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Developments in time-lapse electrical resistivity tomography (ERT) technology are transforming our ability to monitor the subsurface due to purpose-built monitoring instruments, advances in automation and modeling, and the resulting improvements in spatial and temporal resolution. We describe the development of a novel ERT-based remote monitoring system called PRIME that integrates new low-power measurement instrumentation with data delivery, automated data processing and image generation, and web-based information delivery. Due to the sensitivity of ERT to hydrologic processes in the near surface, we focus on the application of PRIME for moisture-driven landslide monitoring. Case examples are considered of landslides in engineered and natural slopes, including those impacting geotechnical assets in rail and highways, where slope hydrology is seen to be controlled by lithology, vegetation, fissuring, and drainage structures. We conclude by taking a forward look at emerging developments in ERT monitoring relating to hardware, software and modeling, and applications.

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.

A complete assessment of slope stability is achieved by identifying and monitoring the subsurface properties and processes leading to slope failure conditions. Monitoring technologies need to be applied at appropriate scales and resolution, and with sufficient coverage, to be able to assess these conditions in local landslide early warning systems. A holistic understanding of the subsurface at the slope-scale is not always captured by some landslide monitoring approaches, such as remote sensing observations with limited depth penetration or sparse resolution, or point sensor measurements with highly localised information. Geophysical techniques have demonstrable capacity to link between the different scales, resolutions and coverage of these established landslide monitoring techniques. Here, we present a novel framework identifying the benefits and limitations of including geophysical imaging and monitoring techniques at different stages of local landslide early warning system strategies. These include the use of geophysical inputs to aid the design of local landslide early warning systems, monitor slopes at risk of failure, inform forecasting, and support decision making for stakeholders.