scholarly journals Measurements of mid-winter spatial distribution of meltwater saturation

2010 ◽  
Vol 51 (54) ◽  
pp. 146-152
Author(s):  
J.C. Kapil ◽  
Anupam Kumar ◽  
P.S. Negi
Keyword(s):  
Spatial Distribution ◽  
Spatial Variability ◽  
Snow Cover ◽  
Measurement Techniques ◽  
Three Dimensional ◽  
Dielectric Measurement ◽  
Snow Stratigraphy ◽  
Wet Snow ◽  
Water Contents ◽  
Saturation Profiles

AbstractUnder melt–freeze conditions crusts may evolve within a snowpack, which may favour avalanche initiation by forming a hard bed surface for weakly bonded faceted grains. We used a parallel-probe saturation profiler (PPSP) to record the distribution of water contents within the snowpack. Diurnal effects of melt–freeze action on the growth of crusts were monitored with the help of the PPSP device. Saturation profiles were collected from a partially wet snow cover. Snow stratigraphy was conducted manually in the morning, after overnight freezing, to identify the location and the granular compositions of the crusts that had evolved. A one-to-one correspondence between the saturation spikes collected using the PPSP and the actual positions of the crusts was established. The PPSP was also used to monitor three-dimensional variations in the maximum percolation depths within a south-facing snowpack. The operation of the PPSP is faster than existing dielectric measurement techniques, so it was applied to study the spatial variability of maximum percolation depths on the slopes of different aspects.

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

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

<p>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 – 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.</p>

scholarly journals Modelling wet snow avalanche runout to assess road safety at a high-altitude mine in the central Andes

2016 ◽  
Vol 16 (11) ◽  
pp. 2303-2323 ◽  
Author(s):  
Cesar Vera Valero ◽  
Nander Wever ◽  
Yves Bühler ◽  
Lukas Stoffel ◽  
Stefan Margreth ◽  
...  
Keyword(s):  
High Altitude ◽  
Snow Cover ◽  
Three Dimensional ◽  
Central Andes ◽  
Early Spring ◽  
Avalanche Dynamics ◽  
Wet Snow ◽  
Dynamics Modelling ◽  
Snow Conditions ◽  
Del Rio

Abstract. Mining activities in cold regions are vulnerable to snow avalanches. Unlike operational facilities, which can be constructed in secure locations outside the reach of avalanches, access roads are often susceptible to being cut, leading to mine closures and significant financial losses. In this paper we discuss the application of avalanche runout modelling to predict the operational risk to mining roads, a long-standing problem for mines in high-altitude, snowy regions. We study the 35 km long road located in the "Cajón del rio Blanco" valley in the central Andes, which is operated by the Codelco Andina copper mine. In winter and early spring, this road is threatened by over 100 avalanche paths. If the release and snow cover conditions can be accurately specified, we find that avalanche dynamics modelling is able to represent runout, and safe traffic zones can be identified. We apply a detailed, physics-based snow cover model to calculate snow temperature, density and moisture content in three-dimensional terrain. This information is used to determine the initial and boundary conditions of the avalanche dynamics model. Of particular importance is the assessment of the current snow conditions along the avalanche tracks, which define the mass and thermal energy entrainment rates and therefore the possibility of avalanche growth and long runout distances.

Simulating snow instability in complex terrain

2020 ◽  
Author(s):  
Bettina Richter ◽  
Alec van Herwijnen ◽  
Mathias W. Rotach ◽  
Jürg Schweizer
Keyword(s):  
Spatial Variability ◽  
Snow Cover ◽  
Complex Terrain ◽  
Laser Scanning ◽  
Winter Season ◽  
Temporal Variations ◽  
Full Potential ◽  
Avalanche Forecasting ◽  
Snow Stratigraphy ◽  
Operational Forecasting

<p><span>Numerical snow cover models are increasingly used in operational avalanche forecasting. While these models can provide snow stratigraphy and some snow instability information, their full potential is not yet exploited in forecasting. We investigated, how well the snow cover model Alpine3D simulated spatial and temporal variations in snow instability. Therefore, simulations were performed in highly varying complex terrain for the winter season 2016-2017 in the region of Davos, Switzerland for an area of about 21 km x 21 km. Alpine3D was forced with data from several automatic weather stations within the region, which were interpolated to a resolution of 100 m. To reproduce observed spatial variability, we scaled precipitation input with snow height measurements derived with airborne laser scanning. For comparison, we also simulated the snowpack without scaling. The simulation with scaling precipitation showed significantly higher spatial variability in modeled snow instability than the simulation without scaling. However, when information was aggregated to aspect and elevation dependent information for the whole region, as it is done for operational forecasting, this variability vanished and scaling precipitation seems unnecessary. At the beginning of the season and towards the end, snow instability depended on aspect, while in the winter months December to March, differences between different aspects were small. The simulations with scaling precipitation revealed a strong influence of snow depth on snow instability, although the various snow instability criteria provided inconsistent results. Simulated profiles, which were classified as rather favourable were rated as rather unstable and vice versa. A comparison to traditional snow profiles shows that snow stratigraphy was reproduced well, but assessing snow instability from stratigraphy alone is not feasible.</span></p>

scholarly journals Spatial variability of micropenetration resistance in snow layers on a small slope

2004 ◽  
Vol 38 ◽  
pp. 202-208 ◽  
Author(s):  
Kalle Kronholm ◽  
Martin Schneebeli ◽  
Jürg Schweizer
Keyword(s):  
Spatial Variability ◽  
Spatial Variation ◽  
Snow Cover ◽  
Three Dimensional ◽  
Penetration Resistance ◽  
Snow Layer ◽  
Depositional Processes ◽  
Layer Deposition ◽  
Buried Layer ◽  
Linear Trends

AbstractThe mechanisms leading to dry-snow slab release are influenced by the three-dimensional variability of the snow cover. We measured 113 profiles of penetration resistance with a snow micropenetrometer on an alpine snow slope. Seven distinct layers were visually identified in all snow micropenetrometer profiles. The penetration resistance of adjacent layers did not change abruptly, but gradually across layer boundaries that were typically 2 mm thick. In two layers, penetration resistance varied around 200% over the grid, possibly due to wind effects during or after layer deposition. Penetration resistance varied around 25%in five layers. Statistically significant slope-scale linear trends were found for all layers. The semivariogram was used to describe the spatial variation. Penetration resistance was autocorrelated, but the scale of variation was layer-specific. A buried layer of surface hoar was the most critical weak layer. It had little spatial variation. The layers in the slab above had higher spatial variation. The penetration resistance of each snow layer had distinct geostatistical properties, caused by the depositional processes.

Incorporation of spatial variability in modeling non-point source groundwater nitrate pollution

1996 ◽  
Vol 33 (4-5) ◽  
pp. 233-240 ◽  
Author(s):  
F. S. Goderya ◽  
M. F. Dahab ◽  
W. E. Woldt ◽  
I. Bogardi
Keyword(s):  
Spatial Variability ◽  
Point Source ◽  
Three Dimensional ◽  
Nitrate Contamination ◽  
Geostatistical Simulation ◽  
Chemical Measurements ◽  
Spatially Distributed ◽  
Potential Benefits ◽  
Zone Modeling ◽  
Physical And Chemical

A methodology for incorporation of spatial variability in modeling non-point source groundwater nitrate contamination is presented. The methodology combines geostatistical simulation and unsaturated zone modeling for estimating the amount of nitrate loading to groundwater. Three dimensional soil nitrogen variability and 2-dimensional crop yield variability are used in quantifying potential benefits of spatially distributed nitrogen input. This technique, in combination with physical and chemical measurements, is utilized as a means of illustrating how the spatial statistical properties of nitrate leaching can be obtained for different scenarios of fixed and variable rate nitrogen applications.

scholarly journals Three-Dimensional Spatial Distribution of Synapses in the Neocortex: A Dual-Beam Electron Microscopy Study

2013 ◽  
Vol 24 (6) ◽  
pp. 1579-1588 ◽  
Author(s):  
Angel Merchán-Pérez ◽  
José-Rodrigo Rodríguez ◽  
Santiago González ◽  
Víctor Robles ◽  
Javier DeFelipe ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Spatial Distribution ◽  
Three Dimensional ◽  
Microscopy Study ◽  
Electron Microscopy Study ◽  
Beam Electron ◽  
Dual Beam

The Three-Dimensional Surface Topographic Characterisation of Diamond Grinding Wheels

2010 ◽  
Vol 126-128 ◽  
pp. 690-695
Author(s):  
David Lee Butler
Keyword(s):  
Measurement Techniques ◽  
Three Dimensional ◽  
Surface Measurement ◽  
Grinding Wheel ◽  
Profile Measurement ◽  
Detailed Knowledge ◽  
Grinding Wheels ◽  
Diamond Grinding ◽  
Insight Into ◽  
Dimensional Surface

Surface measurement using three-dimensional stylus instruments is a relatively new technique that offers numerous advantages over more traditional profilometry methods. The information generated is, unlike profile measurement, less subjective and more statistical providing additional insight into the surface structure. One application of surface measurement that has encountered problems when using the profilometry method is that of grinding wheel characterisation. The wheel surface texture (topography) and the conditions under which it is generated have a profound effect upon the grinding performance as characterised by the grinding forces, power consumption, temperature, and surface integrity of components. A detailed knowledge of the nature of the topography of the grinding wheel would provide further insight into surface interactions between the wheel and workpiece as well as enabling improved control of the grinding process in general. In this paper four diamond grinding wheels of 91 and 181 micron grit size were subjected to differing dressing conditions to produce varying final wheel topographies. Three-dimensional surface measurement techniques were employed to quantitatively characterise the topographic change and provide an aerial estimation of the number of cutting grains. The results demonstrate that the techniques can distinguish between a worn and dressed wheel. In addition, the parametric values generated from the various surfaces can aid the user in determining when re-dressing is required.

Three-dimensional Force Perception of Robotic Bipolar Forceps for Brain Tumor Resection

2021 ◽  
Author(s):  
Xiu-Heng Zhang ◽  
Heng Zhang ◽  
Zhen Li ◽  
Gui-Bin Bian
Keyword(s):  
Brain Tumor ◽  
Real Time ◽  
Force Measurement ◽  
Measurement Techniques ◽  
Tumor Resection ◽  
Three Dimensional ◽  
Contact Forces ◽  
Surgical Instruments ◽  
Force Perception ◽  
Brain Tumor Resection

Abstract Three-dimensional force perception is critically important in the enhancement of human force perception to minimize brain injuries resulting from excessive forces applied by surgical instruments in robot-assisted brain tumor resection. And surgeons are not responsive enough to interpret tool-tissue interaction forces. In previous studies, various force measurement techniques have been published. In neurosurgical scenarios, there are still some drawbacks to these presented approaches to forces perception. Because of the narrow, and slim configuration of bipolar forceps, three-dimensional contact forces on forceps tips is not easy to be traced in real-time. Five fundamental acts of handling bipolar forceps are poking, opposing, pressing, opening, and closing. The first three acts independently correspond to the axial force of z, x, y. So, in this paper, typical interactions between bipolar forceps and brain tissues have been analyzed. A three-dimensional force perception technique to collect force data on bipolar forceps tips by installing three Fiber Bragg Grating Sensors (FBGs) on each prong of bipolar forceps in real-time is proposed. Experiments using a tele-neurosurgical robot were performed on an in-vitro pig brain. In the experiments, three-dimensional forces were tracked in real-time. It is possible to experience forces at a minimum of 0.01 N. The three-dimensional force perception range is 0-4 N. The calibrating resolution on x, y, and z, is 0.01, 0.03, 0.1 N, separately. According to our observation, the measurement accuracy precision is over 95%.

Spatial Distribution of Snow Storage and Snowmelt Dynamics in Central Yenisei Siberia

2021 ◽  
pp. 82-92
Author(s):  
I. V. Danilova ◽  
◽  
A. A. Onuchin ◽  
◽  
Keyword(s):  
Spatial Distribution ◽  
Snow Cover ◽  
Sea Level ◽  
Thermal Regime ◽  
Regression Models ◽  
Weather Station ◽  
Digital Maps ◽  
Independent Variables ◽  
Snow Storage

In this paper the spatial distribution of water reserves in the snow cover and the dynamics of snow cover melting due to the peculiarity of the thermal regime were analyzed for the central part of Yenisei Siberia. To create digital maps of water reserves in the snow cover, regression models were developed. The geographic coordinates, elevation above sea level and the distance from the orographic boundaries were used as independent variables in regression models. Based on the created maps, the dynamics of snow cover melting was obtained in the study area, taking into account the thermal regime at a key weather station.

Effect of Savanna windrow wood burning on the spatial variability of soil properties

2021 ◽  
Vol 51 ◽  
Author(s):  
Diogo Neia Eberhardt ◽  
Robélio Leandro Marchão ◽  
Pedro Rodolfo Siqueira Vendrame ◽  
Marc Corbeels ◽  
Osvaldo Guedes Filho ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Spatial Variability ◽  
Spatial Dependence ◽  
Chemical Properties ◽  
Spatial Arrangement ◽  
Nugget Effect ◽  
Tropical Savannas ◽  
Geostatistical Methods ◽  
Exchangeable Ca ◽  
Spherical Models

ABSTRACT Tropical Savannas cover an area of approximately 1.9 billion hectares around the word and are subject to regular fires every 1 to 4 years. This study aimed to evaluate the influence of burning windrow wood from Cerrado (Brazilian Savanna) deforestation on the spatial variability of soil chemical properties, in the field. The data were analysed by using geostatistical methods. The semivariograms for pH(H2O), pH(CaCl2), Ca, Mg and K were calculated according to spherical models, whereas the phosphorus showed a nugget effect. The cross semi-variograms showed correlations between pH(H2O) and pH(CaCl2) with other variables with spatial dependence (exchangeable Ca and Mg and available K). The spatial variability maps for the pH(H2O), pH(CaCl2), Ca, Mg and K concentrations also showed similar patterns of spatial variability, indicating that burning the vegetation after deforestation caused a well-defined spatial arrangement. Even after 20 years of use with agriculture, the spatial distribution of pH(H2O), pH(CaCl2), Ca, Mg and available K was affected by the wood windrow burning that took place during the initial deforestation.

Sign in / Sign up

Export Citation Format

Share Document