Production and decay of random kinetic energy in granular snow avalanches

Buser, Othmar; Bartelt, Perry

doi:10.3189/002214309788608859

Cited by 68 publications

(88 citation statements)

References 25 publications

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“…The decay, , was defined according to snow characteristics, ¼ 0:7 (Buser and Bartelt, 2009). We defined the forested regions, A f , identical to simulations with the VS model ( ¼ 0) with K -values of 10 and 30 Pa, depending on the forest structure.…”

Section: Simulations With 6 ¼mentioning

confidence: 99%

Observations and modeling of the braking effect of forests on small and medium avalanches

et al. 2014

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ABSTRACT. A long-standing problem in avalanche science is to understand how forests stop avalanches. In this paper we quantify the effect of forests on small and medium avalanches, crucial for road and skirun safety. We performed field studies on seven avalanches where trees affected the runout. We gathered information concerning the release zone location and dimension, deposition patterns and heights, runout distance and forest structure. In these studies the trees were not destroyed, but acted as rigid obstacles. Wedge-like depositions formed behind (1) individual tree stems, (2) dense tree groups and (3) young trees with low-lying branches. Using the observations as a guide, we developed a oneparameter function to extract momentum corresponding to the stopped mass from the avalanche. The function was implemented in a depth-averaged avalanche dynamics model and used to predict the observed runout distances and mean deposition heights for the seven case studies. The approach differs from existing forest interaction models, which modify avalanche friction to account for tree breakage and debris entrainment. Our results underscore the importance of forests in mitigating the danger from small-to-medium avalanches.

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Section: Simulations With 6 ¼mentioning

confidence: 99%

Observations and modeling of the braking effect of forests on small and medium avalanches

et al. 2014

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“…As input parameters, the model uses the release area (measured), the snowcover initial conditions (calculated) and a set of friction and avalanche parameters. The avalanche parameters were found by Buser and Bartelt (2009);Vera et al (2015); Buser and Bartelt 275 (2015). These parameters were kept constant for all 12 case studies as in .…”

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confidence: 79%

Modeling the influence of snowcover temperature and water content on wet snow avalanche runout

Valero¹,

Wever²,

Christen³

et al. 2017

Preprint

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Abstract. Snow avalanche motion is strongly dependent on the temperature and water content of the snowcover. In this paper we use a snowcover model, driven by measured meteorological data, to set the initial and boundary conditions for wet snow avalanche calculations. The snowcover model provides estimates of snow depth, density, temperature and liquid water content. This information is used to prescribe fracture heights and erosion depths for an avalanche dynamics model. We 5 compare simulated runout distances with observed avalanche deposition fields using a contingency table analysis. Our analysis of the simulations reveals a large variability in predicted runout for tracks with flat terraces and gradual slope transitions to the runout zone. Reliable estimates of avalanche mass (height and density) in the release and erosion zones is identified to be more important than an exact specification of temperature and water content. For wet snow avalanches, this implies that the 10 layers where meltwater accumulates in the release zone must be identified accurately as this defines the height of the fracture slab and therefore the release mass. This is an interesting result because it indicates the critical role of fracture depth as an input parameter in avalanche simulations. Advanced thermomechanical models appear to be better suited than existing guideline procedure to simulate wet snow avalanches when accurate snowcover information is available.

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“…The parameter β defines the dissipation of free energy of the granular solid by collisions, rubbing, abrasion, etc. It can be shown that this procedure is mass and energy conserving [Buser and Bartelt, 2009].…”

Section: Free Mechanical Energymentioning

confidence: 99%

Dispersive Pressure, Boundary Jerk and Configurational Changes in Debris Flows

Bartelt

McArdell²,

Graf³

et al. 2016

IJECE

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The granular rock material within a debris flow experiences jerk (change in acceleration) as it runs over a rough basal bed or collides with sidewalls. This creates a pressure -the so-called dispersive pressurewhich acts to change the configuration of the granular mass and therefore the frictional relationship of the debris flow with the basal boundary. Normal pressures are no longer hydrostatic and pressure fluctuations are created in the fluid phase. In this paper we formulate relationships between internal shear work, free mechanical energy, dispersive pressure and configurational changes within a debris flow. We associate the potential energy of the debris flow configuration with dilatant kinematic motions and show why it is necessary to integrate the shear work over time to calculate boundary jerks which cannot be represented by closed-form, analytical pressure functions. The effect of the dispersive pressure is mediated by the presence of the viscous muddy fluid which consists of two types: a) the free fluid and b) the bonded fluid attached to the solid granular phase.

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Production and decay of random kinetic energy in granular snow avalanches

Cited by 68 publications

References 25 publications

Observations and modeling of the braking effect of forests on small and medium avalanches

Observations and modeling of the braking effect of forests on small and medium avalanches

Modeling the influence of snowcover temperature and water content on wet snow avalanche runout

Dispersive Pressure, Boundary Jerk and Configurational Changes in Debris Flows

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