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The addition of water on or below the earth's surface generates changes in stress that can trigger both stable and unstable sliding of landslides and faults. While these sliding behaviours are well-described by commonly used mechanical models developed from laboratory testing (e.g., critical-state soil mechanics and rate-and-state friction), less is known about the field-scale environmental conditions or kinematic behaviours that occur during the transition from stable to unstable sliding. Here we use radar interferometry (InSAR) and a simple 1D hydrological model to characterize 8 years of stable sliding of the Mud Creek landslide, California, USA, prior to its rapid acceleration and catastrophic failure on May 20, 2017. Our results suggest a large increase in pore-fluid pressure occurred during a shift from historic drought to record rainfall that triggered a large increase in velocity and drove slip localization, overcoming the stabilizing mechanisms that had previously inhibited landslide acceleration. Given the predicted increase in precipitation extremes with a warming climate, we expect it to become more common for landslides to transition from stable to unstable motion, and therefore a better assessment of this destabilization process is required to prevent loss of life and infrastructure.
Pubmed ID: 30733588
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Multi paradigm numerical computing environment and fourth generation programming language developed by MathWorks. Allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. Used to explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, and computational finance.
View all literature mentionsAccepts and provides access to high-resolution (meter to sub-meter scale) Earth science-oriented topography data (e.g. LiDAR) and bathymetric data, and related tools and resources. The OpenTopography Tool Registry provides a community populated clearinghouse of software, utilities, and tools oriented towards high-resolution topography data (e.g. collected with LiDAR technology) handling, processing, and analysis. Tools registered range from source code to full-featured software applications. Contributions to the registry via the Contribute a Tool page are welcome. OpenTopography also hosts a dataset catalog to which users can register datasets hosted elsewhere; these entries are discoverable by users alongside OpenTopography hosted datasets. Lidar point cloud data are available in LAS, LAZ and ASCII formats. Raster datasets and derived products can be downloaded in Arc ASCII, IMG, and GeoTIFF formats. Derived products and visualizations are available in Google Earth KML format. The OpenTopography user community and advisory committee provides feedback to define the scope of collaborations on data hosting and cyberinfrastructure development
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