The evolution of supraglacial hydrologic networks on the Greenland Ice Sheet

Surface melt and runoff is an important, growing source of mass loss from the Greenland Ice Sheet (GrIS) and its ongoing contribution to global sea level rise (SLR). The transportation, storage and evacuation of surface melt is governed by the supraglacial hydrologic network, consisting of an array of rivers, streams and lakes which fundamentally control the timing and delivery of meltwater outputs, with wider hydro-dynamic implications. Motivated by the need to improve understanding of the spatial distribution, composition and evolution of GrIS-wide hydrology, this thesis expands supraglacial network mapping to understudied and spectrally-complex regions of the GrIS via remotely-sensed and field-acquired imagery over a multitude of temporal and spatial scales.

For the first time, the supraglacial hydrologic network is mapped and quantified over consecutive melt seasons (2016-2020) and over long, multi-annual timescales (1985-2021) at a major northern outlet glacier, Humboldt (Sermersuaq) Glacier. Work reveals an extensive and complex supraglacial hydrologic network exists, seasonally developing from an inefficient to efficient network in-line with snowline migration. Long-term, this network is shown to have expanded inland and doubled in areal extent. Field- and commercial-based imagery also reveal small-scale microchannels, inter-stream networks and complex surface facies comprise the spectrally-complex ice marginal region of Russell Glacier (south-western Greenland) and the bare ice zone of Humboldt Glacier.

Collectively, findings from this thesis demonstrate the complex behaviour of the supraglacial hydrologic network, including the variety of sized channels that comprise it and the differing abilities of remotely-sensed data to capture such features. This work provides new insights into the past, present and suggestions of the future nature of this network, with continued hydrologic-research directed towards further mapping of the GrIS and other cryospheric bodies to better predict surface mass balance and SLR contributions now and into the future.