Comment on tc-2022-89

Abstract

<strong class="journal-contentHeaderColor">Abstract.</strong> 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. We present here a workflow to fuse Sentinel-1 SAR and optical data from Landsat-8 and Sentinel-2 to estimate the onset and duration of snowmelt in the Lajoie Basin, a large 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 by elevation and aspect on the watershed scale and reflect snowmelt records from continuous SWE observations. SAR estimates of snowpack saturation are most effective on moderate to low slopes (&lt; 30&deg;) in open areas. The accuracy of snowmelt durations is reduced due to persistent cloud cover in optical imagery. Despite these challenges, snowmelt durations agree with trends in snow depths observed in the Lajoie. This approach has high potential for adaptability to other alpine regions and can provide estimates of snowmelt timing in ungauged basins.