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Chinese Journal of Applied Ecology ›› 2023, Vol. 34 ›› Issue (8): 2091-2100.doi: 10.13287/j.1001-9332.202308.024

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Prediction models of fire spread rate of Pinus koraiensis plantation's surface fuel

REN Menglin, GUO Yan, CHEN Boxuan, FAN Jiale, HU Tongxin, SUN Long*   

  1. School of Forestry, Northeast Forestry University, Harbin 150040, China
  • Received:2023-03-10 Accepted:2023-06-20 Online:2023-08-15 Published:2024-02-15

Abstract: Pinus koraiensis plantation has high fire risks due to high oil content in branches and leaves. The spread of surface fire is the main way of forest fire expansion. Understanding the surface fire spread rate can provide scientific guidance for fire fighting. We carried out a laboratory experiment with surface fuel of Pinus koraiensis plantation in Maoershan area of Heilongjiang Province. We set different levels of fuel moisture contents (5%, 15%, 25%), fuel loads (0.5, 0.7, 0.9, 1.1 kg·m-2), and slope (0°, 10°, 20°, 30°, 40°) to simulate the characteristics of fuel bed in the field, and quantified the spread rate by thermocouple method. We further compared and analyzed the prediction accuracy of Rothermel model, modified Rothermel model and random forest model, and evaluated the optimal model for predicting the surface fire spread rate of P. koraiensis plantation. The results showed that the overall efficacy of directly using the Rothermel model to predict the surface fire spread rate of P. koraiensis plantations was good, but the prediction result of the spread rate under the conditions of high slope and high moisture content was not satisfied. The Rothermel model after refitting the slope parameters and the random forest model had good prediction efficacy and similar prediction accuracy. The random forest model needed to be further evaluated and verified due to its own characteristics. The modified Rothermel model was more suitable for predicting the surface fire spread rate of P. koraiensis plantations at a slope range of 0°-40° than the others.

Key words: spread rate, Rothermel model, random forest, Pinus koraiensis plantation.