Applying GIS to Investigate the Spatial Variability of Sub-Glacial Hydrology under Land Terminating Ice Sheets in Western Greenland Ice Sheet.

Sammanfattning: With continued warming regional surface air temperatures around the Artic in recent decades, there is growing importance in understanding how ice sheet dynamics interact with a shifting global climate system. This research investigates the spatial variability of sub-glacial hydrology under land terminating ice sheets in Western GrIS, when applying varying overburden ice pressures within Shreve’s (1972) hydraulic potential equation. The application of ArcGIS is used with adjusted k-values in the equation to route hydrological network systems under the ice sheet and help identify the processes taking place within the sub-glacial system. With focus on processes such as water piracy, we are able illustrate the effects that water at the base can have on ice sheet behaviors. i.e. velocity and mas balance. The findings conclude that the ice sheet is operating under conditions at its base with a k-value somewhere within the range of 0.9 to 1.1. This assumption is based on comparisons between modelled pro-glacial output with observed data taken from studies by Mikkelsen et al. (2014) and Smith et al. (2015), using input melt data at the surface (Lindback et. al., 2015). At this level of hydraulic potential, water piracy is effectively changing the course pathways of the hydrological network and therefore manipulating the size and shape of the sub-glacial catchments. As a result, discharge may leave the glacier from a different location than what would be assumed. Identifying the location and volume of water under particular ice sheets, compared to neighboring ice sheets, can be used to explain spatial and temporal differences in ice sheet characteristics. Such research is important in understanding both environmental and socio-economic implications at local to global scale. Although the application of GIS methodology is extremely useful is producing such results, it must be recognised that a high level of uncertainty and error exists in the data results.