Author(s):
Eric Robert Lutz - Department of Earth Sciences, Montana State University
Kalle Kronholm - Department of Earth Sciences, Montana State University
Karl W. Birkeland - USDA Forest Service National Avalanche Center, Bozeman, Montana
Katherine J. Hansen - Department of Earth Sciences, Montana State University
Abstract:
An important prerequisite to slab avalanche formation is the presence of weak layers within the mountain snowpack. Determining the presence and character of potential failure planes is therefore essential to avalanche hazard evaluation and forecasting. Over the years, several probes have been developed to improve our ability to quickly identify weak layers and to assess snow hardness, a proxy of snow strength. Recent research has shown that the SnowMicroPen (SMP), a high-resolution snow penetrometer, can be used to identify thin weak layers and to detect changes in the hardness of weak layers and their boundaries with adjacent strata. However, these techniques have been dependent on the manual delineation of stratigraphic boundaries.
In this study, we developed SMP signal analysis techniques to automatically delineate stratigraphic boundaries within seasonal snowpacks. We utilized data collected between 2001 and 2005 in the eastern Swiss Alps and in the Rockies of Southwestern Montana, USA. Using moving-window regression analysis, the first derivative of the penetration hardness and the explanatory value of the linear fit were calculated for each SMP profile. These parameters were used to automatically delineate stratigraphic boundaries which were then compared with manually delineated boundaries, as well as with those observed in traditional manual snow profiles. Results indicated that the automated technique was capable of detecting many of the observed stratigraphic boundaries, including weak layer boundaries. In combination with previously developed analysis techniques, this methodology may prove useful for efficiently acquiring and analyzing stratigraphic information essential to avalanche forecasting and research.
