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Martin E. Alexander, Miguel G. Cruz
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Fire Behavior
Data Evaluation or Data Analysis for Fire Modeling

NRFSN number: 12417
FRAMES RCS number: 16278
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Evaluation is a crucial component for model credibility and acceptance by researchers and resource managers. The nature and characteristics of free-burning wildland fires pose challenges to acquiring the kind of quality data necessary for adequate fire behavior model evaluation. As a result, in some circles it has led to a research culture that tends to avoid evaluating model performance. Operational fire modelling systems commonly used in western North America have been shown to exhibit an under-prediction bias when employed to determine the threshold conditions necessary for the onset of crowning and the associated spread rate of active crown fires in conifer forest stands. This pronouncement was made a few years ago after at least a decade of model misapplication in fire and fuel management simulation modelling stemming from a lack of model evaluation. There are signs that the same situation may be repeated with developing physics-based models that simulate potential wildland fire behaviour; these models have as yet undergone limited testing against observations garnered from planned and/or accidental wildland fires. We propose abroad cooperative project encompassing modellers and experimentalists is needed to define and acquire the benchmark fire behavior data required for model calibration and evaluation.


Alexander, Martin E.; Cruz, Miguel G. 2013. Are the applications of wildland fire behaviour models getting ahead of their evaluation again? Environmental Modelling & Software. 41: 65-71.

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