We present a first decadal scale study of supraglacial extent and volume across the entire Greenland Ice Sheet. We adapted and validated a random forest algorithm (RF) to classify superglacial hydrology (SGH) using the optical sensors Sentinel-2 and Landsat-8. We used a radiative transfer model to quantify the depth of SGH features to estimate the volume of surface water which exists on the Greenland Ice Sheet on a monthly and yearly scale from 2013 through 2022. We find strong seasonal trends in SGH behaviour, with melt beginning in May, peaking in July/August, and refreezing occurring in September in each year. We find significant variability in the extent and volume of SGH features between melt seasons, and although the inter-annular trend suggests SGH is becoming more widespread with a greater volume of water, a study of longer duration is needed to fully determine inter-annular trends of SGH on the ice sheet.