamMap (Vers.6). We calculated wildfire connectivity using the simulated FLI to: (1) guide the choice of the area of the landscape to be treated; and (2) identify the relative importance of single fuel patches to overall landscape connectivity. Results showed that significant decreases in BP (36%), FS (39%), FLI (61%) and wildfire connectivity (48%) were obtained when 20% of the landscape was treated. For the same treatment level, the median FLI decreases to values below 2000 kW/m, with likely areas to burn at high intensity decreasing by 4.4%. We also estimated ca. 15% decrease in the area with fires larger than 1000 ha. We discuss the results and highlight the relevance of integrating wildfire connectivity into wildfire hazard assessment, to support landscape fuel management plans aiming at decreasing fire intensity and thus the mitigation of its impacts.
Author Contributions
A.C.L.S., J.P., B.A., A.B., M.S. and F.S. were involved in the conceptualization; A.C.L.S., M.S. md J.P. developed the methodology; A.R. supervised S.C. and M.M.-A. in the weather data processing; C.B. explored the fire spread modelling system and prepared input weather data; B.A. performed the connectivity analysis; A.C.L.S. and B.A. analysed the data; B.A. and A.C.L.S. developed R-codes for 540 data analysis and visualization; A.C.L.S. developed the calibration framework; A.C.L.S. wrote the manuscript draft and edited the co-authors revisions; all co-authors were involved in the review of the manuscript. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by the Forest Research Centre research unit, funded by Fundação para a Ciência e a Tecnologia I.P. (FCT), Portugal (UIDB/00239/2020). B.A. Aparício was supported by the Ph.D. fellowship funded by FCT (UI/BD/150755/2020). A.C.L. Sá was supported under the framework of the contract-program nr.1382 (DL 57/2016/CP1382/CT0003). A. Benali was supported by the research contract (CEECIND/03799/2018/CP1563/CT0003). C. 555 Bruni grant was supported by the project foRESTER, a project funded by FCT (PCIF/SSI/0102/2017). J.M.C. Pereira was supported by the FireCast - Forecasting fire probability and characteristics for a habitable pyroenvironment project (PCIF/GRF/0204/2017), funded by FCT. The participation of S. Pereira and A. Rocha was supported by the project FIREMODSAT II (PTDC/ASP-SIL/28771/2017) also funded by FCT.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
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