Honningsvåg Snow Data 2022

Portions of Honningsvåg's infrastructure are situated under the slopes of the mountain Storefjell. Steep slopes in combination with plentiful winter snowfall lead to situations where buildings and roads in the areas around Holmbukt and Honningsvåg are exposed to snow avalanche hazards.

Real-time snow depth data serve as an important input for general monitoring of avalanche path conditions and for daily avalanche hazard forecasts. Six DRIVA snow sensors were installed in the slopes over Honningsvåg for the 2021/2022 winter. These sensors measure the snow depth with an ultrasonic ranging system and send these data to users in real-time via Telenors Narrowband Internet of Things (NB-IoT) communications protocol.

The sensors in Honningsvåg form a portion of the DRIVA project which employs "low-cost, low-power" solutions to acquire natural hazard-related data. These data are made available on a website where they serve as a data source for those responsible for avalanche hazard assessments and relevant decision-making in the kommune.

Nordkapp kommune has, in cooperation with the Arctic Safety Centre (ASC), Telenor Svalbard AS, and with input from NVE and Skred AS, placed six snow depth sensors in the vicinity of known avalanche release areas. In the Holmbukt area, three sensors monitor an avalanche path in which avalanche hazard resulted in closed roads and evacuated homes in the winter of 2020. Three additional sensors installed on the south and east-facing slopes of Storefjell monitor snow depths in the avalanche paths over buildings in Honningsvåg's central area. The interactive 3D map scene below shows the locations of the sensors with slope steepness and the 100 year hazard zone delineated for reference.

The snow sensors monitor snow depth throughout the winter, measuring and sending data every ten minutes for 144 measurements each day. Data are made available in real-time on a website developed specifically for users of these data. The example below shows data registerd during a snow storm in January 2021. The arrows indicate (1) when it began to snow and how the snow accumulated (between 1 and 2), and (2) when the wind direction shifted, transporting snow off of the release area. This example demonstrates how these data can be employed to monitor the snow conditions and snow accumulation in an avalanche release area.

Mapping the distribution of snow (e.g. spatially-distributed snow depths) across a slope also helps to select appropriate sensor locations. In February 2022, the ASC used a terrestrial laser scanner (TLS) to measure the snow depths across Storefjell's slopes. TLS is an active remote sensing technology which sends pulses of light and measures the time it takes the light to reflect off a target surface (in this case, the snow covering Storefjell) and return to the TLS. These data are then used to create a digital elevation model (DEM) of the slope. The elevation difference between a "scan" or DEM of the slope with snow and the slope without snow represents the snow depth. Thus, TLS technology allows for the accurate calculation of snow depths across a slope, with measurement accuracy typically under 10 cm. ASC's scanning campaign in February 2022 followed a period with considerable precipitation and wind, therefore giving a representative picture of snow distribution and accumulation after a period of "avalanche weather."

Comparing photos taken from the scanning locations for scans without and with snow allows for a better visualization of what the TLS "sees." The photos below display Storefjell with and "without" snow. The first photo shows the terrain over Honningsvåg after the season's first snowfall, with just a few centimeters of new snow, while the second photo shows the mid-winter snow cover in February.

After data processing, TLS snow depth data can be displayed as layer data in a 3D map scene, with differing colors representing varying snow depths draped over a terrain model. Map 3 below shows snow depth data from Storefjell in February 2022. Darker colors represent deeper snow (click on the circle in the lower left corner for the map legend). Note that snow depths approach 6 meters on the east-facing slope of Storefjellsryggen!

The photos below show the slopes when they were scanned with the TLS in February 2022. The TLS data from Map 3 can not only help identify areas with deep snow accumulations, but can also be used to check the placement of each DRIVA snow sensor. Optimal sensor placement provides data representative of the relevant avalanche path and the snow depth in the area. TLS data also provide an avenue to verify the accuracy of the sensor's measurements. The tables included with the photos below compare the snow depths measured by the sensors with point and area-averaged snow depths derived from the TLS data acquired the same day.

As one navigates around in Map 3, it is possible to obtain a picture of how the point-scale data from the sensors represents the distribution of snow depth. As an example, Honningsvåg B is located in a gully characterized by relatively deep snow and Honningsvåg C is located high in an avalanche release area with 1-2 meter snow depths. Visualizing this snow depth information in combination with, for example, mapped avalanche hazard zones, as shown in Map 4 below, can help place these data in a risk management context

The snow depth data from the DRIVA sensors additionally serve as useful information in support of the manual snow observations which also provide important input for avalanche hazard assessments. For example, an observer can monitor or check the snow depth in various locations before deciding where to dig a snow profile to investigate the snowpack and test snowpack stability.

The photo above shows a snow profile dug approximately 50 meters over the Honningsvåg C sensor. The information from the snow profile gives an indication of the different snow layers in the snowpack. Snow profiles are conducted by observers using standardized methods and recording procedures, and the data are stored and made publically available on NVE's VarsomRegobs application. Profiles and other manual observations are therefore online throughout the entire winter, available for both avalanche forecasters and the public alike. The snow profile visualization to the right show the characteristics (hardness, snow crystal form, depth of the layer) of each snow layer in the snowpack. Stability tests of the snowpack are then used to assess the ease with which a weak layer can potentially fail and result in an avalanche. In the profile to the right, the identified weak layer is highlighted in red and denoted (ECTN12) with a stability test result.

Snow data from TLS scans provide an avenue to map and understand snow distribution and accumulation across entire mountainsides. This, combined with information from traditional snow depth sensors and manual snow observations, gives an opportunity to develop a picutre of the current avalanche hazard with respect to the relevant avalanche paths which threaten infrastructure.

A combination of point-scale snow depth data from snow sensors, slope-scale snow depth data from TLS, and manual snow observations from snow observers provides a comprehensive overview of snow conditions to avalanche forecasters and decision-makers in the community. The  Arctic Safety Centre  and the  ARCT-RISK  project are currently conducting research on how to best employ various sensor technologies in combination with local knowledge from observers to improve local avalanche forecasting practices and management of other natural hazards. Contact (MartinI@unis.no or HoltH@unis.no) for more information!