부산대학교 도서관

Snowmelt runoff serves both human needs and ecosystem services and is an important parameter in operational forecasting systems. Sentinel-1 synthetic-aperture-radar (SAR) observations can estimate the timing of melt within a snowpack; however, these estimates have not been applied on large spatial scales. Here we present a workflow to combine Sentinel-1 SAR and optical data from Landsat-8 and Sentinel-2 to estimate the onset and duration of snowmelt in the La Joie Basin, a 985 km2 watershed in the southern Coast Mountains of British Columbia. A backscatter threshold is used to infer the point at which snowpack saturation occurs and the snowpack begins to produce runoff. Multispectral imagery is used to estimate snow-free dates across the basin to define the end of the snowmelt period. SAR estimates of snowmelt onset form consistent trends in terms of elevation and aspect on the watershed scale and reflect snowmelt records from continuous snow water equivalence observations. SAR estimates of snowpack saturation are most effective on moderate to low slopes (< 30∘) in open areas. The accuracy of snowmelt duration is reduced due to persistent cloud cover in optical imagery. Despite these challenges, snowmelt duration agrees with trends in snow depths observed in the La Joie Basin. This approach has high potential for adaptability to other alpine regions and can provide estimates of snowmelt timing in ungauged basins.