Evolution of Wet and Dry Snow Covered Area from Optical and Radar Satellite Observations, Lajoie Basin, British Columbia, Canada

Abstract:

Seasonal snowmelt strongly influences hydrologic regimes in many mountain basins. Satellite-based observations of snow-covered area (SCA) thus provide valuable data for hydrologic forecasting in alpine regions. We examine the evolution of wet and dry SCA for the Lajoie Basin using optical and radar satellite imagery from Sentinel-1, Sentinel-2 and Landsat-8 platforms. We produced a temporal stack of wet and dry SCA for the 2018 and 2019 snow seasons. Landsat-8 and Sentinel-2 images are fused in Google Earth Engine to create two-week median composites. Total SCA is determined from the composites using an NDSI based classification system. Wet snow masks are then created for the SCA maps from Sentinel-1 radar data via Nagler’s method. From the time series, we assess the influences of slope, elevation, and aspect on both wet and dry snow covers. Topography strongly influences spatial patterns of snow accumulation and ablation in the Lajoie Basin. Elevation has the strongest spatial control on the presence of snow cover, followed by slope. Patterns of wet snow accumulation and ablation are more sensitive to changes in topography when compared to dry snow. During ablation, the minimum elevation of wet snow rises on average 13 m/day. The boundary line between wet and dry snow, however, rises on average 11 m/day. These controls further demonstrate the need for spatially distributed measurements and models for improved runoff prediction. Future work in the Lajoie Basin will focus on an analysis of radar backscatter values from the SCA time series. We assess the relation between backscatter and the timing of snow ablation. Furthermore, we evaluate the covariance of backscatter and reflectance values from the time series to examine whether these parameters can be used for mapping of snow cover. The provided SCA maps and analysis will be used in subsequent studies to improve an estimate of snow water equivalence for operational forecasting systems.