EGU21-980
https://doi.org/10.5194/egusphere-egu21-980
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Combining wildfire behaviour simulations and complex network theory to support decision-making: A case-study in a Mediterranean region

Bruno A. Aparício1, Ana C.L. Sá1, Francisco C. Santos2, Chiara Bruni1, and José M.C. Pereira1
Bruno A. Aparício et al.
  • 1University of Lisbon, School of Agriculture, Forest Research Centre, Lisbon, Portugal
  • 2INESC-ID and Instituto Superior Técnico, Universidade de Lisboa, IST-Taguspark, 2744-016 Porto Salvo, Portugal

Wildfires represent one of the most devastating natural disasters, bearing relevant environmental and socioeconomic impacts. The Mediterranean region is characterized by large and recurring summer wildfires that often jeopardize people’s safety. Currently, wildfire management largely (if not entirely) relies on wildfire suppression, despite growing evidence of its inefficiency to control the larger and more intense wildfires [1]. Moreover, climate change is expected to significantly affect the Mediterranean region and further exacerbate such hazard, even if global warming does not exceed 1.5°C (target of the Paris Agreement) [2]. Hence, fire prevention measures based on landscape fuel reduction strategies are crucial to decrease the magnitude of the impacts of future wildfires.

Here, we used FlamMap, a widely applied fire spread simulation system, to estimate fire spread and behaviour properties in the Monchique region, a highly fire-prone area, located in Southern Portugal. Five weather scenarios were defined based on hierarchical clustering analysis of temperature, relative humidity, wind speed and direction data derived from the spreading days of large wildfires (larger than 100 ha) between 2001 and 2019. Complex networks were generated from fireline intensity and rate of spread estimates (proxies for the difficulty of suppression and safety) with the main goal of decreasing landscape fire hazard. More precisely, we aimed to: i) evaluate how different weather scenarios/conditions affect landscape connectivity; ii) identify the location of fuel treatments; and iii) assess the impact of the proposed fuel breaks on the fire properties. These challenges were addressed under the perspective of connectivity indexes and metrics from the field of network science.

The results show that, as expected, weather conditions affect both the amount of area with more intense wildfires and wildfire connectivity, with more severe weather conditions presenting the greatest hazards. Additionally, the identified optimal locations of fuel treatments were compared against the locations previously proposed for fuel breaks and the potential impact on fire properties of both was evaluated. Further analysis of the effectiveness of different management options (fraction of landscape treatment and extent of each intervention) will be assessed under the previously identified weather scenarios, considering the extent of high-intensity classes of fires and multiple landscape connectivity indexes. Based on our results, we discuss the best strategies to reduce wildfire hazard for different criteria and under different weather scenarios. Moreover, both methods can be used to assess fire transmission between land uses and then to identify the key values exposed. We demonstrate that combining network graphs and fire spread simulations have a large potential to support more informed decision-making and significantly wildfire impact mitigation.

 

References

[1] Moreira, F., Ascoli, D., Safford, H. et al. (2020) Wildfire management in Mediterranean-type regions: paradigm change needed. Environmental Research Letters, 15, 011001. https://doi.org/10.1088/1748-9326/ab541e

[2] Turco, M., Rosa-Cánovas, J.J., Bedia, J. et al. (2018) Exacerbated fires in Mediterranean Europe due to anthropogenic warming projected with non-stationary climate-fire models. Nature Communications 9, 3821. https://doi.org/10.1038/s41467-018-06358-z

How to cite: Aparício, B. A., Sá, A. C. L., Santos, F. C., Bruni, C., and Pereira, J. M. C.: Combining wildfire behaviour simulations and complex network theory to support decision-making: A case-study in a Mediterranean region, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-980, https://doi.org/10.5194/egusphere-egu21-980, 2021.

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