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Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation

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Published on: November 18, 2015

Exploring Explanations of Subglacial Bedform Sizes Using Statistical Models.

John K Hillier¹, Ioannis A Kougioumtzoglou², Chris R Stokes³

¹Department of Geography, Loughborough University, Loughborough, United Kingdom.

|July 27, 2016

Summary

This summary is machine-generated.

Subglacial bedform sizes, like drumlins and ribbed moraines, are best explained by random ice-water-sediment dynamics. This new statistical model links bedform size to ice sheet flow, improving our understanding of these hidden processes.

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Area of Science:

Glaciology
Geomorphology
Statistical Modeling

Background:

Subglacial sediments significantly influence ice sheet flow but are difficult to study directly.
Palaeo-ice sheet beds offer accessible insights into subglacial processes through bedforms.
The relationship between subglacial bedform characteristics and ice flow dynamics remains poorly understood.

Purpose of the Study:

To explore statistical models for explaining the size distribution of subglacial bedforms.
To investigate the link between bedform size and ice sheet flow conditions.
To develop a method for bridging geomorphological observations and physical ice sheet models.

Main Methods:

Application of various statistical models to analyze subglacial bedform size distributions (e.g., drumlins, ribbed moraine, MSGL).
Development and testing of a 'stochastic instability' (SI) model integrating random growth and shrinking dynamics.
Demonstration of a statistical approach to link geomorphological data with physical ice sheet processes.

Main Results:

Subglacial bedform size distributions are most effectively explained by fundamentally random ice-water-sediment interaction dynamics.
The 'stochastic instability' (SI) model is preferred, aligning with palaeo-bedform and geophysical data.
The statistical approach successfully links measurable size-frequency parameters to ice sheet flow properties like velocity.

Conclusions:

Statistical analysis of subglacial bedform size-frequency distributions provides a novel method to infer subglacial processes.
The developed models offer quantitative, testable predictions for bedform sizes, aiding future research.
This approach enhances our ability to constrain ice sheet models by better understanding subglacial environments.