Maximizing the use of remote sensing to quantify Greenland ice sheet runoff

Our ability to monitor and quantify ice sheet runoff is essential for a better understanding of the hydrology of the Greenland Ice Sheet and its contribution to global sea-level rise in a future warming climate. The amount of liquid water at the surface of the Greenland Ice Sheet has particularly increased due to large regional warming that this region has experienced over the last decades.

Here, we present the initial results of monthly runoff estimates from the Watson drainage basin in West Greenland, developed within the 4DGreenland project. 4DGreenland is a 2-year project funded by  the European Space Agency (ESA), which is focused on quantifying and analyzing the dynamic variations in the hydrological components of the ice sheet, while maximizing the use of Earth Observation (EO) data. 

The basin scale runoff estimate is derived from adding each component of the hydrological cycle: We have used a Random Forest approach (Supervised Learning algorithm) to map supraglacial hydrology ice sheet wide from optical imagery, and used ICESat-2 derived lake bathymetry as calibration to derive storage volumes. To map meltwater we have developed algorithms for generating maps of surface melt extent from high-medium resolution C-band backscatter measurements, and Low resolution PMW data. The subglacial melt is inherently difficult to monitor. The melt produced by friction heat though is derived from a model run of an ice sheet model (Elmer/Ice) which is tuned to assimilate observed ice velocities. Lastly, we have further developed a firn model to quantify the amounf of the meltwater that is retained in the snow/firn column.

By adding these component we are able to present monthly estimated of runoff from the drainage basin, and specifically show how each of the hydrologically components change over time.