大兴安岭北部主要森林类型林内积雪特征

为研究大兴安岭北部地区不同森林类型的积雪特征,探索雪水文过程机理,选择该地区3种主要森林类型,于2014年10—12月对其降雪截留、积雪特征进行系统研究。对观测期内12场降雪的大气降雪量以及对林内积雪深度、积雪密度以及雪水当量进行了周期性观测与统计分析。结果表明:1)3种森林类型的降雪截留率随降雪级别的增大而增大,相同降雪等级中不同林型的降雪截留率不同。樟子松林对降雪的截留作用最大,其降雪截留率为22.54%,是兴安落叶松林的1.9倍,是杨桦林的5.4倍。2)森林类型对林内积雪深度有直接影响,常绿树种组成的林型林内积雪深度小于落叶树种组成的林型。其中落叶松林林内积雪深度最大,为27.92 cm,樟子松林最小,为23.56 cm。 3)不同林型林内积雪密度在观测初期会随降雪的输入而降低,无雪期有相应的升高。其中,落叶松林与杨桦林林内积雪密度变化基本相同,而樟子松林林内积雪密度变化幅度较小。4)不同林型林内积雪雪水当量差异显著(P0.05),总体表现为杨桦林落叶松林樟子松林,樟子松林最小,为26.49 mm,杨桦林最大,为39.18 mm。由此可见,不同森林类型的降雪截留效应主要受冬季林分郁闭度的影响。同时,郁闭度对林内积雪深度、积雪密度及雪水当量也有直接影响。 

Characteristics of snowpack in major forest types of northern Daxing'anling Mountains,northeastern China

In order to explore the snowpack characteristics and their relationship associated to various forest types in northern Daxinganling Mountains of northeastern China, we observed snowfall amount, snowpack depth and density in and out of three main forest types from October to December, 2014. Based on the observation, we further calculated snow water equivalent (SWE) and interception rate and analyzed their features. The results indicated that: 1) the snow interception rate was closely related to forest types. Specifically, the snow interception rates increased with the upward level of snowfall for all three forest types. Regarding to the same amount of snowfall, the snow interception rates of different forest types were significantly different. Pinus sylvestris var. mongolica forest intercepted the maximum snowfall with a snow interception rate of 22.54% ,which was 1.9 times of Larix gmelinii forest, and 5.4 times of Betula platyphylla-Populus davidiana forest. 2) During the entire observation period, the forest type affected directly the snowpack depth. The snowpack depth in forest composed of evergreen species was lower than that in deciduous forest. The Larix gmelinii forest had the deepest snowpack of 27.92 cm while the Pinus sylvestris var. mongolica forest had the thinnest depth of 23.56 cm. 3) At the beginning of observation period, the snowpack density decreased due to the new snowfall inputting. But the snowpack density would increase when there was less or no snowfall input. The Larix gmelinii forest and Betula platyphylla-Populus davidiana forests showed quite similar variation of snowpack density while the Pinus sylvestris var. mongolica forest presented smaller variation than the other two forest types. 4) In entire observation period, the SWEs in different forest types showed significant differences (P 0.05). And the SWE in Pinus sylvestris var. mongolica forest was minimum with an amount of 26.49 mm, while the Betula platyphylla-Populus davidiana forests had the maximum SWE of 39.18 mm. In a word, the interception effect of different forest types was mainly influenced by forest canopy closure in winter and the latter also impacted the snowpack depth, density and consequent SWE directly.