An assessment of landslide risk using 4-Dimensional Electrical Resistivity Tomography for monitoring an unstable slope that affects transport infrastructure in British Columbia, Canada

Abstract:

The Ripley Landslide is a small (0.04 km²), slow moving, translational landslide, that threatens the integrity of two major railway lines (Canadian National and Canadian Pacific Railways) in the Thompson River valley, British Columbia, Canada. There is a need for monitoring at the site as elements at risk from slope failure here are extensive, and include vital transport infrastructure, the economy, the environment, potable water supply, public safety, culture and heritage, and salmon runs. To monitor slope movement, a 4-D Electrical Resistivity Tomography (ERT) monitoring programme was commenced on the Ripley Landslide in November 2017. A Proactive Infrastructure Monitoring and Evaluation (PRIME) geoelectrical monitoring system, which uses a telemetry link to send measured ERT data to remote servers, was installed across the head scarp of the landslide, providing near-real-time resistivity data for use in slope stability assessment. The first two years of monitoring data from the Ripley Landslide PRIME system will be presented. Petrophysical relationships have been established, in the laboratory, between resistivity, soil suction, and moisture content – key factors in slope stability assessment. These are applied to the ERT models to provide insights into the hydrogeological pathways in the subsurface and their response to changing weather conditions. Temperature also exerts control on electrical resistivity and soil suction at this site, as soil at the near surface undergoes annual freeze-thaw cycles. Therefore, laboratory relationships between temperature, electrical resistivity, and soil suction are also applied to the ERT models to better understand the behaviour of the slope during freeze-thaw periods. The calibrated PRIME images reveal complex hydrogeological pathways and subsurface responses to seasonal changes in weather conditions. When used in conjunction with movement data from Geocubes, precursors to movement can be identified in the ERT images to enable the prediction of the timing of failure at this site in the long-term.