Linking snow distribution and forest canopy characteristics by way of hemispherical photography

Bc. Jiří Roubínek

Master's thesis

Abstract:

Snow accumulation and ablation processes are strongly influenced by forest canopy. Larger variability of snow depths and snow depletion rates are found under the canopy in comparison to open areas. However, the interactions between forest snow processes and the impacts on snowpack evolution under canopy are not fully understood. This study investigates the temporal and spatial dynamics between the forest canopy and the underlying snow pack. A series of field areas under various canopy and elevation classes centered around Davos, Switzerland containing approximately 2000 geo-rectified (+/-50cm) and labeled points have been setup for repeatable measurements of total snow depth, new snow depth and snow depletion rates. Canopy coverage characteristics have been estimated by a variety of methods, (1) hemispherical photography, (2) manual characterization and (3) airborne light detection and ranging data. The canopy characteristics derived from these methods were analyzed for correlation to approximately 40000 manual snow measurements collected at the field sites during the 2012/2013 winter season. These methods were then intercompared and evaluated for applicability to large scale forest snow studies. The best snow predictors among the canopy characteristics were identified and used in modeling of snow in forests. Physical based model was compared to pure statistical regression. The thesis is linked to ongoing research of snow distribution dynamics under forest canopy within WSL Institute for Snow and Avalanche Research SLF.

Keywords

snow hydrology, canopy metrics, leaf area index (LAI), light detection and ranging (LiDAR)

Language used: English

Date on which the thesis was submitted / produced: 10. 12. 2015

Thesis defence

• Supervisor: Ing. Jiří Pavlásek, Ph.D.

Czech University of Life Sciences Prague

Faculty of Environmental Science

Master programme / field:
Landscape Engineering / Environmental Modelling