Modeling Multi-Frequency Tomograms for Snow Stratigraphy

Estimating snow water equivalent over long mountain transects using snowmobile-mounted ground-penetrating radar

Geophysics ◽

10.1190/geo2015-0121.1 ◽

2016 ◽

Vol 81 (1) ◽

pp. WA183-WA193 ◽

Cited By ~ 9

Author(s):

W. Steven Holbrook ◽

Scott N. Miller ◽

Matthew A. Provart

Keyword(s):

Ground Penetrating Radar ◽

Snow Water Equivalent ◽

Ground Surface ◽

Snow Accumulation ◽

Accurate Estimation ◽

Snow Density ◽

Snow Stratigraphy ◽

Flood Estimation ◽

Snow Water ◽

Ground Penetrating

The water balance in alpine watersheds is dominated by snowmelt, which provides infiltration, recharges aquifers, controls peak runoff, and is responsible for most of the annual water flow downstream. Accurate estimation of snow water equivalent (SWE) is necessary for runoff and flood estimation, but acquiring enough measurements is challenging due to the variability of snow accumulation, ablation, and redistribution at a range of scales in mountainous terrain. We have developed a method for imaging snow stratigraphy and estimating SWE over large distances from a ground-penetrating radar (GPR) system mounted on a snowmobile. We mounted commercial GPR systems (500 and 800 MHz) to the front of the snowmobile to provide maximum mobility and ensure that measurements were taken on pristine snow. Images showed detailed snow stratigraphy down to the ground surface over snow depths up to at least 8 m, enabling the elucidation of snow accumulation and redistribution processes. We estimated snow density (and thus SWE, assuming no liquid water) by measuring radar velocity of the snowpack through migration focusing analysis. Results from the Medicine Bow Mountains of southeast Wyoming showed that estimates of snow density from GPR ([Formula: see text]) were in good agreement with those from coincident snow cores ([Formula: see text]). Using this method, snow thickness, snow density, and SWE can be measured over large areas solely from rapidly acquired common-offset GPR profiles, without the need for common-midpoint acquisition or snow cores.

Recording microscale variations in snowpack layering using near-infrared photography

Journal of Glaciology ◽

10.3189/002214310791190938 ◽

2010 ◽

Vol 56 (195) ◽

pp. 75-80 ◽

Cited By ~ 18

Author(s):

Ken D. Tape ◽

Nick Rutter ◽

Hans-Peter Marshall ◽

Richard Essery ◽

Matthew Sturm

Keyword(s):

Near Infrared ◽

Digital Camera ◽

Post Processing ◽

Snow Layer ◽

Avalanche Forecasting ◽

The North ◽

Nir Imaging ◽

Snow Stratigraphy ◽

Wind Events ◽

Lateral Variations

AbstractDeposition of snow from precipitation and wind events creates layering within seasonal snowpacks. The thickness and horizontal continuity of layers within seasonal snowpacks can be highly variable, due to snow blowing around topography and vegetation, and this has important implications for hydrology, remote sensing and avalanche forecasting. In this paper, we present practical field and post-processing protocols for recording lateral variations in snow stratigraphy using near-infrared (NIR) photography. A Fuji S9100 digital camera, modified to be sensitive to NIR wavelengths, was mounted on a rail system that allowed for rapid imaging of a 10 m long snow trench excavated on the north side of Toolik Lake, Alaska (68°38′ N, 149°36′ W). Post-processing of the images included removal of lens distortion and vignetting. A tape measure running along the base of the trench provided known locations (control points) that permitted scaling and georeferencing. Snow layer heights estimated from the NIR images compared well with manual stratigraphic measurements made at 0.2 m intervals along the trench (n = 357, R2 = 0.97). Considerably greater stratigraphic detail was captured by the NIR images than in the manually recorded profiles. NIR imaging of snow trenches using the described protocols is an efficient tool for quantifying continuous microscale variations in snow layers and associated properties.

Mechanical stability indicators derived from detailed snow cover simulations

10.5194/egusphere-egu21-1341 ◽

2021 ◽

Author(s):

Léo Viallon-Galinier ◽

Pascal Hagenmuller ◽

Nicolas Eckert ◽

Benjamin Reuter

Keyword(s):

Mechanical Properties ◽

Snow Cover ◽

Mechanical Stability ◽

Weather Forecasting ◽

Large Data ◽

Failure Initiation ◽

Avalanche Hazard ◽

Snow Stratigraphy ◽

Numerical Weather Forecasting ◽

Numerical Tools

The use of numerical modeling of the snow cover in support of avalanche hazard forecasting has been increasing in the last decade. Besides field observations and numerical weather forecasting, these numerical tools provide information otherwise unavailable on the present and future state of the snow cover. In order to provide useful input for avalanche hazard assessment, different mechanical stability indicators are typically computed from simulated snow stratigraphy. Such indicators condense the wealth of information produced by snow cover models, especially when dealing with large data (e.g., large domains, high spatial resolution, ensemble forecasting). Here, we provide an overview of such indicators. Mechanical stability indicators can be classified in two types i.e., whether they are solely based on mechanical rules or whether they include additional expert rules. These indicators span different mechanical processes involved in avalanche release: failure initiation and crack propagation, for instance. The indicators rely on mechanical properties of each layer. We discuss parameterizations of mechanical properties and the associated technical implementation details. We show simplified examples of snow stratigraphy to illustrate the benefit of different stability indicators in typical situations. There is no perfect indicator to describe the instability for any situation. All indicators are sensitive to the snow cover modeling assumptions and the computation of mechanical properties and hence, require some tuning before operational use. In practice, a combination of indicators should be considered to capture the variety of avalanche situations.

A tracking algorithm to identify slab and weak layer combinations for assessing snow instability and avalanche problem type

10.5194/egusphere-egu21-1578 ◽

2021 ◽

Author(s):

Benjamin Reuter ◽

Léo Viallon-Galinier ◽

Stephanie Mayer ◽

Pascal Hagenmuller ◽

Samuel Morin

Keyword(s):

Snow Cover ◽

Winter Season ◽

Essential Element ◽

Problem Type ◽

Model Output ◽

Avalanche Forecasting ◽

Weak Layer ◽

Problem Types ◽

Snow Stratigraphy ◽

Wet Snow

Snow cover models have mostly been developed to support avalanche forecasting. Recently developed snow instability metrics can help interpreting modeled snow cover data. However, presently snow cover models cannot forecast the relevant avalanche problem types &#8211; an essential element to describe avalanche danger. We present an approach to detect, track and assess weak layers in snow cover model output data to eventually assess the related avalanche problem type. We demonstrate the applicability of this approach with both, SNOWPACK and CROCUS snow cover model output for one winter season at Weissfluhjoch. We introduced a classification scheme for four commonly used avalanche problem types including new snow, wind slabs, persistent weak layers and wet snow, so different avalanche situations during a winter season can be classified based on weak layer type and meteorological conditions. According to the modeled avalanche problem types and snow instability metrics both models produced weaknesses in the modeled stratigraphy during similar periods. For instance, in late December 2014 the models picked up a non-persistent as well as a persistent weak layer that were both observed in the field and caused widespread instability in the area. Times when avalanches released naturally were recorded with two seismic avalanche detection systems, and coincided reasonably well with periods of low modeled stability. Moreover, the presented approach provides the avalanche problem types that relate to the observed natural instability which makes the interpretation of modeled snow instability metrics easier. As the presented approach is process-based, it is applicable to any model in any snow avalanche climate. It could be used to anticipate changes in avalanche problem type due to changing climate. Moreover, the presented approach is suited to support the interpretation of snow stratigraphy data for operational forecasting.

Snow Stratigraphy and Water Equivalence Measured With an Active Microwave System

Journal of Glaciology ◽

10.3189/s0022143000010765 ◽

1980 ◽

Vol 26 (94) ◽

pp. 225-233

Author(s):

D. A. Ellerbruch ◽

H. S. Boyne

Keyword(s):

Electromagnetic Scattering ◽

Direct Determination ◽

Snow Pack ◽

Frequency Range ◽

Microwave Radar ◽

Snow Stratigraphy ◽

Microwave System ◽

The Relationship ◽

System Operating

AbstractThis paper reports on research on the relationship between the electromagnetic scattering properties and physical properties of snow-pack. An FM-CW active microwave radar system operating in the frequency range 8-12 GHz is used to scatter electromagnetic radiation from surface and subsurface stratigraphic layers in the snow-pack. The amplitude of the scattered radiation as a function of depth in the snow-pack can be correlated with such physical characteristics as density, hardness, stratigraphy, and moisture content. A direct determination of snow-pack water equivalence can be made from these observations.

Instruments and Methods Snow Density Profiling by Nuclear Means

Journal of Glaciology ◽

10.1017/s0022143000019158 ◽

1966 ◽

Vol 6 (43) ◽

pp. 171-176

Author(s):

Robert D. Leighty

Keyword(s):

Soil Moisture ◽

Field Investigation ◽

Present Form ◽

Snow Density ◽

Nuclear Technique ◽

Density Profiles ◽

Snow Stratigraphy ◽

Modes Of Processing ◽

Nuclear Detectors ◽

Nuclear Method

Abstract During the period 8–19 May 1963 a preliminary field investigation was conducted in Greenland to determine the feasibility of using a nuclear technique to determine snow and ice density profiles. A standard nuclear soil-moisture depth probe was used with two modes of processing and recording the nuclear pulses. Example data are compared with snow densities obtained by the standard weighing technique. The nuclear method was found to be feasible; however, deficiencies related to poor resolution render the probe unusable for detailed profiling of snow stratigraphy in its present form, but expected progress in nucleonics should enable improved resolution and accuracy to be achieved by improvement of nuclear detectors.

Snow Stratigraphy and Water Equivalence Measured With an Active Microwave System

Journal of Glaciology ◽

10.1017/s0022143000010765 ◽

1980 ◽

Vol 26 (94) ◽

pp. 225-233 ◽

Cited By ~ 27

Author(s):

D. A. Ellerbruch ◽

H. S. Boyne

Keyword(s):

Electromagnetic Scattering ◽

Direct Determination ◽

Snow Pack ◽

Frequency Range ◽

Microwave Radar ◽

Snow Stratigraphy ◽

Microwave System ◽

The Relationship ◽

System Operating

Abstract This paper reports on research on the relationship between the electromagnetic scattering properties and physical properties of snow-pack. An FM-CW active microwave radar system operating in the frequency range 8-12 GHz is used to scatter electromagnetic radiation from surface and subsurface stratigraphic layers in the snow-pack. The amplitude of the scattered radiation as a function of depth in the snow-pack can be correlated with such physical characteristics as density, hardness, stratigraphy, and moisture content. A direct determination of snow-pack water equivalence can be made from these observations.

Measuring specific surface area of snow by near-infrared photography

Journal of Glaciology ◽

10.3189/172756506781828412 ◽

2006 ◽

Vol 52 (179) ◽

pp. 558-564 ◽

Cited By ~ 134

Author(s):

Margret Matzl ◽

Martin Schneebeli

Keyword(s):

Specific Surface ◽

Surface Area ◽

Specific Surface Area ◽

Near Infrared ◽

Two Dimensions ◽

Chemical Models ◽

Snow Stratigraphy ◽

Physical And Chemical

AbstractThe specific surface area (SSA) is considered an essential microstructural parameter for the characterization of snow. Photography in the near-infrared (NIR) spectrum is sensitive to the SSA. We calculated the snow reflectance from calibrated NIR images of snow-pit walls and measured the SSA of samples obtained at the same locations. This new method is used to map the snow stratigraphy. The correlation between reflectance and SSA was found to be 90%. Calibrated NIR photography allows quantitative determination of SSA and its spatial variation in a snow profile in two dimensions within an uncertainty of 15%. In an image covering 0.5–1.0 m2, even layers of 1mm thickness can be documented and measured. Spatial maps of SSA are an important tool in initializing and validating physical and chemical models of the snowpack.

Comparing simulated and manual snow profiles to derive thresholds for modeled snow instability metrics

10.5194/egusphere-egu2020-18898 ◽

2020 ◽

Author(s):

Stephanie Mayer ◽

Alec van Herwijnen ◽

Mathias Bavay ◽

Bettina Richter ◽

Jürg Schweizer

Keyword(s):

Snow Cover ◽

Input Data ◽

Climate Models ◽

Weather Prediction ◽

Mechanical Instability ◽

Critical Crack ◽

Critical Crack Length ◽

Snow Stratigraphy ◽

Meteorological Input ◽

Weather Stations

Numerical snow cover models enable simulating present or future snow stratigraphy based on meteorological input data from automatic weather stations, numerical weather prediction or climate models. To assess avalanche danger for short-term forecasts or with respect to long-term trends induced by a warming climate, the modeled vertical layering of the snowpack has to be interpreted in terms of mechanical instability. In recent years, improvements in our understanding of dry-snow slab avalanche formation have led to the introduction of new metrics describing the fracture processes leading to avalanche release. Even though these instability metrics have been implemented into the detailed snow cover model SNOWPACK, validated threshold values that discriminate rather stable from rather unstable snow conditions are not readily available. To overcome this issue, we compared a comprehensive dataset of almost 600 manual snow profiles with simulations. The manual profiles were observed in the region of Davos over 17 different winters and include stability tests such as the Rutschblock test as well as observations of signs of instability. To simulate snow stratigraphy at the locations of the manual profiles, we obtained meteorological input data by interpolating measurements from a network of automatic weather stations. By matching simulated snow layers with the layers from traditional snow profiles, we established a method to detect potential weak layers in the simulated profiles and determine the degree of instability. To this end, thresholds for failure initiation (skier stability index) and crack propagation criteria (critical crack length) were calibrated using the observed stability test results and signs of instability incorporated in the manual observations. The resulting instability criteria are an important step towards exploiting numerical snow cover models for snow instability assessment.

Potential avalanche release in windthrow areas: the effect of snow height and terrain roughness

10.5194/egusphere-egu2020-8922 ◽

2020 ◽

Author(s):

Natalie Brožová ◽

Tommaso Baggio ◽

Michaela Teich ◽

Alexander Bast ◽

Peter Bebi

Keyword(s):

Surface Roughness ◽

Snow Accumulation ◽

Critical Conditions ◽

Continuous Increase ◽

Snow Stratigraphy ◽

Roughness Elements ◽

Close Range ◽

Undisturbed Forest ◽

Local Release ◽

Avalanche Formation

Windthrow is an important disturbance agent in forest ecosystems and is expected to become more frequent and severe under climate change. Windthrow creates large amounts of surface roughness from downed trees, root plates and stumps. In mountain forests, these elements increase the surface roughness and provide a considerable protective effect against snow avalanches during the first years following a disturbance event. However, if large volumes of snow covers the surface roughness elements, a windthrow area may become prone to avalanche release. Snow accumulation produces terrain smoothing, which is an important factor in avalanche formation.To assess the effect of snow accumulation on surface roughness in windthrow areas, we quantified terrain smoothing using a vector ruggedness measure and corresponding snow heights, based on digital surface models from summer and winter terrain produced from repetitive UAV flights. Additionally, the snowpack structure was examined using a digital snow micro penetrometer (SMP) to quantify the heterogeneity of snow stratigraphy and to monitor a possible development of weak snow layers over distances greater than 10-20&#160;m, which may contribute to slab avalanche formation. Four study plots were selected to characterize different conditions: i) undisturbed forest, windthrow area with ii) high and iii) low surface roughness, and iv) an open meadow control plot. We then quantified how surface roughness is smoothed depending on the snow height, and at the same time characterized the snowpack structure and the extent of potential weak layers.We found that increasing snow height leads to decreasing surface roughness, which can produce local release areas. We expect that with continuous increase of snow height, these release areas expand in size; however, further analyses of the snowpack structure will provide deeper insights in potential weak layer formation. Critical conditions for avalanche releases in windthrow areas may thus be defined based on scenarios for snow height and close-range sensing-based roughness data.