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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Landslides in the Thompson River Valley, British Columbia, Canada, threaten the serviceability of two railway lines that connect Vancouver to the rest of Canada and the US. To minimise the impact of slope instability on vital transport infrastructure, as well as on terrestrial and aquatic ecosystems, public safety, communities, local heritage, and the economy, and to better inform decision making, there is a need for monitoring. Since 2013, the Ripley Landslide – a small, slow-moving, translational landslide – has been the focus of monitoring efforts in the Thompson River Valley transportation corridor. In November 2017, a novel Electrical Resistivity Tomography (ERT) monitoring system was installed on the site, providing near-real-time data collection via a telemetric link. 4-Dimensional resistivity models are presented in the context of moisture content and soil suction, two parameters known to influence slope stability in the Thompson River Valley. Here, we discuss the development of laboratory-based petrophysical relationships that relate electrical resistivity to moisture content and soil suction directly, building on relationships developed in the field. The 4-D ERT models were calibrated using these petrophysical relationships to provide insights into the complex spatial and temporal variations in moisture content and soil suction. This study highlights the utility of geoelectrical monitoring for assessing slope stability in the context of moisture-driven landslides.
Author(s): Holmes J, Chambers J, Wilkinson P, Meldrum P, Cimpoiasu M, Boyd J, Huntley D, Williamson P, Gunn D, Dashwood B, Whiteley J, Watlet A, Kirkham M, Sattler K, Elwood D, Sivakumar V, Donohue S
Publication type: Article
Publication status: Published
Journal: Engineering Geology
Year: 2022
Volume: 301
Print publication date: 01/05/2022
Online publication date: 11/03/2022
Acceptance date: 08/03/2022
Date deposited: 24/05/2022
ISSN (electronic): 0013-7952
Publisher: Elsevier
URL: https://doi.org/10.1016/j.enggeo.2022.106613
DOI: 10.1016/j.enggeo.2022.106613
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