Study On The Fuel Moisture Codes And Dynamic Of Fuel Moisture Content In Jiagedaqi And Fuyuan

Forest fuel moisture content is a fundamental parameter in forest fire research and fire management.Dynamic and accurate prediction of fuel moisture content are of great importance in fire risk forecast.Fine Fuel Moisture Code(FFMC)is used to reflect the relationship between fine fuel moisture and meteorological factors,which indicates the potential of ignition and initial spread in surface fire.Duff Moisture Code(DMC)is used to reflect the relationship between upper duff fuel moisture and meteorological factors,which indicates the ignition probability caused by lightning and the upper duff fuel to be consumed in flaming and smoldering combustion.Many studies about FFMC and DMC have been conducted in many countries and regions.But the relevent focused researches in China are still lack.This paper based on the studies on Jiagedaqi and Fuyuan,which climate and landform differ largely in Heilongjiang province.The dynamic of fine fuel moisture content and upper duff moisture content and meteorological factors(air temperature,relative humidity,wind speed and rainfall amount)were analyzed in Scots pine planation,larch planation and secondary Mongolian oak forest of Jiagedaqi,as well as broadleaf mixed forest,secondary aspen forest and secondary Mongolian oak forest of Fuyuan.The weather condition(dry or wet)was determined whether the accumulated rainfall amount within 24 hours before observation time was more than 0.5 mm,in order to analysis the prediction ability of FFMC(daily FFMC,hourly FFMC and diurnal FFMC)and DMC to fine fuel moisture content and upper duff fuel moisture content.In addition,multiple stepwise regression models for observed fine fuel moisture content and associated meteorological data were built.At last,equilibrium moisture content(EMC)and time lag(T)for fine fuels were calibrated based on control experiments for air temperature and relative humidity in laboratory.Fuel moisture models after rain in FFMC were calibrated through nonlinear regression.The parameters of scaling function for DMC were calibrated through nonlinear regression.In general,the following conclusions were drawn from this study:(1)The fire risks in the spring and autumn were higher in Jiagedaqi than that in Fuyuan.Fine fuel moisture content decreased mainly between 8:00～14:00.Under dry weather condition,the fine fuel moisture content mainly controlled by air temperature and relative humidity.But under wet weather condition,they mainly controlled by hourly rainfall amount and relative humidity.The corresponding regression models built for Jiagedaqi performed better.In addition,the regression models based on meteorological factors were not adapted in daily fire risk forecast in Jiagedaqi and Fuyuan.(2)Among different forest plots,the moisture content of fine fuel and upper duff fuel in larch forest and broadleaf mixed forest located in flat ground,which were not responsive to meteorological factors,were higher than those in other plots.But the fuel moisture content in Scots pine planation and other broadleaf forests were lower and changed rapidly.(3)In the absence of calibration,the predicted values for fine fuel in the plots based on hourly FFMC and diurnal FFMC were generally lower than observed values.The predicted values from diurnal FFMC were closer to the corresponding observed values.But hourly FFMC,which based on iterative calculation,performed better under wet weather condition than diurnal FFMC.Daily FFMC underestimated the fine fuel moisture under dry weather condition,but still performed better than the situation under wet condition.DMC overestimated the upper duff moisture content in most cases,and performed better under wet weather condition.Overall,FFMC and DMC were more suitable to predict corresponding fuel moisture content in those fuels which moisture content lost rapidly.FFMC and DMC performed better under dry weather condition than under wet weather condition.In addition,FFMC and DMC performed better in the forenoon than in the aftercoon.The impact of rain event on the applicability of FFMC and DMC was great.(4)The calibration for EMC and timelag reduced RMSE and MAE for FFMC in all plots,and approximated the gap of prediction error among the plots and observation times.But the prediction accuracy is still lower under wet weather condition.The calibrated DMC performed better in most cases,but the prediction accuracy dropped instead of increasing in some plots.The field observation occurred all in the daytime and the corresponding results obtained during the drying process.Whether the conclusions are suitable to the conditions in the wetting process are to be studied.In future,the fuel moisture content will be collected from more forest types for longer observation time to facilitate the application of FFMC and DMC to improve forest fire risk forecasting in more regions.