Down The Drain: Understanding How Meltwater Cascades Through The GrIS Hydrological System To Impact Its Ice Velocity

Document Type

Presentation

Publication Date

12-14-2017

Abstract

Despite over a decade of research, dynamic links between the hydrological system and ice motions of the Greenland Ice Sheet remain poorly understood. To a large degree, this lack of understanding has persisted because most studies have investigated the supraglacial, englacial, and subglacial drainage systems as separate entities. Despite the segmentation of research foci, each component of the GrIS hydrological system is connected, and changes in each component can impact ice motion. The changes can increase efficiency of the supraglacial drainage system and increase the rate of the delivery of meltwater from the surface of the GrIS moulins; if the rate of meltwater delivery to moulins exceeds the hydraulic capacity of the connected subglacial drainage system, the meltwater backs up in moulin shaft and increases subglacial water pressure and ice sliding speeds. Full understanding of how the GrIS hydrological system impacts ice velocity thus requires simultaneous investigation of each component of the system itself. Here, we present the results of the first simultaneous investigation of supraglacial, englacial, and subglacial drainage processes and their links to ice motion in the Taakitsoq region of the GrIS. We use meteorological, hydrological, and kinematic GPS data collected at a camp located approximately 30km from the ice margin to investigate the seasonal evolution of logs between peak meltwater production, peak meltwater delivery to a moulin via supraglacial streams, peak moulin water level, and peak ice velocity over the 2017 melt season. This analysis, which simultaneously collected measurements from the entire hydrological system, enables us to achieve a holistic understanding of the underlying processes controlling the ice velocity of the GrIS.

Was this content written or created while at USF?

Yes

Citation / Publisher Attribution

Presented at the AGU Fall Meeting on December 14, 2017 in New Orleans, LA

Share

COinS