Modeling mass‐dependent flow regime transitions to predict the stopping and depositional behavior of snow avalanches

Bartelt, Perry; Bühler, Yves; Buser, Othmar; Christen, Marc; Meier, Lorenz

doi:10.1029/2010jf001957

Cited by 64 publications

(77 citation statements)

References 60 publications

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“…For the numerical simulation of snow avalanches with up-to-date tools such as RAMMS (Christen et al, 2010a;Bartelt et al, 2012a), SAMOS (Sampl and Zwinger, 2004) or ELBA+ (Keiler et al, 2006), accurate information on the location of the release area and high-quality digital elevation models are crucial (Bühler et al, 2011). They are also the base for large-scale snow avalanche hazard mapping.…”

Section: Y Bühler Et Al: Identification Of Potential Avalanche Relementioning

confidence: 99%

Automated identification of potential snow avalanche release areas based on digital elevation models

Bühler¹,

Kumar

Veitinger

et al. 2013

Nat. Hazards Earth Syst. Sci.

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109

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The identification of snow avalanche release areas is a very difficult task. The release mechanism of snow avalanches depends on many different terrain, meteorological, snowpack and triggering parameters and their interactions, which are very difficult to assess. In many alpine regions such as the Indian Himalaya, nearly no information on avalanche release areas exists mainly due to the very rough and poorly accessible terrain, the vast size of the region and the lack of avalanche records. However avalanche release information is urgently required for numerical simulation of avalanche events to plan mitigation measures, for hazard mapping and to secure important roads. The Rohtang tunnel access road near Manali, Himachal Pradesh, India, is such an example. By far the most reliable way to identify avalanche release areas is using historic avalanche records and field investigations accomplished by avalanche experts in the formation zones. But both methods are not feasible for this area due to the rough terrain, its vast extent and lack of time. Therefore, we develop an operational, easy-to-use automated potential release area (PRA) detection tool in Python/ArcGIS which uses high spatial resolution digital elevation models (DEMs) and forest cover information derived from airborne remote sensing instruments as input. Such instruments can acquire spatially continuous data even over inaccessible terrain and cover large areas. We validate our tool using a database of historic avalanches acquired over 56 yr in the neighborhood of Davos, Switzerland, and apply this method for the avalanche tracks along the Rohtang tunnel access road. This tool, used by avalanche experts, delivers valuable input to identify focus areas for more-detailed investigations on avalanche release areas in remote regions such as the Indian Himalaya and is a precondition for large-scale avalanche hazard mapping

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Section: Y Bühler Et Al: Identification Of Potential Avalanche Relementioning

confidence: 99%

Automated identification of potential snow avalanche release areas based on digital elevation models

Bühler¹,

Kumar

Veitinger

et al. 2013

Nat. Hazards Earth Syst. Sci.

Self Cite

109

View full text Add to dashboard Cite

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“…Avalanche risk can be recorded by temporal and spatial overlapping of the two independent processes of avalanche hazard and use of the area (Bartelt et al, 2012;Hendrikx et al, 2006;Seliverstov et al, 2008;Wilhelm, 1998). The use of the area corresponds to the probability of presence and the number of people present.…”

Section: Methodsmentioning

confidence: 99%

Risk assessment in the North Caucasus ski resorts

Komarov

Seliverstov

Glazovskaya

et al. 2016

Nat. Hazards Earth Syst. Sci.

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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.

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“…In order to refine the slope mask we would ideally need to obtain more precisely mapped avalanche release and runout zones. This could be done initially through manual detection of the paths or computationally using paths generated by numerical simulation models [Bartelt et al, 2012;Bühler et al, 2013].…”

Section: Misclassificationmentioning

confidence: 99%

A method for automated snow avalanche debris detection through use of synthetic aperture radar (SAR) imaging

Vickers

Eckerstorfer

Malnes

et al. 2016

Earth and Space Science

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Avalanches are a natural hazard that occur in mountainous regions of Troms County in northern Norway during winter and can cause loss of human life and damage to infrastructure. Knowledge of when and where they occur especially in remote, high mountain areas is often lacking due to difficult access. However, complete, spatiotemporal avalanche activity data sets are important for accurate avalanche forecasting, as well as for deeper understanding of the link between avalanche occurrences and the triggering snowpack and meteorological factors. It is therefore desirable to develop a technique that enables active mapping and monitoring of avalanches over an entire winter. Avalanche debris can be observed remotely over large spatial areas, under all weather and light conditions by synthetic aperture radar (SAR) satellites. The recently launched Sentinel-1A satellite acquires SAR images covering the entire Troms County with frequent updates. By focusing on a case study from New Year 2015 we use Sentinel-1A images to develop an automated avalanche debris detection algorithm that utilizes change detection and unsupervised object classification methods. We compare our results with manually identified avalanche debris and field-based images to quantify the algorithm accuracy. Our results indicate that a correct detection rate of over 60% can be achieved, which is sensitive to several algorithm parameters that may need revising. With further development and refinement of the algorithm, we believe that this method could play an effective role in future operational monitoring of avalanches within Troms and has potential application in avalanche forecasting areas worldwide.

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Modeling mass‐dependent flow regime transitions to predict the stopping and depositional behavior of snow avalanches

Cited by 64 publications

References 60 publications

Automated identification of potential snow avalanche release areas based on digital elevation models

Automated identification of potential snow avalanche release areas based on digital elevation models

Risk assessment in the North Caucasus ski resorts

A method for automated snow avalanche debris detection through use of synthetic aperture radar (SAR) imaging

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