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tance” (R rup ) defined as the closest distance to co-seismic ruptureplane.The next set of plots in Figures 2–5 (row B) shows thedistance distribution of residuals. Linear fit lines illustrate thedistance bias; the trend line passing through zero means thatthere is no bias in predictions. Unlike the attenuation curvesshown in row A, based on average V S30 , the residuals are computedbased on specific V S30 values at each station estimatedfrom topographic slope (Figure 1) in order to explicitly incorporatethe site effects on ground motion estimates. To quantifythe quality of fit, the standard errors of predictions (σ InY ) arecomputed based on residuals, and these values are given in eachpanel for each GMPE. The larger σ InY indicates a poorer performanceof the GMPE. For PGA, all GMPEs indicate an overallgood fit to observations up to ~100 km (Figure 2 row A); fordistances larger than 100 km, ground motion exhibits fasterattenuation, and as a result the observed peak values are lowerthan expected. This is more pronounced for the Christchurchevent. Low ground accelerations recorded at large distancesshow the effect of the anelastic attenuation due to regional lowQ (Zhao and Gerstenberger 2010).In Figure 2 (row B), residuals for the Darfield eventreveal overestimation for distances greater than 70 km for theAB08 and 100 km for the BA08 and CB08 models. On theother hand, the GK07 and CY08 fit better to the observationsbecause their trend lines fitting to residuals do not showa notable distance bias. For the AS08 and CB08, the misfit atlarger distances is more evident. In case of PGA, the GK07,BA08, and CY08 models yield the smallest σ InY of 0.52 forthe Darfield event. For the Christchurch event (Figure 2 bottompanels), the GK07, AS08, BA08, and CY08 present betterresidual fits than CB08, for which the overestimation beginsat 20 km. The smallest σ InY is due to the CY08. The same istrue for spectral acceleration at 0.3 s as shown in Figure 3 (rowB). Finally, Figure 2 (row C) shows the distance distribution ofLLH values. In these plots, trend lines identify the consistencyof the GMPE in predicting ground motion at various distances;if the slope is close to zero, then GMPE has low distance variability,meaning that it is consistent. Much higher LLH valueswith increasing distance suggest a poorer fit at far-field, whichis observed for all GMPEs for the Christchurch event.As shown in Figure 3, spectral acceleration at 0.3 s reaches1 g at 40 km for the Darfield earthquake, and 2 g at 10 kmfor the Christchurch earthquake. For the Darfield event, theAS08 and CB08 overestimate observations for distances largerthan 70 km as shown by the residual plots. The same trend isevident for the Christchurch event (Figure 3 bottom panels).The BA08 performs better for the Darfield event since there isonly a minor overestimation for distances larger than 20 km.For the Christchurch event (Figure 3 bottom panels), however,the distance trend line of LLH reveals a poorer performance ofthe BA08 and CB08.Ground motion estimates are given for spectral accelerationat 1 s in Figure 4, where the observations exceed 1 g in thenear field of both earthquakes. For Darfield, all GMPEs presentan excellent fit to the observations up to 70 km from the fault.Beyond 70 km, they slightly overestimate the observations dueto faster attenuation of ground motion at far distances. For theChristchurch event, the overestimation is evident for the BA08and CB08 over 50 km, which resulted in higher LLH values.In Figure 5 (top panels), comparisons are given for thespectral acceleration at 3 s. For both Darfield and Christchurchevents, spectral peaks reach 0.5 g. For the former event, the GK07is the best fitting model to observations with zero distance biasand with lowest LLH values. The NGA models underestimatelong period ground motions up to 100 km, whereas beyond 100km they tend to overestimate. For the Christchurch earthquake,none of the models provide an excellent fit (Figure 5 bottom panels).The GK07 overestimates observations, as opposed to underestimationof NGA models over a wide distance range.RANKING GROUND MOTION PREDICTIONEQUATIONSIn Table 1, the mean (μ LLH ) and standard deviation (σ LLH )of LLH values over the total number of observations for eachearthquake and for each GMPE are tabulated; the standarderrors (σ InY ) of predictions are also listed. This table is used forranking the GMPEs according to these three parameters. Forranking, each parameter is first normalized with the respect toits lowest value due to different GMPEs, and then the arithmetic-meanof normalized values is computed for μ LLH , σ LLH , andσ InY for each GMPE. The GMPE with the lowest arithmeticmeanis ranked as first. This exercise is repeated for each periodand for each earthquake, and the results of ranking are given inTable 2. The best performing GMPE has a combined performancevalue close to unity. The ranking results show that performanceof the GK07, BA08, and CY08 are equally the samefor different periods and events, while the CB08 and AS08show relatively poorer performance.CONCLUDING REMARKSIn this study, we examined the performance of global groundmotion prediction equations (GMPEs) for the New Zealand M7.1 Darfield and M 6.2Christchurch earthquakes, with the objective of improvingfuture seismic hazard assessment and engineering applicationsfor the Canterbury region. These events are characterized bysignificantly large ground motions at high frequencies, whichshowed faster attenuation through the crust due to low regionalQ. Amplified spectral accelerations at long periods at long distancesare attributed to Canterbury’s deep sedimentary basin.For similar shallow earthquakes in New Zealand, there is anevidence of Moho reflection, which potentially might furtheramplify long-period ground motions (Zhao and Gerstenberger2010). Comparison of predictions derived from the five differentGMPEs with observations reveal overall good performanceof these models, supporting their applicability for the region.For the purpose of selecting and weighting GMPEs in a logictree approach for regional seismic hazard analysis, we applieda simple ranking procedure based on the average LLH values872 Seismological Research Letters Volume 82, Number 6 November/December 2011
TABLE 1Mean (μ LLH ) and standard deviation (σ LLH ) of average log-likelihood (LLH) values, and standard error of predictions (σ InY ).GK07: Graizer and Kalkan (2007, 2009); AS08: Abrahamson and Silva (2008); BA08: Boore and Atkinson (2008); CB08:Campbell and Bozorgnia (2008); CY08: Chiou and Youngs (2008).μ LLH σ LLH σ InYGK07 AS08 BA08 CB08 CY08 GK07 AS08 BA08 CB08 CY08 GK07 AS08 BA08 CB08 CY08M 7.1 DarfieldPGA 0.77 0.84 0.80 0.96 0.73 0.80 0.96 0.74 1.13 0.90 0.52 0.58 0.52 0.63 0.52SA (0.3s) 0.91 1.04 0.95 1.10 0.94 0.86 0.99 0.85 1.12 1.00 0.59 0.69 0.63 0.71 0.63SA (1 s) 0.93 0.93 0.90 0.91 0.95 0.52 0.52 0.46 0.53 0.58 0.61 0.62 0.60 0.60 0.60SA (3 s) 1.02 1.06 1.09 1.11 1.23 0.45 0.65 0.63 0.76 0.80 0.65 0.69 0.71 0.68 0.69M 6.2 ChristchurchPGA 0.98 0.91 1.12 0.92 1.41 1.12 0.93 1.42 2.82 0.94 0.61 0.63 0.77 0.53 0.61SA (0.3s) 1.01 1.04 1.02 0.99 1.69 1.03 1.00 1.70 2.29 0.99 0.68 0.72 0.80 0.62 0.68SA (1 s) 1.00 1.11 0.67 0.89 1.12 0.68 0.89 1.13 1.29 0.79 0.71 0.73 0.73 0.64 0.71SA (3 s) 1.17 0.98 0.63 0.67 0.82 0.63 0.68 0.83 0.78 0.59 0.65 0.75 0.67 0.61 0.65TABLE 2Combined performance parameters of ground motion prediction equations (GMPEs; GMPE with the lowest performanceparameter can be interpreted as better performing one (shown by bold).Combined Performance ParameterGK07 AS08 BA08 CB08 CY08M 7.1 DarfieldPGA 1.05 1.19 1.04 1.35 1.07SA (0.3s) 1.00 1.16 1.04 1.24 1.09SA (1 s) 1.07 1.07 1.00 1.06 1.11SA (3 s) 1.00 1.18 1.19 1.28 1.35M 6.2 ChristchurchPGA 1.17 1.08 1.37 2.36 1.00SA (0.3s) 1.04 1.07 1.46 1.85 1.00SA (1 s) 1.01 1.21 1.39 1.49 1.08SA (3 s) 1.09 1.10 1.30 1.18 1.02considering their mean and standard deviation, as well as standarderrors (σ InY ) of predictions. The ranking results show thatperformance of GK07 (Graizer and Kalkan 2007, 2009), BA08(Boore and Atkinson 2008), and CY08 (Chiou and Youngs2008) perform equally well, while the CB08 (Campbell andBozorgnia 2008) and AS08 (Abrahamson and Silva 2008)show relatively poorer performance.ACKNOWLEDGMENTSThe authors thank Jim Cousins (GNZ) for providing parametersof strong motion recordings, and Volkan Sevilgen for preparingthe V S30 map for the Canterbury region. We also wishto thank David Boore, Tom Hanks, and Vladimir Graizer fortheir reviews.DATA AND RESOURCESFor NGA models, we used the Fortran code written by DavidBoore (Kaklamanos et al. 2010); for the Graizer and Kalkan(2007, 2009) ground motion prediction model, Matlab andFortran codes are available online at http://nsmp.wr.usgs.gov/ekalkan/PGA07/index.html. The flat-file for both Darfield andChristchurch events is also available online at http://nsmp.wr.usgs.gov/ekalkan/NZ/index.html.Seismological Research Letters Volume 82, Number 6 November/December 2011 873
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Volume 82, Number 6 November/Decemb
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News and Notes (continued)Nominatio
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Preface to the Focused Issue on the
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TABLE 1Peak ground acceleration (PG
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▲▲Figure 2. A) Sketch of the
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▲▲Figure 4. A) Adopted moment r
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▲▲Figure 7. As in Figure 6 but
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▲ ▲ Figure 8. Misfit parameters
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▲ ▲ Figure 10. Spatial variabil
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▲ ▲ Figure 12. Standard spectra
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Quigley, M., R. Van Dissen, P. Vill
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slip on a 59-degree striking fault
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▲▲Figure 4. Convergence of inve
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observations and other source studi
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-42. 5-43. 0-43. 5-44. 0-44. 5-43.2
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“Product CSK © ASI, (ItalianSpac
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TABLE 2Solutions for fault location
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-43.45(A)degrees N-43.50-43.552.52.
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is still a good fit to the horizont
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Coulomb Stress Change Sensitivity d
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mation takes on a larger strike-sli
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P 9.4267BLDU45P 20.1213CASY39P 2.62
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ERMJNUMAJOINUJHJ2CBIJMIDWJOWYHNBTPU
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(A)6.146.13(B)6.246.36Misfit6.156.1
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(A)(B)(C)(D)▲▲Figure 10. The co
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(A)(B)(C)(D)▲▲Figure 12. The co
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Luo, Y., Y. Tan, S. Wei, D. Helmber
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−44˚00' −43˚00'4-Sep-2010Mw 7
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TABLE 1Pairs of SAR imagery used in
Page 67 and 68: Depth (km)Coulomb Stress Change(bar
Page 69 and 70: Crippen, R. E. (1992). Measurement
Page 71 and 72: AlpineFaultHope Fault38 mm/yr0+ +-1
Page 73 and 74: σ 1dσ 3Nuσ 3CM w 7.1dw 6.2u70°M
Page 75 and 76: Right-lateral Faults(A) Range Front
Page 77 and 78: DISCUSSIONThe 2010-2011 Canterbury
Page 79 and 80: Large Apparent Stresses from the Ca
Page 81 and 82: ▲ ▲ Figure 2. Observed vs. pred
Page 83 and 84: 10Obs SA(1s)AS1AS+SDAB 2006AB+SDSA(
Page 85 and 86: Fine-scale Relocation of Aftershock
Page 87 and 88: −43.25°OXZ0 10 20km−43.5°−4
Page 89 and 90: A’0 km 4 8−43.5°B’B−43.6°
Page 91 and 92: REFERENCESAvery, H. R., J. B. Berri
Page 93 and 94: ▲ ▲ Figure 2. A) shows three-co
Page 95 and 96: ▲ ▲ Figure 4. Vertical accelera
Page 97 and 98: 0.8PRPC Z0.40Normalized (Max PGA +
Page 99 and 100: Near-source Strong Ground MotionsOb
Page 101 and 102: (A)Magnitude, M w876542009 NZdataba
Page 103 and 104: Scale0.5 g5 seconds▲▲Figure 4.
Page 105 and 106: (A)(B)Spectral Acc, Sa (g)North/Wes
Page 107 and 108: Vertical-to-horizontal PGA ratio543
Page 109 and 110: (A)(B)Station:CCCCSolid:AvgHorizDas
Page 111 and 112: REFERENCESAagaard, B. T., J. F. Hal
Page 113 and 114: ▲ ▲ Figure 1. Shear-wave veloci
Page 115 and 116: Spectral Acceleration (0.3 s), (g)I
Page 117: Spectral Acceleration (3 s), (g)In[
Page 121 and 122: Strong Ground Motions and Damage Co
Page 123 and 124: ings and the Modified Takeda-Slip M
Page 125 and 126: high, but there were no buildings d
Page 127 and 128: REFERENCES▲▲Figure 8. Heavily d
Page 129 and 130: (A)(B)(C)(D)(E)▲▲Figure 1. A) M
Page 131 and 132: (A) (B) (C)▲ ▲ Figure 3. A) Typ
Page 133 and 134: (A) (B) (C)▲ ▲ Figure 4. A) Typ
Page 135 and 136: Case StudyKey ParametersTABLE 1Key
Page 137 and 138: ▲ ▲ Figure 9. Representative bu
Page 139 and 140: Soil Liquefaction Effects in the Ce
Page 141 and 142: ▲ ▲ Figure 2. Representative su
Page 143 and 144: Location of structures illustrated
Page 145 and 146: Shading indicates areaover which pr
Page 147 and 148: 1.8 deg15 cmGround cracking due to
Page 149 and 150: 30 cm17 cm30 cmFoundation beam▲
Page 151 and 152: Comparison of Liquefaction Features
Page 153 and 154: (A)(B)▲▲Figure 2. A) Simplified
Page 155 and 156: (A)Acceleration (Gal)6004002000-200
Page 157 and 158: (A)(B)▲▲Figure 7. Distribution
Page 159 and 160: (A)(B)▲▲Figure 10. Damage to a
Page 161 and 162: (A)(B)▲ ▲ Figure 14. A) Subside
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Page 165 and 166: Ambient Noise Measurements followin
Page 167 and 168: ▲▲Figure 1. Location of the noi
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▲▲Figure 5. Site N20 showing HV
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▲▲Figure 8. Comparison between
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Use of DCP and SASW Tests to Evalua
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▲ ▲ Figure 2. Aerial image of C
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(A)(B)▲▲Figure 4. DCP test bein
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▲▲Figure 7. SASW setup at a sit
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where X ~ N(μ X , σ X 2 ) is shor
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Using the same critical layers as s
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Performance of Levees (Stopbanks) d
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▲▲Figure 3. Typical geometry an
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TABLE 1Damage severity categories (
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(A)(B)▲▲Figure 6. A) Large sand
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(A)(B)▲▲Figure 8. A) Representa
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each of the Waimakariri River and a
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▲ ▲ Figure 2. Horizontal peak g
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only minor damage, mostly to their
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(A)(C)(B)▲▲Figure 5. Ferrymead
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(A)(B)▲▲Figure 7. Damage to sou
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(A)(B)▲▲Figure 11. Settlement o
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(A)(C)(B)▲▲Figure 14. Railway B
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Events Reconnaissance (GEER) Associ
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New PublicationsCanGeoRefThe Americ
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Wednesday, 18 AprilTechnical Sessio
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Verification of a Spectral-Element
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EASTERN SECTIONRESEARCH LETTERSReas
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(A)70°N100°W 60°W70°N(B)100°E1
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Mongolia SCRThe presence or absence
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the small horizontal relative motio
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80°100°120°140°EXPLANATIONBorde
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Chang, K. H. (1997). Korean peninsu
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Wheeler, R. L. (2008). Paleoseismic
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A significant outcome of this study
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TABLE 1 (continued)Earthquakes for
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▲▲Figure 2. Earthquakes used in
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Meeting CalendarM E E T I N GC A L
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201 Plaza Professional Bldg. • El
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Seismological Research Letters (SRL
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Christa von Hillebrandt-Andrade, Pr
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