Quantifying Supraglacial Lake Volumes on the Greenland Ice Sheet From Spaceborne Optical Sensors

Mahsa Sadat Moussavi, University of Colorado Boulder


The acceleration of mass loss from the Greenland ice sheet (GrIS) over the last two decades is of great significance when considering the associated increasing rates of its contribution to sea level rise. With meltwater runoff accounting for more than half of Greenland's contribution to sea level, it is imperative to improve our understanding of the ice sheet hydrologic processes. This dissertation describes research to quantify surface meltwater volumes, specifically stored in supraglacial lakes, over large areas of the ablation region from spaceborne observations made by current and future optical sensors. Methods for remote-derivation and validation of supraglacial water depths from WorldView-2, Landsat 7's Enhanced Thematic Mapper (ETM+), and Landsat 8's Operational Land Imager (OLI) are discussed. While enabling large-scale assessments of lake volumes with unprecedented levels of accuracy and precision, these methods address the major limitation of spaceborne bathymetry, which is its dependence on the availability of costly in-situ measurements.

This dissertation also investigates the potential capability of the future ICESat-2 laser altimetry mission in providing depth information over supraglacial lakes, which could be used in conjunction with passive optical data to assess lake volumes. A nominal (first-order) prediction of ICESat-2's performance suggests that it might be able to retrieve lake depths down to 6 m. Given such a premise, this dissertation takes one step further to develop an automatic depth-retrieval algorithm from simulated ICESat-2 datasets, provided by the mission's Project team at Goddard Space Flight Center (GSFC). By developing a surface detection algorithm for the most complex surfaces that ICESat-2 will be looking at, namely forested ecosystems, this dissertation provides a method applicable to land ice, sea ice, and water surfaces. Furthermore, as part of ICESat-2's science definition team efforts and in direct support of the mission, this work assesses the capability of photon-counting altimetry in retrieving canopy heights over vegetated surfaces. The results of this study will aid in developing data processing and analysis methods for future ICESat-2 measurements in order to maximize its application to the science objectives.

By demonstrating the capability of space-based techniques in constraining the estimates of surface meltwater, this dissertation directly addresses the need for large-scale assessments of meltwater volumes in models of ice sheet evolution. Improved insight into the surface hydrologic features could help constrain future estimates of the ice sheet's contribution to sea level rise.