Parameter calibration of the Rothermel model for predicting rate of spread in mixed fuels

Background Vegetation, terrain and weather properties vary greatly spatially and temporally, all of which influence fire behavior. Aims This study aims to enhance the applicability and predictive accuracy of the Rothermel model for mixed fuel spread rates under varying wind conditions in northeast China. Methods Laboratory fuel beds were constructed of surface fuels from Pinus koraiensis and Quercus mongolica plantations with controlled moisture content, wind speed and packing ratios. A total of 142 controlled flame spread experiments were conducted under varying wind conditions. Empirical rate of spread (ROS) data were then utilized to calibrate key parameters in the Rothermel model. Key results Observed ROS values ranged from 1.38 to 11.09 m min−1. Direct application of the Rothermel model showed limited accuracy for mixed fuels. Targeted adjustment of the wind coefficient (ϕw) under flat terrain conditions yielded the most significant improvement. Further calibration of the reaction intensity (IR) parameter enhanced model performance substantially. Conclusion The unmodified Rothermel model inadequately predicts ROS in mixed Pinus koraiensis–Quercus mongolica surface fuels. Parameter calibration using empirical combustion data significantly reduces prediction errors and improves model accuracy. Implications This research offers a technique for applying the Rothermel model locally in China, thereby assisting in forest fire suppression and management efforts.