Predicting the rate of spread of mixed-fuel surface fires in northeastern China using the Rothermel wildfire behaviour model: a laboratory study

Hui Yang , Huiying Cai , Guang Yang , Daotong Geng , Long Sun

Journal of Forestry Research ›› 2024, Vol. 35 ›› Issue (1) : 108

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Journal of Forestry Research ›› 2024, Vol. 35 ›› Issue (1) : 108 DOI: 10.1007/s11676-024-01730-w
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Predicting the rate of spread of mixed-fuel surface fires in northeastern China using the Rothermel wildfire behaviour model: a laboratory study

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Abstract

The rate of fire spread is a key indicator for assessing forest fire risk and developing fire management plans. The Rothermel model is the most widely used fire spread model, established through laboratory experiments on homogeneous fuels but has not been validated for conifer-deciduous mixed fuel. In this study, Pinus koraiensis and Quercus mongolica litter was used in a laboratory burning experiment to simulate surface fire spread in the field. The effects of fuel moisture content, mixed fuel ratio and slope on spread rate were analyzed. The optimum packing ratio, moisture-damping coefficient and slope parameters in the Rothermel model were modified using the measured spread rate which was positively correlated with slope and negatively with fuel moisture content. As the Q. mongolica load increased, the spread rate increased and was highest at a fuel ratio of 4:6. The model with modified optimal packing ratio and slope parameters has a significantly lower spread rate prediction error than the unmodified model. The spread rate prediction accuracy was significantly improved after modifying the model parameters based on spread rates from laboratory burning simulations.

Keywords

Rothermel model / Mixed fuel / Fuel moisture content / Slope / Parameter modification

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Hui Yang, Huiying Cai, Guang Yang, Daotong Geng, Long Sun. Predicting the rate of spread of mixed-fuel surface fires in northeastern China using the Rothermel wildfire behaviour model: a laboratory study. Journal of Forestry Research, 2024, 35(1): 108 DOI:10.1007/s11676-024-01730-w

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