Establishing Propagation Nodes as a Basis for Preventing Large Wildfires: The Proposed Methodology

Abstract

In Spain, traditional forest fire management practices have been conducted for many decades, for both prevention- and extinction-oriented purposes. This management model has been forced to shift as a result of changes in fire behavior and has also been adapted to the use of new technologies. The challenge presented by wildfires is amplified due to socioeconomic changes in the last 40 years and inadequate land management in the context of climate change. The principal objective of this work is to establish the most adequate methodology to define the “propagation nodes” in a territory. To do that, the new simulation modes offered by the WildFire AnalystTM simulator (WFA) have been explored to obtain fire behavior data. Likewise, the behavior of large fires in the area has been extrapolated to future scenarios, according to forecasts of different climate change, analyzing extreme weather conditions that can occur in such scenarios (ONU, 2019). The WFA simulator (Tecnosylva, 2014) works efficiently in simulating fire, proving greatly useful in both real suppression operations and fire prevention analysis. It can very accurately generate large wildfires' main pathways without making any kind of adjustments; this is quite useful when planning operations at the head of a fire. It also allows evacuation time evaluation for a given Wildland Urban Interface zone. The area selected for this study is called Sot de Chera, in the Valencia region (Spain). The methodology employed here uses the simulation with WFA setting extreme meteorological and phenological windows associated with wind-driven fires or convection fires dominated with wind, from different starting points looking for the areas where they are grouped. In other words, it is a matter of identifying on the territory the areas where the heads of these higher-intensity fires will arrive, in order to offer realistic control possibilities to the firefighting teams. The results of the simulation identify the heads of the fires with the greatest rate of spread and intensity, exceeding suppression capabilities and efforts, allowing thus to plan for appropriate fuel management strategies to effectively manage emergency responses to fires in these areas.