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Li Bingyi, Liu Guanhong, Shu Lifu. Simulation study on surface fire behavior of main forest types in Mentougou District, Beijing[J]. Journal of Beijing Forestry University, 2022, 44(6): 96-105. DOI: 10.12171/j.1000-1522.20210204
Citation: Li Bingyi, Liu Guanhong, Shu Lifu. Simulation study on surface fire behavior of main forest types in Mentougou District, Beijing[J]. Journal of Beijing Forestry University, 2022, 44(6): 96-105. DOI: 10.12171/j.1000-1522.20210204

Simulation study on surface fire behavior of main forest types in Mentougou District, Beijing

More Information
  • Received Date: June 01, 2021
  • Revised Date: July 15, 2021
  • Available Online: April 08, 2022
  • Published Date: June 24, 2022
  •   Objective  Surface fire is the most common type of forest fire, which directly affects vegetation regeneration and nutrient allocation and circulation of ecosystem. The common indexes reflecting forest fire behavior are fire spreading speed, calorific value per unit area, fire intensity and flame height. The fire behavior simulation based on the actual stand and site conditions can reveal the conditions of forest fire occurrence, effectively judge the possibility of crown fire occurrence, and provide a scientific basis for forest fire prevention and firefighting decision-making.
      Method  Typical forest stands (Robinia pseudoacacia forest, Pinus tabuliformis forest and Platycladus orientalis forest) in Mentougou District of Beijing were selected as the survey objects. 5 sample plots were set for each stand, a total of 15 sample plots. Through field investigation, the data of fuel load (shrub fuel, herb fuel, 1 h fuel load, 10 h fuel load, 100 h fuel load), stand factors (height of the first living branch, height under dead branches, tree height, DBH, canopy density) and site factors (altitude, slope gradient, slope aspect, slope position) were obtained. The BehavePlus6 software was used to simulate the fire behavior indicators of different stand types under varied fuel conditions based on meteorological parameters and fuel parameters, they are the spreading speed of surface fire, the calorific value per unit area, the intensity of fire line and the length of flame. Principal component analysis was conducted with R language, and the potential effects of stand factors, site factors and fuel factors on fire behavior were discussed according to the contribution rate.
      Result  The total fuel loads of Platycladus orientalis forest (POF), Robinia pseudoacacia forest (RPF) and Pinus tabuliformis forest (PTF) were respectively 15.35, 17.59, 15.28 t/ha, in which, the inflammable fuel loads (up-layer leaf, flammable herb, 1 h fuel) were respectively 4.55, 4.41, and 6.18 t/ha, accounting for 29.6%, 25.1% and 40.4% of the total fuel load of the stand, respectively. In the period of fire protection, the average wind speed was 2.2 m/s (corresponding to 7.92 km/h), the simulation result of surface fire rate of spread was PTF > POF > RPF, and the numerical values respectively were 11.5, 11.1, 8.0 m/min. The simulation results of fire heat per unit area were PTF > POF > RPF, and the numerical values were 23 091, 21 155, and 18 413 kJ/m2, respectively. The simulation result of fireline intensity was PTF > POF > RPF, and the numerical values were 4 426, 3 882, 2 468 kW/m. The flame height range of POF, RPF and PTF was respectively 0.89−3.40 m, 1.34−2.91 m, 1.78−3.88 m. Under the same conditions, the flame height was PTF > POF > RPF. According to the contribution rates, the principal component analysis results were different by stands. The first and second principal components in POF, RPF and PTF respectively were fuel material composition and stand factors, fuel material composition and fuel moisture content, stand factors and fuel moisture content.
      Conclusion  (1) Flammable combustible material load is a key factor affecting forest fire behavior. (2) Fuel moisture rate plays a decisive role in the value of fire behavior indicators, and the critical value of fuel moisture rate affects the type of forest fire. Combustibles are flammable when dry, and surface fires with fast spread and high intensity are easy to occur in windy weather. (3) The continuity of combustibles is the key factor that determines the development of surface fire into crown fire. The flame height greater than the height under first living or dead branches is very likely to develop from surface fire to crown fire, and it is very difficult to put out. It is recommended to prune and mow regularly to clean up the combustibles under the forest and then reduce the fire risk.
  • [1]
    白尚斌. 基于多智能体理论的林火蔓延模拟[D]. 北京: 北京林业大学, 2008.

    Bai S B. Simulation of forest fire spreading based on multi-agent theory [D]. Beijing: Beijing Forestry University, 2008.
    [2]
    赵璠, 舒立福, 周汝良, 等. 西南林区森林火灾火行为模拟模型评价[J]. 应用生态学报, 2017, 28(10): 3144−3154.

    Zhao P, Shu L F, Zhou R L, et al. Evaluating fire behavior simulators in southwestern China forest area[J]. Chinese Journal of Applied Ecology, 2017, 28(10): 3144−3154.
    [3]
    舒立福, 刘晓东. 森林防火学概论[M]. 北京: 中国林业出版社, 2016: 187−192.

    Shu L F, Liu X D. Introduction to forest fire prevention [M]. Beijing: China Forestry Publishing House, 2016: 187−192.
    [4]
    胡海清, 牛树奎. 林火生态与管理[M]. 北京: 中国林业出版社, 2005.

    Hu H Q, Niu S K. Forest fire ecology and management [M]. Beijing: China Forestry Publishing House, 2005.
    [5]
    Vilà-Vilardell L, Keeton W S, Thom D, et al. Climate change effects on wildfire hazards in the wildland-urban-interface-blue pine forests of Bhutan[J]. Forest Ecology and Management, 2020, 461: 117927. doi: 10.1016/j.foreco.2020.117927
    [6]
    牛树奎, 贺庆棠, 陈锋, 等. 北京山区主要针叶林可燃物空间连续性研究: 可燃物水平连续性与树冠火蔓延[J]. 北京林业大学学报, 2012, 34(4): 1−9.

    Niu S K, He Q T, Chen F, et al. Spatial continuity of fuels in major coniferous forests in Beijing mountainous area: fuel horizontal continuity and crown fire spread[J]. Journal of Beijing Forestry University, 2012, 34(4): 1−9.
    [7]
    陶长森, 牛树奎, 陈锋, 等. 北京山区主要针叶林潜在火行为及冠层危险指数研究[J]. 北京林业大学学报, 2019, 40(9): 55−62.

    Tao C S, Niu S K, Chen F, et al. Potential fire behavior and canopy hazard index of main coniferous forests in Beijing mountain area[J]. Journal of Beijing Forestry University, 2019, 40(9): 55−62.
    [8]
    王刚, 金晓钟. 细小可燃物易燃性的试验研究[J]. 森林防火, 1995(3): 5−7.

    Wang G, Jin X Z. Experimental study on flammability of fine fuel[J]. Forest Fire Prevention, 1995(3): 5−7.
    [9]
    陶长森, 牛树奎, 陈羚, 等. 妙峰山林场主要针叶林冠层特征及潜在火行为[J]. 北京林业大学学报, 2018, 40(5): 82−89.

    Tao C S, Niu S K, Chen L, et al. Canopy characteristics and potential crown fire behavior of main coniferous forest in Miaofeng Mountain Forest Farm in Beijing[J]. Journal of Beijing Forestry University, 2018, 40(5): 82−89.
    [10]
    赵凤君, 王明玉, 舒立福. 森林火灾中的树冠火研究[J]. 世界林业研究, 2010, 23(1): 39−43.

    Zhao F J, Wang M Y, Shu L F. A review of crown fire research[J]. World Forestry Research, 2010, 23(1): 39−43.
    [11]
    Pimont F, Dupuy J L, Linn R R, et al. Impacts of tree canopy structure on wind flows and fire propagation simulated with FIRETEC[J]. Annals of Forest Science, 2011, 68(3): 523−530. doi: 10.1007/s13595-011-0061-7
    [12]
    Stankevich T S. Forecasting the spatial behavior of a forest fire at uncertainty and instability of the process[J]. Lesnoy Zhurnal (Forestry Journal), 2021(1): 20−34. doi: 10.37482/0536-1036-2021-1-20-34
    [13]
    Arif M, Alghamdi K K, Sahel S A, et al. Role of machine learning algorithms in forest fire management: a literature review[J]. Journal of Robotics and Automation, 2021, 5(1): 212−226.
    [14]
    Finney M A. Design of regular landscape fuel treatment patterns for modifying fire growth and behavior[J]. Forest Science, 2001, 47(2): 219−228.
    [15]
    Marshall G, Dan K T, Anderson K, et al. The impact of fuel treatments on wildfire behavior in North American boreal fuels: a simulation study using FIRETEC[J]. Fire, 2020, 3(2): 18. doi: 10.3390/fire3020018
    [16]
    Xie H T, Fawcett J E, Wang G G. Fuel dynamics and its implication to fire behavior in loblolly pine-dominated stands after southern pine beetle outbreak[J]. Forest Ecology and Management, 2020, 466: 118130. doi: 10.1016/j.foreco.2020.118130
    [17]
    Iqbal N I, Ahmad S, Kim D H. Towards mountain fire safety using fire spread predictive analytics and mountain fire containment in IoT environment[J]. Sustainability, 2021, 13(5): 2461. doi: 10.3390/su13052461
    [18]
    Andrews P L. Current status and future needs of the BehavePlus fire modeling system[J]. International Journal of Wildland Fire, 2014, 23(1): 21−33. doi: 10.1071/WF12167
    [19]
    Starns H D, Fuhlendorf S D, Elmore R D, et al. Recoupling fire and grazing reduces wildland fuel loads on rangelands [J/OL]. Ecosphere, 2019, 10(1): e02578[2021−08−15]. https://esajournals.onlinelibrary.wiley.com/doi/full/10.1002/ecs2.2578.
    [20]
    Hahn G E, Coates T A, Aust W M, et al. Long-term impacts of silvicultural treatments on wildland fuels and modeled fire behavior in the Ridge and Valley Province, Virginia (USA)[J]. Forest Ecology and Management, 2021, 496: 119475. doi: 10.1016/j.foreco.2021.119475
    [21]
    Rothermel R C. How to predict the spread and intensity of forest and range fires [M]. Ogden: General Technical Report/Intermountain Forest and Range Experiment Station, 1983: 161.
    [22]
    Bufacchi P, Santos J C, de Carvalho J A, et al. Estimation of the surface area-to-volume ratios of litter components of the Brazilian rainforest and their impact on litter fire rate of spread and flammability[J]. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2020, 42(5): 1−10.
    [23]
    Drury S A, Rauscher H M, Banwell E M, et al. The interagency fuels treatment decision support system: functionality for fuels treatment planning[J]. Fire Ecology, 2016, 12(1): 103−123.
    [24]
    Gibson S. Examining the effect of annual grass invasion on fire spread and severity: fuel modeling for Ventenata dubia[D]. Corvallis: Oregon State University, 2021.
    [25]
    Zhiri A B, Olayiwola R O, Odo C E. Modeling fire spread behavior in coupled atmospheric-forest fire[J]. Journal of Science, Technology, Mathematics and Education (JOSTMED), 2020, 16(4): 104−113.
    [26]
    赵方莹, 程小琴. 门头沟区煤矿废弃地自然恢复植物群落种间关系[J]. 东北林业大学学报, 2010, 38(8): 50−53.

    Zhao F Y, Cheng X Q. Interspecific relationship of plant communities in degraded mined land in Mentougou District, Beijing during natural rehabilitation[J]. Journal of Northeast Forestry University, 2010, 38(8): 50−53.
    [27]
    王九中, 邬明权. 北京市门头沟区2003—2014年植被初级生产力时空变化[J]. 华东师范大学学报(自然科学版), 2018, 197(1): 168−175.

    Wang J Z, Wu M Q. Spatio-temporal analysis about the primary productivity of Mentougou District in Beijing from 2003 to 2014[J]. Journal of East China Normal University (Natural Science), 2018, 197(1): 168−175.
    [28]
    李克. 北京山区主要森林类型潜在火行为及扑救措施研究[D]. 北京: 北京林业大学, 2019.

    Li K. Fire behavior and fighting measures of major forest types in the mountainous area [D]. Beijing: Beijing Forestry University, 2019.
    [29]
    韩梅, 温鹏, 许慧敏, 等. 北京市十三陵林场油松林地表火行为模拟[J]. 北京林业大学学报, 2019, 40(10): 95−101.

    Han M, Wen P, Xu H M, et al. Simulation of surface fire behavior of Pinus tabuliformis forest in Ming Tombs Forest Farm in Beijing[J]. Journal of Beijing Forestry University, 2019, 40(10): 95−101.
    [30]
    Rothermel R. A mathematical model for predicting fire spread in wildland fuels [M]. Ogden: General Technical Report/Intermountain Forest and Range Experiment Station, 1972: 115.
    [31]
    舒立福, 王明玉, 田晓瑞, 等. 关于森林燃烧火行为特征参数的计算与表述[J]. 林业科学, 2004, 40(3): 179−183. doi: 10.3321/j.issn:1001-7488.2004.03.031

    Shu L F, Wang M Y, Tian X R, et al. Calculation and description of forest fire behavior characters[J]. Scientia Silvae Sinicae, 2004, 40(3): 179−183. doi: 10.3321/j.issn:1001-7488.2004.03.031
    [32]
    卢欣艳. 北京西山森林火险影响因素时空规律研究[D]. 北京: 北京林业大学, 2010.

    Lu X Y. The spatial and temporal rules of forest fire factors in Beijng Xishan Centre [D]. Beijing: Beijing Forestry University, 2010.
    [33]
    宁吉彬, 瓮岳太, 邸雪颖, 等. 大兴安岭沟塘草甸地表可燃物载量快速测定方法[J]. 东北林业大学学报, 2018, 46(5): 44−48. doi: 10.3969/j.issn.1000-5382.2018.05.009

    Ning J B, Weng Y T, Di X Y, et al. Rapid determination method for swamp meadow surface fuel loads of Daxing’an Mountains[J]. Journal of Northeast Forestry University, 2018, 46(5): 44−48. doi: 10.3969/j.issn.1000-5382.2018.05.009
    [34]
    刘冠宏. 北京地区典型林分地表火及向树冠火蔓延机制研究[D]. 北京: 北京林业大学, 2019.

    Liu G H. Study on the mechanism of surface fire and spread of canopy fire of typical tree species in Beijing area [D]. Beijing: Beijing Forestry University, 2019.
    [35]
    单延龙, 舒立福, 王洪伟, 等. Rothermel火蔓延模型特征参数的解析[J]. 森林防火, 2003(1): 22−25. doi: 10.3969/j.issn.1002-2511.2003.01.012

    Shan Y L, Shu L F, Wang H W, et al. Analysis of characteristic parameters of Rothermel’s fire spread model[J]. Forest Fire Prevention, 2003(1): 22−25. doi: 10.3969/j.issn.1002-2511.2003.01.012
    [36]
    王凯, 牛树奎. 基于Rothermel模型的北京鹫峰国家森林公园潜在火行为[J]. 浙江农林大学学报, 2016, 33(1): 42−50. doi: 10.11833/j.issn.2095-0756.2016.01.006

    Wang K, Niu S K. Research on the potential fire behavior in Jiufeng National Forest Park of Beijing based on the Rothermel Model[J]. Journal of Zhejiang A&F University, 2016, 33(1): 42−50. doi: 10.11833/j.issn.2095-0756.2016.01.006
    [37]
    田晓瑞, 舒立福, 阎海平, 等. 华北地区防火树种筛选[J]. 火灾科学, 2002, 11(1): 43−48. doi: 10.3969/j.issn.1004-5309.2002.01.007

    Tian X R, Shu L F, Yan H P, et al. Selecting fire-resistance tree species in northern China[J]. Fire Safety Science, 2002, 11(1): 43−48. doi: 10.3969/j.issn.1004-5309.2002.01.007
    [38]
    田晓瑞, 舒立福, 乔启宇, 等. 南方林区防火树种的筛选研究[J]. 北京林业大学学报, 2001, 23(5): 43−47. doi: 10.3321/j.issn:1000-1522.2001.05.011

    Tian X R, Shu L F, Qiao Q Y, et al. Research on fire-resistance tree species in south China[J]. Journal of Beijing Forestry University, 2001, 23(5): 43−47. doi: 10.3321/j.issn:1000-1522.2001.05.011
    [39]
    李炳怡, 刘冠宏, 李伟克, 等. 不同火强度对河北平泉油松林土壤有机碳及土壤养分影响[J]. 生态科学, 2018, 37(4): 35−44.

    Li B Y, Liu G H, Li W K, et al. Effects of different wildfire intensities on soil organic carbon and soil nutrients in Pinus tabulaeformis forests in Pingquan County, Hebei Province[J]. Ecological Science, 2018, 37(4): 35−44.
    [40]
    郭利峰. 北京八达岭林场人工油松林燃烧性研究[D]. 北京: 北京林业大学, 2007.

    Guo L F. Research on artificial Pinus tabulaeformis forest combustibility of Badaling Forest Center in Beijing [D]. Beijing: Beijing Forestry University, 2007.
    [41]
    葛学林, 董广生. 林火学 [M]. 哈尔滨: 东北林业大学出版社, 1997: 132−181, 163.

    Ge X L, Dong G S. Forest fire science [M]. Harbin: Northeast Forestry University Press, 1997: 132−181, 163.
    [42]
    李炳怡, 丁永全, 舒立福, 等. 我国人工林森林可燃物特点及管理技术研究进展[J]. 世界林业研究, 2020, 34(1): 90−95.

    Li B Y, Ding Y Q, Shu L F, et al. Research progress in plantation fuel characteristics and management in China[J]. World Forestry Research, 2020, 34(1): 90−95.
    [43]
    Tian X R, Shu L F, He Q T. Selection of fire-resistant tree species for southwestern China[J]. Forest Ecosystems (Forestry Studies in China), 2001, 3(2): 32−38.
    [44]
    李世友, 王秋华, 张尚书, 等. 滇东北中高海拔地区防火树种筛选[J]. 西南林学院学报, 2006, 26(3): 55−58.

    Li S Y, Wang Q H, Zhang S S, et al. Selection of fire resistant tree species for the middle-high altitude areas in northeastern part of Yunnan Province[J]. Journal of Southwest Forestry University, 2006, 26(3): 55−58.
    [45]
    闫想想, 王秋华, 李晓娜, 等. 昆明周边主要林型地表可燃物的燃烧特性研究[J]. 西南林业大学学报, 2020, 40(5): 135−142. doi: 10.11929/j.swfu.201912035

    Yan X X, Wang Q H, Li X N, et al. Combustibility of surface fuels in major forest types around Kunming[J]. Journal of Southwest Forestry University, 2020, 40(5): 135−142. doi: 10.11929/j.swfu.201912035
    [46]
    王晓丽. 北京山区森林燃烧性研究[D]. 北京: 北京林业大学, 2010.

    Wang X L. Study on combustibility of forests in Beijing mountain area [D]. Beijing: Beijing Forestry University, 2010.
    [47]
    Banerjee T, Heilman W, Goodrick S, et al. Effects of canopy midstory management and fuel moisture on wildfire behavior[J]. Scientific Reports, 2020, 10(1): 17312. doi: 10.1038/s41598-020-74338-9
    [48]
    贺红士, 常禹, 胡远满, 等. 森林可燃物及其管理的研究进展与展望[J]. 植物生态学报, 2010, 34(6): 741−752. doi: 10.3773/j.issn.1005-264x.2010.06.013

    He H S, Chang Y, Hu Y M, et al. Contemporary studies and future perspectives of forest fuel and fuel management[J]. Chinese Journal of Plant Ecology, 2010, 34(6): 741−752. doi: 10.3773/j.issn.1005-264x.2010.06.013
    [49]
    van Wagner C E. Prediction of crown fire behavior in two stands of jack pine[J]. Canadian Journal of Forest Research, 1993, 23(3): 442−449. doi: 10.1139/x93-062
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