During the melting season, substantial quantities of surface meltwater converge in topographically depressed regions, forming supraglacial lakes (SGLs). We extract SGL area and profile depth using remote sensing data and then invert the depth of entire SGLs based on the machine learning method. By applying the above-mentioned methods, we capture the volumetric evolution of SGLs throughout the entire melt season of 2022 in southwestern Greenland.