Near-Source Ground Motion Characteristics of the Ridgecrest Earthquake Sequence

Session: Observations From the 2019 Ridgecrest Earthquake Sequence [Poster]
Type: Poster
Date: 4/28/2020
Time: 08:00 AM
Room: Ballroom
Description: 

In this study, we evaluate the performance of ground motion models (GMMs) developed for the active shallow crustal region of southern California using instrumental ground motion observations of peak ground acceleration (PGA) and 5% damped pseudo-spectral acceleration (PSA) (0.02 to 10 s) from the 2019 Ridgecrest, California earthquake sequence (Mw 4.0-7.1). The ground motion dataset from the Ridgecrest earthquake sequence contains numerous (#2020 at <100 km hypocentral distance) and valuable near-source strong shaking observations and provides an independent dataset allowing us to evaluate the predictive power of GMMs. Observations of this size and proximity are rare, and therefore this is an important dataset to validate GMMs. We investigate GMM performance as a function of regional Q and earthquake source parameters such as magnitude and depth. We also investigate the ability of site amplification models to capture the distribution of shaking due to basin effects and Vs30. In general, we find that the NGAW2 GMMs perform the best, using the log likelihood (LLH) probabilistic scoring method, for the range of magnitudes and distances in the dataset. However, some seismic station sites are not well modeled due to local basin edge effects and require further study before incorporating into seismic hazard models. These sites located in and near the town of Trona, CA experienced the most damage. Results from this analysis will inform logic-tree weights for updates of the USGS National Seismic Hazard Model.

Presenting Author: Daniel E. McNamara

Authors