UPDATED GRAIZER-KALKAN GROUND- MOTION PREDICTION EQUATIONS FOR WESTERN UNITED STATES

Transcription

1 10NCEE Tenth U.S. National Conference on Earthquake Engineering Frontiers of Earthquake Engineering July 1-5, 014 Anchorage, Alaska UPDATED GRAIZER-KALKAN GROUND- MOTION PREDICTION EQUATIONS FOR WESTERN UNITED STATES V. Graizer 1 ABSTRACT Ground motion prediction equations (GMPEs) for peak-ground acceleration and 5 percent damped pseudo spectral accelerations of horizontal component ground motions were developed by Graizer and Kalkan (007, 009). Their functional form is derived from filters each filter represents a certain physical phenomenon affecting the radiation of seismic waves from the source. This paper presents updated Graizer-Kalkan GMPE for peak-ground acceleration and 5 percent damped pseudo spectral accelerations of horizontal component ground motions. The recent updates include an anelastic attenuation filter as a function of quality-factor and improved basin-effect filter, which is a function of depth to 1.5 km/s shear-wave velocity isosurface, source distance, and spectral period (T). In our previous model, spectral shape decayed at long-periods with a slope of T -1.5, averaging basin and non-basin site effects. In the updated model, the spectral shape decays at long-periods faster (T - ) for non-basin sites and slower (T -1.4 ) for basin sites as compared to our previous model. The updated GMPEs are applicable for earthquakes with 5 M 8 (where M is moment magnitude), distances of up to 50 km, and range of shear wave velocities of 50<V S30 <1,00 m/sec. 1 Geophysicist, U.S. Nuclear Regulatory Commission, Mail Stop: T-7F3, Washington, DC , Vladimir.Graizer@nrc.gov Graizer V. Updated Graizer-Kalkan ground-motion prediction equations for Western United States. Proceedings of the 10 th National Conference on Earthquake Engineering, Earthquake Engineering Research Institute, Anchorage, AK, 014.

2 10NCEE Tenth U.S. National Conference on Earthquake Engineering Frontiers of Earthquake Engineering July 1-5, 014 Anchorage, Alaska Updated Graizer-Kalkan Ground-Motion Prediction Equations for Western United States V. Graizer 1 ABSTRACT Ground motion prediction equations (GMPEs) for peak-ground acceleration and 5 percent damped pseudo spectral accelerations of horizontal component ground motions were developed by Graizer and Kalkan (007, 009). Their functional form is derived from filters each filter represents a certain physical phenomenon affecting the radiation of seismic waves from the source. This paper presents updated Graizer-Kalkan GMPE for peak-ground acceleration and 5 percent damped pseudo spectral accelerations of horizontal component ground motions. The recent updates include an anelastic attenuation filter as a function of quality-factor and improved basin-effect filter, which is a function of depth to 1.5 km/s shear-wave velocity isosurface, source distance, and spectral period (T). In our previous model, spectral shape decayed at long-periods with a slope of T -1.5, averaging basin and non-basin site effects. In the updated model, the spectral shape decays at long-periods faster (T - ) for non-basin sites and slower (T -1.4 ) for basin sites as compared to our previous model. The updated GMPEs are applicable for earthquakes with 5 M 8 (where M is moment magnitude), distances of up to 50 km, and range of shear wave velocities of 50<V S30 <1,00 m/sec. Introduction Ground-motion prediction equations (GMPEs) for peak ground acceleration (PGA) and 5 percent damped pseudo spectral accelerations (SA) of horizontal component ground-motions were developed by Graizer and Kalkan [1, ] using the Next Generation of Attenuation (NGA) relations project database [3] with additional ground-motion data from major California events including the 004 Parkfield (M6.0) and 003 San Simeon (M6.5), and a number of smaller magnitude (5.0 M 5.7) shallow-crustal earthquakes. The important characteristics of these GMPEs are: The number of predictors used in the model was limited to a few measurable parameters (moment magnitude (M), closest distance to fault rupture (R), average S-wave velocity in 1 Geophysicist, U.S. Nuclear Regulatory Commission, Mail Stop: T-7F3, Washington, DC Vladimir.Graizer@nrc.gov Graizer V. Updated Graizer-Kalkan ground-motion prediction equations for Western United States. Proceedings of the 10 th National Conference on Earthquake Engineering, Earthquake Engineering Research Institute, Anchorage, AK, 014.

3 the upper 30 m of the geological profile (V S30 ), style of faulting and if available basin depth defined as depth to the 1.5 km/sec shear-wave velocity isosurface (Z 1.5 )). The predictive model for SA is a continuous function of spectral period (T), which eliminates the standard matrix of estimator coefficients, and allows for calculation of SA at any period of interest within the model range, which is 0.01 to 10 seconds. The functional form of the GMPEs is derived from filters each filter represents a particular physical phenomenon affecting the seismic wave radiation from the source. The filter-based approach in modeling ground motion attenuation is shown to provide accuracy (expected median prediction without significant bias) and efficiency (relatively small standard deviation of predictions) (Graizer and Kalkan [4]). This paper presents updated Graizer-Kalkan GMPE for peak-ground acceleration and 5 percent damped pseudo spectral accelerations of horizontal component ground motions (GMRotI50 as defined in [5]). Graizer-Kalkan GMPEs are improved in two aspects: Anelastic attenuation is modeled as a function of the quality-factor (Q 0 ); The basin response filter is modified to better represent amplified long-period groundmotion due to deep sedimentary basin response. The updated GMPEs use functional forms guided by physical simulations. Reducing the standard deviation by 4 percent on average relative to the original model [1, ] enhances the predictive power of the updated GMPEs. The applicability range is also increased by improving the model for the basin-response effect and the long-distance ground motion attenuation rate associated with regional anelastic attenuation factor Q 0 as compared to the previous versions. The revised GMPEs (henceforth we call it GK13) utilize M, R, V S30, style of faulting F, quality factor Q 0 and Z 1.5 as input parameters. Ground Motion Prediction Modeling The modular filter-based modeling approach, first introduced in [1, ] for PGA attenuation modeling, and later extended in Graizer and others [6] for developing the global PGA prediction model, was re-applied here to develop GK13. In this approach, a GMPE is expressed as a series of filters each filter represents a certain physical phenomenon affecting the radiation of seismic waves from the source. In this representation, filters (denoted as G n in Eq. (1), where n is the filter number) are in multiplication form (cascade of filters). This way simplifies controlling their relative contributions on resultant ground-motion intensity measures. PGA = G 1 G G 3 G 4 G 5 σ Y (1) In Eq. 1, G 1 n is a function of set of independent parameters representing, magnitude, distance, style of faulting (F), shallow site conditions, basin and other parameters affecting the physical process of ground-motion distance attenuation with standard deviation σ Y. Our previous GMPE for PGA was composed of five different filters (see Fig. in [4]). The first filter, G 1 is for magnitude scaling and style of faulting scaling. The G filter models the distance attenuation of ground-motion. The G 3 filter adjusts intermediate distance attenuation rate, and also includes basin-response effects (if basin exists). The G 4 filter models ground-motion amplification due to

4 shallow site conditions, and the G 5 adjusts the rate of attenuation at far distances (R>100 km). The G filter modeling ground motion distance attenuation is similar to the frequency response function of a damped single-degree-of-freedom oscillator. This filter is expressed as: [ ] G (M, R, D ) = 1 1 ( R R ) + 4 D ( R/ R ) () where R is the corner distance in the near-source defining the plateau without significant attenuation of ground-motion. This parameter is directly proportional to earthquake magnitude; the larger M, the wider the plateau defined by R. Data show that R varies from ~4 km for M 5.0 events to ~10 km for M 8.0 events [1]. There is an analogy between R and the corner frequency defined in Brune s model [7, 8] since both are related to the earthquake magnitude. The parameter D is the damping term describing the amplitude of the bump (increase in amplitude of ground motion at certain distance from the fault). Setting D =0.7 results in no bump. The fact that the highest PGA may not be recorded at the closest distance but at some distance from the fault is observed in the 1979 M6.5 Imperial Valley and the 004 M6.0 Parkfield earthquakes [1, 4]. This bump phenomenon was recently demonstrated in modeling amplitudes of ground-motions in eastern North America, and it is attributed to radiation pattern effects combined with wave propagation through a one-dimensional layered earth model (Chapman and Godbee [9]). We speculate that, in the case of recorded earthquakes, it is a result of the radiation pattern aforementioned, directivity, nonlinear behavior of media in the nearsource of an earthquake fault, and measuring distance as the closest distance to the rupture plane and not from the seismogenic (most energetic) part of the fault rupture. In GK13, the G 1 and G filters are identical to those in our previous GMPEs except for one coefficient that determines the amplitude of the bump. Fig. 1 demonstrates the filter representation in GK13. Anelastic Attenuation Model The G 3 filter in our previous GMPEs modeled the ground-motion amplification due to basin effect in a simple way, and also defined the ground-motion distance attenuation rate in the order of R This filter is now replaced with an anelastic attenuation filter, given as: G = exp( c R Q ) (3) where Q 0 is the regional quality-factor for propagation of seismic waves from source to the site at a frequency of 1 Hz, and c 11 is a coefficient. Eq. (3) changes the PGA attenuation rate after it is plugged into Eq. (1). The value for Q 0 varies regionally. It is, on average, 150 for California, and for central and northeast United States [10, 11]. With c 11 = Eq. (3) produces similar effects as our previous GMPEs for distances of up to 00 km; the original G 3 filter produces a constant slope (R -1.5 ) at all large distances. Lower crustal quality-factor (Q 0 = 75) results in faster attenuation, and a higher one (Q 0 = 300) results in slower attenuation (Fig., left panel).

5 Figure 1. Graizer-Kalkan PGA attenuation relation for the free-field horizontal component of ground motion GK13. Trifunac [1] suggested that Q associated with strong-motion is different from seismological measurements cited above since the typical seismological Lg and Coda wave estimates of Q sample different volumes of the crust surrounding the station and different paths than typical propagation paths of strong motion signals. He demonstrated that the strong-motion Q increases from very low values near the fault (Q=0 associated with the upper part of the soil profile with relatively low S-wave velocity) to larger values at about km away from the source associated with typical crustal attenuation [1]. For Parkfield, frequency independent Q increases from 0 in the upper 300 m of the soil profile to higher values of for depth range of 00 m to 5 km (Abercrombie [13]). Our new filter in Eq. (3) allows for Q to be distance dependent (Fig., right panel). However,

6 the effect of variable (distance dependent) Q relative to the constant (distance independent) Q0 is not significant. Based on our tests, we concluded that it is reasonable to use a constant Q0 typical for a given region (usually that for Lg or Coda waves). In our updated model we assume frequency independent Q. We expect that our model can be adjusted to other active tectonic regions similar to California by using Q0 values typical for that region and determined using Lg or Coda waves (e.g., [10-11]). Figure. Modeling anelastic attenuation with constant and variable Q0-factor. Basin-Response Model A basin consists of alluvial deposits and sedimentary rocks that are geologically younger, and have significantly lower shear-wave velocities than underlying rocks creating a strong interface. As shown in a number of publications basin amplifies earthquake generated body and surface waves (e.g., [14-0]). Basin effect is a complicate phenomenon depending upon a number of parameters. Our basin model considers a combined effect of amplification of both shear and surface waves due to basin depth under the site (e.g., [17, 18]). For the sake of simplicity, the basin shape and distance to the basin edge are not accounted for. Mechanisms and results of shear and surface wave amplifications in the basin are different, with basin amplification of Swaves affecting mostly frequencies lower than ~10 Hz (e.g., Hruby and Beresnev [17]), and basin amplification of surface waves affecting spectral frequencies from PGA up to long periods. This effect is clearly demonstrated in the 199 M7.3 Landers, the 1999 M7.1 Hector Mine and the 010 M7. El-Mayor Cucapah earthquakes where PGAs in Los Angeles and San Bernardino basins were associated with surface waves and amplified significantly [19, 0]. Similar to our previous model [], our new spectral acceleration (SA) prediction model for the 5 percent damping explicitly integrates PGA as a scaling factor for the spectral shape (response spectrum normalized by PGA). Unlike all other existing predictive relations for SA, which are discrete functions of period, the proposed SA model is a continuous function of period. In our previous predictive model for SA, spectral shape decayed at long-periods with a slope of T-1.5, averaging basin and non-basin site effects. Fig. 3 demonstrates our new SA predictive model. In this model the improved basin-response filter is used. This filter is a function of three parameters; these are (1) depth to 1.5 km/sec shear-wave velocity isosurface, denoted as Z1.5

7 (same as B depth ) (Day and others [18]); () distance from the earthquake source; and (3) period (T). In the updated SA model, spectral shape decays at long-periods faster (T - ) for non-basin sites and slower (T -1.4 ) for deep basin sites as compared to our previous SA model. Figure 3. PGA-based GK13 prediction model for 5% damped response spectral acceleration ordinates. The improved basin-response filter is: G (, ) 1 ( ) ( ) 5 R Bdepth = + ABdist R ABdepth Bdepth (4) where B depth is the basin depth under the site (same as Z 1.5 ) and R is the source-to-site distance. All distance parameters are in km. In case when site is located in the basin and earthquake source

8 is located under the basin PGA is same as in case of no basin. In this case of basin and source under the site, there is no effect on high frequencies, and amplification affects lower frequencies by lowering the slope of the response spectrum from T - to T When basin is located at large distance from the source, PGA and not only long-periods, are amplified (surface waves exceeds in amplitudes S-waves) (Fig. 4). Figure 4. Dependence of basin effect on basin depth and distance to the fault. As the basin depth increases, the amplification coefficient increases: Bdepth( depth ) = (1.5 ( depth + 0.1)) + 4(0.7) (1.5 ( depth + 0.1)) A B B B (5) where A Bdepth is function describing amplitude of the basin effect depending upon B depth. A Bdepth varies from 0 (no basin) to about (deep basin) and saturating for basins deeper than ~3 km. The basin effect is smaller at short fault distances by amplifying S-waves (it decreases the slope of response spectral decay at long periods), and reaches its maximum at distances more than about 30 km where surface waves appear. At these distances basin amplification affects both shear and surface waves. Its distance dependence is controlled by the following function of R: ABdist ( R) = 1 1 (40 ( R 0.1)) + + 4(0.7) (40 ( R+ 0.1)) (6) Based on a 3-D modeling of ground motion a possible explanation for the distance dependent pattern was suggested by Olsen [1]. According to Olsen amplification factors are greater for events located farther from the basin edge. He suggested that the larger-amplitude surface waves generated for the distant events, in part at basin edges, are more prone to amplification than are the predominant body waves impinging onto the basin sediments from the nearby earthquakes.

9 Eq. (4-6) describe the basin effect on SA. The parameters of these empirical equations were finetuned according to data from Hector Mine, Landers, and Loma Prieta earthquakes. When basin depth is zero, A Bdepth (B depth ) becomes negligibly small and the G 5 filter does not have any effect (G 5 = 1.0). It should be noted that our approach on modeling the basin effect is based on a 3-D numerical simulations of Day et al. [18]. Eq. 5 approximates Eq. 5a (and also Fig. 9 and Table ) of [18]. They found depth to the 1.5 km/s S-wave velocity isosurface to be a suitable predictor variable and recommended their results for use in construction of attenuation relationships taking into account correlation of basin depth with other predictor variables such as V S30. Similar basin amplification was observed in Northridge and Whittier Narrows earthquakes by Hruby and Beresnev [17]. Our dependence of period amplification on Z 1.5 approximates the period dependence in their Table 3. Fig. 5 compares response spectra computed from recordings of major California earthquakes (Imperial Valley, Northridge, Parkfield, Landers, Loma Prieta and Hector Mine) with predicted response spectral ordinates at different fault distances. As evident in these plots, the median predictions match very well with the observations for a wide range of distances and magnitudes. Standard Error The standard deviation of GK13 (σ lny ) increases with period (T). For short periods (from 0.01 s to 0.11 s), σ lny is almost constant. For longer periods (from 0.1 s to 10 s), σ lny may be approximated by a linear relationship as: σ σ InY InY = lnt < T < 0.1 sec = lnt T 10 sec (7) On average, standard deviation (σ lny ) of GK13 is 4% lower than that of our previous GMPEs. For instance, standard deviation for PGA is reduced from 0.55 to In order to investigate whether our predictions are biased against any independent parameters of estimations, residual analyses of PGA, 0., 1 and sec spectral acceleration estimates for the full data set as functions of magnitude, fault distance, and VS30 were performed. With respect to those three independent variables, no significant trends are observed. Summary Graizer-Kalkan western United States GMPEs for PGA and SA are updated to be applicable for earthquakes with 5.0 M 8.0, distances of up to 50 km, and shear wave velocities in the range of 50<V S30 <1,00 m/sec. The predictive model for SA is applicable in the period range of 0.01 to 10 sec. GK13 s predictions are controlled by a number of measurable parameters including M, distance to the fault rupture, style of faulting, V S30, Q 0, and basin depth (Z 1.5 ). The updated Graizer-Kalkan ground-motion prediction models for PGA and SA are available from the author in Fortran, Excel and MatLab format.

10 Figure 5. Example of GK13 model comparisons with spectral accelerations for major California earthquakes at fault distances up to 5 km. Acknowledgments I thank Erol Kalkan for his participation in development of the new model. I wish to thank Stephen Harmsen and Nick Gregor for the independent testing of the GK13 that helped improving our predictive model, and Paul Spudich for his constructive comments and suggestions that helped to improve technical quality and description of the model.

11 Disclaimer Any opinions, findings and conclusions expressed in this paper are those of the author and do not necessarily reflect the views of the U.S. Nuclear Regulatory Commission. References 1. Graizer, V. and Kalkan, E. (007). Ground-motion attenuation model for peak horizontal acceleration from shallow crustal earthquakes, Earthquake Spectra, 3 (3), Graizer, V. and Kalkan, E. (009). Prediction of response spectral acceleration ordinates based on PGA attenuation, Earthquake Spectra, 5 (1), Chiou, B. S.-J., Darragh, R., and Silva, W., 008. An overview of the NGA database, Earthquake Spectra 4, Graizer, V. and Kalkan, E. (011). Modular filter-based approach to ground-motion attenuation modeling, Seism. Res. Lett., 8, No. 1, Boore, D. M., Watson-Lamprey, J. & Abrahamson, N. A. (006). Orientation-independent measures of ground motion. Bull. Seism. Soc. Am., 96 (4A), Graizer, V., E. Kalkan, and K.W. Lin (013). Global ground-motion prediction equation for shallow crustal regions, Earthquake Spectra, 9 (3), Brune, J. (1970). Tectonic stress and the spectra of seismic shear waves from earthquakes. J. Geophys. Res., 75, Brune, J. (1971). Correction. J. Geophys. Res., 76, Chapman, M. C., and Godbee, R. W. (01). Modeling geometrical spreading and the relative amplitudes of vertical and horizontal high-frequency ground-motions in eastern North America. Bull. Seismol. Soc. Am., 10, Mitchell, B. J. & Hwang, H. J. (1987) Effect of low Q sediments and Crustal Q on Lg attenuation in the United States, Bull. Seism. Soc. Am., 77, Erickson, D., D. E. McNamara, and H. M. Benz (004). Frequency-dependent Lg Q within the continental United States. Bull. Seism. Soc. Am., 94, Trifunac, M. D. (1994). Q and high-frequency strong motion spectra. Soil Dynamics and Earthquake Engineering, 13, Abercrombie, R. E. (000). Crustal attenuation and site effects at Parkfield, California. J. Geophys. Res., 105 (B3), Lee, V. W., Trifunac, M. D., Todorovska, M. I. and Novikova, E. I. (1995). Empirical equations describing attenuation of peak of strong ground-motion, in terms of magnitude, distance, path effects and site conditions. Report No. CE Los Angeles, California. 68 p. 15. Campbell, K.W. (1997). Empirical near-source attenuation relations for horizontal and vertical components of peak ground acceleration, peak ground velocity, and pseudo-absolute acceleration response spectra. Seismol. Res. Lett., 68, Frankel, A., Carver, D., Cranswick, E., Bice, T., Sell, R., and Hanson, S. (001). Observation of basin groundmotions from a dense seismic array in San Jose, California. Bull. Seism. Soc. Am., 91, Hruby, C. E., and I. A., Beresnev (003). Empirical corrections for basin effect in stochastic ground-motion prediction, based on the Los Angeles basin analysis. Bull. Seism. Soc. Am., 93, Day, S. M., R. Graves, J. Bielak, D. Dreger, S. Larsen, K. B. Olsen, A. Pitarka, and L. Ramirez-Guzman (008). Model for basin effects on long-period response spectra in Southern California. Earthquake Spectra, 4 (1), Graizer, V., A. Shakal, C. Scrivner, E. Hauksson, J. Polet and L. Jones (00). TriNet strong-motion data from the M 7.1 Hector Mine, California, earthquake of 16 October Bull. Seism. Soc. Am., 9, Hatayama, K. and Kalkan, E. (01). Spatial Amplification of Long-Period (3 to 16 s) Ground Motions in and around the Los Angeles Basin during the 010 M7. El Mayor-Cucapah Earthquake, Proc. of the 15th World Conf. on Earthquake Engineering, Lisbon, Portugal. 1. Olsen, K. B. (000). Site amplification in the Los Angeles basin from three-dimensional modeling of ground motion. Bull. Seism. Soc. Am., 90, 6B, S77-S94.