Stochastic Simulations and Ground Motion Prediction Equation for Peak Accelerations, Peak Velocities and Response Spectra for the Ural Region

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Abstract

The characteristics of radiation and propagation of seismic waves in the Ural region were refined based on stochastic modeling of the records of local earthquakes; these characteristics correspond to transient characteristics from areas of stable continental seismicity to seismically active regions with crustal seismicity. Ground motion prediction equation (GMPE) has been constructed for the Ural region, describing the dependence of peak accelerations (PGA), peak velocities (PGV) and acceleration response spectrum amplitudes (SA) on rock on magnitude and distance. The GMPE is applicable in a wide range of magnitudes (MW~4–6.5) and distances (1–250 km) and can be applied to assess seismic hazard in the design and construction of earthquake-resistant structures in the Ural region. To account for the epistemic uncertainty of the estimates of seismic impacts in probabilistic seismic hazard analysis and construct a logic tree, five alternative modern GMPEs from other regions were selected: a global model for crustal seismicity, two models developed for the mountain regions of the Swiss and French Alps, two models for regions of stable continental seismicity – eastern North America and Great Britain. These models were tested using the array of synthetic ground motion parameters; the equation for the Swiss Alps turned out to be the closest to the developed GMPE for the Urals.

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About the authors

V. А. Pavlenko

Schmidt Institute of Physics of the Earth of the Russian Academy of Sciences

Author for correspondence.
Email: pavlenko.vasily@gmail.com
Russian Federation, Moscow

О. V. Pavlenko

Schmidt Institute of Physics of the Earth of the Russian Academy of Sciences

Email: olga@ifz.ru
Russian Federation, Moscow

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Supplementary files

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2. Fig. 1. Map of epicentres of local earthquakes in the Ural region, from records of which regional characteristics of radiation and propagation of seismic waves were studied. Epicentres of earthquakes and mountain shocks, information about which is given in Table 1, are shown with yellow circles. Foci of identified earthquakes are circled in black, and the date of the event is given for them.

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3. Fig. 2. Velocity section of the Earth's crust along the central part of the Sverdlovsk profile obtained by depth seismic sounding methods (based on [Druzhinin et al., 1976; Depth structure..., 1985]).

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4. Fig. 3. Recorded (NS- and EW-components, black lines) and modelled (blue lines) accelerograms of horizontal components and corresponding Fourier amplitude spectra of NS- and EW-components of the recorded accelerograms (red and black lines) and averaged spectra of the calculated accelerograms (blue lines). The parameters of the sources from IRIS data were used in the modelling.

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5. Fig. 4. Recorded and modelled accelerograms of horizontal components. The designations are the same as in Fig. 3. In the modelling we used the parameters of the sources according to the data of FIC EGS RAS.

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6. Fig. 5. Dependence of the estimates of (a) PGA, (b) PGV, (c) SA (0.1 s), (d) SA (0.5 s), (e) SA (1.0 s), (f) SA (5.0 s) obtained from equation (2) on the magnitude and Joyner-Boer distance. Black dots show the mean values of the estimates of the corresponding motion parameters constructed by stochastic modelling. Black lines show the estimates of equation (2) for magnitudes MW = 4.0-6.5.

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7. Fig. 6. Acceleration response spectra with 5% attenuation calculated using equation (2) for values of (a) rJB = 3 km and (b) rJB = 35 km. Black dots show the mean values of the SA estimates constructed by stochastic modelling. Black lines show the estimates of equation (2) for magnitudes MW = 4.0-6.5.

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8. Fig. 7. Comparison of PGA and SA estimates obtained from the UPDG of different authors and from the UPDG proposed in the present work (a), (b) for MW = 4.5; (c), (d) for MW = 6.5.

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9. Fig. 8. Calculation of LLH value on random samples: (a) - shows the original distribution (1) and distributions with modified parameters (2-5); (b)-(f) - shows the results of LLH value calculation when testing distributions with modified parameters on a sample from the original distribution. Grey dots show the likelihood values of individual observations, black lines show the LLH values.

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10. Fig. 9. Values of the LLH value when testing different SDGs on a set of synthetic parameters of surface oscillations constructed by stochastic modelling methods: (a) - for a set of 5 SDGs considered in this paper; (b) - for a set of SDGs recommended for the Urals by the GEM project.

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