Electronic Thesis and Dissertation Repository


Doctor of Philosophy




Dr. Gail M. Atkinson


We develop a simulation-based generic ground-motion prediction equation (GMPE) that can be adjusted for use in any region by simple modifications to its key modeling parameters.

First, we determine how to treat ground-motion saturation effects observed at close distances to large magnitude earthquakes in a point-source sense. We model the source and attenuation attributes of well-recorded M ≥ 6 events, considering ground motions originate from an equivalent point source placed at an overall effective distance such that the empirically-observed saturation effects are successfully reproduced. We investigate the trade-offs between source and attenuation modeling parameters through analysis of Fourier amplitudes for several alternative attenuation models.

Next, we describe response spectra for California earthquakes of 3.0 ≤ M < 7.5 using stochastic ground-motion simulations based on the equivalent point-source concept. The best-fit simulation model suggests that the attenuation in California can be modeled as R-1.3 at distances < 50 km and R-0.5 at further distances; this does a better job at matching attenuation trends than the traditional model 1/R model at distances < 50 km, particularly for small magnitude events. We develop a stress parameter model for California earthquakes based on matching the simulated and observed response spectral shapes over a wide frequency range. We determine a simulation calibration factor for amplitude adjustment to match the observed spectral amplitudes with zero bias.

Finally, we perform equivalent point-source simulations with parameters calibrated to empirical data in California to determine the decoupled effects of basic source and attenuation parameters on response spectral amplitudes. Based on these isolated effects, we formulate the generic GMPE as a function of magnitude, distance, stress parameter, geometrical spreading rate and anelastic attenuation coefficient. This provides a fully adjustable predictive model, allowing users to calibrate its parameters using observed motions in the target region. As an example application, we show how the generic GMPE can be adjusted for use in central and eastern North America.