Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Why is the Effect of Live Fuel Moisture Content on Fire Rate of Spread Underestimated in Field Experiments in Shrublands?

Version 1 : Received: 19 October 2018 / Approved: 19 October 2018 / Online: 19 October 2018 (16:53:50 CEST)

A peer-reviewed article of this Preprint also exists.

Pimont F., Ruffault J., Martin-StPaul N.K., Dupuy J.-L. A Cautionary Note Regarding the Use of Cumulative Burnt Areas for the Determination of Fire Danger Index Breakpoints. International Journal of Wildland Fire. 2019, https://doi.org/10.1071/WF18056. Pimont F., Ruffault J., Martin-StPaul N.K., Dupuy J.-L. A Cautionary Note Regarding the Use of Cumulative Burnt Areas for the Determination of Fire Danger Index Breakpoints. International Journal of Wildland Fire. 2019, https://doi.org/10.1071/WF18056.

Abstract

Live fuel moisture content (LFMC) influences fire activity at landscape scale and fire behavior in laboratory experiments. However, field evidences linking LFMC to fire behavior are very limited despite numerous field experiments. In the present study, we reanalyze a shrubland fire dataset with a special focus on LFMC to explain this counterintuitive outcome. We found that this controversy might result from three reasons. First, the range of experimental LFMC data was too moist to reveal significant effect with the widespread exponential or power functions. Indeed, LFMC exhibited a strong effect below 100%, but marginal above this threshold, contrary to these functions. Second, we found that the LFMC significance was unlikely when the size of the dataset was smaller than 40. Finally, a complementary analysis suggested that 10 to 15% of random measurement error in variables could lead to an underestimation by 30 % of the LFMC effect. The effect of LFMC in field experiments is thus stronger than previously reported in the range prevailing during the actual French fire season and in accordance with observations at different scales. This highlights the need to improve our understanding of the relationship between LFMC and fire behavior to refine fire danger predictions.

Keywords

Sample size, Measurement error, Generalized Additive Model, GAM, Réseau Hydrique.

Subject

Environmental and Earth Sciences, Environmental Science

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