Subglacial sediment distribution from constrained seismic inversion, using MuLTI software: examples from Midtdalsbreen, Norway

ABSTRACT Fast ice flow is associated with the deformation of subglacial sediment. Seismic shear velocities, Vs, increase with the rigidity of material and hence can be used to distinguish soft sediment from hard bedrock substrates. Depth profiles of Vs can be obtained from inversions of Rayleigh wav...

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Published in:Annals of Glaciology
Main Authors: Killingbeck, Siobhan F., Booth, Adam D., Livermore, Philip W., West, Landis J., Reinardy, Benedict T. I., Nesje, Atle
Format: Article in Journal/Newspaper
Language:English
Published: Cambridge University Press (CUP) 2019
Subjects:
Online Access:http://dx.doi.org/10.1017/aog.2019.13
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0260305519000132
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spelling crcambridgeupr:10.1017/aog.2019.13 2024-09-09T19:00:54+00:00 Subglacial sediment distribution from constrained seismic inversion, using MuLTI software: examples from Midtdalsbreen, Norway Killingbeck, Siobhan F. Booth, Adam D. Livermore, Philip W. West, Landis J. Reinardy, Benedict T. I. Nesje, Atle 2019 http://dx.doi.org/10.1017/aog.2019.13 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0260305519000132 en eng Cambridge University Press (CUP) http://creativecommons.org/licenses/by/4.0/ Annals of Glaciology volume 60, issue 79, page 206-219 ISSN 0260-3055 1727-5644 journal-article 2019 crcambridgeupr https://doi.org/10.1017/aog.2019.13 2024-07-24T04:03:29Z ABSTRACT Fast ice flow is associated with the deformation of subglacial sediment. Seismic shear velocities, Vs, increase with the rigidity of material and hence can be used to distinguish soft sediment from hard bedrock substrates. Depth profiles of Vs can be obtained from inversions of Rayleigh wave dispersion curves, from passive or active-sources, but these can be highly ambiguous and lack depth sensitivity. Our novel Bayesian transdimensional algorithm, MuLTI, circumvents these issues by adding independent depth constraints to the inversion, also allowing comprehensive uncertainty analysis. We apply MuLTI to the inversion of a Rayleigh wave dataset, acquired using active-source (Multichannel Analysis of Surface Waves) techniques, to characterise sediment distribution beneath the frontal margin of Midtdalsbreen, an outlet of Norway's Hardangerjøkulen ice cap. Ice thickness (0–20 m) is constrained using co-located GPR data. Outputs from MuLTI suggest that partly-frozen sediment (Vs 500–1000 m s −1 ), overlying bedrock (Vs 2000–2500 m s −1 ), is present in patches with a thickness of ~4 m, although this approaches the resolvable limit of our Rayleigh wave frequencies (14–100 Hz). Uncertainties immediately beneath the glacier bed are <280 m s −1 , implying that MuLTI cannot only distinguish bedrock and sediment substrates but does so with an accuracy sufficient for resolving variations in sediment properties. Article in Journal/Newspaper Annals of Glaciology glacier Ice cap Cambridge University Press Norway Annals of Glaciology 60 79 206 219
institution Open Polar
collection Cambridge University Press
op_collection_id crcambridgeupr
language English
description ABSTRACT Fast ice flow is associated with the deformation of subglacial sediment. Seismic shear velocities, Vs, increase with the rigidity of material and hence can be used to distinguish soft sediment from hard bedrock substrates. Depth profiles of Vs can be obtained from inversions of Rayleigh wave dispersion curves, from passive or active-sources, but these can be highly ambiguous and lack depth sensitivity. Our novel Bayesian transdimensional algorithm, MuLTI, circumvents these issues by adding independent depth constraints to the inversion, also allowing comprehensive uncertainty analysis. We apply MuLTI to the inversion of a Rayleigh wave dataset, acquired using active-source (Multichannel Analysis of Surface Waves) techniques, to characterise sediment distribution beneath the frontal margin of Midtdalsbreen, an outlet of Norway's Hardangerjøkulen ice cap. Ice thickness (0–20 m) is constrained using co-located GPR data. Outputs from MuLTI suggest that partly-frozen sediment (Vs 500–1000 m s −1 ), overlying bedrock (Vs 2000–2500 m s −1 ), is present in patches with a thickness of ~4 m, although this approaches the resolvable limit of our Rayleigh wave frequencies (14–100 Hz). Uncertainties immediately beneath the glacier bed are <280 m s −1 , implying that MuLTI cannot only distinguish bedrock and sediment substrates but does so with an accuracy sufficient for resolving variations in sediment properties.
format Article in Journal/Newspaper
author Killingbeck, Siobhan F.
Booth, Adam D.
Livermore, Philip W.
West, Landis J.
Reinardy, Benedict T. I.
Nesje, Atle
spellingShingle Killingbeck, Siobhan F.
Booth, Adam D.
Livermore, Philip W.
West, Landis J.
Reinardy, Benedict T. I.
Nesje, Atle
Subglacial sediment distribution from constrained seismic inversion, using MuLTI software: examples from Midtdalsbreen, Norway
author_facet Killingbeck, Siobhan F.
Booth, Adam D.
Livermore, Philip W.
West, Landis J.
Reinardy, Benedict T. I.
Nesje, Atle
author_sort Killingbeck, Siobhan F.
title Subglacial sediment distribution from constrained seismic inversion, using MuLTI software: examples from Midtdalsbreen, Norway
title_short Subglacial sediment distribution from constrained seismic inversion, using MuLTI software: examples from Midtdalsbreen, Norway
title_full Subglacial sediment distribution from constrained seismic inversion, using MuLTI software: examples from Midtdalsbreen, Norway
title_fullStr Subglacial sediment distribution from constrained seismic inversion, using MuLTI software: examples from Midtdalsbreen, Norway
title_full_unstemmed Subglacial sediment distribution from constrained seismic inversion, using MuLTI software: examples from Midtdalsbreen, Norway
title_sort subglacial sediment distribution from constrained seismic inversion, using multi software: examples from midtdalsbreen, norway
publisher Cambridge University Press (CUP)
publishDate 2019
url http://dx.doi.org/10.1017/aog.2019.13
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0260305519000132
geographic Norway
geographic_facet Norway
genre Annals of Glaciology
glacier
Ice cap
genre_facet Annals of Glaciology
glacier
Ice cap
op_source Annals of Glaciology
volume 60, issue 79, page 206-219
ISSN 0260-3055 1727-5644
op_rights http://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.1017/aog.2019.13
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