Long-Term Slip History Discriminates Among Occurrence Models for Seismic Hazard Assessment

Today, the probabilistic seismic hazard assessment (PSHA) community relies on one or a combination of stochastic models to compute occurrence probabilities for large earthquakes. Considerable efforts have been devoted to extracting the maximum information from long catalogues of large earthquakes (CLE) based on instrumental, historical, archeological and paleoseismological data (Biasi et al, 2009, Parsons, 2008, Rhoades and Dissen 2003). However, the models remain only and insufficiently constrained by these rare single-slip event data. Therefore, the selection of the models and their respective weights is necessarily left with the appreciation of a panel of experts (WGCEP, 2003). Since cumulative slip data with high temporal and spatial resolution are now available, we propose here a new approach to incorporate these pieces of evidence of mid- to long-term fault behavior into the next generation of PSHA: the Cumulative Offset-Based Bayesian Recurrence Analysis (COBBRA). Applied to the Jordan Valley segment of the Dead Sea Fault, the method yields the best combination of occurrence models for full-segment ruptures knowing the available single-event and cumulative data. Not only does our method provide data-driven, objective weights to the competing models, but it also allows to rule out time-independence, and to compute the cumulative probability of occurrence for the next full-segment event reflecting all available data.

References:

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