Improved snow interception modeling using canopy parameters derived from airborne LiDAR data

Abstract

Forest snow interception can account for large snow storage differences between open and forested areas. The effect of interception can also lead to significant variations in sublimation, with estimates varying from 5 to 60% of total snowfall. Most current interception models utilize canopy closure and LAI to partition interception from snowfall and calculate interception efficiency as an exponential decrease of interception efficiency with increasing precipitation. However, as demonstrated, these models can show specific deficiencies within heterogeneous canopy. Seven field areas were equipped with 1932 surveyed points within various canopy density regimes in three elevation bands surrounding Davos, Switzerland. Snow interception measurements were taken from 2012 to 2014 ($9000 samples) and compared with measurements at two open sites. The measured data indicated the presence of snow bridging from a demonstrated increase in interception efficiency as precipitation increased until a maximum was reached. As precipitation increased beyond this maximum, the data then exhibited a decrease in interception efficiency. Standard and novel canopy parameters were developed using aerial LiDAR data. These included estimates of LAI, canopy closure, distance to canopy, gap fraction, and various tree size parameters. These canopy metrics and the underlying efficiency distribution were then integrated to formulate a conceptual model based upon the snow interception measurements. This model gave a $27% increase in the r 2 (from 0.39 to 0.66) and a $40% reduction in RMSE (from 5.19 to 3.39) for both calibration and validation data sets when compared to previous models at the point scale. When upscaled to larger grid sizes, the model demonstrated further increases in performance.

A two-layer canopy model with thermal inertia for an improved snowpack energy balance below needleleaf forest (model SNOWPACK, version 3.2.1, revision 741)

“…We see our contribution as a necessary step in a sequential, multi-directional development and validation process, whereby the careful and independent validation of each component of the snow model will gradually improve its skills; SNOWPACK, now equipped with a more reliable and sophisticated radiative transfer scheme for the canopy, diagnosing flaws originating from other processes (mixed-precipitations, rain-on-snow events, or misrepresented canopy interception), should be easier. Promising work has just been published very recently as to new ways to parameterize canopy interception in alpine forests (Moeser et al, 2015). The proposed methodology should later serve the improvement of snow models like SNOW-PACK in aspects of crucial interest for the snow mass balance.…”

Snowfall interception in a deciduousNothofagusforest and implications for spatial snowpack distribution

“…Snowmelt is affected by shading and long‐wave radiation patterns, whereas forest interception can reach up to 80% of annual precipitation in some climates. In turn, intercepted snow is more exposed to sublimation, which can reach up to 50% of intercepted snow (Hedstrom & Pomeroy, ; Essery & Pomeroy, ; Lundberg & Halldin, ; Storck, Lettenmaier, & Bolton, ; Essery, Pomeroy, Parviainen, & Storck, ; Montesi, Elder, Schmidt, & Davis, ; Martin et al, ; Moeser, Stähli, & Jonas, ; Moeser, Mazzotti, Helbig, & Jonas, ). Due to their hydrological and ecological implications, snow–forest interactions have been intensely studied in cold regions of the world, particularly in the Northern Hemisphere; there, forests cover vast expanses of snow‐dominated landscape.…”

“…Snow interception studies in the Northern Hemisphere coincide in the complexity of the forest–snow interaction and present different methods and results to estimate snow interception. In a majority of cases, the species under study correspond to pine, fir, and mixed forests (Hedstrom & Pomeroy, ; Pomeroy et al, ; Lundberg, Nakai, Thunehed, & Halldin, ; López‐Moreno & Latron, ; López‐Moreno and Stähli, ; Moeser et al, ; Moeser et al, ) with maximum interception values between 4 and 8 mm of snow water equivalent (SWE; Hedstrom & Pomeroy, ; Moeser et al, ; Pomeroy et al, ; Suzuki & Nakai, ). The methods applied for estimating snow interception include physically based models, mass and energy balance, and mechanistic models based on canopy parameters like canopy closure ( C c ) and leaf area index ( LAI ; Moeser et al, ).…”

Evaluating the functionality and streamflow impacts of explicitly modelling forest–snow interactions and canopy gaps in a distributed hydrologic model

“…In the Cedar River Watershed located on the western slope of the Cascade Range (characterized by a maritime climate) in the Pacific Northwest, the mean snow duration in a circular gap cut in the forest with a diameter of 20 m (equal to approximately one tree height) was observed to be 1–2 weeks longer than in the adjacent control forest covered by untreated second‐growth forest dominated by western hemlock and Douglas‐fir (Dickerson‐Lange et al, ). These unique benefits of forest gaps have led to recent modelling developments that address the distinct radiation scheme in a forest gap from entirely open or forested areas (Lawler & Link, ; Musselman, Molotch, Margulis, Lehning, & Gustafsson, ), the energy budget at the forest gap floor (Seyednasrollah & Kumar, ), net canopy interception (Moeser, Morsdorf, & Jonas, ; Moeser, Stähli, & Jonas, ), and snow distributions (Broxton et al, ) in the presence of forest gaps.…”