Abstract:
The reliability and accuracy of the ground-motion prediction equations
(GMPEs) are of prime interest while evaluating seismic hazard for any region. The
regular updates and minimization of the uncertainties associated with the coefficients
of the GMPEs are important for improving ground-motion predictions and consequent
performance of seismic hazard maps.
Thus, in the present study, we propose an update of the GMPEs estimated by
Sharma et al. (2013) in The Geysers geothermal area. The update is done using
the huge dataset available and by extending the magnitude range as well as distance
range. The previous dataset used by Sharma et al. (2013) was composed of 212 earthquakes
recorded at 29 stations with the magnitude range between 1:3 ≤ Mw ≤ 3:3 and
distance range between 0:6 ≤ Rhypo ≤ 20 km. The new dataset encloses 10,974
induced earthquakes recorded at 29 stations with the magnitude range between
0:7 ≤ Mw ≤ 3:3 and distance range between 0:1 ≤ Rhypo ≤ 73 km. We compute
updated GMPEs for peak ground velocity (PGV), peak ground acceleration (PGA),
and 5% damped spectral acceleration (SA) (T) at T 0.05, 0.1, 0.2, 0.5, and 1.0 s.
The mean ground-motion predictions of the updated model proposed in the
present study and the associated uncertainties are compared with the previous model
proposed by Sharma et al. (2013) and with other models specifically developed for
small-magnitude earthquakes. The GMPEs are derived using a nonlinear mixed-effect
regression technique that accounts for both interevent and intraevent dependencies in
the data. We also demonstrate the dependency of aleatory (random) uncertainties and
epistemic (informative) uncertainties on source, medium, and site properties. We also
concluded that the medium is behaving homogeneously in terms of peak groundmotion
attenuation by analyzing uncertainties associated with different groundmotion
periods.
