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Quantifying Sensitivities of PSHA for France to Earthquake Catalog Uncertainties, Truncation of Ground-Motion Variability, and Magnitude Limits

Institut de Radioprotection et de Sûreté Nucléaire
Bureau d'Evaluation des Risques Sismiques pour la Sûreté des Installations
BP 17
92262 Fontenay-aux-Roses Cedex
France

Manuscript received 8 December 2003.

The results of this study clearly identify four key parameters controlling the estimation of probabilistic seismic hazard assessment (PSHA) in France in the framework of the Cornell-McGuire method. Results in terms of peak ground acceleration demonstrate the equally high impact, at all return periods, of the choice of truncation of the predicted ground-motion distribution (at + 2) and of the choice between two different magnitude-intensity correlations. The choice of minimum magnitude (3.5/4.5) on hazard estimates can have an important impact at small return periods (<1000 years), whereas the maximum magnitude (6.5/7.0), on the other hand, is not a key parameter even at large return periods (10,000 years). This hierarchy of impacts is maintained at lower frequencies down to 5 Hz. Below 5 Hz, the choice of the maximum magnitude has a much greater impact, whereas the impact due to the choice of the minimum magnitude disappears. Moreover, variability due to catalog uncertainties is also quantified; these uncertainties that underly all hazard results can engender as high a variability as the controlling parameters. Parameter impacts, calculated at the centers of each source zone, show a linear trend with the seismicity models of the zone, demonstrating the lack of contributions coming from neighboring zones. Indeed, the region of influence that contributes to the PSHA estimate at a given site decreases with increasing return periods. The resulting overall variability in hazard estimates due to input uncertainties is quantified through a logic tree, obtained coefficients of variation vary between 10% and 20%. Until better physical models are obtained, the uncertainty on hazard estimates may be reduced by working on an appropriate magnitude-intensity correlation.

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