C052-07
Variability in Subglacial Bedforms at Assemblage and Regional Scales across the Deglaciated Puget Lowland, Washington State

Monday, 14 December 2020: 17:48
Virtual
Marion McKenzie, University of Virginia, Environmental Sciences, Charlottesville, VA, United States, Jacob Slawson, University of Virginia, Environmental Sciences, Charlottesville, United States and Lauren Miller Simkins, University of Virginia, Charlottesville, VA, United States
Abstract:
The former Cordilleran Ice Sheet (CIS), arguably the least understood of all late Pleistocene ice sheets, provides an opportunity to enhance our understanding of ice sheet dynamics, particularly the relationship between ice sheet behavior and bed properties. Streamlined bedforms in the Puget Lowland, largely below sea level when glaciated by the CIS, archive the influence of geologic factors such as tectonic activity, variable bedrock substrate, and solid Earth rebound on ice flow and margin stabilization. To identify, characterize, and analyze fields of streamlined bedforms, a unique landform identification automation was created using the semi-automatic Topographic Position Index (TPI) landscape classification system. While TPI landscape analysis was originally developed with the intention to highlight topography and categorize landscapes based on relative slope and elevation, this study uses TPI to identify bedforms across the entire Puget Lowland. The correlation of faults and streamlined bedforms across >15,000km2 of land area suggests a relationship between weaknesses in the Earth's crust and qualitatively streaming ice. We find a wider range of bedform elongation ratios at lower elevations than at higher elevations, arguably indicating more variability in bedform morphology for elevations that are directly influenced by marine processes and associated with thicker sediment cover. We will assess spatial patterns of bedform morphology, spacing, and orientation at assemblage and regional scales to determine geologic influence on bedform occurrence and characteristics. Importantly, we demonstrate that TPI can be used across deglaciated landscapes and variable paleo-subglacial bed topography.