Incêndios florestais no Parque Nacional Serra de Itabaiana - Sergipe - White, Benjamin Leonardo Alves (2010)
This research was developed with the objective to determine the forest fire danger index that is the most efficient to predict forest fire inside the National Park Serra de Itabaiana . It also simulates the characteristics of the fire inside each type of vegetation, in order to characterize the risk in each situation. To simulate the forest fires, was used the program BEHAVEPLUS 4.0 . With the proper environmental information, this software can calculate the fire characteristics. The input variables measured in this work were: total amount and humidity content of the fuel; fuel model; mid flame wind speed; and slope steepness. By the results simulated, the vegetations of White Sands had greater flame length (2m), greater Fireline Intensity (1186kW/m), and greater Heat per Unit Area (9628Kj/m2). The Grasses Fields presented the biggest Surface Rate of Spread (12,3m/min), however in the Closed Forests, the simulated fires presented lesser intensity and, consequently, more easily controlled. In order to search for the best forest fire danger index for the Sergipe state and for the National Park Serra de Itabaiana , the values of the five most important indices, cited in literature, were submitted to Pearson s test of correlation and to the Skill Score test. In accordance with the results, the Angstron index was the most efficient to forecast the occurrence of heat points inside Sergipe, as well as to forecast forest fires inside the National Park. The present work also elaborated a forest fire risk calendar of occurrence, on the basis of the daily precipitation in Itabaiana city, and on the basis of the historical register of fire occurrences in the National Park. The precipitation demonstrated to have a significant correlation with the fire register, however, the months that presented lesser rainfall, between 1999 to 2009 (November and December), was not the months with the biggest fire register. In accordance with the unconditional probability, based in the fire register between 1991 to 2009, the month of February presented greater forest fire probability of occurrence.