Snow avalanches

Fuchs, S.; Keiler, M.; Sokratov, S.

Авторы: Fuchs S., Keiler M., Sokratov S.
Сборник: Extreme hydroclimatic events and multivariate hazards in a changing environment: a remote sensing approach / Maggioni V., Massari Ch. (Eds.)
Глава в коллективной монографии
Год издания: 2019
Место издания: Elsevier
Первая страница: 369
Последняя страница: 389
DOI: 10.1016/B978-0-12-814899-0.00015-8
Аннотация: After seasonally frozen ground, the seasonal snow cover has the second largest extent of any component of the cryosphere. With a mean annual area of approximately 26 million km2 worldwide (Barry and Thian, 2011), snow cover affects a large part of the populated areas and provides a considerable share of hydroclimatic hazards, above all in mountain regions (Fuchs et al., 2015a). In parallel, snow cover plays an important role as an economic factor in mountain areas (e.g., hydropower, agriculture, tourism, etc.; Callaghan et al., 2011). Correspondingly, snow cover is a determinant of snow avalanches and other hazards in these regions (McClung and Schaerer, 2006; Keiler et al., 2010) as a consequence of its seasonal dynamics and variation. Even though in comparison to other hydroclimatic hazards, such as heavy precipitation and flooding, snow avalanches are relatively limited in their spatial and temporal extent, they cause the majority of winter fatalities both in settlements (e.g. Fuchs et al., 2013, 2017b; Kazakova et al., 2017) and in the tourism and leisure industry (e.g. Spencer and Ashley, 2011; Badoux et al., 2016; Jekich et al., 2016; Höller, 2017; Walcher et al., in press), as well as significant infrastructure loss worldwide (Schweizer, 2008). Therefore, the understanding of temporal and spatial issues of avalanche formation relative to hydroclimate and snowpack development is crucial (Schweizer et al., 2003; McClung, 2005; Schweizer, 2008), in particular for regional avalanche forecasting. Temporal and spatial variability of snow cover and snow pack is strongly related to local and regional temperature regimes and precipitation patterns, hence the hydroclimate (Grünewald et al., 2013). The necessity of involving new and/or innovative methods using remote sensing techniques in identifying areas endangered by snow avalanches is obvious; however, it is not the same for highly-explored regions, such as the Central European mountains or the American Rocky Mountains, and relatively unexplored regions, such as mountain areas in artic regions of the Russian Federation. While for the former detailed and extensive documentation of snow avalanches as well as release conditions and triggers can be used to validate remote sensing data and to further develop data processing models (Eckerstorfer et al., 2017), for the latter remote sensing may be used for avalanche detection and forecast only with limited possibilities of validation due to an overall data-scarceness (Fuchs et al., 2017b).
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