Future impacts of climate change on forest fire danger in northeastern China

Climate warming has a rapid and far-reaching impact on forest fire management in the boreal forests of China. Regional climate model outputs and the Canadian Forest Fire Weather Index （FWI） Sys- tem were used to analyze changes to fire danger and the fire season for future periods under IPCC Special Report on Emission Scenarios （SRES） A2 and B2, and the data will guide future fire management planning. We used regional climate in China （1961 1990） as our validation data, and the period （1991–2100） was modeled under SRES A2 and B2 through the weather simulated by the regional climate model system （PRECIS）. Meteorological data and fire danger were interpolated to 1 km 2 by using ANUSPLIN software. The average FWI value for future spring fire sea- sons under Scenarios A2 and B2 shows an increase over most of the region. Compared with the baseline, FWI averages of spring fire season will increase by 0.40, 0.26 and 1.32 under Scenario A2, and increase by 0.60, 1.54 and 2.56 under Scenario B2 in 2020s, 2050s and 2080s, respectively. FWI averages of autumn fire season also show an increase over most of the region. FWI values increase more for Scenario B2 than for Scenario A2 in the same periods, particularly during the 2050s and 2080s. Average future FWI values will increase under both scenarios for autumn fire season. The potential burned areas are expected to increase by 10% and 18% in spring for 2080s under Scenario A2 and B2, respectively. Fire season will be prolonged by 21 and 26 days under ScenariosA2 and B2 in 2080s respectively.

Forest fire danger ratings in the 2040s for northeastern China

The average temperature of northeastern China is expected to increase 2.22 and 2.55℃ under two scenarios selected from the Intergovemmental Panel on Climate Change （IPCC）, i.e., A2 and B2, during the 2040s （2041-2050）, which will have an impact on fire activities in those areas. We calculated the output of regional climate models, using the Canadian Forest Fire Weather Index （FWI） on a scale of 50 km × 50 km. Meteorological data and fire weather index were interpolated to a scale of 1 km × 1 km by using ANUSPLIN software. The results show that the model of Providing Regional Climate for Impacts Studies （PRECIS） had the ability to provide good temperature and precipitation estimates of the study area in the baseline period, by simulation. In the 2040s the mean FWI values of the study area will increase during most of the fire seasons under both selected scenarios, compared with the baseline period. Under scenario B2 the peak fire season will appear in advance. The changes of FWI ratio （2×CO2/l ×CO2） show that the potential burned areas will increase 20% under scenario B2 and lightly increase under scenario A2 in 2040s. The days of high, very high and extreme fire danger classes will add 5 and 18 d under scenarios A2 and B2, respectively. It suggests adapting the climate change through improving fuel management and enhancing the fighting abilities.

STUDY ON FOREST FIRE DANGER MODEL WITH REMOTE SENSING BASED ON GIS

Forest fire is one of the main natural hazards because of its fierce destructiveness. Various researches on fire real time monitoring, behavior simulation and loss assessment have been carried out in many countries. As fire prevention is probably the most efficient means for protecting forests, suitable methods should be developed for estimating the fire danger. Fire danger is composed of ecological, human and climatic factors. Therefore, the systematic analysis of the factors including forest characteristics, meteorological status, topographic condition causing forest fire is made in this paper at first. The relationships between biophysical factors and fire danger are paid more attention to. Then the parameters derived from remote sensing data are used to estimate the fire danger variables, According to the analysis, not only PVI (Perpendicular Vegetation Index) can classify different vegetation but also crown density is captured with PVI. Vegetation moisture content has high correlation with the ratio of actual evapotranspiration (LE) to potential ecapotranspiration (LEp). SI (Structural Index), which is the combination of TM band 4 and 5 data, is a good indicator of forest age. Finally, a fire danger prediction model, in which relative importance of each fire factor is taken into account, is built based on GIS.

Preliminary Study on Forest Fire Prevention and Extinguishing in Townships in the Southern Mountainous Areas of Zhejiang Province:A Case Study of Lishui

Forest fires seriously threaten forestry resources and the life and property safety of people in mountainous areas of Lishui City. In this paper, a fire prevention concept with refined forecast and early warning of forest fire danger weather ratings in townships as the starting point, satellite real-time observation of fire spots, monitoring of the Internet of Things and other high-tech products as an implementation means, and strengthening forest fire prevention equipment and personnel in townships as a guarantee was established. The command system for rapid emergency response by cities, counties and townships should be improved. During the forest fire prevention period, fire sources should be strictly controlled, and the basic principles of forest fire fighting in townships should be implemented into the actual fire prevention and fire fighting work to eliminate forest fires in time at the initial stage and before the disaster.

川南经济区森林火险气象预报技术研究

根据川南经济区(泸州市、内江市、宜宾市、自贡市)20个国家气象站1990~2022年逐日气象数据、1990~2022年森林火灾资料,通过计算林火分类条件概率,完善20个国家站12个气象要素单因子贡献度数学模型的参数调整,最终构建出适用于川南经济区的森林火险气象等级预报模型。经验证,模型计算得到的火灾发生时森林火险气象等级均在3级以上,表明森林火灾风险高,与川南经济区林火的出现较为吻合,适用于川南经济区森林火险气象等级实际预报中。

The impact of climate change on fire risk in Daxing'anling,China

Daxing’anling is a key region for forest fire prevention in China. Assessing changes in fire risk in the future under multiple climatic scenarios will contribute to our understanding of the influences of climate change for the region and provide a reference for applying adaptive measures for fire management. This study analyzed the changes in fire weather indices and the fire season under four climate scenarios (RCP2.6, RCP4.5, RCP6.0, RCP8.5) for 2021-2050 using data from five global climate models together with observation data. The results showed that the analog data could project the average state of the climate for a given period but were not effective for simulating extreme weather conditions. Compared with the baseline period (1971-2000), the period 2021-2050 was predicted to have an increase in average temperature of 2.02-2.65 °C and in annual precipitation 25.4-40.3 mm, while the fire weather index (FWI) was predicted to increase by 6.2-11.2% and seasonal severity rating (SSR) by 5.5-17.2%. The DMC (Duff moisture code), ISI (initial spread index), BUI (build-up index), FWI and SSR were predicted to increase significantly under scenarios RCP4.5, RCP6.0, and RCP8.5. Furthermore, days with high or higher fire danger rating were predicted to be prolonged by 3-6 days, with the change in the southern region being greater under scenarios RCP4.5, RCP6.0, and RCP8.5.

基于ArcGIS的森林火灾隐患分析及防范对策研究——以厦门市同安区为例

基于同安区森林火灾综合风险普查数据,结合森林资源“一张图”数据,运用ArcGIS空间分析技术,以林业小班为评价单元,对同安区森林火灾风险等级进行评价定级。研究分析了森林火灾隐患的影响因素、分布情况特征,评估了研究区森林火灾防范能力。结果表明:1)可燃物载量是影响同安区森林火灾隐患最大的指标;2)同安区森林火灾风险等级高、中高风险等级占据较大比例,存在较大的火灾隐患风险;3)同安区森林火灾的防范能力水平一般,有待提高。为提高同安区森林火灾防范能力,提出了一系列建议措施,以期为同安区在森林火灾应急管理方面提供决策参考。

森林火灾区域风险性分析与防范对策--以河南省范县为例

森林火灾是八大自然灾害之一,具有事发突然、蔓延快、防治难、不确定因素多且损失大的基本特点。以范县地区为例,采集森林火灾可燃调查数据,数据包括地表覆盖物、腐殖质厚度、林木密度、蓄积量、可燃物实验检测等,将调查单元(样方)的危险性评估各项指标数据化和指标化,带入危险性指数计算公式,通过ArcGIS软件导出危险性等级图,并评估单元的承灾体暴露度等级和承受体脆弱性,带入风险指数计算公式进行计算,通过ArcGIS软件导出风险性等级图,分析得出范县总体森林火灾发生可能性和危险性为中等水平,针对此情况采取加强森林防火队伍建设和物资储备措施,做到监管有效、防患未然,为我国平原地区森林防火提供理论依据。

基于网格化的越西县雷击森林火险区划

为了更好地了解越西县雷击森林火险分布特点,针对性地预防雷击森林起火,降低森林草原火险风险。文章采用越西县气象局2005—2020年的逐日雷电定位仪数据资料,分别选取雷击点密度、地闪强度、高程以及森林植被覆盖度4个指标,通过AHP方法构建越西县雷级森林火险指数,并使用ArcGIS软件对其进行区划。结果表明,越西县总体的雷击森林火险等级较高,低风险区域主要分布在新民镇这些森林植被覆盖较少的地区,高雷击森林火险区主要在县城南部。

全国森林火险预报系统的研究与运行

The methodology on forest fire danger forecast system of national level and daily operation of the system was discussed. The system determined prediction model and method according to forest fire danger rating and fire danger indexes defined by related professional standards of forestry. The system obtains daily collection of meteorological observation dataset and information of digital weather forecast through the network. It also obtained daily weather observation data and observed data of fire danger factors on key areas through network. It thus concluded the weather forecast of national forest fire danger and forest fire danger forecast within future 24 hours and 48 hours, under the support of basic databases and after colligated processing and analysis of various data on GIS software platform. The forecast results have been daily promulgated through special forestry network and were published 4 times a week through China Central Television Program (CCTV2).

甘肃省林区气候特征及其与森林火险的关系

【目的】为保护和发展甘肃省现有森林，改善自然资源匮乏、生态环境脆弱的局面提供参考依据。【方法】利用甘肃林区1971-2003年气象要素、1988-2003年森林火灾及1990-2001年植被指数资料，采用统计分析方法对甘肃11个主要林区的气候特征及变化进行了分析，并对林区气象条件与火险的关系进行了研究。【结果】甘肃林区气温自东南向西北、由盆地向高山逐渐递减，各林区气温在1971-2003年总体呈上升趋势；林区降水量自东南向西北递减，且逐年呈下降的趋势。各林区相对湿度的年变化有春低秋高和冬低秋高2种类型，蒸发量具有明显的季节变化特征；在3～10月植物生长期，干旱现象明显，近十几年来干旱状况较严重。气象要素及干旱指数与森林火险密切相关。【结论】在气温高、湿度大、降水量多、干旱指数高的季节，火灾发生率较低，而在天气寒冷、空气干燥、降水量稀少、干旱指数低的季节，火灾发生率较高。相对湿度、平均气温、最低气温、最高气温、降水量等气象要素及干旱指数，可用于甘肃森林火险的预警工作。

基于RS和GIS的庐山森林火险区划研究

依据庐山历史森林火灾特点,选取防火期平均最高气温、平均气温、平均降水量、平均最长连旱天数、平均风速、植被类型、海拔、坡度和坡向9个因子作为森林火险区划指标,并按照各区划因子对林火的灵敏度或其对成火的影响分别被赋予不同的权重。通过采用RS和GIS技术,利用Landsat TM影像提取植被信息图层;再利用地形图扫描数字化生成1∶5万的数字高程模型(DEM),一方面提取有关地形信息(海拔、坡度、坡向),另一方面结合庐山及周边7个气象站气候资料建立的气候资源数据库和地理推算模型,采用小网格推算方法进行整体插值,生成气候资源分布图;最后采用因子加权叠置法整合所有单因子专题图,生成综合区划图,并将研究区划分为特级、Ⅰ级、Ⅱ级3个森林火险区。

大兴安岭南部春季火行为特征及可燃物消耗

利用标准地调查分析2007年春季大兴安岭2起森林火灾的火行为及可燃物变化。采用加拿大火险天气指数(FWI)系统分析火险变化,地表可燃物载量调查采用线状相交可燃物调查方法,并利用MODIS遥感数据对火烧程度进行分级。结果表明:FWI系统各指标可以很好地指示森林火险变化,2007年4—5月细小可燃物湿度码(FFMC)基本都在90以上,腐殖质湿度码(DMC)和干旱指数(DC)在4月份持续升高,2场大火也发生在火险高的时段。火烧类型以地表火为主,部分林分有冲冠火。火后阔叶林地表径级可燃物增加不明显,针阔混交林主要是5.0～6.99cm径级可燃物增加,而落叶松纯林火烧后除0.50～0.99cm径级可燃物减少外,其他径级可燃物都明显增加。不同火烧程度对地表可燃物载量的影响有差异。中度和重度火烧后草本盖度明显下降,有些林分下木层死亡率较高。罕诺河火场和松岭区壮志林场过火区重度火烧分别占33.2%和46.4%。

气候变化对中国森林火险的影响

【目的】在全国尺度上研究气候变化对森林火险的影响,为我国宏观林火管理提供科学参考依据。【方法】研究区包括中国的主要森林分布区,并根据中国生态地理系统分成6个区域,研究过去50年和未来2021—2050年的主要气候特征及火险变化。地面气候资料包括824个国家级基准、基本站的日值观测资料(1961—2010年)数据集,利用距离方向加权平均法把各气象因子差值到空间分辨率为0.25°×0.25°的网格点。气候情景数据包括4个情景(RCP2.6、RCP4.5、RCP6.0和RCP8.5)下5个全球气候模式(GFDL-ESM2M、Had GEM2-ES、IPSLCM5A-LR、MIROC-ESM-CHEM和Nor ESM1-M)的日值数据(1951—2050年),水平分辨率为0.5°×0.5°。分别根据观测数据和订正后的气候模式预测数据计算每个格点每日的森林火险天气指数。因子突变检验采用Mann-Kendall法。【结果】历史观测数据表明,基准时段(1971—2010年)研究区平均气温呈上升趋势,但降水量无明显变化。1961—2010年各森林分布区的火险期平均气温增加趋势显著,而降水量只有中温带干旱地区荒漠针叶林区显著增加,其他区域的变化不显著。1976—2010年各生态地理区内森林分布区的火险期指数平均值大部分表现出增加趋势。区域气候情景模型预测2021—2050年森林分布区的平均气温将增加1.6~2.1℃,降水将增加2.3%~4.8%。2021—2050年各生态区防火期的平均气温在都比基准时段显著增加,但降水量只有寒温带湿润地区针叶林区和中北亚热带湿润地区阔叶林、人工植被区显著增加。RCP2.6、RCP4.5、RCP6.0和RCP8.5情景下火险天气指数95th百分位数比基准时段分别增加13.5%,18.9%,14.9%和22.33%;不同气候情景下的火险天气指数的未来增量存在空间差异,其中南方和西南林区的高火险天气日数将明显增加。【结论】1976—2010年我国的森林火险指数表现出增加趋势。气候模式对气温与降水的模拟基本和观测值一致,其预测的2021—2050年我国森林分布区的平均气温和降水量都将有所增加,导致火险期气候呈现暖干化变化趋势,大部分区域的火险指数将升高,尤其南方比北方林区的增幅更加显著,华北和西南地区将是未来森林火灾预防的重点区域。目前气候模型还不能很好地模拟极端气候事件,这对森林火险的分析会有一定的影响,但研究结果可以反映森林火险天气的变化趋势。未来需要更加注重极端气候事件对森林火险和潜在火行为影响的研究。

大兴安岭地区森林火险变化及FWI适用性评估

根据研究区内及附件气象站每日气温、相对湿度、24小时降水和风速计算1987—2006年大兴安岭每日的加拿大林火天气指数系统(FWI)各组分值。利用空间插值方法,获得1987—2006年所有森林火灾发生日的FWI系统各组分值。大兴安岭林区森林火灾主要发生在落叶针叶林(61.3%)、草地(23.9%)和落叶阔叶林(8.0%),主要火源是雷击火(占57.1%)。4—6月份森林火灾发生时的FWI、FFMC和ISI平均值高。根据1987—2006年FWI组分指数的分布和火发生情况,对森林火险指数进行了分级,低、中、高、很高和极高火险的FWI取值范围分别为0～2.5,2.6～10.0,10.1～18.0,18.1～31.0,≥31.1。FWI对大兴安岭地区森林火险有显著的指示意义,FFMC和ISI对预测火灾的发生与蔓延有较好的指示作用。1987—2001年每年明显有春季和秋季2个火险期,但2002—2006年火险期显著延长。春季火险严重度指数(SSR)波动幅度比较大,夏季SSR和春季SSR有相反的波动趋势,2000—2006年秋季火险严重度明显升高。

基于MODIS数据的森林火险时空分异规律研究

森林火灾严重危害生态环境,引起了全球的高度重视。将从MODIS(MODerate-resolution imagingspectroradiometer)中提取的活动火点与历史火烧痕迹进行比较研究,发现MOD14A1(火掩膜数据产品a dai-ly Level 3 1-km fire hot spot product)中提取的8+9波段适合消防监测,与现场勘察数据相比较吻合度高达0.83。使用MOD14A1中8+9波段结合相关数据对这个区域的长达11年(2000—2010年)的森林火灾发生的时间和空间分析,结果表明:火灾发生频率最多的是春季,秋季次之,夏天概率最低,除非干旱。通过对研究区域黑龙江省分析,针叶林和温带针阔混交林过火面积所占比例分别为53.68%,44%,草原区过火面积较小为2.32%。大兴安岭是主要的燃烧区域,面积达到64.74%,小兴安岭约为23.49%,而其他区域面积不超过5%。且火灾发生的较大部分森林有个平缓的斜坡(≤5°),大部分处于中海拔(200m≤H≤500m)。因此,通过卫星遥感对森林火区区域的时间序列分析,阐明火灾活动规律和气候、地形、植被类型的相互关系,有助于预测火灾区域危险性等级。

3S技术在森林火险等级研究中的应用

综合运用"3S"技术,以北京鹫峰国家森林公园林场的小班作为研究单元,综合考虑了立地条件因素、地形因素以及人为因素作为研究火险等级的依据,对火险等级进行描绘,生成了鹫峰林场的火险等级分布图。鹫峰地区火险等级划分为5级,经统计,较易燃烧(4级)和一般燃烧(3级)区域占80%,易燃(5级)区域占18.66%,难燃(1级)和可燃(2级)区域不到2%。"3S"技术在火险等级研究中的应用为该地区林场的林火防范提供了借鉴。

森林火险气象指数及其构建方法回顾

森林火灾是威胁地球生态的主要灾害之一。为实现对林区起火可能性大小、火灾强度、火灾蔓延速度以及火灾扑救难易程度进行评估和预测,国内外专家学者利用森林火灾与气象条件之间的关系研制了诸多森林火险气象指数的构建方法。作者对近几十年来国内外森林火险气象指数的研究工作进行回顾和总结,得出广泛应用的火险指数可以归纳为指数查对法、综合指标法和统计回归法等3种类型,究其原理和使用效果,各有优缺点。在实际使用过程中,需要结合我国的气候和环境特点进行适用性修正和完善。

基于Logistic回归的森林火险天气等级模型

根据大兴安岭地区林业局1975—2004年火灾资料及气象数据,利用logistic回归选择最优配比建立了森林火险天气等级模型,并对其进行检验。经验证该模型具有较好的应用效果,能够为当地林业部门制定防火策略时提供参考。

国家级森林火险等级预报方法研究

对国家级森林火险等级的定量化预报方法进行了探讨,即:利用MODIS数据反演获得可燃物状态指数;将通过网络获得的全国气象数据和建立的可燃物类型分布、森林火险区划等基础数据库,在ArcGIS平台上数量化后计算背景综合指数,由这两者计算获得火险指数,以火险指数为国家级森林火险等级预报的量化指标,并利用它进行全国森林火险等级的分级,从而实现了全国森林火险等级从定性描述到定量估测。同时,以近几年我国发生的重特大森林火灾为例,对该方法进行了验证。实验表明:该方法可较好地对国家级森林火险等级进行定量化预报。