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林业科学 ›› 2019, Vol. 55 ›› Issue (7): 197-204.doi: 10.11707/j.1001-7488.20190722

• 研究简报 • 上一篇    

南方8种森林地表死可燃物在平地无风时的燃烧蔓延速率与预测模型

满子源, 孙龙, 胡海清, 张运林   

  1. 东北林业大学林学院 哈尔滨 150040
  • 收稿日期:2018-09-26 修回日期:2019-01-04 出版日期:2019-07-25 发布日期:2019-08-16
  • 基金资助:
    国家林业局“948”项目(2014-4-06)。

Prediction Model of the Spread Rate of Eight typical Surface Dead Fuel in Southern China under Windless and Flat Land

Man Ziyuan, Sun Long, Hu Haiqiang, Zhang Yunlin   

  1. College of Forestry, Northeast Forestry University Harbin 150040
  • Received:2018-09-26 Revised:2019-01-04 Online:2019-07-25 Published:2019-08-16

摘要: [目的]研究Rothermel林火蔓延速率预测模型及另外2种以Rothermel模型为核心的蔓延速率预测模型对南方8种典型森林地表死可燃物的适用性,为林火蔓延速率预测提供理论支撑和指导。[方法]以南方地区8种典型速率地表死可燃物为对象,根据研究对象的野外实际条件,在东北林业大学帽儿山实验林场风洞实验室内,构建不同可燃物床层含水率、载量及高度的可燃物床层,每种可燃物在平地无风条件下进行36次点烧试验,共288次点烧,记录每种可燃物类型不同配比条件下的蔓延速率。通过直接使用Rothermel模型、重新估计Rothermel模型参数、对Rothermel模型形式改进后自建模型的对比,得到最合适的预测模型。[结果]1)平地无风条件下,南方8种典型森林地表死可燃物床层最大蔓延速率为0.55 m·min-1,平均蔓延速率由大到小依次为:华山松、云南松、毛竹、柳杉、杉木、马尾松、麻栎及青冈栎。2)直接使用Rothermel模型预测的林火蔓延速率误差较大,平均绝对误差为0.18 m·min-1,平均相对误差为70.0%。3)重新估计参数后的Rothermel模型及自建模型,预测的可燃物蔓延速率精度显著提高,平均绝对误差分别为0.04、0.037 m·min-1,平均相对误差分别<18%、16.45%。4)重新估计参数的Rothermel模型与自建模型的预测误差的差异不显著,其中自建模型的预测值与实测值的R2变化在0.71~0.90,平均为0.80。[结论]对南方8种典型森林的地表死可燃物类型,在平地无风条件下,重新估计参数的Rothermel模型及自建模型的预测精度相近,但自建模型可能更简单易用,可预测平地无风条件下可燃物地表火蔓延速率。

关键词: Rothermel模型, 蔓延速率, 火行为, 床层高度, 含水率

Abstract: [Objective] The Rothermel model is the most widely used semi-physical prediction model at present. The aim of this study was to investigate the applicability of the Rothermel forest fire spread rate prediction model and the other two kinds of spread rate prediction models based on the Rothermel model to eight typical surface dead fine fuels in southern China to provide theoretical support and guidance for the forest fire spread rate prediction.[Method] Eight typical surface dead fine fuels in southern China were chosen as the research material, according to the actual conditions of the research material in the field, the fuel bed with different fuel moisture contents, fuel load and height was constructed in the wind tunnel laboratory of Maoer Mountain Experiment Forest Station of Northeast Forestry University. The 36 burning tests were carried out for each fuels under flat and windless condition, totaling 288 burning tests. The spread rate of each fuel type in different proportions was recorded. The most suitable prediction models for the forest fire spread rates of eight typical fuels in southern China were obtained by comparing the Rothermel model, re-estimating the Rothermel model parameters and the self-built model after improving the form of Rothermel model.[Result] 1) Under the flat and windless conditions, the maximum spread rate of eight typical fuels in southern China was 0.55 m·min-1. The average spread rate from big to small was as follows:Pinus armandi, Pinus yunnanensis, Phyllostachys edulis, Cryptomeria fortune, Cunninghamia lanceolate, Pinus massoniana, Quercus acutissima, Cyclobalanopsis glauca. 2) The Rothermel model was used to predict the spread rate of forest fire, the prediction error was large, the mean absolute error was 0.18 m·min-1, and the average relative error was 70.0%. 3) The prediction accuracy of re-estimating the Rothermel model parameters and self-built model was significantly higher than that of Rothermel model. The average absolute error of the re-estimating Rothermel model was 0.04 m·min-1, the average relative error was less than 18%; the average error of the self-built model was 0.037 m·min-1, the average relative error was 16.45%. 4) The prediction error was not significantly different between the re-estimating the Rothermel model parameters and the self-built models. The correlation coefficient between the predicted value and the measured value of the self-built model was 0.71-0.90, and the average value was 0.80.[Conclusion] For the eight typical surface dead fine fuel in southern China, the error of re-estimating the Rothemel model parameters and the self-built model was not significant, but the format of the self-built model was more simple and easy to use. The self-built model can be used to predict the surface fire spread rate of typical fuels in southern China.

Key words: Rothermel model, spread rate, fire behave, fuel bed height, moisture content

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