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

The 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

Avalanche characterization for regional forecasting

In the Sunnmøre and Romsdal road districts in Western Norway, the local road authorities have compiled a register of more than 300 sites where avalanches encounter principal roads in the area. The area covered is about 5 000 km2. The local climate varies substantially throughout the area, mainly due to elevation ranging from sea level to 1500 m, and to highly varying proximity to the coast. To con-duct avalanche hazard evaluation and warning for the roads in the region, a database was constructed based on the compiled register. In addition, each avalanche path was characterized by it’s sensibility to different wind directions (based on starting zone aspect and shape), starting zone height and area, local climate, steepness and the road segment’s situation relative to the run out potential of the avalanche. Us-ing this data, the road segments were grouped to identify segments exposed to avalanches that run un-der similar conditions. This allowed an operational probability assessment of which road segments are more likely to have an avalanche reaching the road in given weather conditions. The method can be eas-ily implemented in a GIS application and thus give decision makers a fast overview of the anticipated situation in the road district during a given weather situation

Integrated Database for Rapid Mass Movements in Norway

Rapid mass movements include all kinds of slides in geological material, snow or ice. Traditionally, information about such events is collected separately in different databases covering selected geographical regions and event types. In Norway the terrain is susceptible to all types of rapid mass movements ranging from single rocks hitting roads and houses to large avalanches and huge rock falls where entire mountainsides collapse into fjords creating flood waves and endangering large areas. In addition, quick clay slides occur in desalinated marine sediments in south eastern and mid Norway. For the authorities and inhabitants of endangered areas, the type of treat is of minor importance and mitigation measures have to consider all types of mass movements. This demand asks for a national overview over all registered slide events that allows fast and easy access to the available data. Therefore an integrated national database for all kind of rapid mass movements was developed. The database is built around the single slide event. Only three data entries are mandatory: Time, location and type of slide. The remaining optional information enables registration of detailed information about the terrain, involved materials and damages. Pictures, movies and other documentation can be uploaded into the database. A web based graphical user interface was developed that allows entering new slides, editing and search for slide events. An integration of the database into a GIS system is currently under development. Datasets from various national sources like the road authorities and geological survey were imported into the database. Today, the database contains 21,000 slide events from the last 500 hundred years covering the entire country. A first analysis of the data shows that most slide registrations cover snow avalanche and rock fall events followed by debris slide events. Most events are registered in the steep fjord terrain of the Norwegian west coast, but major slides are registered all over the country. Avalanches clearly account for most fatalities, while large rock avalanche events causing flood waves are the most severe single events. The data is strongly influenced by the personal engagement of local observers and varying observation routines. This database gives a unique source for statistical analysis of slide events, risk analysis and the relation between slides and climate

Could retrieval of snow layer formation by optical satellite remote sensing help avalanche forecasting? Presentation of first results

Of special interest within the field of avalanche research and avalanche warning are properties related to snow grain type and snow grain size at the surface. In continental and intermountain avalanche climates weak layers or interfaces are the main cause of avalanches. Knowledge about such weak layers helps to increase the precision of avalanche forecasting. Some of these potential weak layers form on the snow surface and are preserved until burial. Optical satellite sensors measure reflected sunlight at different wavelengths. The near-infrared region is sensitive to the optical grain size of the snow. Due to the distinct size and shape characteristics of potential weak layers such as, for example, surface hoar, their reflectance is quite different from new snow in general. If the weather permits optical observations it should, therefore, be possible to detect such layers by remote sensing. We present the results of a pilot study where in situ measured surface snow grain characteristics are compared to snow grain characteristics as derived from multispectral data from the MODIS satellite sensor. The pilot study showed that parallel in situ snow measurements and snow analyses exploiting data from MODIS are possible for the selected test sites in Norway. The study aims at establishing a relationship between the satellite-observed snow grain size index (SGS) variable and the snow grain size and shape as measured in the field. Based on satellite and in situ data measured over several years, we intend to establish a snow grain evolution model. The model will be used as an input to the avalanche forecasting model

GIS aided avalanche warning in Norway.

By 2008 detailed avalanche warning for the entire Norway is not available. The Norwegian Meteorological Institute only issues a general warning for large regions of the country for danger level 4 or 5, mainly based on automatic indexes integrated in the meteorological forecasting models. Regional and local avalanche warning are issued by the NGI on request of customers such as the railway or road administration and local communities. The NGI warning projects cover vast areas of several 1000 sq km with a very limited budget, approx. 2 man hours a day. Therefore the workflow has to be extremely efficient from acquiring observation data, evaluation of the situation and sending out the new forecast. It has been an aim to include the entire workflow in an all in one web application. A GIS solution was chosen to integrate all data needed by the forecaster for the avalanche danger evaluation. This interactive system of maps features background information for the entire country such as topographic maps, slope steepness, aspect and hill shade to give a 3D impression of the terrain. In each avalanche warning area, all active avalanche paths are plotted including information on the most wind exposed direction. Each avalanche path is linked to a database generated webpage, which will inform the user on more details on the path, such as fall height, release area elevation, pictures etc. In this way the forecaster easily can get an overview over large areas and can give detailed avalanche warnings to the customer. The system is under constant development and is planned to be completely available on web browser such that no special software is needed on local PCs. Future versions will include interactive access to weather data both as 2D fields as well as time series at selected stations

Spatial variability - so what?

Since the landmark papers of Conway and Abrahamson many studies have tried to quantify spatial variability. Many different methods have been used and the studies covered a variety of scales. Accordingly, some results appear contradictory, suggesting that the degree of spatial variation varies widely. This is not surprising, and is partly due to the methodology used and of course, due to varying natural conditions. Spatial variability is doubtless an inherent property of the snowpack. One important result seems to be that the layering is less variable than, for example, the stability of small column tests. Whereas it is often perceived that the results of the studies were not conclusive, it seems clear that they completely changed our view of spatial variability. We realized the importance of scale issues. For example, the variation will strongly depend on the measurement scale – the so-called support – of the method (SnowMicroPen vs. compression test vs. rutschblock test). Geostatistical analysis has been intro duced and used to derive appropriate input data for numerical models. Model results suggest that spatial variation of strength properties have a substantial knockdown effect on slope stability and that the effect increases with increasing spatial correlation. The focus on scale has also revealed that spatial variations can promote instability or inhibit it. With the awareness of scale we can now address the causes of spatial variability. Many processes such as radiation and wind act at several scales. The most challenging process is probably wind that might hinder prediction of variability at the slope scale. However, at the regional scale, already today, many avalanche forecasting services try to address differences in respect to slope aspect. We will review the present state of knowledge, discuss consequences for avalanche forecasting and snow stability evaluation, and recommend future research directions

Spatial variability - So what?

Since the landmark papers of Conway and Abrahamson many studies have tried to quantify spatial variability. Many different methods have been used and the studies covered a variety of scales. Accordingly, some results appear contradictory, suggesting that the degree of spatial variation varies widely. This is not surprising, and is partly due to the methodology used and of course, due to varying natural conditions. Spatial variability is doubtless an inherent property of the snowpack. One important result seems to be that the layering is less variable than, for example, the stability of small column tests. Whereas it is often perceived that the results of the studies were not conclusive, it seems clear that they completely changed our view of spatial variability. We realized the importance of scale issues. For example, the variation will strongly depend on the measurement scale – the so-called support – of the method (SnowMicroPen vs. compression test vs. rutschblock test). Geostatistical analysis has been introduced and used to derive appropriate input data for numerical models. Model results suggest that spatial variation of strength properties have a substantial knockdown effect on slope stability and that the effect increases with increasing spatial correlation. The focus on scale has also revealed that spatial variations can promote instability or inhibit it. With the awareness of scale we can now address the causes of spatial variability. Many processes such as radiation and wind act at several scales. The most challenging process is probably wind that might hinder prediction of variability at the slope scale. However, at the regional scale, already today, many avalanche forecasting services try to address differences in respect to slope aspect. We will review the present state of knowledge, discuss consequences for avalanche forecasting and snow stability evaluation, and recommend future research directions

Temporal changes in the spatial variability of shear strength and stability.

Avalanche forecasting involves the prediction of spatial and temporal variability of the snowpack. To predict avalanches with more accuracy it is important to determine whether the snowpack is becoming more spatially variable or more spatially uniform. Greater variability increases uncertainty in extrapolation and prediction. Our results offer a look at the evolution of the spatial variability of shear strength and stability of a buried surface hoar layer in southwestern Montana, USA, from shortly after burial until it was no longer the weakest layer in the snowpack. We selected the study site for its 27- degree planar slope, uniform ground cover, and wind-sheltered location. This simplified the comparison of the plots by minimizing initial spatial differences so we could focus on temporal change. Within the site, we sampled four 14 m x 14 m arrays of more than 70 shear frame tests in a layout optimized for spatial analysis. Over a three-week period, the sampling of the four adjacent arrays showed temporal change. The variability of the shear strength of this layer initially decreased then became increasingly variable through time. This suggests that extrapolating test results to other locations becomes increasingly unreliable as layers age, a result that matches practical experience. The data also provide indications that shear strength has a correlation length, the distance at which test results are related, of just a few meters. This short correlation length demonstrates quantitatively why stability tests that are relatively close together can be quite different