Abstract
Abstract. The storage of water within the seasonal snow cover is a substantial source of runoff in high mountain catchments. Information about the spatial distribution of snow accumulation is necessary for calibration and validation of hydro-meteorological models. Generally, only a small number of precipitation measurements deliver precipitation input for modelling in mountain areas. The spatial interpolation and extrapolation of measurements of precipitation is still difficult. Multi-temporal application of lidar techniques from aircraft, so-called airborne laser scanning (ALS), provides surface elevations changes even in inaccessible terrain. These ALS surface elevation changes can be used to derive changes in snow depths of the mountain snow cover for seasonal or subseasonal time periods. However, since glacier surfaces are not static over time, ablation, densification of snow, densification of firn and ice flow contribute to surface elevation changes. ALS-derived surface elevation changes were compared to snow depths derived from 35.4 km of ground penetrating radar (GPR) profiles on four glaciers. With this combination of two different data acquisitions, it is possible to evaluate the effect of the summation of these processes on ALS-derived snow depth maps in the high alpine region of the Ötztal Alps (Austria). A Landsat 5 Thematic Mapper image was used to distinguish between snow covered area and bare ice areas of the glaciers at the end of the ablation season. In typical accumulation areas, ALS surface elevation changes differ from snow depths calculated from GPR measurements by −0.4 m on average with a mean standard deviation of 0.34 m. Differences between ALS surface elevation changes and GPR derived snow depths are small along the profiles conducted in areas of bare ice. In these areas, the mean absolute difference of ALS surface elevation changes and GPR snow depths is 0.004 m with a standard deviation of 0.27 m. This study presents a systematic approach to analyze deviations from ALS generated snow depth maps to ground truth measurements on four different glaciers. We could show that ALS can be an important and reliable data source for the spatial distribution of snow depths for most parts of the here investigated glaciers. However, within accumulation areas, just utilizing ALS data may lead to systematic underestimation of total snow depth distribution.
Highlights
In alpine catchments, the so-called glacio–nival runoff regime is caused by the storage of water in the seasonal snow cover and in glaciers (Aschwanden et al, 1986; Kuhn and Batlogg, 1998; Kuhn, 2000)
Areal snow cover extent on 31 August 2009 is generally in good agreement with the small firn areas observed for the last decade, which caused low accumulation area ratios (AAR) on these Alpine glaciers Landsat snow cover (LSC) area probably do not display the total zone of submergence ice flow, because flow dynamics are controlled by a variety of properties and usually adapt to mass changes within decades
The study presented here was accomplished to evaluate surface elevation changes derived from airborne laser scanning on glacier surfaces for snow cover studies in the Ötztal Alps
Summary
The so-called glacio–nival runoff regime is caused by the storage of water in the seasonal snow cover and in glaciers (Aschwanden et al, 1986; Kuhn and Batlogg, 1998; Kuhn, 2000). High flow rates caused by snow- and ice melt in spring and summer are of interest in terms of water resources management for reservoirs and flood forecasting Sevruk, 1985; Lundberg et al, 2010) and only insufficient data are available for model calibration and validation of the snow depth distribution on the catchment scale. Thereby the spatial representativeness of individual measurements of snow depths and snow densities derived from direct measurements in terms of snow probings and snow pits (Fierz et al, 2009) and from automatic measurement systems (Lundberg et al, 2010) has to be questioned (Grünewald and Lehning, 2011)
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