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林业科学 ›› 2011, Vol. 47 ›› Issue (6): 114-121.doi: 10.11707/j.1001-7488.20110617

• 论文 • 上一篇    下一篇

用直接估计法预测落叶松枯枝含水率的稳定性和外推误差分析

金森, 李亮, 赵玉晶   

  1. 东北林业大学林学院 哈尔滨 150040
  • 收稿日期:2010-11-15 修回日期:2010-12-12 出版日期:2011-06-25 发布日期:2011-06-25

Analysis on Robustness and Extrapolation Errors of Modeling Fuel Moisture Content of Dead Twigs of Larch by Direct Estimation From Observed Data

Jin Sen, Li Liang, Zhao Yujing   

  1. College of Forestry, Northeast Forestry University Harbin 150040
  • Received:2010-11-15 Revised:2010-12-12 Online:2011-06-25 Published:2011-06-25

摘要:

采用Catchpole等提出的直接估计法分析实验室中3组不同直径(0.5,1.0,1.5 cm)的兴安落叶松枯枝的失水过程,通过交叉验证研究所得模型的稳定性,并对模型的外推误差进行分析。结果表明: 枯枝的时滞和平衡含水率参数变化很小,结果具有良好的稳定性。同一直径的不同枝条在时滞、平衡含水率参数等方面存在差异。模型外推没有改变残差的正态分布,但外推后的残差增大。非外推残差集中出现在数值较小的区间上,而外推残差在这些区间上出现的概率下降,在非外推残差没有出现的数值较大的区间上出现的概率增加。研究给出枯枝在不同含水率预测值时不同残差出现的条件概率和均值。随含水率预测值的增加,残差有增加的趋势,不仅是平均值,大的残差出现的概率也在增加。据此可对外推模型所预测的含水率进行评判,确定其误差均值和不同残差出现的可能性,以减少据此进行的火险预报和火行为预报中的不确定性。用至少4个枯枝的混合数据在一定程度上可降低外推误差,减少这种不确定性。由于所有材料和实验条件最大程度上减少了材料和环境的差异,上述结果也可被看作用模型外推预测野外可燃物含水率时可能出现的误差的下限。

关键词: 落叶松, 可燃物, 含水率, 稳定性, 外推, 误差

Abstract:

Absorption processes of dead larch twigs with three different diameters(0.5, 1.0 and 1.5 cm) in laboratory were modeled by a method proposed by Catchpole et al.(2001). Robustness of the model was tested by cross validation. Errors occurred in the model extrapolation were also analyzed. Results showed that moisture-related parameters of timelag and equilibrium moisture content had small variation in the cross validation, which indicated the results were quite robust. Variety existed in timelag and parameters related to equilibrium moisture content among twigs with the same diameter. Although both the errors in applying the models to data on which the models were based and those in applying the models to data on which the models were not based followed normal distribution, the latter was larger than the former. The latter errors occurred with lower probability in sections where the former errors occurred with higher probability and also occurred in sections where the latter errors did not occur. This paper also presented conditional probability and means of errors under different predicted fuel moisture content, which indicated that not only the means but also the probability of larger errors increased with increasing predicted moisture. This probability could allow users of the models to estimate errors on a particular predicted moisture value, which can reduce uncertainty in fire danger rating and fire behavior modeling which uses the predicted moisture. The results also suggested that models established using pooled data from at least 4 twigs could reduce the uncertainty in the model extrapolation in fuel moisture prediction. Since the variation between the twigs and conditions is much less than those occurred in the field, the results can be regarded as lower limits of errors occurred in model extrapolation, which, nevertheless, can provide useful clues to assess model performance when it is extrapolated though full evaluation of the performance is still needed by further research.

Key words: larch, fuel, moisture content, robustness, extrapolation, error

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