LAUSR

Abstract. With the advent of computation and the progressive advancement of geotechnologies, the use of mathematical models of wildfire risk became more expressive in quantitative terms. The existence of a significant and variable number of models of wildfires risk presents the necessity to select the model that best fits a probable region – which can be done in two ways: visually or through the confrontation of existing models. In this sense, the present study aims at selecting the wildfire risk models FWI, FMA⁺ and RIF-Database for the Eucalyptus plantations. The study area extends from the north-central coast of the state of Espirito Santo and the south coast of Bahia, Brazil. The database was comprised the period between January 1st, 2010 to June 30st, 2016, with 10,447 occurrences. The validation and choice of the results were determined by the success percentages and the skill score value, for each subzone and risk model. After, it was performed the parametric analysis of Variance Analysis (ANOVA), if the F test was significant, the Tukey-Kramer post-hoc test (p