A comparison of fire danger rating systems for use in forests

Abstract

Fire danger indices are an important tool for fire and land managers. This study examines two fire danger indices developed for use in Australian forests, the Forest Fire Danger Index and the Forest Fire Behaviour Tables, and a third, the Fire Weather Index, which was developed for use in Canadian pine forests but is finding use in other countries. The indices are described and their structures examined by comparing the response of each index to wind, fuel moisture, and fuel availability. The application of the indices is examined by comparing their predictions across a range of wind, fuel moisture, and fuel availability conditions, and in a case study using weather station data. The three systems are found to have similar structures but to provide widely varying assessments of fire danger for a given set of inputs. In the case study, differences between how weather variables are incorporated by the indices cancelled out some of the differences in structure and the results were in closer agreement, particularly for the two systems developed for eucalypt forest.

Fire weather risk differs across rain forest—savanna boundaries in the humid tropics of north‐eastern Australia

“…We assessed fire risk across elevational and rainfall gradients in the humid tropics of north-eastern Australia using FFDI, as this is the standard measure of fire danger rating in Australia most suitable for all the vegetation types in this study. Reviews of the relative performance of different fire danger rating systems have shown that this index is one of the best performing in Australian ecosystems, including those in this study (Xiao-rui et al 2006;Dowdy et al 2009Dowdy et al , 2010Matthews 2009;Sharples et al 2009). …”

Behind the flaming zone: Predicting woody fuel consumption in eucalypt forest fires in southern Australia

“…1 3991 12 3 2805 12 44 2 678 12 7 497 12 8 3 545 12 7 387 12 16 4 328 12 14 217 12 24 5 129 11 12 82 11 21 n: number of sample woody fuels. Matthews, 2009), a GLM approach based on these variables used individually yield poor goodness-of-fit statistics. The McCorkhill subset showed large variability in the fuel consumption outcomes which was attributed to unquantified variation in field plots and data collection techniques (Hollis et al, in press).…”

Fire-Risk Assessment in Northern Greece Using a Modified Fosberg Fire-Weather Index That Includes Forest Coverage

“…The classification of most fire-danger indices is divided into 5 categories, that is, low, moderate, high, very high, and extreme (e.g., [25]). The Fosberg index varies between 0 (no danger) and 100 (extreme danger), while any index value above 100 is set to 100.…”