The Prediction Of Moisture Content Of Surface Ground Fuel Of Xilinji Forestry Bureau In Da Hinggan Mountain

Global climate change and human disturbance to natural systems has dramatically exacerbated,which increased the risk of forest fires and make its threatening.Consequently,prevention and control of the occurrence forest fires,and avoid the enormous economic losses to the forest,and how to control and prevent forest fires,which has highly attracted attention by Governments,experts and academics.Da Hinggan Mountain is a key State-owned forest region in China,and also is of high incidence of forest fires,carrying out of the work of fuel moisture content in this region is of great theoretical significance and practical value.This paper analyzes the moisture content of five typical surface ground fuel of Xilinji Forestry Bureau in Da Hinggan Mountain of Heilongjiang Province,China.A large number of field studies and extensive sampling were measured to determine moisture content of surface ground fuel and Dynamic changes.By fitting surface ground fuel measured data and meteorological data,we build the predicted model of moisture of the surface ground fuel and validated by precision compared with instrument monitoring data,research results will provide fast and accurate fire forecast for forest fire sector,furthermore,supply important technology support of effective control forest fire,and ensure forest ecological security and the construction ecological civilization,which has important value of production practice and broad application prospects.By analyzing the results of forest fuel moisture,which pointed out the problems exist in the current and further optimization of the current study path.The results were as follows:(1)There are differences of the moisture content of different slope position and slope direction,while different forest canopy density reaches 0.7 and above,as the whole,change of moisture content of the surface ground fuel is relatively close to the bottle of slope,slope and top of slope,while the forest canopy density is only 0.4,the total change of moisture content of the surface ground fuel is: slope down > slope > slope top.In different slopes upward,the water holding capacity of the surface ground fuel in sunny slopes is lower than that of the overcast slope because of absorbing different solar radiation,and the water holding capacity of mixed forest is higher than that of pure forest.(2)Surface ground fuel moisture content of 5 forest types in the study area was significantly positive correlated with relative humidity(p < 0.01),significantly negatively correlated with temperature(p < 0.05),and altitude correlation is not obvious.(3)In the process of forest fuel moisture change,when the fuel moisture content rises,Nelson and Simard model forecast data exceeded measured value,and when fuel moisture decreases,2 model forecasts are slightly lower than measured value.Among them,the prediction of shade slope larch Betula platyphlla is best,very close to the actual value.When measuring fuel moisture is greater than 0.6,2 model overestimated the forecast values.When measured fuel moisture value below 0.5,2 forecast model worked best.(4)In the Nelson model,5 types of MAE ranges from 0.08 to 0.15,MRE-0.09~0.29.Sunny slope Pinus sylvestris MAE-0.08,MRE-0.29.Sunny slopes of birch MAE-0.11,MRE-0.23,shady slopes of birch MAE-0.15,MRE-0.26.Shade leaves of Betula platyphylla mixed forest MAE-0.13,MRE-0.26.Slope larch MAE-0.09,MRE-0.09.5 forest prediction accuracy results for: slope larch > sunny slopes of birch > slope Birch larch > slope Birch > sunny slope Pinus sylvestris.Simard prediction model,5 types of MAE-0.08~0.14,MRE-0.09~0.42.Sunny slope Pinus sylvestris MAE-0.08,MRE-0.42.Sunny slopes of birch MAE-0.11,MRE-0.23.MAE slope Birch-0.13,MRE-0.34.Shade leaves of Betula platyphylla mixed forest MAE-0.14,MRE-0.43.Larch MAE slope for 0.10,MRE for 0.10.5 forest prediction accuracy results for: slope larch > slope Birch > sunny slopes of Birch > slope Birch larch > sunny slope Pinus sylvestris.Nelson model prediction accuracy over Simard model.(5)The prediction of 2 model to the moisture content of Larix slope accuracy is higher than the other 4 types of forest stands.Shows extrapolation of 2 models are not fully adapted for predicting water content of different fuel types in several different forest stand,should be taken into account spatial and temporal heterogeneity and complexity of the change mechanism in different fuel of different fuel or the same forest ecosystem.(6)Adopted paired samples t-test,observation and instrument monitoring data were compared and analyzed,the results show that P>0.05,indicated pairs detected of observation and monitoring value has no significant differences automatic monitoring instrument performed well.