4.4 Article

Statistical Analyses of Great Earthquake Recurrence along the Cascadia Subduction Zone

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SEISMOLOGICAL SOC AMER
DOI: 10.1785/0120120105

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  1. BC Hydro & Power Corporation (BC Hydro)
  2. URS Corporation
  3. Directorate For Geosciences
  4. Division Of Ocean Sciences [1137986] Funding Source: National Science Foundation

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Goldfinger et al. (2012) interpreted a 10,000 year old sequence of deep sea turbidites at the Cascadia subduction zone (CSZ) as a record of clusters of plate-boundary great earthquakes separated by gaps of many hundreds of years. We performed statistical analyses on this inferred earthquake record to test the temporal clustering model and to calculate time-dependent recurrence intervals and probabilities. We used a Monte Carlo simulation to determine if the turbidite recurrence intervals follow an exponential distribution consistent with a Poisson (memoryless) process. The latter was rejected at a statistical significance level of 0.05. We performed a cluster analysis on 20 randomly simulated catalogs of 18 events (event T2 excluded), using ages with uncertainties from the turbidite dataset. Results indicate that 13 catalogs exhibit statistically significant clustering behavior, yielding a probability of clustering of 13/20 or 0.65. Most (70%) of the 20 catalogs contain two or three closed clusters (a sequence that contains the same or nearly the same number of events) and the current cluster T1-T5 appears consistently in all catalogs. Analysis of the 13 catalogs that manifest clustering indicates that the probability that at least one more event will occur in the current cluster is 0.82. Given that the current cluster may not be closed yet, the probabilities of an M 9 earthquake during the next 50 and 100 years were estimated to be 0.17 and 0.25, respectively. We also analyzed the sensitivity of results to including event T2, whose status as a full-length rupture event is in doubt. The inclusion of T2 did not change the probability of clustering behavior in the CSZ turbidite data, but did significantly reduce the probability that the current cluster would extend to one more event. Based on the statistical analysis, time-independent and time-dependent recurrence intervals were calculated.

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