High-Complexity Deterministic Q(f) Simulation of the 1994 Northridge Mw 6.7 Earthquake

Wednesday, 17 December 2014
Kyle Withers1, Kim Bak Olsen2, Zheqiang Shi1 and Steven M Day1, (1)San Diego State University, San Diego, CA, United States, (2)San Diego State Univ, San Diego, CA, United States
With the recent addition of realistic fault topography in 3D simulations of earthquake source models, ground motion can be deterministically generated more accurately up to higher frequencies. However, the earthquake source is not the only source of complexity in the high-frequency ground motion; there are also scattering effects caused by small-scale velocity and density heterogeneities in the medium that can affect the ground motion intensity. Here, we model dynamic rupture propagation for the 1994 Mw 6.7 Northridge earthquake up to 8 Hz using a support operator method (SORD). We extend the ground motion to further distances by converting the output to a kinematic source for the finite difference anelastic wave propagation code AWP-ODC, which incorporates frequency-dependent attenuation via a power law above a reference frequency in the form Q0fn.

We model the region surrounding the fault with and without small-scale medium complexity, with varying statistical parameters. Furthermore, we analyze the effect of varying both the power-law exponent of the attenuation relation (n) and the reference Q (Q0) (assumed to be proportional to the S-wave velocity), and compare our synthetic ground motions with several Ground Motion Prediction Equations (GMPEs) as well as observed accelerograms. We find that the spectral acceleration at various periods from our models are within 1 interevent standard deviation from the median GMPEs and compare well with that of recordings from strong ground motion stations at both short and long periods. At periods below 1 second, Q(f) is needed to match the decay of spectral acceleration seen in the GMPEs as a function of distance from the fault (n~0.6-0.8).We find when binning stations with a common distance metric (such as Joyner-Boore or rrup) that the effect of media heterogeneity is canceled out, however, the similarity between the intra-event variability of our simulations and observations increases when small-scale heterogeneity is included.