Probability of surface fire spread in Brazilian rainforest fuels from outdoor experimental measurements

Abstract

This paper describes the development of a logistic model to predict the probability of surface fire spread in Brazilian rainforest fuels from outdoor experimental measurements. Surface fires spread over litter composed mostly of dead leaves and twigs. There were 72 individual outdoor experiments in eighteen sites. The fire propagated in 49% of the experiments. In each experiment, the litter height, litter temperature, unburned litter mass, wet and dry litter mass, soil temperature, wet and dry soil mass, ambient wind velocity, ambient air temperature, ambient air relative humidity and duration of fire spread were measured. Using these data, the rate of fire spread, litter bulk density, litter and soil moisture content, litter load and litter residue fraction were determined. For the sake of analysis, experimental results were classified into two groups: one for which the fire propagated and the other one for which the fire self-extinguished. Analyses of a logistic regression model showed that the relevant parameters for fire propagation are litter height and litter moisture content. Concerning the probability of successful fire propagation, the model showed a true positive rate of 71% and a true negative rate of 84%. The outdoor experiments also served to gather data to improve the understanding of surface fires and to provide input data for future computer simulations. Keywords Surface fire Á Brazilian rainforest Á Flammability Á Logistic regression model List of symbols A Area of the frame used to determine litter mass, litter height and soil mass for measurement (m 2) AT Ambient air temperature (°C) DLM Dry litter mass (g) DSM Dry soil mass (g) i Auxiliary variable [-] LBD Litter bulk density (kg m-3) LH Litter height (cm) LL Litter load (kg m-2) LMC Litter moisture content [-] LRF Litter residue fraction [-] LT Litter temperature (°C) m Vegetation, soil or residue mass (g) n Number of values of a variable [-] Pr Probability associated with the logistic regression model [-] RH Ambient air relative humidity [-] ROS Rate of spread (cm min-1) SMC Soil moisture content [-] ST Soil temperature (°C) u Standard uncertainty [variable] Communicated by Jarmo Holopainen.

Brote posfuego de la palma en el bosque amazónico: ¿son los tallos subterráneos una ventaja?

“…The parameters followed in the simulations describes the surface fire with 30 cm maximum height, 50 kW m-1 intensity and 760oC of maximum temperature, with propagation speed ranging from 0.1 to 0.35 m min-1 (Uhl and Kauffman, 1990;Michaletz and Johnson, 2007;Krieger F et al, 2017).…”

Summary of workshop large outdoor fires and the built environment

“…The flammability of local/native species has been studied using less detailed techniques for ranking species [42, 44] or using more comprehensive techniques including fire calorimetry and soot production measurements [45–47]. Fire spread testing has been carried out on forest fuel beds in different forest types and in field and laboratory conditions [48–50]. Work also includes ignition studies by idealized firebrands [51], a key fire spread mechanism at the WUI.…”

Fire Occurrences and Greenhouse Gas Emissions from Deforestation in the Brazilian Amazon

“…Selective logging degrades forest, reduces canopy and soil moisture, and increases canopy temperature and tree mortality, intensifying fire outbreaks [22,28,29]. The cycle grows in a spiral configuration: forest fires and smoke emissions reduce rainfall, particularly in the dry season [24,[30][31][32][33][34][35], previously burned areas are more prone to recurrence, changes in the global and local climate, along with land use intensification, contribute to increasing the level of forest degradation [28,[35][36][37][38][39][40][41], most significant changes in forest canopy density take place in regions close to the forest edges [16,22,35,42], and land management fires can penetrate the standing degraded forests, as demonstrated by others studies [21,43,44]. Several in-situ measurements of the slash-and-burn forest clearing practices have been conducted to infer greenhouse gas (GHG) emission [45][46][47][48][49].…”

“…Finally, the remaining scorched logs are stockpiled and burned along the coming years until the terrain becomes dominantly bare soil (Figure 3D). Fire may penetrate the standing forest if moisture favors flame propagation through the understory vegetation [42][43][44]. Forest degradation increases after successive fires, observed by the combustion of growing small trees in dry seasons.…”