The forces snow avalanches are able to exert on protection dams or buildings are of crucial interest in order to improve avalanche mitigation measures and to quantify the mechanical vulnerability of structures likely to be damaged by snow avalanches. This paper presents an analytical model that is able to calculate these forces taking into account dead-zone mechanisms. First, we present a 2-D analytical hydrodynamic model describing the forces on a wall overflown by gravity-driven flows down an inclined plane. Second, the 2-D model is successfully validated on discrete simulations of granular flows. Third, we provide ingredients to extend the 2-D model to flows of dry and cold snow. Fourth, we propose a simplified 3-D analytical model taking into account lateral fluxes. Finally, the predictions from the simplified 3-D analytical model are successfully compared to recent measurements on two full-scale snow avalanches released at the Lautaret site in France.

This paper presents a method for deriving the snowline altitude using a combined analysis of terrain elevation and multispectral Advanced Wide Field Sensor (AWiFS) data from the RESOURCESAT-1 satellite, launched by India on 17 October 2003. AWiFS is a unique instrument capable of acquiring imagery of the world repeatedly every 5 days with very high radiometric resolution. It provides a wide swath width, which is very useful for snow-cover mapping. Snowline altitude is a good indicator of snow coverage. Snowline altitude for the period from October 2004 to June 2005, and from October 2006 to June 2007, is determined for the Baspa Basin, which is located in the Kinnaur district of Himachal Pradesh, India. It is observed that snowline altitude is generally higher during the year 2006/07 than during 2004/05, except in December 2006 and March 2007. The results obtained with the analysis presented here are validated using available meteorological data and are found to be satisfactory. This thus establishes a method that can be applied to other terrains and over longer periods of time within the coverage of the AWiFS sensor data.

In this study, we use MM5 weather-forecast model output and observed surface weather data from 11 stations in the western Himalaya to develop a statistical downscaling model (SDM) to better predict precipitation, 10 m wind speed and 2 m temperature. The analysis covers three consecutive winters: 2004/05, 2005/06 and 2006/07. The performance of the SDM was assessed using an independent dataset from the 2007/08 winter season. This assessment shows that the SDM technique substantially improves the forecast over specific station locations, which is important for avalanche-threat assessment.

Stratigraphic boundaries at fine-to-coarse transitions in snow can introduce impeding layers to infiltrating water. In our present investigation, such impeding horizons were observed within sub-freezing homogeneous snow as a consequence of subsurface melting caused by the penetration of solar radiation. This new texture impeded the further downward flow of meltwater at fine-to-coarse transitions, leading to the formation of low-permeability melt–freeze crusts following multiple melt–freeze cycles. In this work, a large sub-freezing (–6°C) homogeneous sample, consisting of small rounded grains, was periodically exposed to intense radiation generated by a sun simulator. Due to the penetration of shortwave radiation into the snow, subsurface melting caused the growth of melt–freeze polycrystals from clustered rounded crystals. Variations in mass growth (%) of melt–freeze polycrystals and mass loss (%) of grain clusters were studied within the sub-freezing snow with respect to different melt–freeze cycles. In this work, we study the growth of melt–freeze polycrystals in the top and bottom sub-layers with respect to collective saturation. Saturation profiles from the snow were recorded with a parallel-probe saturation profiler (PPSP) device, sampling at vertical intervals of 7mm, after each melting cycle. Intrinsic permeabilities across different stratified sub-layers were monitored in relation to saturation as a function of different melt–freeze cycles. Our observations revealed that there is a significant decrease in intrinsic permeability for the first few top sub-layers. Also, permeability in the second topmost sub-layer was less than that in the topmost sub-layer directly interacting with the radiation. These results support the evolution of a new coarse grain texture within the homogeneous snow that subsequently converts into a layer of low permeability. In the various transects of the snow sample, two melt–freeze crusts and one ice crust were manually identified through stratigraphic mapping. A correlation was also established between the saturation spikes recorded with the help of the PPSP and corresponding depth positions of the crusts.

We present a velocity time series of a dry-mixed real-scale avalanche that was recorded at different heights on a mast at the Swiss Vallée de la Sionne avalanche test site. The dataset is of extraordinary quality in terms of completeness and spatio-temporal resolution, and allows the evolution of distinct flow phases of the avalanche to be traced. In particular, we found velocity profile inversions at the transition from the avalanche front to the avalanche body. We provide a tentative empirical description of the profile inversions and briefly discuss our observations in the light of theoretical considerations.

Daily new snow water equivalent (HNW) and snow depth (HS) are of significant practical importance in cryospheric sciences such as snow hydrology and avalanche formation. In this study we present a virtual network (VN) for estimating HNW and HS on a regular mesh over Switzerland with a grid size of 7 km. The method is based on the HNW output data of the numerical weather prediction model COSMO-7, driving an external accumulation/melting routine. The verification of the VN shows that, on average, HNW can be estimated with a mean systematic bias close to 0 and an averaged absolute accuracy of 4.01 mm. The results are equivalent to the performance observed when comparing different automatic HNW point estimations with manual reference measurements. However, at the local scale, HS derived by the VN may significantly deviate from corresponding point measurements. We argue that the VN presented here may introduce promising cost-effective options as input for spatially distributed snow hydrological and avalanche risk management applications in the Swiss Alps.

Snow hardness is the resistance to penetration. It can be measured by the Swiss rammsonde or estimated by the hand hardness test. According to the International Classification of Seasonal Snow on the Ground (ICSSG), snow hardness is divided into five levels (without ice). However, the hand test is subjective and provides only an index value of snow hardness. The main objective of this study was to determine the hardness using an alternative method which can be applied in the same way as the hand test and which can deliver accurate data. In this study the conventional hand hardness test was used; additionally, a digital force gauge (push-pull gauge) was applied where the hardness was measured horizontally (for comparison with the hand hardness test). The push-pull gauge could be provided with five different attachments. The size and design of each attachment corresponded to the equivalent application of the hand hardness test (fist, four fingers, one finger, pencil, knife). This paper indicates how snow hardness measured by hand is related to snow hardness measured with the push-pull gauge. Moreover, the variability of the hardness, both vertical and horizontal, is demonstrated. The results show agreement with the ICSSG for hand hardness indices 3, 4 and 5; for hand hardness indices 1 and 2, the range indicated by the ICSSG is below the lower quartile of the measurements.

The impact energy of an avalanche on the flat surface of an instrumented structure has been quantified by full-scale experiments performed at the Lautaret avalanche test site, France. The deformation and acceleration of the structure were measured during the avalanche. The impact energy of the avalanche was calculated from an energy balance via the mechanical energy theorem. First the elastic potential energy and kinetic energy of the structure were calculated from the measured deformations and an adequate mechanical model of the structure. Internal energy dissipation due to material damping and potential plastic deformation was calculated. Finally the mechanical work done on the structure by the avalanche forces was deduced from the energy balance. Results show that the elastic energy is the main component of the energy injected in the structure. The kinetic and viscous components are negligible because of the very low displacement rate of the structure during the impact. Another important result is that the maximum of the mechanical power (work rate) is done when the head of the avalanche impacts the structure. This occurs before the pressure reaches its nominal value, approximately when the product of the pressure by the pressure rate is maximum.

A method for automated and fast classification of snow texture would be useful for applications where snow structure must be quantified. Large numbers of field measurements were carried out on natural snow in order to investigate small-scale variations of the micro-penetration force. Snow characterization was done for snow from the Himalaya and the Alps, using a high-resolution snow penetrometer (SnowMicroPen). Measurements of snow resistance at equal intervals of 4 μm were geostatistically evaluated. The range parameter (correlation length, or CL) of penetration force was estimated for all major snow classes from the sample semivariogram. Average CL was lowest for new snow and highest for melt–freeze snow. For major snow classes, CL was found to increase with snow density. Ground-perpendicular and ground-parallel snow profiles were also obtained for homogeneous snow, and CL was estimated along these directions. New snow showed larger CL in the ground-parallel direction, and depth-hoar snow showed larger CL in the ground-perpendicular direction. Based on CL, the directional anisotropy was calculated. An attempt was also made to show the relationship between CL and texture index. The semivariogram was used to estimate the fractal dimension. Both CL and fractal dimension were found to be potential parameters to describe snow.

The changeable, variable and fragile nature of snow creates unique sampling challenges. In this paper, we present Star: an efficient, field-usable method for use in point-sampling spatial studies. We validate the accuracy of the Star method using a comparative Monte Carlo simulation of 1024 detailed samples of elevation data. As spatial snow studies generally attempt to find spatial continuity in layers and other properties, we use variogram ranges to compare the ability of four sampling methods to accurately reveal such spatial correlation. The three methods compared to Star represent gridded, gridded-random and pure-random methods; Star can be described as a linear-random method. The simulation shows Star’s accuracy to be comparable to both gridded and gridded-random methods. Following this comparative process we introduce a new measure of appropriateness for sampling methods: the correct convergence on a variogram model, which we call correct spatial correlation detection. This directly measures how many sampled areas become correctly classified with either spatially correlated or non-correlated variance for a given variogram model fit. In this measure, Star performs equivalently to the other methods, and in correct convergence it performs as well as pure-random sampling.

The process of temperature gradient metamorphism in snow strongly affects the microstructure and associated mechanical properties of the snow. The purpose of this study was to: (1) examine the temporal variations in three-dimensional snow microstructure under the influence of a strong temperature gradient for 6 days using X-ray computed microtomography (μCT); and (2) numerically simulate the linear elastic properties of snow from microtomographic data using a voxel-based finite-element technique. The temporal changes in the snow structure were analyzed in terms of density, specific surface area (SSA), thickness distribution of ice matrix and pores, structure model index and mean intercept length (MIL) fabric tensor. The structural indices and orthotropic elastic compliance matrix were computed over several sub-volumes within the reconstructed volume to account for statistical uncertainties. The mean density increased by about 14% on day 1 and no significant trend was observed thereafter. The SSA decreased by 22%, whereas both the ice and pore thickness distributions widened with time. The computed Young’s moduli were 1.5–4 times larger than previously published dynamic measurements and found to be significantly correlated with ice volume fraction and MIL fabric measures. The increasing trend in computed moduli during the experiment is consistent with the observed development of thicker vertical ice structures. Multiple linear regression models of elastic compliances using fabric tensor formulation and ice volume fraction could explain 89.9–93.0% of the variance. Our results suggest a strong dependence of elastic properties on both density and microstructural fabric.

Reflectance data for contaminated and different grain-size snow were collected using a spectroradiometer ranging from 350 to 2500 nm. Contamination was predominantly due to soil. The radiometer data were binned at 10 nm intervals by averaging, and then principal component analysis, shape, size and strength of the absorption peak, first and second derivatives were computed, providing information about the effect of grain size and contamination on snow reflectance. Relative strength for contamination and grain size showed a distinct reverse pattern at 1025 nm after continuum removal. Band absorption depth at 1025 nm showed an increase with increasing snow grain size, whereas the band depth was found to decrease with increased soil contamination. The curve shape was right asymmetric and showed a change to left asymmetry with increase in contamination. The first derivative of reflectance in the visible region showed a shift of peak due to contamination. Soil contamination significantly reduced the albedo of snow at a low level of contamination but showed little influence at higher level. Relative strength, shape of curve and reflectance characteristics have shown the potential to identify the influence of contamination and grain-size based metamorphism using satellite-based hyperspectral remote sensing.

This paper aims to show how recent knowledge developed in the field of avalanche research can be used for a real case study, the Taconnaz avalanche path, where passive structures already existed but had to be improved. First a morphological analysis of the site is done and historical data are analysed. Second, each recorded event is back-calculated using a numerical model of dense-flow avalanches. For each surveyed avalanche, parameters at the entry of the runout zone upstream of the defence structures are defined. Third, a statistical analysis of these parameters allows characterization of 100 year return period events. Fourth, physical and numerical models of dense avalanches interacting with defence structures are combined in order to design the most effective passive structure able to contain the reference scenarios. Finally, physical and numerical modelling of the interaction between the powder avalanche and the designed defence structure is performed, to show that the proposed improvements do not increase the residual risk due to the powder part in areas downstream of the defence structures.

We use velocity profile measurements captured at the Vallée de la Sionne test site, Switzerland, to find experimental evidence for the value of extreme, Voellmy-type runout parameters for snow avalanche flow. We apply a constitutive relation that adjusts the internal shear stress as a function of the kinetic energy associated with random motion of the snow granules, R. We then show how the Voellmy dry-Coulomb and velocity-squared friction parameters change (relax) as a function of an increase in R. Since the avalanche head is characterized by high random energy levels, friction decreases significantly, leading to rapidly moving and far-reaching avalanches. The relaxed friction parameters are near to values recommended by the Swiss avalanche dynamics guidelines. As the random kinetic energy decreases towards the tail, friction increases, causing avalanches to deposit mass and stop even on steep slopes. Our results suggest that the Voellmy friction model can be effectively applied to predict maximum avalanche velocities and maximum runout distances. However, it cannot be applied to model the full range of avalanche behaviour, especially to find the distribution of mass in the runout zone. We answer a series of questions concerning the role of R in avalanche dynamics.

The high Himalayan mountains in the north of India are important sources for generating and maintaining the climate over the entire northern belt of the Indian subcontinent. They also influence extreme weather events, such as the western disturbances over the region during winter. The work presented here describes some current trends in weather and climate over the western Himalaya and suggests some possible explanations in the context of climate change. The work also shows how the special features of Indian orography in the western Himalaya affect climate change in the long term, changing the pattern of precipitation over the region. Data analysis of different ranges of the western Himalaya shows significant variations in temperature and snowfall trends in the past few decades. Possible explanations for the changing climate over the western Himalaya are proposed, in terms of variations in cloudiness. The possible effects of climate change on the number of snowfall days and the occurrences of western disturbances over the western Himalaya are also analysed.

We present, analyse and discuss air-pressure data from finite-volume chute flows of dry fine snow in air. These experiments have the correct similarity criteria to model powder-snow avalanches and demonstrate the transition from a dense to a suspended flow. We measured the dynamic air pressure at the base of the flow, which features a marked negative pressure peak immediately behind the front. This feature is also seen in observations of natural powder-snow avalanches measured in Russia, Japan and Switzerland in direct numerical simulations of non-Boussinesq suspension flows and in ping-pong ball avalanches. This is evidence for large internal motions and suggests that there is a coherent vortex in the avalanche front. This can result in impact pressures many times larger than those expected from the mean flow velocity. We analyse the external air pressures using three models and show how the geometry and velocity of the flow can be found from this single air-pressure measurement. We also measured flow heights and speeds using image analysis and show that the speed is roughly independent of the slope angle and scales with the release size raised to the power 1/4, as predicted by similarity analysis for pseudo two-dimensional (2-D) flows.

Indian rivers originating in the Himalaya depend on seasonal snow-cover melt during crucial summer months. The seasonal snow cover was monitored using Advanced Wide Field Sensor (AWiFS) data of the Indian Remote Sensing Satellite (IRS) and using the Normalized Difference Snow Index (NDSI) algorithm. The investigation was carried out for a period of 3 years (2004/05, 2005/06 and 2006/07) between October and June. A total of 28 sub-basins of the Ganga and Indus river basins were monitored at intervals of 5 or 10 days. Approximately 1500 AWiFS scenes were analyzed. A combination of area–altitude distribution and snow map was used to estimate the distribution of snow cover in altitude zones for the individual basins and for the western and central Himalaya. Hypsographic curve and snow-free area was used to estimate monthly snow-line elevation. The lowest snow-line altitude in the winters of 2004/05, 2005/06 and 2006/07 was observed at 2480 ma.s.l. on 25 February 2005. In Ravi basin for the year 2004/05, snow accumulation and ablation were continuous processes throughout the winter. Even in the middle of winter, the snow area was reduced from 90% to 55%. Similar trends were observed for 2005/06 and 2007/08. In Bhaga basin, snowmelt was observed in the early part of the winter, i.e. in December, and no significant melting was observed between January and April.

We present simple scaling relationships that allow us to predict the main dynamical characteristics (height, length and velocity) of constant-volume snow avalanches with minimal input data. In particular, we show that both avalanche height and length can be expressed as a function only of the avalanche volume and the distance travelled by the front, independently of the specific rheological parameters of the snow. These scaling relationships are derived from a large-time asymptotic solution to the avalanche dynamic equations, corresponding to a balance between gravity and Voellmy friction (the kinematic wave approximation). Numerical simulations of the complete hydraulic shallow-flow equations confirm that this asymptotic solution, and the predicted scaling relationships, capture the main avalanche characteristics, even for relatively small travel distances. Though derived under restrictive assumptions, we argue that the scaling relationships described in this paper may constitute useful tools for avalanche engineering and design of protective structures.

Wet snow avalanches in India are common during the mid- and late winter in the Pir Panjal Range (2000–3000ma.s.l.) and during the late winter in the Great Himalayan Range (3000 ma.s.l. and above). Although it is well known that the presence of liquid water in snow makes the flow behaviour of wet snow avalanches different from that of dry snow avalanches, there exist few actual flow measurements with wet snow. The aim of this investigation is to understand the dynamics of wet snow avalanches by conducting medium-scale experiments (volumes of 3, 6 and 11 m3) on the Dhundi snow chute in Himachal Pradesh, India. We measured flow velocities using video data, as well as optical velocity sensors installed on the side walls and running surface. Measurement results relating to the slip velocity of the front and tail of the moving snow mass, as well as the average slip velocity, are presented. In addition, we use the results of the vertical velocity profile measurements to calculate the effective viscosity of snow at two locations within the flow. We identified a shear thinning type of behaviour, suggesting that a single avalanche rheology cannot describe wet snow avalanche behaviour.