Statistical Evaluation of Seismic Velocity Models of PermafrostSource: Journal of Cold Regions Engineering:;2024:;Volume ( 038 ):;issue: 003::page 04024021-1DOI: 10.1061/JCRGEI.CRENG-760Publisher: American Society of Civil Engineers
Abstract: The warming climate in high-latitude permafrost regions is leading to permafrost degradation. Estimating seismic wave velocities in permafrost could help predict the geomechanical properties of permafrost and provide information to plan and design resilient civil infrastructure in cold regions. This paper evaluates the performance of seven models when predicting the seismic wave velocities of permafrost statistically; these models are the time-average, Zimmerman and King, Minshull et al., weighted equation, three-phase, Biot–Gassmann theory modified by Lee (BGTL), and Dou et al. models. The data used in the evaluation are from published laboratory and in situ data, which includes 369 data points for joint P and S wave velocities from nine publications and 943 unfrozen water content data points from 12 publications. The unfrozen water content that is used in these models is determined from a modified Dall’Amico’s model that is proposed, which is evaluated against six existing unfrozen water content models based on soil temperature. This paper finds that saturated nonsaline permafrost generally shares similar linear trends between the P and S wave velocities, regardless of soil type, porosity, grain size, and temperature. Fitting all existing data, an empirical linear relationship is derived between the P and S wave velocities. Among the seven models evaluated, the Minshull et al. and BGTL models are the most accurate when predicting the seismic velocities of permafrost. Unfrozen water content and seismic wave velocity models are valuable tools for quantitatively predicting permafrost dynamics and degradation, with practical applications in various engineering areas with permafrost environments. As permafrost thaws due to rising temperatures, these models could be used to guide the quantitative interpretation of geophysical changes in subsurface conditions, assess the potential for ground instability, and predict future permafrost degradation. Unfrozen water content models are used to predict the percentage of unfrozen water within permafrost, which links the changes with permafrost temperature. Unfrozen water content models of permafrost are essential when assessing permafrost thaw, thermal performance, heat transfer processes in permafrost, and the effect of civil infrastructure on permafrost (Chen et al.,). The seismic wave velocity models could help engineers assess the subsurface conditions in permafrost areas; this assessment is crucial for environmental and seismic monitoring, land use planning, infrastructure design and construction, and natural resources exploration.
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contributor author | Xiaohang Ji | |
contributor author | Ming Xiao | |
contributor author | Eileen R. Martin | |
contributor author | Tieyuan Zhu | |
date accessioned | 2024-12-24T10:24:16Z | |
date available | 2024-12-24T10:24:16Z | |
date copyright | 9/1/2024 12:00:00 AM | |
date issued | 2024 | |
identifier other | JCRGEI.CRENG-760.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4298853 | |
description abstract | The warming climate in high-latitude permafrost regions is leading to permafrost degradation. Estimating seismic wave velocities in permafrost could help predict the geomechanical properties of permafrost and provide information to plan and design resilient civil infrastructure in cold regions. This paper evaluates the performance of seven models when predicting the seismic wave velocities of permafrost statistically; these models are the time-average, Zimmerman and King, Minshull et al., weighted equation, three-phase, Biot–Gassmann theory modified by Lee (BGTL), and Dou et al. models. The data used in the evaluation are from published laboratory and in situ data, which includes 369 data points for joint P and S wave velocities from nine publications and 943 unfrozen water content data points from 12 publications. The unfrozen water content that is used in these models is determined from a modified Dall’Amico’s model that is proposed, which is evaluated against six existing unfrozen water content models based on soil temperature. This paper finds that saturated nonsaline permafrost generally shares similar linear trends between the P and S wave velocities, regardless of soil type, porosity, grain size, and temperature. Fitting all existing data, an empirical linear relationship is derived between the P and S wave velocities. Among the seven models evaluated, the Minshull et al. and BGTL models are the most accurate when predicting the seismic velocities of permafrost. Unfrozen water content and seismic wave velocity models are valuable tools for quantitatively predicting permafrost dynamics and degradation, with practical applications in various engineering areas with permafrost environments. As permafrost thaws due to rising temperatures, these models could be used to guide the quantitative interpretation of geophysical changes in subsurface conditions, assess the potential for ground instability, and predict future permafrost degradation. Unfrozen water content models are used to predict the percentage of unfrozen water within permafrost, which links the changes with permafrost temperature. Unfrozen water content models of permafrost are essential when assessing permafrost thaw, thermal performance, heat transfer processes in permafrost, and the effect of civil infrastructure on permafrost (Chen et al.,). The seismic wave velocity models could help engineers assess the subsurface conditions in permafrost areas; this assessment is crucial for environmental and seismic monitoring, land use planning, infrastructure design and construction, and natural resources exploration. | |
publisher | American Society of Civil Engineers | |
title | Statistical Evaluation of Seismic Velocity Models of Permafrost | |
type | Journal Article | |
journal volume | 38 | |
journal issue | 3 | |
journal title | Journal of Cold Regions Engineering | |
identifier doi | 10.1061/JCRGEI.CRENG-760 | |
journal fristpage | 04024021-1 | |
journal lastpage | 04024021-24 | |
page | 24 | |
tree | Journal of Cold Regions Engineering:;2024:;Volume ( 038 ):;issue: 003 | |
contenttype | Fulltext |