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大兴安岭典型林分地表死可燃物含水率动态变化及预测模型 被引量:20

Dynamics and prediction models of ground surface dead fuel moisture content for typical stands in Great Xing'an Mountains,Northeast China
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摘要 对春季和秋季大兴安岭地区西林吉林业局山杨-白桦混交林、落叶松林、樟子松林、落叶松-白桦混交林、白桦林5种典型林分不同坡位地表细小死可燃物含水率动态进行研究,构建了不同季节防火期、不同林分地表死可燃物含水率的预测模型,并分析了其预测误差.结果表明:相同林分地表可燃物含水率在春季和秋季差异显著;在相同季节相同林分下不同坡位可燃物含水率存在差异.采用Nelson模型对地表死可燃物含水率预测的平均绝对误差(MAE)的平均值为0.13,略低于Simard模型(0.14),明显低于气象要素回归模型(0.25).Nelson和Simard模型的预测效果好于气象要素回归模型.秋季模型对地表死可燃物含水率的预测精度好于春季模型和春季秋季混合模型. The fuel moisture content dynamics of mixed forest of Populus davidiana- Betula platyphylla, Larix gmelinii, Pinus sylvestris var. mongolica, mixed forest of L. gmelinii- B. platyphylla, B. platyphylla at different slope positions in spring and autumn were investigated in Xilinji Forestry Bureau ofthe Great Xing' an Mountains region. The moisture content prediction mod- els of different stands in different seasons were established and the predicted errors were analyzed. The results showed that the fuel moisture content in the same stand varied with slope position. The mean absolute error of Nelson model (0.13) was lower than that of Simard model (0.14), and was significantly lower than that of meteorological element regression model (0.25). The prediction ac- curacy of the autumn model was higher than the spring model and spring-autumn mixed model.
出处 《应用生态学报》 CAS CSCD 北大核心 2016年第7期2212-2224,共13页 Chinese Journal of Applied Ecology
基金 林业公益性行业科研专项(201404402)资助~~
关键词 大兴安岭 地表死可燃物 含水率 气象要素回归 Great Xing' an Mountains surface dead fuel moisture content meteorological ele-ment regression.
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  • 1田甜,邸雪颖.森林地表可燃物含水率变化机理及影响因子研究概述[J].森林工程,2013,29(2):21-25. 被引量:25
  • 2Rothermel RC, Wilson RA, Morris GA, et al. Modeling moisture content of fine dead wildland fuels: Input to the behave fire prediction system// United States Depart- ment of Agriculture Forest Service Intermountain Re- search Station, ed. USDA Forest Service Research Paper INT-359. Ogden, UT: Intermountain Forest and Range Experiment Station, Forest Service, United States De- partment of Agriculture, 1986:1-61.
  • 3Nelson RM. Prediction of diurnal change in 10-h fuel stick moisture content. Canadian Journal of Forest Re-search, 2000, 30:1071-1087.
  • 4Toomey M, Vierling LA. Muhispectral remote sensing of landscape level foliar moisture: Techniques and applica- tions for forest ecosystem monitoring. Canadian Journal of Forest Research, 2005, 35 : 1087-1097.
  • 5Pellizzaro G, Cesaraccio C, Duce P, et al. Influence of seasonal weather variations and vegetative cycle on live moisture content and ignitability in Mediterranean ma- quis species. Forest Ecology and Management, 2006, 234: Slll.
  • 6金森,李绪尧,李有祥.几种细小可燃物失水过程中含水率的变化规律[J].东北林业大学学报,2000,28(1):35-38. 被引量:40
  • 7金森,姜文娟,孙玉英.用时滞和平衡含水率准确预测可燃物含水率的理论算法[J].森林防火,1999,0(4):12-14. 被引量:26
  • 8Catchpole EA, Catchpole WR, Viney NR, et al. Esti- mating fuel response time and predicting fuel moisture content from field data. International Journal of Wildland Fire,2001, 10:215-222.
  • 9Van Wagner CE. Equilibrium moisture contents of some fine forest fuels in eastern Canada// Petawawa Forest Experiment Station, ed. Petawawa Forest Experiment Station Information Report PS-X-36. Ontario, Canadian: Petawawa Forest Experiment Station, Canadian Forestry Service, 1972: 56-62.
  • 10Viney NR, Catchpole EA. Estimating fuel moisture re- sponse times from field observations. International Jour- nal of Wildland Fire, 1991, 1:211-214.

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