林业科学 ›› 2021, Vol. 57 ›› Issue (7): 121-130.doi: 10.11707/j.1001-7488.20210713
宁吉彬,耿道通,于宏洲,邸雪颖,杨光*
收稿日期:
2019-11-07
出版日期:
2021-07-25
发布日期:
2021-09-02
通讯作者:
杨光
基金资助:
Jibin Ning,Daotong Geng,Hongzhou Yu,Xueying Di,Guang Yang*
Received:
2019-11-07
Online:
2021-07-25
Published:
2021-09-02
Contact:
Guang Yang
摘要:
目的: 基于室内模拟的飞火引燃试验数据,使用Logistic模型对影响飞火引燃的因子进行建模,探究该模型在预测飞火引燃中的适用性,为林火行为研究提供依据和参考。方法: 选取黑龙江大兴安岭兴安落叶松纯林为对象,以球果、1 h时滞、10 h时滞小枝为火源,构造不同风速、可燃物含水率和压缩比的可燃物床层,进行引燃试验,建立以Logistic模型为基础的3种火源的引燃概率模型。结果: 3种类型火源分别进行了1 800次点烧试验,球果、1 h时滞和10 h时滞小枝引燃次数分别为414、161和337次;本研究梯度范围内,火源引燃概率随着风速增加而显著增加;可燃物含水率与引燃概率负相关,但受火源的干质量影响较大,在可燃物含水率为40%时,较大的3种火源干质量造成了引燃率升高;床层压缩比对火源引燃概率并没有表现出明显的正或负相关性;构建的球果模型预测引燃准确率为87.2%,总预测准确率为71.1%;1 h时滞小枝模型预测引燃准确率为79.6%,总预测准确率为78.6%;10 h时滞小枝模型预测引燃准确率为81.5%,总预测准确率为79.5%。结论: 3种火源引燃能力为球果>10 h时滞小枝>1 h时滞小枝,风速、可燃物含水率和火源干质量对引燃有较大作用,建立的3种Logistic引燃概率模型有较高准确率,可供飞火引燃预测时参考,以提高森林火灾扑救效率和减少扑救伤亡。
中图分类号:
宁吉彬,耿道通,于宏洲,邸雪颖,杨光. 基于Logistic回归的兴安落叶松林飞火引燃试验[J]. 林业科学, 2021, 57(7): 121-130.
Jibin Ning,Daotong Geng,Hongzhou Yu,Xueying Di,Guang Yang. Experiment on Spotting Ignition of Larix gmelinii Forest Based on Logistic Regression[J]. Scientia Silvae Sinicae, 2021, 57(7): 121-130.
表1
试验材料基本特征及燃烧特性"
试验材料 Experimental materials | 长度 Length (cm·ind-1) | 直径 Diameter (cm·ind-1) | 干质量 Dry mass (g· ind-1) | 含水率 Moisture content(%) | 灰分 Ash(%) | 抽提物 Extract(%) |
球果Cone | 1.955 | 2.052 | 0.566 | 7.254 | 0.025 | 0.083 |
1 h时滞小枝1 h time-lag twig | 5 | 0.428 | 0.436 | 5.649 | 0.100 | 3.667 |
10 h时滞小枝10 h time-lag twig | 5 | 0.956 | 0.342 | 2.654 | 0.130 | 2.500 |
可燃物床层Fuel bed | — | — | 42.4 | 29.591 | 0.031 | 3.000 |
表2
3种火源模型多重共线性诊断(VIF值)"
变量 Variables | 球果模型 Cone model | 1 h时滞小枝模型 1 h time-lag twig model | 10 h时滞小枝模型 10 h time-lag twig model |
温度Temperature | 1.256 | 1.153 | 1.848 |
相对湿度 Relative humidity | 1.265 | 2.518 | 2.167 |
风速Wind speed | 1.141 | 1.046 | 1.035 |
火源干质量 Firebrand ovendry mass | 3.571 | 3.986 | 5.495 |
火源含水率 Firebrand moisture content | 1.145 | 1.192 | 1.159 |
火源直径 Firebrand diameter | 1.572 | 3.818 | 5.285 |
火源长度 Firebrand length | 2.960 | — | — |
可燃物含水率 Fuel moisture content | 1.109 | 1.096 | 1.114 |
压缩比Packing ratio | 1.103 | 2.508 | 1.327 |
表3
Logistic模型变量在中间样本中的显著性次数"
变量 Variables | 球果模型 Cone model | 1 h时滞小枝模型 1 h time-lag twig model | 10 h时滞小枝模型 10 h time-lag twig model |
温度Temperature | 2 | 2 | 0 |
相对湿度 Relative humidity | 2 | 1 | 0 |
风速Wind speed | 5 | 5 | 5 |
火源干质量 Firebrand ovendry mass | 3 | 5 | 0 |
火源含水率 Firebrand moisture content | 0 | 1 | 5 |
火源直径 Firebrand diameter | 2 | 1 | 1 |
火源长度 Firebrand length | 2 | — | — |
压缩比 Packing ratio | 1 | 3 | 0 |
可燃物含水率 Fuel moisture content | 5 | 5 | 5 |
表4
基于建模样本的Logistic模型参数拟合"
火源类型Firebrand type | 变量Variables | 系数Coefficient | 标准误SE | 显著性Sig |
球果模型 Cone model | 风速Wind speed | 1.078 | 0.083 | 0.000 |
火源干质量Firebrand ovendry weight | 2.377 | 0.397 | 0.000 | |
可燃物含水率Fuel moisture content | -3.778 | 0.579 | 0.000 | |
常量Constant | -4.552 | 0.410 | 0.000 | |
1 h时滞小枝模型 1 h time-lag twig model | 风速Wind speed | 1.240 | 0.135 | 0.000 |
火源干质量Firebrand ovendry weight | 3.396 | 0.560 | 0.000 | |
可燃物含水率Fuel moisture content | -2.850 | 0.849 | 0.001 | |
压缩比Packing ratio | -28.679 | 9.912 | 0.004 | |
常量Constant | -4.684 | 0.887 | 0.000 | |
10 h时滞小枝模型 10 h time-lag twig model | 风速Wind speed | 1.575 | 0.119 | 0.000 |
可燃物含水率Fuel moisture content | -2.427 | 0.645 | 0.000 | |
火源含水率Firebrand moisture content | 11.495 | 4.164 | 0.006 | |
常量Constant | -5.919 | 0.466 | 0.000 |
表5
Logistic模型预测准确率"
火源类型 Firebrand type | 样本类型 Sample type | 预测引燃准确率 Prediction accuracy of ignition | 预测未燃准确率 Prediction accuracy of unignited | 总预测准确率 Total prediction accuracy |
球果模型 Cone model | 建模样本Modeling sample | 87.2 | 65.9 | 71.1 |
验证样本Validating sample | 81.8 | 65.3 | 69.3 | |
1 h时滞小枝模型 1 h time-lag twig mode | 建模样本Modeling sample | 79.6 | 78.5 | 78.6 |
验证样本Validating sample | 75.5 | 81.7 | 81.2 | |
10 h时滞小枝模型 10 h time-lag twig mode | 建模样本Modeling sample | 81.5 | 79.0 | 79.5 |
验证样本Validating sample | 82.1 | 77.6 | 78.7 |
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