Ground ice estimation in permafrost samples using industrial Computed Tomography
The distribution and abundance of ground ice in permafrost is a fundamental property that determines the potential for thaw subsidence and terrain effects of permafrost landscapes. However, most methods to characterize permafrost are destructive and of low resolution. Here, some of the limitations o...
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ftcopernicus:oai:publications.copernicus.org:egusphere119941 2024-09-15T18:11:20+00:00 Ground ice estimation in permafrost samples using industrial Computed Tomography Roustaei, Mahya Pumple, Joel Harvey, Jordan Froese, Duane 2024-06-10 application/pdf https://doi.org/10.5194/egusphere-2024-1353 https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1353/ eng eng doi:10.5194/egusphere-2024-1353 https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1353/ eISSN: Text 2024 ftcopernicus https://doi.org/10.5194/egusphere-2024-1353 2024-08-28T05:24:22Z The distribution and abundance of ground ice in permafrost is a fundamental property that determines the potential for thaw subsidence and terrain effects of permafrost landscapes. However, most methods to characterize permafrost are destructive and of low resolution. Here, some of the limitations of traditional destructive methods are overcome using industrial computed tomography (CT) scanning to systematically log permafrost cores, visualize cryostructures, measure frozen bulk density, and estimate volumetric and excess ice contents non-destructively. The results show strong agreement with destructive analyses as well as recent developments using a multi-sensor core logger (MSCL), demonstrating that these approaches can produce consistent results, and provide the added benefit of enhanced digital archives of permafrost physical properties. Development of standardized and interoperable methods for permafrost characterization will build more robust permafrost datasets and strengthen efforts to understand future thaw trajectories of permafrost landscapes. Text Ice permafrost Copernicus Publications: E-Journals |
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Copernicus Publications: E-Journals |
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ftcopernicus |
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English |
description |
The distribution and abundance of ground ice in permafrost is a fundamental property that determines the potential for thaw subsidence and terrain effects of permafrost landscapes. However, most methods to characterize permafrost are destructive and of low resolution. Here, some of the limitations of traditional destructive methods are overcome using industrial computed tomography (CT) scanning to systematically log permafrost cores, visualize cryostructures, measure frozen bulk density, and estimate volumetric and excess ice contents non-destructively. The results show strong agreement with destructive analyses as well as recent developments using a multi-sensor core logger (MSCL), demonstrating that these approaches can produce consistent results, and provide the added benefit of enhanced digital archives of permafrost physical properties. Development of standardized and interoperable methods for permafrost characterization will build more robust permafrost datasets and strengthen efforts to understand future thaw trajectories of permafrost landscapes. |
format |
Text |
author |
Roustaei, Mahya Pumple, Joel Harvey, Jordan Froese, Duane |
spellingShingle |
Roustaei, Mahya Pumple, Joel Harvey, Jordan Froese, Duane Ground ice estimation in permafrost samples using industrial Computed Tomography |
author_facet |
Roustaei, Mahya Pumple, Joel Harvey, Jordan Froese, Duane |
author_sort |
Roustaei, Mahya |
title |
Ground ice estimation in permafrost samples using industrial Computed Tomography |
title_short |
Ground ice estimation in permafrost samples using industrial Computed Tomography |
title_full |
Ground ice estimation in permafrost samples using industrial Computed Tomography |
title_fullStr |
Ground ice estimation in permafrost samples using industrial Computed Tomography |
title_full_unstemmed |
Ground ice estimation in permafrost samples using industrial Computed Tomography |
title_sort |
ground ice estimation in permafrost samples using industrial computed tomography |
publishDate |
2024 |
url |
https://doi.org/10.5194/egusphere-2024-1353 https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1353/ |
genre |
Ice permafrost |
genre_facet |
Ice permafrost |
op_source |
eISSN: |
op_relation |
doi:10.5194/egusphere-2024-1353 https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1353/ |
op_doi |
https://doi.org/10.5194/egusphere-2024-1353 |
_version_ |
1810448920296292352 |