Snowmelt provides critical water resources that impact ecosystem health and hazard frequency; however, the timing of melt is difficult to infer on large spatial scales. While Synthetic Aperture Radar (SAR) has been used to detect snowmelt onset, the accuracy of the method requires evaluation for varying satellite configurations. We use Sentinel-1 SAR observations to estimate snowmelt timing at automated snow water equivalence (SWE) stations (n = 56) across British Columbia for the 2018 ablation season. We compare the timing of SAR minima, taken as snowmelt onset, to melt onset estimates derived from continuous SWE records at each location. When the complete Sentinel-1 time series is analyzed (i.e., using images from varying orbital directions and tracks), 36% (n = 20) of co-polarized SAR snowmelt onset estimates occur within seven days of SWE melt onset. For cross-polarized images the accuracy decreases to 34% (n =19). The accuracy of SAR snowmelt onset estimates improves when Sentinel-1 time series are separated by satellite track or orbital direction. When the most accurate melt onset estimate for each satellite track is selected, the accuracy of SAR snowmelt onset estimates increases to 54% (n = 30) when co-polarized images are used, and 70% (n = 39) for cross-polarized images. Our results indicate that images with similar viewing geometries should be used for snowmelt onset detection with SAR, and suggests that cross-polarized images are more suitable for large-scale snowmelt detection. Meteorological conditions, local incidence angle, land cover, and slope further impact the accuracy of SAR snowmelt onset estimates.