Monitoring snow wetness evolution from satellite with Sentinel-1 multi-track composites

Abstract. Information about snowpack wetness at high temporal and spatial resolutions is important for timely identification of pre-disposing conditions for avalanche release. However, such information is often available only for specific, instrumented locations. Space-borne techniques such as synthetic aperture radar (SAR) allow us acquiring information over large areas and in remote and challenging terrain. Here, we show how Sentinel-1 SAR multi-track composites can be used to monitor snow wetness evolution over multiple seasons for a 5 study site of 400 km² around Davos in the eastern Swiss Alps. We validate the performance of our method using both in-situ measurements and modelled snowpack data. Moreover, we compared snow wetness maps and time series with wet avalanches records. We found correlations between SAR backscatter and modelled liquid water content between -0.25 and -0.59 for Spearman’s rank coefficient and -0.25 and -0.64 for Pearson’s correlation coefficient. By calculating the percentage of detected wet snow to dry/no snow per elevation, the season-elevation related 10 melting can be tracked. Moreover, we show that a rise of wet snow ratio above 40 % coincides with an increase in wet snow avalanches releases in corresponding elevation bands. Our results suggest that wet snow products derived from Sentinel-1 SAR data may assist in identifying regions featuring a potential increase of wet snow avalanche activity. However, we could not find evidence of precursors of wet avalanche initiation with the accuracy required for operative monitoring applications.