The Ripley Landslide is a small (0.04 km2), 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.

We discuss issues in developing scalable parallel algorithms and focus on the distribution, as opposed to the replication, of key data structures. Replication of large data structures limits the maximum calculation size by imposing a low ratio of processors to memory. Only applications which distribute both data and computation across processors are truly scalable. The use of shared data structures that may be independently accessed by each process even in a distributed memory environment greatly simplifies development and provides a significant performance enhancement. We describe tools we have developed to support this programming paradigm. These tools are used to develop a highly efficient and scalable algorithm to perform self‐consistent field calculations on molecular systems. A simple and classical strip‐mining algorithm suffices to achieve an efficient and scalable Fock matrix construction in which all matrices are fully distributed. By strip mining over atoms, we also exploit all available sparsity and pave the way to adopting more sophisticated methods for summation of the Coulomb and exchange interactions. © 1996 by John Wiley & Sons, Inc.

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Landslides along a 10 km reach of Thompson River south of Ashcroft, British Columbia, have repeatedly damaged vital railway infrastructure, while also placing public safety, the environment, natural resources, and cultural heritage features at risk. Government agencies, universities, and the railway industry are focusing research efforts on a representative test site — the very-slow-moving Ripley Landslide — to manage better the geohazard risk in this corridor. We characterize the landslide’s form and function through hydrogeological and geophysical mapping. Field mapping and exploratory drilling distinguish 10 hydrogeological units in surficial deposits and fractured bedrock. Electrical resistivity tomography, frequency domain electromagnetic conductivity measurements, ground-penetrating radar, seismic pressure wave refraction, and multispectral analysis of shear waves; in conjunction with downhole measurement of natural gamma radiation, induction conductivity, and magnetic susceptibility provide a detailed, static picture of soil moisture and groundwater conditions within the hydrogeological units. Differences in electrical resistivity of the units reflect a combination of hydrogeological characteristics and climatic factors, namely temperature and precipitation. Resistive earth materials include dry glaciofluvial outwash and nonfractured bedrock; whereas glaciolacustrine clay and silt, water-bearing fractured bedrock, and periodically saturated subglacial till and outwash are conductive. Dynamic, continuous real-time monitoring of electrical resistivity, now underway, will help characterize water-flow paths, and possible relationships to independently monitor pore pressures and slope creep. These new hydrogeological and geophysical data sets enhance understanding of the composition and internal structure of this landslide and provide important context to interpret multiyear slope stability monitoring ongoing in the valley.

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