摘要
The fuel moisture content is an integral part of any workable fire danger-rating system. This paper presented dynamic models for estimating 1-h, 10-h. 100-h and 1000-h timelag fuels, that were developed by multiple regression and stepwise variable selection of statistics. The variables include both meteorological factors and moisture contents observed prior to the day correspondingly. The analysis revealed that the fuel moisture content are correlated positively with the precipitation of 24 hours prior to the observation time, and negatiyely with air temperature at observing height of 1.5 meter in forest.
The fuel moisture content is an integral part of any workable fire danger-rating system. This paper presented dynamic models for estimating 1-h, 10-h. 100-h and 1000-h timelag fuels, that were developed by multiple regression and stepwise variable selection of statistics. The variables include both meteorological factors and moisture contents observed prior to the day correspondingly. The analysis revealed that the fuel moisture content are correlated positively with the precipitation of 24 hours prior to the observation time, and negatiyely with air temperature at observing height of 1.5 meter in forest.
