Multi-factor coupled forest fire model based on cellular automata

Abstract

The risk of forest fires is substantial due to uneven precipitation distributions and abnormal climate change. This study employs cellular automata principles to analyze forest fire behavior, taking into account meteorological elements, combustible material types, and terrain slopes. The Wang Zhengfei model is utilized to compute fire spread speed, and a multifactor coupled forest fire model is developed. Comparisons with experimental data show a mean calculated fire spread speed of 0.69 m/min, which is consistent with the experimental results. Using the forest fire in Anning city, Yunnan Province, as a case study with a mean burned area of 2281 ha, the burned area, rate of change in burned area, and burning area demonstrated an increasing trend, with fluctuating states in the rate of change of the burning area. Employing the controlled variable method to examine forest fire spreading patterns under varying factors such as wind speed, vegetation type, and maximum slope reveals that under wind influence, the fire site adopts an elliptical shape with the downwind direction as the major axis. Quantitatively, when the wind speed increases from 2 m/s to 10 m/s, the burned area expands by a factor of 1.37. The ratio of the combustible material configuration coefficient to the burned area remains consistent across the different vegetation types, and the burned area increases by a factor of 1.92 when the maximum slope increases from 5° to 25°.

Keywords

• Cellular automata
• Forest fire spread
• Forest fires
• Forest fire prevention
• Forest fire model