Characterisation of the subglacial environment using geophysical constrained Bayesian inversion techniques

An accurate characterization of the inaccessible subglacial environment is key to accurately modelling the dynamic behaviour of ice sheets and glaciers, crucial for predicting sea-level rise. The composition and water content of subglacial material can be inferred from measurements of shear wave vel...

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Main Author: Killingbeck, Siobhan
Format: Thesis
Language:English
Published: University of Leeds 2020
Subjects:
Ice
Online Access:https://etheses.whiterose.ac.uk/26331/
https://etheses.whiterose.ac.uk/26331/1/Killingbeck_SF_Earth_and_Environment_PhD_2020.pdf
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spelling ftwhiterose:oai:etheses.whiterose.ac.uk:26331 2023-05-15T16:37:54+02:00 Characterisation of the subglacial environment using geophysical constrained Bayesian inversion techniques Killingbeck, Siobhan 2020-03 text https://etheses.whiterose.ac.uk/26331/ https://etheses.whiterose.ac.uk/26331/1/Killingbeck_SF_Earth_and_Environment_PhD_2020.pdf en eng University of Leeds https://etheses.whiterose.ac.uk/26331/1/Killingbeck_SF_Earth_and_Environment_PhD_2020.pdf Killingbeck, Siobhan (2020) Characterisation of the subglacial environment using geophysical constrained Bayesian inversion techniques. PhD thesis, University of Leeds. cc_by_nc_sa CC-BY-NC-SA Thesis NonPeerReviewed 2020 ftwhiterose 2023-01-30T21:27:29Z An accurate characterization of the inaccessible subglacial environment is key to accurately modelling the dynamic behaviour of ice sheets and glaciers, crucial for predicting sea-level rise. The composition and water content of subglacial material can be inferred from measurements of shear wave velocity (Vs) and bulk electrical resistivity (R), themselves derived from Rayleigh wave dispersion curves and transient electromagnetic (TEM) soundings. Conventional Rayleigh wave and TEM inversions can suffer from poor resolution and non-uniqueness. In this thesis, I present a novel constrained inversion methodology which applies a Markov chain Monte Carlo implementation of Bayesian inversion to produce probability distributions of geophysical parameters. MuLTI (Multimodal Layered Transdimensional Inversion) is used to derive Vs from Rayleigh wave dispersion curves, and its TEM variant, MuLTI-TEM, for evaluating bulk electrical resistivity. The methodologies can include independent depth constraints, drawn from external data sources (e.g., boreholes or other geophysical data), which significantly improves the resolution compared to conventional unconstrained inversions. Compared to such inversions, synthetic studies suggested that MuLTI reduces the error between the true and best-fit models by a factor of 10, and reduces the vertically averaged spread of the Vs distribution twofold, based on the 95% credible intervals. MuLTI and MuLTI-TEM were applied to derive Vs and R profiles from seismic and TEM electromagnetic data acquired on the terminus of the Norwegian glacier Midtdalsbreen. Three subglacial material classifications were determined: sediment (Vs < 1600 m/s, 50 Ωm < R < 500 Ωm), permafrost (Vs > 1600 m/s, R > 500 Ωm) and weathered/fractured bedrock containing saline water (Vs > 1900 m/s, R < 50 Ωm). These algorithms offer a step-change in our ability to resolve and quantify the uncertainties in subsurface inversions, and show promise for constraining the properties of subglacial aquifers ... Thesis Ice permafrost White Rose eTheses Online (Universities Leeds, Sheffield, York)
institution Open Polar
collection White Rose eTheses Online (Universities Leeds, Sheffield, York)
op_collection_id ftwhiterose
language English
description An accurate characterization of the inaccessible subglacial environment is key to accurately modelling the dynamic behaviour of ice sheets and glaciers, crucial for predicting sea-level rise. The composition and water content of subglacial material can be inferred from measurements of shear wave velocity (Vs) and bulk electrical resistivity (R), themselves derived from Rayleigh wave dispersion curves and transient electromagnetic (TEM) soundings. Conventional Rayleigh wave and TEM inversions can suffer from poor resolution and non-uniqueness. In this thesis, I present a novel constrained inversion methodology which applies a Markov chain Monte Carlo implementation of Bayesian inversion to produce probability distributions of geophysical parameters. MuLTI (Multimodal Layered Transdimensional Inversion) is used to derive Vs from Rayleigh wave dispersion curves, and its TEM variant, MuLTI-TEM, for evaluating bulk electrical resistivity. The methodologies can include independent depth constraints, drawn from external data sources (e.g., boreholes or other geophysical data), which significantly improves the resolution compared to conventional unconstrained inversions. Compared to such inversions, synthetic studies suggested that MuLTI reduces the error between the true and best-fit models by a factor of 10, and reduces the vertically averaged spread of the Vs distribution twofold, based on the 95% credible intervals. MuLTI and MuLTI-TEM were applied to derive Vs and R profiles from seismic and TEM electromagnetic data acquired on the terminus of the Norwegian glacier Midtdalsbreen. Three subglacial material classifications were determined: sediment (Vs < 1600 m/s, 50 Ωm < R < 500 Ωm), permafrost (Vs > 1600 m/s, R > 500 Ωm) and weathered/fractured bedrock containing saline water (Vs > 1900 m/s, R < 50 Ωm). These algorithms offer a step-change in our ability to resolve and quantify the uncertainties in subsurface inversions, and show promise for constraining the properties of subglacial aquifers ...
format Thesis
author Killingbeck, Siobhan
spellingShingle Killingbeck, Siobhan
Characterisation of the subglacial environment using geophysical constrained Bayesian inversion techniques
author_facet Killingbeck, Siobhan
author_sort Killingbeck, Siobhan
title Characterisation of the subglacial environment using geophysical constrained Bayesian inversion techniques
title_short Characterisation of the subglacial environment using geophysical constrained Bayesian inversion techniques
title_full Characterisation of the subglacial environment using geophysical constrained Bayesian inversion techniques
title_fullStr Characterisation of the subglacial environment using geophysical constrained Bayesian inversion techniques
title_full_unstemmed Characterisation of the subglacial environment using geophysical constrained Bayesian inversion techniques
title_sort characterisation of the subglacial environment using geophysical constrained bayesian inversion techniques
publisher University of Leeds
publishDate 2020
url https://etheses.whiterose.ac.uk/26331/
https://etheses.whiterose.ac.uk/26331/1/Killingbeck_SF_Earth_and_Environment_PhD_2020.pdf
genre Ice
permafrost
genre_facet Ice
permafrost
op_relation https://etheses.whiterose.ac.uk/26331/1/Killingbeck_SF_Earth_and_Environment_PhD_2020.pdf
Killingbeck, Siobhan (2020) Characterisation of the subglacial environment using geophysical constrained Bayesian inversion techniques. PhD thesis, University of Leeds.
op_rights cc_by_nc_sa
op_rightsnorm CC-BY-NC-SA
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