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Risk Implications of Poisson Assumptions and Declustering Inferred From a Fully Time-Dependent Earthquake Forecast

Description: 

We use the 3^rdUniform California Earthquake Rupture Forecast ETAS model (UCERF3-ETAS), which is fully time-dependent in terms of including spatiotemporal clustering, to evaluate the effects of the Poisson assumption and declustering algorithms on statewide loss exceedance curves. The model is simulation-based, meaning it produces synthetic catalogs that exhibit realistic behavior with respect to aftershocks and finite-fault ruptures (including muti-fault earthquakes). A Poisson version of the model was constructed by randomizing event times, and the influence of two declustering algorithms was also examined. We demonstrate that for curves that specify the probability of one or more loss exceedances, the Poisson model implies greater risk because it has fewer seismically quiet time periods. The discrepancy is up to a factor of 32% but varies depending on the loss threshold (the x-axis value) and the forecast duration (we examined a range between 24 hours and 50 years, with the discrepancy for the latter being negligible). We discuss how the one-or-more loss exceedance metric is questionable because it ignores all but the maximum loss experienced in each timeframe. An alternative metric based on total aggregate loss in each time window was also examined, for which the Poisson model again implies higher risk at intermediate losses, but lower risk at higher losses (because large, triggered events now contribute to total aggregate losses for the fully time-dependent model). We also argue that declustering is not a scientifically justifiable way to deal with full time dependence, in agreement with a chorus from other recent studies. It is difficult to draw generally applicable conclusions from our research, in part because application-specific details will likely be important, but we hope to have exemplified how full time dependence can easily be reckoned with once authoritative forecast models are made available.

Session: Advancing Time-dependent PSHA and Seismic Risk Assessment: Accounting for Short- to Medium-term Clustering - I

Type: Oral

Date: 4/15/2025

Presentation Time: 11:00 AM (local time)

Presenting Author: Edward

Student Presenter: No

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