Snow and glaciers play a crucial role in various applications such as hydrology, climate and avalanche risk assessment. Remote sensing is a powerful tool for monitoring the snowpack and melt in glacier catchments. SAR imagery, which measures the backscattering signal in the microwave spectrum, is particularly useful for studying snow and glacier-related issues: while it is almost insensitive to cloud cover, it is sensitive to some snow/glacier properties such as liquid water content. In this study, we analyze the snowmelt dynamics in the Saint-Sorlin Glacier catchment in the French Alps using SAR images in Cband from Sentinel-1. Our primary objective is to understand the spatial and temporal variabilities of the SAR signal in a glacierized area by monitoring the SAR signal in regions of snow/ice ablation, accumulation, and outside the glacier. We also rely on complementary meteorological, model and optical data. A second objective is to compare and assess several approaches from the literature to characterize the snowmelt dynamics on a variety of surfaces.Our study confirms and extends the capability of previous methodologies to identify crucial melting phases, such as moistening of the snowpack, saturation, and run-off phases, using SAR backscatter time series. These melting phases were compared with the ones estimated from liquid water content and snow water equivalent simulations simulated with the Crocus state-ofthe-art snowpack model. The transition from snow-covered to an icy surface on ablation areas was detected using VH-polarized images, as SAR imagery is sensitive to surface roughness.