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• W4308148169 endingPage "107593" @default.
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• W4308148169 abstract "Realistic prediction of coseismic landslides is crucial for the design of civil infrastructures and geotechnical systems in seismically active regions. Coseismic landslides are complicated nonlinear and large-deformation processes triggered by ground shaking. To date, many gaps still remain in the scientific understanding of the landslides, particularly in areas lacking information on the subsurface stratigraphy. Analytical methods for estimating coseismic landslides have been based on highly simplified models, where many key influential factors have been overlooked, leading to large uncertainty in using empirical models for landslide prediction. In addition, more evidence recently underscores the necessity of modeling coupled effects between topography and soil amplification, which gives rise to complex wave propagation patterns due to scattering and diffracting of waves within the low-velocity near-surface layers. Neglecting topographic amplification and soil layers could result in significantly underpredicted regional-scale hazards of landslides. In this study, a regional-scale coseismic landslide simulation is carried out using the integral Spectral Element Method (SEM)-Newmark method for Hong Kong Island to quantify the coupled effect of 3D topography, subsurface soil condition as well as hydrogeological conditions. By leveraging extensive geological borehole data, a rigorous statistical model that characterizes uncertainties associated with subsurface soils is established. Influence of key factors that are not well considered in previous coseismic landslide studies, such as variation in irregular rockhead and spatially distributed shear-wave velocity are quantitatively analyzed. Numerical results demonstrate that by rigorously incorporating multiple sources of subsurface soil uncertainties, the total area of landslides in the study region can increase up to 30% compared with benchmark model as evidenced in the physics-based numerical simulation. These case studies will provide a valuable opportunity to revisit key factors that influence coseismic landslides using measured field data." @default.
• W4308148169 created "2022-11-08" @default.
• W4308148169 creator A5014087835 @default.
• W4308148169 creator A5049196788 @default.
• W4308148169 date "2023-01-01" @default.
• W4308148169 modified "2023-10-14" @default.
• W4308148169 title "Regional-scale assessment of earthquake-induced slope displacement considering uncertainties in subsurface soils and hydrogeological condition" @default.
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• W4308148169 doi "https://doi.org/10.1016/j.soildyn.2022.107593" @default.
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