We quantified the effects of forest vegetation on snow accumulation and ablation in a mid-latitude montane environment in Northern New Mexico. Detailed observations of snow depth along transects extending radially from trees showed that snow depth was 25% greater on the northern versus southern side of trees. At maximum accumulation, canopy interception resulted in a 47% reduction of snow water equivalent (SWE) under canopy. An array of ultrasonic snow depth sensors showed that snow ablation rates were 54% greater in open locations compared to locations under canopy. Maximum accumulation of SWE occurred 21 days later on the north versus south side of the trees. Binary regression tree models indicated strong correlation (R2 = 0.68) between micro-scale (i.e. 10-cm resolution) canopy structure indices and snow depth. The regression tree model adequately resolved general tree-well structure, suggesting that future remotely sensed vegetation data may improve snow distribution models.
- Binary regression tree models
- Forest density
- Snow - vegetation interactions
- Snow ablation
- Snow accumulation
ASJC Scopus subject areas
- Water Science and Technology