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Regression models for estimating coseismic landslide displacement

R.W. Jibson
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Abstract

Newmark's sliding-block model is widely used to estimate coseismic slope performance. Early efforts to develop simple regression models to estimate Newmark displacement were based on analysis of the small number of strong-motion records then available. The current availability of a much larger set of strong-motion records dictates that these regression equations be updated. Regression equations were generated using data derived from a collection of 2270 strong-motion records from 30 worldwide earthquakes. The regression equations predict Newmark displacement in terms of (1) critical acceleration ratio, (2) critical acceleration ratio and earthquake magnitude, (3) Arias intensity and critical acceleration, and (4) Arias intensity and critical acceleration ratio. These equations are well constrained and fit the data well (71% < R2 < 88%), but they have standard deviations of about 0.5 log units, such that the range defined by the mean ?? one standard deviation spans about an order of magnitude. These regression models, therefore, are not recommended for use in site-specific design, but rather for regional-scale seismic landslide hazard mapping or for rapid preliminary screening of sites. ?? 2007 Elsevier B.V. All rights reserved.

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R.W. Jibson. 2007. Regression models for estimating coseismic landslide displacement. https://doi.org/10.1016/j.enggeo.2007.01.013

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