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Agrociencia

versão On-line ISSN 2521-9766versão impressa ISSN 1405-3195

Resumo

VILCHIS-FRANCES, Aleida Y. et al. Territorial modeling for danger of wildfires with daily prediction in the Balsas River basin. Agrociencia [online]. 2015, vol.49, n.7, pp.803-820. ISSN 2521-9766.

The Balsas River basin is an area with limited water availability; however, it annually exports 490 hm3 of water to the Valley of Mexico basin through the Cutzamala system. If the forests of this basin deteriorates, the water resources will also diminish and consequently its exported volume will be at risk. For these reasons it is necessary to identify factors that favor the likelihood of fire occurrence in the forest of this basin. In this way, actions can be taken in a preventive manner to manage these phenomena in order to minimize the vulnerability and deterioration of the resources in the region. In a balanced manner, forest fires are necessary for the natural restoration of the ecosystems, nevertheless their frequency has increased by anthropogenic causes and climate dynamics. The objective of this study was to build a logistic regression model for the daily detection of areas with forest fire hazard. This proposal took into account topographic, meteorological and anthropogenic variables for the period from 2006 to 2009. The results provided a spatial and temporal effectiveness larger than 86 %. A risk scale (low, moderate, high and very high) was proposed in accordance with its probability of occurrence. In the analysis, more than 85 % of the fires had a daily category of high or very high risk of ignition. The greatest danger was found in the dams catchment areas of the Valle de Bravo, Colorines-Chilesdo and Ixtapan del Oro, of the Cutzamala system. The results of this study suggests that the methodology can be used to improve early warning systems against fires and complement the design of the strategic location of command centers, camps, watchtowers, as well as priorities for equipment.

Palavras-chave : Fire management; probability of fire occurrence; logistic regression; Cutzamala system.

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