Summary
In this article, Luis Galván and Victor Magaña propose a model for estimating probabilities of forest fires in Mexico. The authors link the frequency of fires in the region to both climate anomalies and anthropological factors such as human activities. One of the main reasons for their occurrence is associated with the economic activity of people, that is, it is determined by factors of anthropogenic origin. At the same time, almost 80% of fires occur due to the local population’s fault. The largest number of fires occurs in regions with a high population density and a developed road network. Large fires take place more often in dry seasons and are also associated with agricultural activities of the population.
The authors suggest that forest fire probabilities assessment should include two major parameters: climatic hazards and related physical and socio-economic dangers. The former are usually calculated based on historical records. This study includes three factors: three-month SPI-3 data, monthly surface maximum temperature anomalies from the Northern American Regional Reanalysis, and bi-weekly anomalies of the NDVI obtained from the US Geological Survey (Galván and Magaña 755). These parameters were put into a mathematical formula of the normalized climate variables linear combination, which resulted in a climatic hazard index. To assess vulnerability, the authors added physical and socio-economical parameters into the model, which were presented directly or indirectly in official sources. Another indicator put in the formula was forest vegetation since some types are more predisposed to fires than others and meteorological drought. All the parameters were brought to a normalized average, i.e., between 0 and 1.
Analysis
This article is an example of recognizing that forest fire prevention and control should be based on more thorough region-specific mathematical prediction and evaluation models. Forest fires have a huge impact on forest ecosystems around the planet. Two of the main negative environmental consequences of fires are smoke and air pollution. Animals and people most often die not from fire, but because of smoke poisoning. During intensive forest burning, the concentration of carbon monoxide, compared with the air’s background content, increases by almost 30 times, methane – twice, carbon dioxide – by 8%. Currently, researchers and practitioners have accumulated enough data for mathematical prediction models development. Such formulas should be based on the analysis of physical and geographic conditions and factors of the occurrence of fires, zoning of the territory according to forest biogenic conditions, information on the number, intensity, and class of forest fires in the region. The article is very insightful in terms of techniques of fire prevention and control.
An essential argument of this article was the inclusion of regional and local public policies aimed at fire prevention and control into the estimation model. One can agree that such policies should be recognized as a factor increasing or reducing vulnerabilities and, subsequently, the probabilities of forest fires. However, one must be cautious when applying this model for the reason that all the parameters put in this model are region-sensitive. Further estimation of probabilities and prognosis should be based on highly specified indicators of each unique zone. This presupposes thorough research of all the data put in the model. Mathematical modeling of forest fires seems one of the most challenging areas of modeling due to the diversity and complexity of physical processes occurring in the fire zone and the atmosphere above the fire, the influence of weather conditions, possible spread of fire over a large area for a long time, and many other factors that should be taken into account. The development of mathematical models of fire proliferation allows predicting its behavior, which contributes to a more effective fight against its elements. However, one of the main difficulties is the lack of information support for the developed mathematical models, particularly about the characteristics of combustible materials, weather, the topography of the area, and other region-specific indicators.
The disadvantage of the model proposed in this article is that it is rather a simple fire behavior model, which means that it is not based on physical criteria. Empirical models are relatively simple, they do not take into account many physical processes occurring in the fire zone, but at the same time, their software implementation does not require large computing resources and allows calculations of fire propagation in real-time. Physically-based models are more complex and can take into account different physical processes occurring in the fire zone. These models can be multiphase in the composition of the medium, and each phase can contain several components. For the numerical simulation of forest fires, both 2D and 3D models are used. Adequate models for predicting and controlling the spread of fire should also include fundamental physical laws of conservation of mass, momentum, and energy, as well as take into account the main physical processes occurring in the fire zone. The latter are essential for the accurate description of the proliferation of the fire front. In addition, for more accurate predictions of the development of a fire in a forest zone, it is necessary to take into account the generation and dissipation of turbulence in the forest and their speed.
Work Cited
Galván, Luis, and Víctor Magaña. “Forest Fires in Mexico: An Approach to Estimate Fire Probabilities.” International Journal of Wildland Fire, vol. 29, no. 9, Sept. 2020, pp. 753-763.