Comparison of snowpack structure in gaps and under the canopy in a humid boreal forest

Abstract

The boreal forest covers a significant portion of the Northern Hemisphere and is snow-covered for over half of the year. Understanding the interactions between the forest canopy and snow is essential in hydrological, meteorological, and climate modelling. However, this is challenging because the density of a forest can range from closed canopies to open gaps. In winter 2018-2019, we assessed differences in snowpack microstructure in small forest gaps and under the canopy of a humid boreal site in eastern Canada. Our experimental approach consisted of quasicontinuous weekly observations of stratigraphy and measurements of density profiles and temperature in a series of snow pits in both environments. High-resolution specific surface area (SSA) profiles were measured twice, allowing for an estimation of snow permeability and hydraulic conductivity. The shallower snowpack under the canopy displayed a stronger vertical temperature gradient and less compaction than in forest gaps. This resulted in the dominance of faceted snow crystals with a small SSA. In contrast, we observed that small, rounded grains with a larger SSA than that of faceted crystals prevailed in the gaps. Due to denser snow and higher SSA, snow permeability inside gaps was found to be lower than under the canopy. Implicitly, the estimated hydraulic conductivity was also lower in gaps. Following rain-on-snow events, snow under the canopy displayed layers of melt-freeze polycrystals, while in the gaps, well-defined ice layers were formed. The combination of low snow permeability and ice layers is likely to affect liquid water transport in the gap snowpack as compared to the canopy. Although observed at relatively small scales in our study, if these differences are confirmed at a catchment scale, they are likely to impact the hydrology of forested areas during snowmelt.

Watershed memory amplified the Oroville rain-on-snow flood of February 2017

“…This may affect (1) the location of the regional snowline (as calculated using fSCA here) and (2) the TWI during ROS inferred from snow pillows ( 76 ). Relatively broader forest cover therefore suggests actual snowpack losses across watersheds may be lower (reducing the snowpack contribution to TWI) ( 74 , 77 ) than what may be implied by in-situ SWE losses. This is supported by our modeling results that account for canopy–snow interactions, indicating lower snowmelt contributions to TWI in the 6F ROS event.…”

“…However, ground and satellite observations are partial to exposed, flat terrain. Vegetation tends to collect less snowpack in-stand compared to exposed areas ( 73 , 74 ), yet it can shelter snow from wind-driven turbulent heat exchange, potentially lowering TWI during ROS ( 12 , 17 , 75 ). Beneath-canopy SWE and its in-storm changes are invisible to both satellites and snow pillows.…”

Exploring the potential of forest snow modelling at the tree and snowpack layer scale

“…While available observations did not allow to evaluate our simulations in more detail, our findings are generally consistent with the few observational studies that have addressed snow microstructural properties, stratigraphy, and its spatial variability within the forest. Comparing snow pits in canopy gaps and closed canopy, Bouchard et al (2022) identified layers specific to closed-canopy locations that were absent in forest gaps. Optical grain size measurements in trenches along tree boles presented by Molotch et al (2016) revealed distinct differences in snow grain size at small vs. large distance from tree trunks, and faster metamorphism at south-vs. north-exposed sides of trees.…”

“…A modelling system that combines both, the most complex snow and canopy representation, is lacking to date. At the same time, a few observational studies have provided evidence that tree-scale processes do impact layer-scale snowpack properties (Bouchard et al, 2022;Teich et al, 2019;Molotch et al, 2016). These observations document, for example, different microstructural properties under trees, in the unloading zone, and in canopy gaps.…”

Impact of rain-on-snow events on snowpack structure and runoff under a boreal canopy

“…A thin snowpack below the canopy favors the diffusion of water vapor among snow layers, leading to gradient metamorphism and grain growth (Colbeck, 1983). Larger grains increase the hydraulic conductivity of the snowpack (Bouchard et al, 2022). Canopy snow unloading, meltwater dripping, and accumulation of vegetation debris enhance the sub-canopy snowpack heterogeneity, thereby increasing the likelihood of preferential flow under the trees and the formation of melt-freeze layers (Bründl et al, 1999;Teich et al, 2019;Bouchard et al, 2022).…”