The Assessment On Forest Fire Danger And Vulnerability For Daxing’anling

The impact factors of forest fire regime include topography, vegetation, ignition source, land use and climate. Forest fire regime has been changed in many regions significantly due to the changes of climate, vegetation and human activities. It is difficult to make an accurate and qualitative analysis of fire regime only with the limited historical forest fire data. The paper studies the fire danger changes in Daxing’anling region under four climate scenarios by using Fire Weather Index system, and simulates the burn probability with BURN-P3 model. The fire danger and vulnerability to fire are evaluated for the region, and the results will provide a reference for improvement forest fire management policies and measures.(1)BURN-P3 model can simulate the fire regime in Daxing’anling. The forest fire regime in 1991-2010 in Daxinganling was simulated by using the model and combining with FWI system. We overlay fire scars in 1991-2010 extracted from NOAA/MODIS satellite data and the simulated burn probability in the same period, and found that most fire scars located in the areas with moderate and high burn probability. The burn probability in Larch forest is higher than the average of other fuel types. The evergreen coniferous forest and typical grassland have less burn probability, and the deciduous forest has the minimum.(2)The temperature under scenario RCP2.6, RCP4.5, RCP6.0 and RCP8.5 in 2021-2050 shows an obvious increase compared with the baseline(1971-2000). The temperature under scenario RCP8.5 shows a significant increase than other scenarios. The average annual rainfall under the four climate scenarios also shows an increasing trend. The annual precipitation under scenario RCP4.5 showed maximum fluctuation, and relatively minimal volatility for the scenario RCP6.0.(3)The mean values of each fire weather index in the fire season under scenario RCP4.5, RCP6.0 and RCP8.5 would increase compared with the baseline. However, the fire weather indexes under scenario RCP2.6 would decrease.(4)Compared with baseline, the fire probability in Daxing’anling under scenario RCP8.5, RCP6.0, RCP4.5 and RCP2.6 would increase by 19.48%, 7.80%, 7.71%, and-6.21%, repectively. The fire intensity under scenario RCP2.6, RCP4.5, RCP6.0 and RCP8.5 would increase by-20.74%, 6.93%,-4.89%, and 2.31%, respectively. The average rate of spread(ROS) and crown fraction of burning(CFB) would increase under scenario RCP4.5, RCP6.0 and RCP8.5, but the average ROS decrease under scenario RCP2.6.The areas with high burn probability are mainly distributing in the southwest of Mohe, Huzhong, Xinlin, south of Tahe, and southern Huma. The areas with high and extremely high degree burn probability would increased by-3.79%, 7.96%, 9.11%, and 14.34% under scenario RCP2.6, RCP4.5, RCP6.0, and RCP8.5, respectively. The proportion of areas in larch forest with high burn probability would increased by-3.19%, 4.42%, 7.93%, and 12.32% under scenario RCP2.6, RCP4.5, RCP6.0, and RCP8.5, respectively.