Surge glaciers have a unique type of glacial acceleration, surging, in which the glacial system leaves a period of quiescence and experiences velocities that are up to 200 times the non-surge velocities. Surge events play a critical role in sea level rise (SLR), as the mass loss from even a single marine-terminating glacier during a surge has been estimated to be upwards of 0.5 percent of annual global SLR. The glacial hydrologic system, the water that flows above, within and below the glacier, plays a critical role in surge evolution and initiation, as the initiation of a surge requires decoupling of the glacier from the bed via reduction of basal friction, which is directly related to the subglacial water pressure at the basal boundary. This work establishes a simple framework for improving the estimation of basal water content in surge glaciers with a data-driven and model-based approach by combining image classification techniques with processing of ICESat-2 altimetry data to realistically estimate changes in volume of supraglacial water during a surge. This can then be related to the physical changes in the englacial hydrologic system.
Distribution of glacial surface water is determined by spectral classification of satellite imagery. The volume of surface water is determined by estimating water and ice surface elevation for each water feature with the Density-Dimension Algorithm for ice surfaces. The DDA-ice-2 determines ice surface height, crevasse morphology of wet and dry crevasses and water depth from ICESat-2 ATLAS data. The DDA-bifurcate algorithm determines ice surface height, melt pond morphology, and water depth from ICESat-2 ATLAS data. An idealized system of drainage through the glacier is established to constrain a numerical 3D model. The primary objective of this work is to establish a framework for determining and modeling the hydrologic conditions of a surge-type glacier. Furthermore, this framework was used to investigate the dynamics of the Negribreen Glacier System in Svalbard, Norway.