Abstract. Avalanches pose a significant problem in most mountain regions of Russia. The constant growth of economic activity, and therefore the increased avalanche hazard, in the North Caucasus region lead to demand for the development of large-scale avalanche risk assessment methods. Such methods are needed for the determination of appropriate avalanche protection measures as well as for economic assessments.The requirement of natural hazard risk assessments is determined by the Federal Law of the Russian Federation (Federal Law 21.12.1994 N 68-FZ, 2016. However, Russian guidelines (SNIP 11-02-96, 2013; SNIP 22-02-2003 SNIP 22-02- , 2012 are not clearly presented concerning avalanche risk assessment calculations. Thus, we discuss these problems by presenting a new avalanche risk assessment approach, with the example of developing but poorly researched ski resort areas. The suggested method includes the formulas to calculate collective and individual avalanche risk. The results of risk analysis are shown in quantitative data that can be used to determine levels of avalanche risk (appropriate, acceptable and inappropriate) and to suggest methods to decrease the individual risk to an acceptable level or better. The analysis makes it possible to compare risk quantitative data obtained from different regions, analyze them and evaluate the economic feasibility of protection measures.
Sven Fuchs studied Geography and Geology at the Universities of Munich (Germany) and Innsbruck (Austria) and graduated in 2000 (MSc). He holds a PhD obtained in 2004 for his spatiotemporal studies on snow avalanche risk undertaken during a four years appointment at the Swiss Federal Institute for Snow and Avalanche Research SLF in Davos, Switzerland; and a Habilitation (venia docendi for Geography, 2010) for his works related to human-environment interaction in mountain regions. Currently he is Assistant Professor at the University of Natural Resources and Life Sciences in Vienna, Austria. His research includes risk assessment and risk management for mountain hazards, vulnerability analyses, human-environment interaction, and geomorphology. He has extensive research experiences in mountain regions of Europe, Southeast Asia, Central Africa, and the Russian Federation. The list of publications can be accessed by following this link: www.sven-fuchs.de/links/publikat.html.
<p>Glacier mass balance is affected by non-climatic factors such as topography, debris cover and geometric parameters of glaciers themselves, avalanche activity, volcanism, etc. The contribution of snow avalanches to the snow accumulation on a glacier is still among the least studied components of the glacier&#8217;s mass balance. We propose a possible approach for the numerical assessment of snow avalanche contribution to accumulation at mountain glaciers. The approach consists on the following steps: terrain analysis; weather data analysis; snow avalanche volume assessment during an analyzed balance year; numerical simulation of snow avalanches using RAMMS; evaluation of snow avalanche contribution to glacier accumulation. The proposed methodology was tested on three glaciers (Batysh Sook, &#8470; 354, Karabatkak) with an area up to 6,5 km<sup>2</sup> in the Inner Tien Shan and Kolka glacier with an area 1,2 km<sup>2</sup> in the Central Caucasus. To evaluate snow avalanche contribution to the winter accumulation, we reconstructed avalanche release zones that were most probably active during the analyzed balance year and corresponding snow fracture height in each zone. The numerical simulations of most probable released snow avalanches during the analyzed year using avalanche dynamics RAMMS software were performed and compared with the field observations and UAV orthophoto images. The outlines of avalanches deposits were realistically reproduced by RAMMS according to the results of field observations. The estimated contribution of snow avalanches to the accumulation on the studied glaciers during the analyzed balance year was as follows: Batysh Sook &#8211; 7,4&#177;2,5%; &#8470; 354 &#8211; 2,2&#177;0,7%; Karabatkak&#8211; 10,8&#177;3,6% of the winter mass balance. In strong contradiction to the benchmark glaciers in the Tien Shan, the Kolka glacier demonstrates rapid mass gain in the Caucasus. It might be explained by significant, up to 80% share of avalanche nourishment to glacier mass gain. We note that avalanche-fed glaciers seem to be more stable at current stage of regional warming observed both in the Caucasus and the Tian Shan. The obtained results show the importance of the non-climatic factors for glacier surface mass balance control.</p>
The aim of the investigation was assessment of spatial variability of the characteristics of snowpack, including the snow water equivalent (SWE) as the main hydrological characteristic of a seasonal snow cover. The study was performed in Khibiny Mountains (Russia), where snow density and snow cover stratigraphy were documented with the help of the SnowMicropen measurements, allowing to determine the exact position of the snow layers’ boundaries with accuracy of 0.1 cm. The study site was located at the geomorphologically and topographically uniform area with uniform vegetation cover. The measurement was conducted at maximum seasonal SWE on 27 March 2016. Twenty vertical profiles were measured along the 10 m long transect. Vertical resolution depended on the thickness of individual layers and was not less than 10 cm. The spatial variation of the measured snowpack characteristics was substantial even within such a homogeneous landscape. Bulk snow density variability was similar to the variability in snow height. The total variation of the snowpack SWE values along the transect was about 20%, which is more than the variability in snow height or snow density, and should be taken into account in analysis of the results of normally performed in operational hydrology snow course SWE estimations by snow tubes.
The authors describe the results of the research’s initial stage devoted to developing a multidimensional space-time model of the Arctic region, viewed as a voluminous area of space north of the northern latitude’s 60th degree, as well as new methods and tools necessary for the formation and functioning of this model. An idea of the nature and properties of the developed model is given. The substantive and logical structure of the model data, location of the sources for the most important characterizing features of the arctic areas; data coordination; methods and software; model building, projecting and integration of thematic data; modification and analysis of digital models, methods of reproduction and design options of virtual models geoimages are discussed. The article gives the examples of the model’s geoimages visualization. The research relevance and importance for the implementation of innovative approaches to the study, development and environmental management of the Arctic are highlighted.
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