The Seismic Hazard Implications of Declustering and Poisson Assumptions Inferred from a Fully Time-Dependent Model

We use the Third Uniform California Earthquake Rupture Forecast (UCERF3) epidemic-type aftershock sequence (ETAS) model (UCERF3-ETAS) to evaluate the effects of declustering and Poisson assumptions on seismic hazard estimates. Although declustering is necessary to infer the long-term spatial distribution of earthquake rates, the question is whether it is also necessary to honor the Poisson assumption in classic probabilistic seismic hazard assessment. We use 500,000 yr, M >= 2.5 synthetic catalogs to address this question, for which UCERF3-ETAS exhibits realistic spatiotemporal clustering effects (e.g., after-shocks). We find that Gardner and Knopoff (1974) declustering, used in the U.S. Geological Survey seismic hazard models, lowers 2% in 50 yr and risk-targeted ground-motion hazard metrics by about 4% on average (compared with the full time-dependent [TD] model), with the reduction being 5% at 40% in 50 yr ground motions. Keeping all earthquakes and treating them as a Poisson process increases these same hazard metrics by about 3%-12%, on average, due to the removal of relatively quiet time periods in the full TD model. In the interest of model simplification, bias minimization, and consideration of the probabilities of multiple exceedances, we agree with others (Marzocchi and Taroni, 2014) that we are better off keeping aftershocks and treating them as a Poisson process rather than removing them from hazard consideration via declustering. Honoring the true time dependence, however, will likely be important for other hazard and risk metrics, and this study further exemplifies how this can now be evaluated more extensively.

Automated summary

In this study, the effects of declustering and Poisson assumptions on seismic hazard estimates are evaluated using the UCERF3-ETAS model. The research findings suggest that it is better to keep aftershocks and treat them as a Poisson process rather than removing them from hazard consideration via declustering. The study also highlights the importance of honoring the true time dependence for other hazard and risk metrics.