以时为步长的塔河林业局白桦林地表死可燃物含水率预测方法

Models for Predicting the Hourly Fuel Moisture Content on the Forest Floor of Birch Stands in Tahe Forestry Bureau

地表死可燃物含水率预测在火险天气预报以及火行为预报中起着重要作用.应用基于时滞和平衡含水率法的直接估计法和气象要素回归法,通过对黑龙江省大兴安岭地区塔河林业局不同郁闭度的白桦林下地表细小死可燃物的含水率的连续测定,建立以时为步长的白桦林下细小死可燃物含水率的预测模型.结果表明：采用Nelson平衡含水率法的平均绝对误差（1.01％ ～1.17％）低于Simard法（1.06％～1.39％）和气象要素回归法（1.62％ ～3.01％）,说明使用以时为步长的死可燃物含水率直接估计法适用于大兴安岭的白桦林,且较传统的气象要素回归法精度高.

Accurately prediction of the dead fuel moisture content on the forest floor is very important for fire behavior forecast and fire danger rating estimation. Dynamics of hourly moisture content of the surface fine dead fuels under birch （Betula platyphylla） stand in Tahe Forestry Bureau, Daxing＇anling Region, Heilongjiang Province, China was modeled using direct timelag methods with Nelson and Simard equilibrium moisture content models and a meteorological variable regression method. The mean absolute error of Nelson （ 1.01%- 1.17 % ） and Simard （ 1.06% -1.39 % ） were lower than that of meteorological variable regression method （1.62% -3.01% ）, which indicated that hourly prediction of fuel moisture by the direct timelag methods would be applicable to the region.