Empirical Predictive Models for Earthquake-Induced Sliding Displacements of Slopes

Abstract

Earthquake-induced sliding displacement is the parameter most often used to assess the seismic stability of slopes. The expected displacement can be predicted as a function of the characteristics of the slope (yield acceleration) and the ground motion (e.g., peak ground acceleration), yet there is significant aleatory variability associated with the displacement prediction. Using multiple ground motion parameters to characterize the earthquake shaking can significantly reduce the variability in the prediction. Empirical predictive models for rigid block sliding displacements are developed using displacements calculated from over 2,000 acceleration–time histories and four values of yield acceleration. These empirical models consider various single ground motion parameters and vectors of ground motion parameters to predict the sliding displacement, with the goal of minimizing the standard deviation of the displacement prediction. The combination of peak ground acceleration and peak ground velocity is the two parameter vector that results in the smallest standard deviation in the displacement prediction, whereas the three parameter combination of peak ground acceleration, peak ground velocity, and Arias intensity further reduces the standard deviation. The developed displacement predictive models can be used in probabilistic seismic hazard analysis for sliding displacement or used as predictive tools for deterministic earthquake scenarios.