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. Synthetic aperture radar (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 C-band 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-of-the-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.