Snowdrift Analysis using FlowCapt FC4 and LiDAR Data at Fv. 53 Tyin-Årdal

Abstract

The wind is essential in distribution of snow and the degree of avalanche danger. There are a lot of uncertainties regarding quantification of wind-transported snow, which is of importance for local avalanche warning and Remote Avalanche Control Systems (RACS) - which is conducted by Skred AS along Fv. 53 (County Road 53) Tyin-Årdal. A snowdrift sensor, FlowCapt 4 (FC4), is installed along this weather-exposed mountain road to function as an additional tool in the decision-making of the avalanche risk assessment - helping determine snowdrift occurrences. In addition, the sensor can provide a basis in forming an empirical relationship between measured snowdrift and snowdrift deposition in the Potential Release Areas (PRAs) for avalanches towards the road. The objective of this study is to look into a method uncovering the correlation between measured snowdrift from the FC4, weather data, and deposited snowdrift in the PRAs - measured from consecutive LiDAR-scans. Fieldwork on the snow cover was conducted to monitor available snow for transport. This study proposes an empirical relationship between measured snowdrift from the FC4 and mean snow surface change measured from LiDAR-scans, and recommends building on this relationship with more measurements with the newly installed snow depth sensor and verifications with fracture heights from future avalanche controls. Snowfall during snowdrift events were not found to have a significant role in determining snow depth deposition as corrections weakened the correlational trend. This study underlines the importance of keeping measurements simple to avoid additional layers of uncertainty when building an empirical relationship. It might be sufficient with point-observations on the measured snowdrift and snow depth deposition given that the locations are representative and chosen for the purpose of collecting conservative data. Focusing on keeping the uncertainties down at the expense of quantitative accuracy can be considered essential in the application of FC4-data, as its role will continue to be an additional tool in the risk assessment, with the role of reducing the uncertainties regarding snowdrift occurences.