Statistical modelling of the snow depth distribution in open alpine terrain
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Date
2013
Authors
Grunewald, T.
Stotter, J.
Pomeroy, J.W.
Dadic, R.
Banos, I.M.
Marturia, J.
Spross, M.
Hopkinson, Christopher
Burlando, P.
Lehnig, M.
Journal Title
Journal ISSN
Volume Title
Publisher
Copernicus Publications
Abstract
The spatial distribution of alpine snow covers is
characterised by large variability. Taking this variability into
account is important for many tasks including hydrology,
glaciology, ecology or natural hazards. Statistical modelling
is frequently applied to assess the spatial variability of the
snow cover. For this study, we assembled seven data sets
of high-resolution snow-depth measurements from different
mountain regions around the world. All data were obtained
from airborne laser scanning near the time of maximum seasonal
snow accumulation. Topographic parameters were used
to model the snow depth distribution on the catchment-scale
by applying multiple linear regressions.We found that by averaging
out the substantial spatial heterogeneity at the metre
scales, i.e. individual drifts and aggregating snow accumulation
at the landscape or hydrological response unit scale (cell
size 400 m), that 30 to 91% of the snow depth variability can
be explained by models that are calibrated to local conditions
at the single study areas. As all sites were sparsely vegetated,
only a few topographic variables were included as explanatory
variables, including elevation, slope, the deviation of the
aspect from north (northing), and a wind sheltering parameter.
In most cases, elevation, slope and northing are very good
predictors of snow distribution. A comparison of the models
showed that importance of parameters and their coefficients differed among the catchments. A “global” model, combining
all the data from all areas investigated, could only explain
23% of the variability. It appears that local statistical models
cannot be transferred to different regions. However, models
developed on one peak snow season are good predictors for
other peak snow seasons.
Description
Sherpa Romeo green journal; open access
Keywords
Statistical modelling , Snow cover , Snow depth , Alpine terrain , Mountain regions
Citation
Grunewald, T., Stotter, J., Pomeroy, J.W., Dadic, R., Banos, I.M., Marturia, J., ... Lehning, M. (2013). Statistical modelling of the snow depth distribution in open alpine terrain. Hydrology and Earth Systems Sciences, 17, 3005-3021. doi:10.5194/hess-17-3005-2013