Abstract
BackgroundAn approach to predict fire growth in an operational setting, with the potential to be used as a decision-support tool for fire management, is described and evaluated. The operational use of fire behaviour models has mostly followed a deterministic approach, however, the uncertainty associated with model predictions needs to be quantified and included in wildfire planning and decision-making process during fire suppression activities. We use FARSITE to simulate the growth of a large wildfire. Probabilistic simulations of fire spread are performed, accounting for the uncertainty of some model inputs and parameters. Deterministic simulations were performed for comparison. We also assess the degree to which fire spread modelling and satellite active fire data can be combined, to forecast fire spread during large wildfires events.ResultsUncertainty was propagated through the FARSITE fire spread modelling system by randomly defining 100 different combinations of the independent input variables and parameters, and running the correspondent fire spread simulations in order to produce fire spread probability maps. Simulations were initialized with the reported ignition location and with satellite active fires. The probabilistic fire spread predictions show great potential to be used as a fire management tool in an operational setting, providing valuable information regarding the spatial–temporal distribution of burn probabilities. The advantage of probabilistic over deterministic simulations is clear when both are compared. Re-initializing simulations with satellite active fires did not improve simulations as expected.ConclusionThis information can be useful to anticipate the growth of wildfires through the landscape with an associated probability of occurrence. The additional information regarding when, where and with what probability the fire might be in the next few hours can ultimately help minimize the negative environmental, social and economic impacts of these fires.Electronic supplementary materialThe online version of this article (doi:10.1186/s40064-016-2842-9) contains supplementary material, which is available to authorized users.
Highlights
An approach to predict fire growth in an operational setting, with the potential to be used as a decision-support tool for fire management, is described and evaluated
We propose to (1) assess the probabilistic predictions of fire spread during the Tavira wildfire; (2) assess the combination of fire spread modelling and satellite active fire data; and (3) assess the decision-support potential of probabilistic fire spread to improve fire suppression in an operational setting, identifying if it could have been helpful to fire suppression and pre-suppression activities
Spotting contributed to fast fire growth during both phases, which was not simulated in this study in order to eliminate one possible confounding source of uncertainty, as spotting is stochastic in Fire Area Simulator (FARSITE)
Summary
An approach to predict fire growth in an operational setting, with the potential to be used as a decision-support tool for fire management, is described and evaluated. The operational use of fire behaviour models has mostly followed a deterministic approach, the uncertainty associated with model predictions needs to be quantified and included in wildfire planning and decision-making process during fire suppression activities. We use FARSITE to simulate the growth of a large wildfire. Probabilistic simulations of fire spread are performed, accounting for the uncertainty of some model inputs and parameters. We assess the degree to which fire spread modelling and satellite active fire data can be combined, to forecast fire spread during large wildfires events. During the 2003 fire season, extreme weather conditions were recorded with a devastating sequence of large wildfires resulting in around 450,000 ha of total burned area, approximately twice the previous highest record (220,000 ha in 1998) (Trigo et al 2006). In 2005, as a consequence of one of the longest and most severe droughts of the last century, a total of 340,000 ha burned, making it the second worst fire year on record
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