川西地区常见森林类型枯落物燃烧性状差异分析
Analysis of the Variation in Burning Characteristics of Litters from Different Forest Types in Western Sichuan
刘韩 1李淑婷 2吴富雨 1兰常军 3崔兴雷 4郑江坤 4侯贵荣4
作者信息
- 1. 甘孜藏族自治州林业科学研究所,四川康定 626001
- 2. 四川农业大学林学院,四川成都 611130
- 3. 峨边彝族自治县毛坪镇人民政府下属事业单位农业综合服务中心,四川乐山 614307
- 4. 四川农业大学林学院,四川成都 611130;国家林业草原西南森林与草原生态防火工程技术研究中心,四川成都 611130
- 折叠
摘要
[目的]研究川西地区常见森林类型枯落物的燃烧性状,评估不同森林类型发生地表火的风险及强度.[方法]选取川西地区常见的6种森林类型,分别测定了其枯落物的含水率、灰分、燃点、干重热值(GCV)、去灰分热值(AFCV);利用主成分分析,综合评价了不同森林类型枯落物的燃烧性差异.[结果]不同森林类型之间,枯落物的含水率、燃点、GCV、AFCV有差异.通过综合分析,将川西地区6种常见森林类型枯落物的燃烧性进行排序,从高到低为辐射松＞高山松＞高山栎＞华山松＞云南松＞云杉-冷杉混交林.[结论]对川西地区常见森林类型林下枯落物的燃烧性进行测定分析,有助于预测不同森林类型发生地表火的风险和强度,同时可为火灾预防提供参考.
Abstract
[Objective]To study the burning characteristics of litters from different common forest types in west Sichuan can help assess the risk and intensity of surface fires in different forest types.[Method]Six common forest types in the western Sichuan region were selected and their litter moisture content,ash content,ignition point,dry weight calorific value(GCV),and ash free calorific value(AFCV)were measured.By using principal component analysis,the variation in burning characteristics across different forests were comprehensively evaluated.[Result]The results showed that the differences in moisture content,ignition point,gross calorific value(GCV),and ash-free calorific value(AFCV)were significant among different forest types.Through comprehensive analysis,the flammability of litters from six common forest types in western Sichuan was ranked as follows:Pinus radiata＞Pinus densata＞Pinus armandii＞Quercus semicarpifolia＞Pinus yunnanensis＞Picea asperata-Abies fabri.[Conclusion]In this study,we measured and analyzed the burning characteristics of litters from six common forest types in western Sichuan.Our study can help predict the risk and intensity of surface fires in different forest types,and provide references for fire prevention.
关键词
枯落物/燃烧性状/主成分分析/川西林区Key words
Litter/Flammability/Principal component analysis/West Sichuan region引用本文复制引用
出版年
2023
国家科技期刊平台
NSTL
维普
万方数据