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    满子源, 胡海清, 张运林, 刘方策, 李远. 帽儿山地区典型地表可燃物含水率动态变化及预测模型[J]. 北京林业大学学报, 2019, 41(3): 49-57. DOI: 10.13332/j.1000-1522.20180326
    引用本文: 满子源, 胡海清, 张运林, 刘方策, 李远. 帽儿山地区典型地表可燃物含水率动态变化及预测模型[J]. 北京林业大学学报, 2019, 41(3): 49-57. DOI: 10.13332/j.1000-1522.20180326
    Man Ziyuan, Hu Haiqing, Zhang Yunlin, Liu Fangce, Li Yuan. Dynamic change and prediction model of moisture content of surface fuel in Maoer Mountain of northeastern China[J]. Journal of Beijing Forestry University, 2019, 41(3): 49-57. DOI: 10.13332/j.1000-1522.20180326
    Citation: Man Ziyuan, Hu Haiqing, Zhang Yunlin, Liu Fangce, Li Yuan. Dynamic change and prediction model of moisture content of surface fuel in Maoer Mountain of northeastern China[J]. Journal of Beijing Forestry University, 2019, 41(3): 49-57. DOI: 10.13332/j.1000-1522.20180326

    帽儿山地区典型地表可燃物含水率动态变化及预测模型

    Dynamic change and prediction model of moisture content of surface fuel in Maoer Mountain of northeastern China

    • 摘要:
      目的可燃物含水率预测是林火预报研究的重要内容,其中地表细小可燃物、半腐殖质和腐殖质含水率在一定程度影响了林火垂直蔓延的持续性及地下火发生的可能性,含水率变化主要是受天气状态和地形特征的影响,而我国关于半腐殖质和腐殖质含水率动态变化及其预测模型的研究较少,分析红松蒙古栎针阔混交林下的地表细小可燃物、半腐殖质和腐殖质3层可燃物含水率的动态变化,对建立我国林火预报系统有指导作用。
      方法本研究对帽儿山地区红松蒙古栎典型针阔混交林下的地表细小可燃物、半腐殖质和腐殖质含水率进行每日监测,同步监测林分内气象数据,统计分析气象要素和3层可燃物含水率的相关性,选择气象要素回归法建立3层可燃物类型的含水率预测模型。
      结果在整个监测期内,地表细小可燃物含水率波动最大,最小值为10.99%,最大值为253.30%;半腐殖质次之,最小值为19.21%,最大值为238.07%;腐殖质含水率最稳定,最小值为48.45%,最大值为193.83%,波动最小。地表可燃物含水率变化对气象因子的响应最敏感,多与当日或前一日气象因子相关,半腐殖质次之,腐殖质含水率仅与空气温度相关;建立3种可燃物含水率气象要素回归预测模型,其中地表细小可燃物、半腐殖质和腐殖质的含水率预测模型平均绝对误差和平均相对误差分别为22.2%、23.5%、17.1%和7.1%、14.8%和23.4%,以MRE为15%为界限,细小可燃物和半腐殖质含水率预测模型精度均能达到林火预报精度,腐殖质含水率预测模型精度较差。
      结论综合分析可得,3层可燃物在防火期内有被引燃,进而发展为森林火灾的可能,在今后的林火预报工作中,还应该注意地下可燃物,包括半腐殖质和腐殖质含水率的预报。

       

      Abstract:
      ObjectiveThe prediction of the fuel moisture content is the major part of forest fire research and the moisture content of surface fine fuel, semi-humus and humus determines the persistence of vertical fire and the probability of underground fire. The change of moisture content is mainly affected by weather conditions and topographical features, while there are few studies on the dynamic changes of moisture content of semi-humus and humus in China. Therefore, analyzing the dynamic changes of moisture content of these three layers of fuel has a guiding role in establishing China ’s forest fire forecasting system.
      MethodThe research conducted daily monitoring of surface fine fuel, semi-humus and humus moisture content under the typical coniferous and broadleaved mixed forest in Maoer Mountain of northeastern China, the meteorological data of forest were also monitored synchronously. This study also statistically analyzed the correlations between meteorological elements and the moisture content of three layers of fuel, and the meteorological element regression method was used to establish a moisture content prediction model for three layers of fuel.
      ResultDuring the whole monitor period, the moisture content of surface fine fuel fluctuated the most, with the minimum value of 10.99% and the maximum value was 253.30%. The semi-humus was the second, and the minimum value was 19.21% and the maximum value was 238.07%. The moisture content of humus was the most stable, and the minimum value was 48.45% and the maximum value was 193.83%. The change of moisture content of surface fuel was the most sensitive to the response of meteorological factors, mostly related to the meteorological factors on the current day or the previous day, followed by semi-humus, and the moisture content of humus was only related to air temperature. Three fuel types of regression prediction model for meteorological elements of moisture content were established. The average absolute error and the average relative error of the moisture content prediction model of surface fine fuel, semi-humus and humus were 22.2%, 23.5%, 17.1% and 7.1%, 14.8%, 23.4%, respectively. The prediction model of moisture content of fine fuel and semi-humus both can basically achieve the accuracy of forest fire prediction, while the accuracy of prediction model of moisture content of humus was bad.
      ConclusionThe three layers of fuel may have a forest fire during the fire prevention period. Attention should be paid to the prediction of underground fuels, including the moisture content of semi-humus and humus, in future forest fire prevention work.

       

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