Repeated Intermittent Earthquake Cycles in the San Francisco Bay Region

Forecasts of future earthquake hazard in the San Francisco Bay region (SFBR) are dependent on the distribution used for the possible magnitude of future events. Based on the limited observed data, it is not possible to statistically distinguish between many distributions with very different tail behavior. These include the modified and truncated Gutenberg–Richter distributions, and a composite distribution assembled by the Working Group on California Earthquake Probabilities. There is consequent ambiguity in the estimated probability of very large, and hence damaging, events. A related question is whether the energy released in earthquakes is a small or large proportion of the stored energy in the crust, corresponding loosely to the ideas of self-organized criticality, and intermittent criticality, respectively. However, the SFBR has experienced three observed accelerating moment release (AMR) cycles, terminating in the 1868 Hayward, 1906 San Andreas and 1989 Loma Prieta events. A simple stochastic model based on elastic rebound has been shown to be capable of producing repeated AMR cycles in large synthetic catalogs. We propose that such catalogs can provide the basis of a test of a given magnitude distribution, via comparisons between the AMR properties of the real and synthetic data. Our results show that the truncated Gutenberg–Richter distribution produces AMR behavior closest to the observed AMR behavior. The proviso is that the magnitude parameters b and m _max are such that a sequence of large events that suppresses activity for several centuries is unlikely to occur. Repeated simulation from the stochastic model using such distributions produces 30-year hazard estimates at various magnitudes, which are compared with the estimates from the 2003 Working Group on California Earthquake Probabilities.