Side-effect of using response spectral amplification ratios for soft soil sites—Earthquake source-type dependent amplification ratios

Zhao, John X.; Zhang, Jian

doi:10.1016/j.soildyn.2009.12.001

Cited by 19 publications

(10 citation statements)

References 15 publications

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“…A regression analysis was performed to adjust the period-dependent coefficients. Recognizing that the frequency impacts the site amplification (Zhao et al, 2016a; Zhao and Zhang, 2010), separate analyses were performed for the earthquake records corresponding to different tectonic environments (intra-slab and interface) so that the fitted models would correspond to a homogeneous tectonic environment. Figure 9 shows coefficients c k ( T ) of the site response term for the different tectonic environments.…”

Section: Regression Analysismentioning

confidence: 99%

Ground-motion model for subduction earthquakes in northern South America

et al. 2021

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Subduction ground motions in northern South America are about a factor of 2 smaller than the ground motions for similar events in other regions. Nevertheless, historical and recent large-interface and intermediate-depth slab earthquakes of moment magnitudes Mw = 7.8 (Ecuador, 2016) and 7.2 (Colombia, 2012) evidenced the vast potential damage that vulnerable populations close to earthquake epicenters could experience. This article proposes a new empirical ground-motion prediction model for subduction events in northern South America, a regionalization of the global AG2020 ground-motion prediction equations. An updated ground-motion database curated by the Colombian Geological Survey is employed. It comprises recordings from earthquakes associated with the subduction of the Nazca plate gathered by the National Strong Motion Network in Colombia and by the Institute of Geophysics at Escuela Politécnica Nacional in Ecuador. The regional terms of our model are estimated with 539 records from 60 subduction events in Colombia and Ecuador with epicenters in the range of −0.6° to 7.6°N and 75.5° to 79.6°W, with Mw≥4.5, hypocentral depth range of 4 ≤ Zhypo ≤ 210 km, for distances up to 350 km. The model includes forearc and backarc terms to account for larger attenuation at backarc sites for slab events and site categorization based on natural period. The proposed model corrects the median AG2020 global model to better account for the larger attenuation of local ground motions and includes a partially non-ergodic variance model.

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Section: Regression Analysismentioning

confidence: 99%

Ground-motion model for subduction earthquakes in northern South America

et al. 2021

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“…Other reference approaches, that is surface-to-borehole spectral ratio (SBSR) or standard spectral ratio (SSR), need multiple events simultaneously recorded at both collocated surface-downhole pairs for the former, and at the ground surface and nearby outcrop rock sites for the latter. Zhao et al (2009) and Zhao & Zhang (2010) utilized numerical simulations to investigate the dependence of siteresponse variability on earthquake scenarios.…”

Section: Earthquake Variability In Site Response 1269mentioning

confidence: 99%

Within-site variability in earthquake site response

Zhu

Cotton

Kwak

et al. 2021

Geophysical Journal International

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Summary The within-site variability in site response is the randomness in site response at a given site from different earthquakes and is treated as aleatory variability in current seismic hazard/risk analyses. In this study, we investigate the single-station variability in linear site response at K-NET and KiK-net stations in Japan using a large number of earthquake recordings. We found that the standard deviation of the horizontal-to-vertical Fourier spectral ratio at individual sites, i.e. single-station HVSR sigma σHV,s, approximates the within-site variability in site response quantified using surface-to-borehole spectral ratios (SBSR, for oscillator frequencies higher than the site fundamental frequency) or empirical ground-motion models (GMMs). Based on this finding, we then utilize the single-station HVSR sigma as a convenient tool to study the site-response variability at 697 KiK-net and 1169 K-NET sites. Our results show that at certain frequencies, stiff, rough and shallow sites, as well as small and local events tend to have a higher σHV,s. However, when being averaged over different sites, the single-station HVSR sigma, i.e. σHV, increases gradually with decreasing frequency. In the frequency range of 0.25–25 Hz, σHV is centred at 0.23–0.43 in ln scales (a linear scale factor of 1.26–1.54) with one standard deviation of less than 0.1. σHV is quite stable across different tectonic regions, and we present a constant, as well as earthquake magnitude- and distance-dependent σHV models.

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“…As for all empirical models, the interaction among the estimates for various parameters is moderately strong, and we were able to use the same α and β values for all site classes without compromising the model goodness-of-fit parameter. Zhao et al (2009) and Zhao and Zhang (2010) found that the numerically simulated amplification ratios of response spectra between soil and rock records depend on magnitude and source distance. We also find the same effects for the amplification ratios in the present study.…”

Section: Model Selection For Response Spectral Amplification Ratiosmentioning

confidence: 99%

“…The second reason for not using it is the usually large variability of a GMPE that can bury the effect of the impedance ratio. Another arguable feature of the simulated amplification ratios is that response spectral amplification ratios depend on the earthquake magnitude and source distance of the rock-site records Zhao and Zhang, 2010). The physical reason for this feature is the frequency content of the rock-site records (Safak, 1997).…”

Section: Introductionmentioning

confidence: 96%

“…Figure 8a shows the within-site standard deviations, and Figure 8b shows the between-site standard deviations for four site classes. The within-site standard deviation contains the variability from the frequency content of the rock-site records (Safak, 1997), which is a function of earthquake magnitude and source distance Zhao and Zhang, 2010). For SC I, II, and III sites, the within-site standard deviation varies between 0.15 and 0.25 in a natural logarithm scale, and the standard deviations for SC IV sites are much larger than those for the other site classes.…”

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confidence: 99%

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Nonlinear Site Models Derived from 1D Analyses for Ground‐Motion Prediction Equations Using Site Class as the Site Parameter

Zhao¹,

Jun-sheng²,

Jiang³

et al. 2015

Bulletin of the Seismological Society of America

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Nonlinear site models are an important part of ground-motion prediction equations (GMPEs) and can be constructed in a number of ways. If numerous soil-site strong-motion records contain the effect of strong nonlinear soil response, the parameters for the nonlinear model can be a part of the regression parameters for GMPEs. It is also possible to derive nonlinear site models by numerical simulation. However, the number of strong-motion records from Japan that contain the effect of strong nonlinear soil response is still too small to derive nonlinear site terms. We present a model of nonlinear site terms using site class as the site parameter in GMPEs based on a 1D equivalent linear model. The 1D model was constructed based on the shear-wave velocity profiles from the KiK-net strong-motion stations with a wide range of site periods, soil depth, and impedance ratios. The rock-site strong-motion records were from different earthquake categories in Japan and the Pacific Earthquake Engineering Research Center dataset. Those records had a wide range of earthquake magnitudes, source distances, and peak ground accelerations. A random effects regression model was fitted to the calculated spectral amplification ratios, accounting for the effect of site impedance ratios, earthquake magnitudes, and source distances of the rock-site records. We also designed a method to adjust the 1D model so it can be used in a GMPE, accounting for the fact that a 1D model is an overly simplistic assumption for many real strong-motion recording stations in many parts of the world.Online Material: Tables of nonlinear site model parameters.

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Side-effect of using response spectral amplification ratios for soft soil sites—Earthquake source-type dependent amplification ratios

Cited by 19 publications

References 15 publications

Ground-motion model for subduction earthquakes in northern South America

Ground-motion model for subduction earthquakes in northern South America

Within-site variability in earthquake site response

Nonlinear Site Models Derived from 1D Analyses for Ground‐Motion Prediction Equations Using Site Class as the Site Parameter

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