Assessment of Predictive Values of Site Response based on GMPE approaches using a Large-N array

Nori Nakata

Submitted August 10, 2016, SCEC Contribution #6608, 2016 SCEC Annual Meeting Poster #277

Ground-motion prediction is a key component for seismic hazard analysis, which is typically carried out with ground-motion prediction equations. The standard deviation of the best-fit model characterizes the residual ground motion variability. These residuals are an admixture of random variability (aleatory uncertainty) and modeling error (epistemic uncertainty). When we compute site-specific ground motion prediction, the residuals can become smaller since different sources, paths, and sites are not mixed. Recent development of dense, capable, and long-term seismometer networks allows us to estimate the site-, path-, and source-specific variability. In this study, we use a very dense array (Large-N array) at Long Beach, California, and demonstrate the potential to characterize the spatial variability for the vertical component of ground motion. Because of the density of the array (2500 receivers with 100-m spacing), we can estimate very dense site information (i.e., detailed near-surface velocities) from the ambient seismic field. With this velocity model, we can theoretically estimate the site amplification. The recording time is only a couple of months, but we observed more than 10 earthquakes, and hence we can estimate site-, path-, and source-specific variability of ground motion. Since we do not have multiple events occurring in close proximity to one another, we cannot separate the source-location and source-parameter effects.

Nakata, N. (2016, 08). Assessment of Predictive Values of Site Response based on GMPE approaches using a Large-N array. Poster Presentation at 2016 SCEC Annual Meeting.

Related Projects & Working Groups
Ground Motion Prediction (GMP)