Assessing supraglacial lake depth using ICESat-2, Sentinel-2, TanDEM-X, and in situ sonar measurements over Northeast Greenland

Abstract. Supraglacial lake development in Greenland consists of intricate hydrological processes, contributing not only to surface mass loss, but also to a lowering of the surface albedo and changes in ice dynamics. While the estimation of lake area has recently improved, the determination of the lake volume is essential to properly estimate the amount of water contained in and lost from supraglacial lakes throughout the melt seasons. In this study, four supraglacial lake depth estimation methods, including two new regression approaches, are presented and compared to each other. The first empirical equation is based on depth information gathered from ICESat-2 crossings over 19 lakes in Northeast and Southwest Greenland, whereas the second empirical equation uses in situ sonar tracks, providing depth information from four lakes on Zachariæ Isstrøm in Northeast Greenland. The depths from both equations are independently correlated to their corresponding Sentinel-2 reflectance values to create empirical relations. The third method is a standardly used radiative transfer model also based on Sentinel-2 data. Finally, the depths for five lakes in Northeast Greenland were derived from TanDEM-X digital elevation models after lake drainage. All four methods were applied to the five lakes for which digital elevation models were able to be procured, allowing for a direct comparison of the methods. In general, the sonar-based equation aligned best with the estimates from the digital elevation model until its saturation point of 8.6 m. Through the evaluation of the ICESat-2-based equation, a strong influence of lake bed sediment could be seen. The appropriately adapted equation produced slightly deeper depths than the sonar-based equation. The radiative transfer model more strongly overestimated nearly all depths below its saturation point of 16.3 m, when compared to the digital elevation model results. This large overestimation can be primarily attributed to the sensitivity of this method’s parameters. Furthermore, all methods, with the exception of the digital elevation model, were applied to an area in Northeast Greenland on the peak melt dates for the years 2016 to 2022. Finally, a closer look into the uncertainties for each method provides insight into associated errors and pitfalls when considering which method to use for supraglacial lake depth estimation. Overall, the use of empirically derived equations are shown to be capable of simplifying supraglacial lake depth calculations, while retaining sufficient accuracy under certain conditions.