Four‐dimensional electrical resistivity tomography for continuous, near‐real‐time monitoring of a landslide affecting transport infrastructure in British Columbia, Canada. Issue 4 (29th April 2020) - Holmes, Jessica; Chambers, Jonathan; Meldrum, Philip; Wilkinson, Paul; Boyd, James; Williamson, Paul; Huntley, David; Sattler, Kelvin; Elwood, David; Sivakumar, Vinayagamoothy; Reeves, Helen; Donohue, Shane
ABSTRACT: The Ripley Landslide is a small (0.04 km 2 ), slow‐moving landslide in the Thompson River Valley, British Columbia, that is threatening the serviceability of two national railway lines. Slope failures in this area are having negative impacts on railway infrastructure, terrestrial and aquatic ecosystems, public safety, communities, local heritage and the economy. This is driving the need for monitoring at the site, and in recent years there has been a shift from traditional geotechnical surveys and visual inspections for monitoring infrastructure assets toward less invasive, lower cost, and less time‐intensive methods, including geophysics. We describe the application of a novel electrical resistivity tomography system for monitoring the landslide. The system provides near‐real time geoelectrical imaging, with results delivered remotely via a modem, avoiding the need for costly repeat field visits, and enabling near‐real time interpretation of the four‐dimensional electrical resistivity tomography data. Here, we present the results of the electrical resistivity tomography monitoring alongside field sensor‐derived relationships between suction, resistivity, moisture content and continuous monitoring single‐frequency Global Navigation Satellite System stations. Four‐dimensional electrical resistivity tomography data allows us to monitor spatial and temporal changes in resistivity, and by extension, in moisture content and soil suction. The models reveal complex hydrogeological pathways, as well as considerable seasonal variation in the response of the subsurface to changing weather conditions, which cannot be predicted through interrogation of weather and sensor data alone, providing new insight into the subsurface processes active at the site of the Ripley Landslide.