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应用生态学报 ›› 2018, Vol. 29 ›› Issue (12): 3959-3968.doi: 10.13287/j.1001-9332.201812.008

• 研究论文 • 上一篇    下一篇

以小时为步长的大兴安岭典型林分地表死可燃物含水率模型预测及外推精度

于宏洲1,2,舒立福2,邓继峰3*,杨光1,梁启4,李景浩5,朱航勇6   

  1. 1东北林业大学林学院, 哈尔滨 150040;
    2中国林业科学研究院森林生态环境与保护研究所, 北京 100091;
    3沈阳农业大学林学院, 沈阳 110866;
    4吉林省林业勘察设计研究院, 长春 130022;
    5国家林业局森林病虫害防治总站, 沈阳 110034;
    6哈尔滨市林业科学研究院, 哈尔滨 150028
  • 收稿日期:2018-05-10 修回日期:2018-09-19 出版日期:2018-12-20 发布日期:2018-12-20
  • 作者简介:于宏洲, 男, 1983年生, 博士, 讲师. 主要从事森林防火与GIS研究. E-mail: yhz-163@163.com
  • 基金资助:
    本文由国家自然科学基金项目(31700575,31870644,31800609)、国家重点研发计划项目(2017YFD0600106-2)和沈阳农业大学引进人才启动经费项目(2015年度)资助

Prediction models and the extrapolation effects for water content of surface dead fuels in the typical stand of the Great Xing’an Mountains of China by one-hour time step

YU Hong-zhou1,2, SHU Li-fu2, DENG Ji-feng3*, YANG Guang1, LIANG Qi4, LI Jing-hao5, ZHU Hang-yong6   

  1. 1College of Forestry, Northeast Forestry University, Harbin 150040, China;
    2Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China;
    3College of Forestry, Shenyang Agricultural University, Shenyang 110866, China;
    4Jilin Academy of Forestry Survey and Design, Changchun 130022, China;
    5Forest Pest Control Station of the State Forestry Administration, Shenyang 110034, China;
    6Harbin Forestry Academy, Harbin 150028, China
  • Received:2018-05-10 Revised:2018-09-19 Online:2018-12-20 Published:2018-12-20
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (31700575, 31870644, 31800609), the National Key Research and Development Plan (2017YFD0600106-2), and the Shenyang Agricultural University Startup Foundation for Introduced Talents (2015).

摘要: 地表死可燃物含水率是火险天气和火行为预报中的重要指标.本研究基于时滞平衡含水率法(Nelson和Simard方法)及气象要素回归方法,于2010年9—10月对黑龙江省大兴安岭地区盘古林场不同郁闭度的山杨-白桦混交林、红皮云杉纯林,以及采伐迹地(原1∶1樟子松-白桦混交林)地表死可燃物含水率进行以小时为步长的连续测定,建立其预测模型,得到预测误差,并使用相应的模型对其他林分地表死可燃物含水率进行外推精度分析.结果表明:采用Nelson平衡含水率法构建的地表死可燃物含水率变化模型的平均绝对误差、平均相对误差和均方误差根(0.0154、0.104和0.0226)低于Simard法(0.0185、0.117和0.0256)和气象要素回归法(0.0222、0.150和0.0331).在外推效果方面,气象要素回归法的平均绝对误差、平均相对误差和均方误差根(0.0410、0.0300和0.0740)低于Simard法(0.610、0.492和0.846),但前两者均高于Nelson法(0.034、0.021和0.0660),说明以小时为步长的时滞平衡含水率法,尤其是Nelson法适用于大兴安岭地区所测林分.外推虽不能降低误差,但有助于提高现有模型应用至不同林分条件或大尺度范围内的地表死可燃物含水率预测精度和利用率.模型建模和外推误差与不同树种和郁闭度条件差异有关,研究时应根据不同林分和地点选择合适的平衡含水率模型.

Abstract: The water content of surface dead fuels is one of the most important indicators for forecasting fire danger and fire behaviors. We employed the timelag equilibrium water content methods (i.e. Nelson and Simard models) and the meteorological variable regression method to continuously measure the water content of surface dead fuels by one-hour time step from September to October in 2010 under Populus davidiana + Betula platyphylla, Picea koraiensis and the cutover lands (Pinus sylvestris var. mongolica + Betula platyphylla) with different canopy densities in Pangu Forestry Bureau, the Great Xing’an Mountains, Heilongjiang Province, China. We established prediction models and obtained prediction errors. The models were also used to extrapolate the water contents of surface dead fuels under other forest stands and the extrapolation accuracy was analyzed. The results showed that the mean absolute error, the mean relative error and the mean square error root of Nelson model (0.0154, 0.104 and 0.0226) were lower than those of Simard model (0.0185, 0.117 and 0.0256). In terms of extrapolation effects, the mean absolute error, the mean relative error and the mean square error root of meteorological variable regression method (0.0410, 0.0300 and 0.0740) were lower than those of Simard model (0.610, 0.492 and 0.846), but they were higher than those of Nelson model (0.034, 0.021 and 0.0660). Such results indicated that the timelag equilibrium moisture content method by one-hour time step, especially Nelson model, was sui-table for the forest stands in the Great Xing’an Mountains. Although extrapolation could not reduce the prediction errors, it could help improve the prediction accuracy and the efficiency of the present models applied to different forest stands or in a larger scale. The modeling and extrapolation errors were closely related to species identity and canopy densities, thus the appropriate timelag equilibrium moisture content methods should be selected according to different forest stands and locations.