Liquid water stored on the surface of ice sheets and glaciers impacts surface mass balance, ice dynamics, and heat transport. Multispectral remote sensing can be used to detect supraglacial lakes and estimate their depth and area. In this study, we use in situ spectral and bathymetric data to assess lake depth retrieval using the recently launched Landsat 8 Operational Land Imager (OLI). We also extend our analysis to other multispectral sensors to evaluate their performance with similar methods. Digital elevation models derived from WorldView stereo imagery (pre-lake filling and post-drainage) are used to validate spectrally derived depths, combined with a lake edge determination from imagery. The optimal supraglacial lake depth retrieval is a physically based single-band model applied to two OLI bands independently (red and panchromatic) that are then averaged together. When OLI- and WorldView-derived depths are differenced, they yield a mean and standard deviation of 0.0 ± 1.6 m. This method is then applied to OLI data for the Sermeq Kujalleq (Jakobshavn Isbræ) region of Greenland to study the spatial and intra-seasonal variability of supraglacial lakes during summer 2014. We also give coefficients for estimating supraglacial lake depth using a similar method with other multispectral sensors.