Abstract
ABSTRACTDetailed surface topography is important when analyzing the stability of slopes. Recent advances in new technologies such as interferometric synthetic aperture radar and light detection and ranging have allowed us to obtain high-precision profiles of distant landscapes and objects including detailed slope information for three-dimensional (3D) slope stability analysis. However, techniques of reconstructing 3D numerical models from scanned data of slope geometry have not been well investigated or tested. This paper proposes a comprehensive approach that integrates laser scanning and finite element method for slope stability analysis, particularly failure prediction under precipitation scenarios. The methodology is applied to a slope in the Wenchuan earthquake-stricken mountainous region that failed in 2013, triggered by severe rainfall. The modelling results show that the surface sampling resolution can affect the prediction accuracy of the potential failure zones. When constructing the slope model, the selected surface grid should be fine enough to capture the important topographic features of the slope while minimizing computation demand. This paper confirms that the proposed method can be successfully used to identify the potential failure zones of the investigated slope under severe rainfall conditions.
Highlights
Effective numerical models for landslide stability analysis require a good set of input parameters
Accurate topology data are essential for a reliable landslide stability model; this requires considerable effort involving various technologies and methods such as field surveys, global positioning system (GPS) mapping, and digital elevation model (DEM) data
Areas that experienced recent earthquakes can be very dangerous, because many of the slopes that need to be assessed for hazard level and possible mitigation measures are at high risk of sliding
Summary
Effective numerical models for landslide stability analysis require a good set of input parameters. The new technologies (InSAR, LiDAR, high-resolution photogrammetry, etc.) provide effective and diversified support in landslide and slope reconstruction, researchers have not yet taken full advantage of the data quality available to improve landslide modelling and simulation and understand the mechanisms that govern landslides, rockfall, and debris flow (Jaboyedoff et al 2012). These include the finite element method (FEM), discrete element method, limit equilibrium method, finite difference method (FDM), and various combinations of these methods (Wang et al 2007; Kanungo et al 2013; Zhang et al 2014; Ozbay et al 2015) These numerical methods have recently been incorporated with new technologies to generate suitable 2D/3D models for analysis.
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