Automated detection of basal icequakes and discrimination from surface crevassing
Annals of Glaciology
Cambridge University Press
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Hudson, T., Smith, J., Brisbourne, A., & White, R. (2019). Automated detection of basal icequakes and discrimination from surface crevassing. Annals of Glaciology, 60 (79), 167-181. https://doi.org/10.1017/aog.2019.18
Icequakes at or near the bed of a glacier have the potential to allow us to investigate the interaction of ice with the underlying till or bedrock. Understanding this interaction is important for studying basal sliding of glaciers and ice streams, a critical process in ice dynamics models used to constrain future sea level rise projections. However, seismic observations on glaciers can be dominated by seismic energy from surface crevassing. We present a method of automatically detecting basal icequakes and discriminating them from surface crevassing, comparing this method to a commonly used spectrum-based method of detecting icequakes. We use data from Skeidararjo ̈kull, an outlet glacier of the Vatnaj ̈okull Ice Cap, South-East Iceland, to demonstrate that our method outperforms the commonly used spectrum-based method. Our method detects a higher number of basal icequakes, has a lower rate of incorrectly identifying crevassing as basal icequakes and detects an additional, spatially independent basal icequake cluster. We also show independently that the icequakes do not originate from near the glacier surface. We conclude that the method described here is more effective than currently implemented methods for detecting and discriminating basal icequakes from surface crevassing.
Tom Hudson was funded by a the Cambridge Earth System Science NERC Doctoral Training Partnership. The Skeidararjo ̈kull data collection was funded by a BAS innovation grant and NERC Geophysical Equipment Facility Loan 1022. The Rutford data collection was funded by NERC grant NE/B502287/1 and NERC Geophysical Equipment Facility Loan 852. University of Cambridge, Department of Earth Sciences contribution number 4390.
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External DOI: https://doi.org/10.1017/aog.2019.18
This record's URL: https://www.repository.cam.ac.uk/handle/1810/292380
Attribution 4.0 International
Licence URL: https://creativecommons.org/licenses/by/4.0