Model of Strong Ground Motions from Earthquakes in Central and Eastern North America: Best Estimates and Uncertainties

Toro, Gabriel R.; Abrahamson, Norman A.; Schneider, John F.

doi:10.1785/gssrl.68.1.41

Cited by 519 publications

(334 citation statements)

References 8 publications

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“…Various aspects of PSHA have been discussed by a number of authors, including the distinction between aleatory and epistemic uncertainty (Toro et al, 1997;Anderson and Brune, 1999;Anderson et al, 2000), use of synthetic earthquake catalogs (Ward, 1991(Ward, , 1996(Ward, , 2000, Monte Carlo methods (Savage, 1991(Savage, , 1992Cramer et al, 1996;Ebel and Kafka, 1999), and logic trees (Coppersmith and Youngs, 1986), application to fault rupture hazards (Youngs et al, 2003), and deaggregation of probabilistic results (Harmsen and Frankel, 2001). …”

Section: Probabilistic Tsunami Hazard Analysis (Ptha)mentioning

confidence: 99%

“…As discussed in Geist (2005), it is convenient to classify uncertainties associated with PTHA calculations according to the generation, propagation, and runup processes and whether the uncertainties are epistemic or aleatory (Senior Seismic Hazard Analysis Committee, SSHAC, 1997;Toro et al, 1997;Anderson and Brune, 1999). In practice, most of the uncertainties associated with PTHA are epistemic in that collection of additional data decreases the level of uncertainty (e.g., higher resolution bathymetry improves the accuracy of numerical propagation computations, Matsuyama et al, 1999).…”

Section: Uncertaintiesmentioning

confidence: 99%

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Probabilistic Analysis of Tsunami Hazards*

2006

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Abstract. Determining the likelihood of a disaster is a key component of any comprehensive hazard assessment. This is particularly true for tsunamis, even though most tsunami hazard assessments have in the past relied on scenario or deterministic type models. We discuss probabilistic tsunami hazard analysis (PTHA) from the standpoint of integrating computational methods with empirical analysis of past tsunami runup. PTHA is derived from probabilistic seismic hazard analysis (PSHA), with the main difference being that PTHA must account for far-field sources. The computational methods rely on numerical tsunami propagation models rather than empirical attenuation relationships as in PSHA in determining ground motions. Because a number of source parameters affect local tsunami runup height, PTHA can become complex and computationally intensive. Empirical analysis can function in one of two ways, depending on the length and completeness of the tsunami catalog. For sitespecific studies where there is sufficient tsunami runup data available, hazard curves can primarily be derived from empirical analysis, with computational methods used to highlight deficiencies in the tsunami catalog. For region-wide analyses and sites where there are little to no tsunami data, a computationally based method such as Monte Carlo simulation is the primary method to establish tsunami hazards. Two case studies that describe how computational and empirical methods can be integrated are presented for Acapulco, Mexico (site-specific) and the U.S. Pacific Northwest coastline (region-wide analysis).

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Section: Probabilistic Tsunami Hazard Analysis (Ptha)mentioning

confidence: 99%

Section: Uncertaintiesmentioning

confidence: 99%

Probabilistic Analysis of Tsunami Hazards*

2006

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“…It has been shown that the use of a Brune point-source spectrum, in conjunction with a stochastic ground-motion model, successfully predicts high-frequency (f Ն 2 Hz) ground-motion amplitudes for earthquakes in California (Hanks and McGuire, 1981;Boore, 1983) and eastern North America (Atkinson, 1984;Boore and Atkinson, 1987;Toro et al, 1997). The underlying spectrum of ground acceleration for this model has a simple x 2 shape, meaning that the spectral amplitudes decay as x ‫2מ‬ for frequencies below the corner frequency, where the corner frequency is a function of earthquake size.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Modeling of California Ground Motions

Atkinson¹

2000

Bulletin of the Seismological Society of America

372

288

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Ground-motion relations are developed for California using a stochastic simulation method that exploits the equivalence between finite-fault models and a two-corner point-source model of the earthquake spectrum. First, stochastic simulations are generated for finite-fault ruptures, in order to define the average shape and amplitude level of the radiated spectrum at near-source distances as a function of earthquake size. The length and width of the fault plane are defined based on the moment magnitude of the earthquake and modeled with an array of subfaults. The radiation from each subfault is modeled as a Brune point source using the stochastic model approach; the subfault spectrum has a single-corner frequency. An earthquake rupture initiates at a randomly chosen subfault (hypocenter), and propagates in all directions along the fault plane. A subfault is triggered when rupture propagation reaches its center. Simulations are generated for an observation point by summing the subfault time series, appropriately lagged in time. Fourier spectra are computed for records simulated at many azimuths, placed at equidistant observation points around the fault. The mean Fourier spectrum for each magnitude, at a reference nearsource distance, is used to define the shape and amplitude levels of an equivalent point-source spectrum that mimics the salient finite-fault effects. The functional form for the equivalent point-source spectrum contains two corner frequencies.Stochastic point-source simulations, using the derived two-corner source spectrum, are then performed to predict peak-ground-motion parameters and response spectra for a wide range of magnitudes and distances, for generic California sites. The stochastic ground-motion relations, given in the Appendix for rock and soil sites, are in good agreement with the empirical strong-motion database for California; the average ratio of observed to simulated amplitudes is near unity over all frequencies from 0.2 to 12 Hz. The stochastic relations agree well with empirical regression equations (e.g., Abrahamson and Silva, 1997;Sadigh et al., 1997) in the magnitude-distance ranges well represented by the data, but are better constrained at large distances, due to the use of attenuation parameters based on regional seismographic data. The stochastic ground-motion relations provide a sound basis for estimation of ground motions for earthquakes of magnitude 4 through 8, at distances from 1 to 200 km.

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“…For Japan, the absolute level is log 10 A HF (M w = 7) = 26.22 after Irikura and Miyake (2011). However, many authors (Toro et al, 1997;Beresnev and Atkinson, 2002;Halldorsson and Papageorgiou, 2005) identified scaling behaviour of AHF that violates similarity. All of them found slower increase of A HF vs. M 0 as compared to (4).…”

Section: G83 Key Featuresmentioning

confidence: 99%

Broadband NDSHA computations and earthquake ground motion observations for the Italian territory

Magrin¹,

Gusev²,

Romanelli³

et al. 2016

IJEIE

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Abstract:The aim of this work is two-fold: 1) to compare the results of national scale NDSHA modelling for the Italian region at 10 Hz cut-off, based on the relevant available knowledge, with observations (e.g., peak ground motion values) and existing empirical attenuation relations; 2) to update the scaling law for source spectra (SLSS) to be used for the selected area. The new set of source spectra, defined along the lines suggested by the comparison with empirical attenuation relations, produces acceptable results in terms of PGV and spectral acceleration at long periods. Synthetic PGA and SA at short periods show a faster attenuation with respect to the observed ones and, therefore, the effect of complex attenuation factors should be explored in future ad hoc studies.

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Model of Strong Ground Motions from Earthquakes in Central and Eastern North America: Best Estimates and Uncertainties

Cited by 519 publications

References 8 publications

Probabilistic Analysis of Tsunami Hazards*

Probabilistic Analysis of Tsunami Hazards*

Stochastic Modeling of California Ground Motions

Broadband NDSHA computations and earthquake ground motion observations for the Italian territory

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