Development Of Ground-motion Prediction Equations Research Articles

Strong ground-motion prediction equations from induced earthquakes in St. Gallen geothermal field, Switzerland

Abstract Ground shaking, whether it is due to natural or induced earthquakes, has always been a matter of concern since it correlates with structural/non-structural damage and can culminate in human anxiety. Industrial activities such as water injection, gas sequestration and waste fluid disposals, promote induced seismicity and consequent ground shaking that can hinder ongoing activities. Therefore, keeping in mind the importance of timely evaluation of a seismic hazard and its mitigation for societal benefits, the present study proposes specifically designed ground-motion prediction equations (GMPEs) from induced earthquakes in the St. Gallen geothermal area, Switzerland. The data analysed in this study consist of 343 earthquakes with magnitude −1.17 ≤ ML, corr ≤ 3.5 and hypocentral distance between 4 and 15 km. The proposed study is one of the first to incorporate ground motions from negative magnitude earthquakes for the development of GMPEs. The GMPEs are inferred with a two-phase approach. In the first phase, a reference model is obtained by considering the effect of source and medium properties on the ground motion. In the second phase the final model is obtained by including a site/station effect. The comparison between the GMPEs obtained in the present study with GMPEs developed for the other induced seismicity environments highlights a mismatch that is ascribed to differences in regional seismic environment and local site conditions of the respective regions. This suggests that, when dealing with induced earthquakes, GMPEs specific for the study should be inferred and used for both monitoring purposes and seismic hazard analyses.

Processed ground-motion records from induced earthquakes for use in engineering applications

We compile and process an electronic database of ground motions recorded on accelerometers and broadband seismographic instruments for induced earthquakes of M ≥ 4 at distances <50 km in central and eastern North America. Most of the data are from Oklahoma, with some records from Alberta. Our focus is on the subset of available records that are of most interest for engineering analyses aimed at evaluation of the potential hazards from induced events, which is a pressing issue in western Canada and other regions experiencing induced seismicity. We considered all records to 50 km for events of M ≥ 4.5. For events of M 4 to 4.5, we select records at close distance (<10 km), having good signal strength (PGA > ∼3%g), to allow high-quality time histories to be obtained. These records have strong signal-to-noise ratio, making them suitable for engineering applications, such as dynamic analysis, after proper scaling. The selected records are windowed, filtered, and instrument-corrected to compile a set of records having acceptable acceleration, velocity, and displacement time histories. The records and their response spectra are provided as an electronic supplement at http://www.seismotoolbox.ca/IS_Strong_Motions/ . We note that the record set is not suitable as a response spectra database for development of ground-motion prediction equations, because for M < 4.5 the record selection is biased to records with higher amplitudes. Rather, the intended use of the records is as seed records, which can be readily scaled in the time domain to approximately represent induced-event target scenarios for engineering applications.

Selection of Ground Motion Prediction Equations for Seismic Hazard Analysis of Peninsular India

Seismic hazard analysis provides an estimation of seismic hazard parameters like peak ground acceleration (PGA) or spectral acceleration (SA) for different periods. The extent of ground shaking and the hazard values at a particular region are estimated using ground-motion prediction equations (GMPEs)/attenuation equations. There are several GMPEs applicable for the region to estimate the PGA and SA values. These equations may result in higher or lower PGA and SA values than the region specific reported values, which are based on the parameters involved in the development of GMPEs. In this study, an attempt has been made to identify the best GMPEs for various parts of Peninsular India (PI) by performing an “efficacy test,” which make use of the average log likelihood value (LLH). Various intraplate earthquakes such as Coimbatore earthquake, Satpura earthquake, Anjar earthquake, Koyna earthquake, Bhadrachalam earthquake, Broach earthquake, Shimoga earthquake, Killari earthquake, Jabalpur earthquake, Pala earthquake, Kottayam earthquake, and Bhuj earthquake have been considered for the same. Macroseismic intensity maps of these earthquakes have been digitalized and European Macroseismic Scale (EMS) values at the surface have been synthesized. PGA value determined from each GMPE for known magnitude and hypocentral distances are then converted to EMS values. These calculated EMS values have been used to estimate LLH values which are further used to compute Data Support Index (DSI), rank and weights corresponding to a particular GMPE. Conventionally, LLH values are estimated for the entire distance range and GMPEs are ranked accordingly, but in this study, the LLH is calculated for the distance segments of 0-200 km and 200 km to maximum damaged distance in the region based on Isoseismal maps. If the maximum damaged distance is less than 200 km, a distance segment up to 200 km is adopted. Comparison between the rankings of the GMPEs in segments 0–200 km and 200–maximum damage distance is presented here. Segment-based GMPEs ranking shows different ranks, DSI and weights for each GMPE as compared to ranking considering entire distance. Finally, this study provides a list of GMPEs that perform best for the estimation of ground motion parameters in different parts of PI. This study shows that the GMPEs of HAHO-97, ATK-08, CAM-06, TOR-02, NDMA-10, and PEZA-11 perform better for the estimation of ground motion in most part of PI in the distance segment 0–200 km. The GMPEs of TOR-02, RAIY-07, and RAIY-07 (PI) perform best in the 200-maximum damage distance segment.

Fourier spectral- and duration models for the generation of response spectra adjustable to different source-, propagation-, and site conditions

One of the major challenges related with the current practice in seismic hazard studies is the adjustment of empirical ground motion prediction equations (GMPEs) to different seismological environments. We believe that the key to accommodating differences in regional seismological attributes of a ground motion model lies in the Fourier spectrum. In the present study, we attempt to explore a new approach for the development of response spectral GMPEs, which is fully consistent with linear system theory when it comes to adjustment issues. This approach consists of developing empirical prediction equations for Fourier spectra and for a particular duration estimate of ground motion which is tuned to optimize the fit between response spectra obtained through the random vibration theory framework and the classical way. The presented analysis for the development of GMPEs is performed on the recently compiled reference database for seismic ground motion in Europe (RESORCE-2012). Although, the main motivation for the presented approach is the adjustability and the use of the corresponding model to generate data driven host-to-target conversions, even as a standalone response spectral model it compares reasonably well with the GMPEs of Ambraseys et al. (Bull Earthq Eng 3:1–53, 2005), Akkar and Bommer (Seismol Res Lett 81(2):195–206, 2010) and Akkar and Cagnan (Bull Seismol Soc Am 100(6):2978–2995, 2010).

A Method for Including Path Effects in Ground-Motion Prediction Equations: An Example Using the Mw 9.0 Tohoku Earthquake Aftershocks

Research Article| May 01, 2013 A Method for Including Path Effects in Ground‐Motion Prediction Equations: An Example Using the Mw 9.0 Tohoku Earthquake Aftershocks Haitham M. Dawood; Haitham M. Dawood The Charles Edward Via, , Jr. Department of Civil and Environmental Engineering, Virginia Tech, 200 Patton Hall, Blacksburg, Virginia 24061hdawood@vt.edu Search for other works by this author on: GSW Google Scholar Adrian Rodriguez‐Marek Adrian Rodriguez‐Marek The Charles Edward Via, , Jr. Department of Civil and Environmental Engineering, Virginia Tech, 200 Patton Hall, Blacksburg, Virginia 24061hdawood@vt.edu Search for other works by this author on: GSW Google Scholar Bulletin of the Seismological Society of America (2013) 103 (2B): 1360–1372. https://doi.org/10.1785/0120120125 Article history first online: 14 Jul 2017 Cite View This Citation Add to Citation Manager Share Icon Share MailTo Twitter LinkedIn Tools Icon Tools Get Permissions Search Site Citation Haitham M. Dawood, Adrian Rodriguez‐Marek; A Method for Including Path Effects in Ground‐Motion Prediction Equations: An Example Using the Mw 9.0 Tohoku Earthquake Aftershocks. Bulletin of the Seismological Society of America 2013;; 103 (2B): 1360–1372. doi: https://doi.org/10.1785/0120120125 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyBulletin of the Seismological Society of America Search Advanced Search Abstract Past studies in tectonic regions dominated by subduction zones that result in the creation of volcanic belts, such as New Zealand and Japan, have pointed to higher attenuation rates across the volcanic regions. This study uses the downhole motions recorded at KiK‐net stations from 117 aftershocks that hit Japan after the great Mw 9.0 Tohoku earthquake to quantify region‐dependent strong‐motion attenuation rates. To this end, an approach to include path effects in the development of ground‐motion prediction equations (GMPEs) is presented. In this approach, regional path terms are constrained using the strong‐motion data. The constraint on path terms also makes this methodology suitable for the development of GMPEs that permit the removal of the ergodic assumption on path. The analysis results indicate the viability of the proposed methodology for constraining regional path terms and provide an estimate of single‐station, single‐path standard deviations. In addition, results confirm that the attenuation rate in volcanic regions is significantly higher than in nonvolcanic regions. Finally, a moderate correlation coefficient was found between the attenuation rate for weak and strong ground motions. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

Consistency of ground-motion predictions from the past four decades: peak ground velocity and displacement, Arias intensity and relative significant duration

Due to the limited observational datasets available for the derivation of ground-motion prediction equations (GMPEs) there is always epistemic uncertainty in the estimated median ground motion. Since the quality and quantity of strong-motion datasets is constantly increasing it would be expected that the epistemic uncertainty in ground-motion prediction (related to lack of knowledge and data) is decreasing. This article is a continuation of the study of Douglas (Bull Earthq Eng 8(6):1515–1526, 2010) for ground-motion parameters other than peak ground acceleration (PGA) and elastic response spectral acceleration (SA). The epistemic uncertainty in the prediction of peak ground velocity and displacement, Arias intensity and relative significant duration is investigated by plotting predictions from dozens of GMPEs for these parameters against date of publication for three scenarios. In agreement with the previous study, all ground-motion parameters considered show high epistemic uncertainty (often even higher than previously reported for PGA and SA), suggesting that research efforts for the development of GMPEs for these parameters should continue and that it is vital that this uncertainty is accounted for in seismic hazard assessments. The epistemic uncertainty in the prediction of relative significant duration, however, appears to be much lower than any other strong-motion parameter, which suggests that currently available GMPEs for this intensity measure are sufficiently mature.

A Short Note on Ground-motion Recordings from the M 7.9 Wenchuan, China, Earthquake and Ground-motion Prediction Equations in the Central and Eastern United States

Ground-motion prediction equations (GMPEs) are one of the key input parameters for seismic hazard assessment ( e.g. , Petersen et al. 2008) and for the site-specific ground-motion response spectrum (GMRS) for nuclear power plants (U.S. Nuclear Regulatory Commission 2007). Examples of GMPEs developed for the central and eastern United States include Somerville et al. (2001), Silva et al. (2002), Campbell (2003), and Atkinson and Boore (2006). Led by Pacific Earthquake Engineering Research, a significant effort is under way to systematically develop GMPEs for the central and eastern United States, next-generation attenuation for the eastern North America, or so-called NGA-East. The development of GMPEs in the central and eastern United States is hindered by the lack of ground-motion observations, particularly from large earthquakes (M 7 or larger). It is desirable to compare any GMPE developed for the central and eastern United States with the ground-motion observations from similar earthquakes in other stable continental regions (SCR) of the world. For example, Cramer and Kumar (2003) compared ground motions recorded by structural response recorders ( i.e. , engineering seismoscopes) within 300 km fault-distance from the 2001 Bhuj, India, earthquake (M 7.6) to several published GMPEs for the central and eastern United States. On 12 May 2008, a large intra-plate earthquake (M 7.9) occurred in Wenchuan, China, along …

Ground-Motion Attenuation at Short Hypocentral Distances (<30 km) near Sudbury, Ontario

Abstract We use seismographic data from 12 local, shallow earthquakes of magnitude M N 1.0–3.1 that occurred near Sudbury, Ontario, recorded at three stations within 30 km of the source, to examine ground-motion attenuation at close distances. This is an important issue for development of ground-motion prediction equations in eastern North America and for the inference of earthquake source parameters from regional earthquake observations. We show that high-frequency (3–10 Hz) horizontal-component ground motions decay at a geometric spreading rate of approximately R -1.3 in the first 25–30 km from the earthquake source (where R is the hypocentral distance). This is in agreement with the geometric spreading rate determined by Atkinson (2004) and used in the ground-motion prediction equations of Atkinson and Boore (2006). Vertical-component ground-motions in this distance range appear to decay at a slightly slower rate of R -1.1 .

A Guide to Differences between Stochastic Point-Source and Stochastic Finite-Fault Simulations

Why do stochastic point-source and finite-fault simulation models not agree on the predicted ground motions for moderate earthquakes at large distances? This question was posed by Ken Campbell, who attempted to reproduce the Atkinson and Boore (2006) ground-motion prediction equations for eastern North America using the stochastic point-source program SMSIM (Boore, 2005) in place of the finite- source stochastic program EXSIM (Motazedian and Atkinson, 2005) that was used by Atkinson and Boore (2006) in their model. His comparisons suggested that a higher stress drop is needed in the context of SMSIM to produce an average match, at larger distances, with the model predictions of Atkinson and Boore (2006) based on EXSIM; this is so even for moderate magnitudes, which should be well-represented by a point- source model. Why? The answer to this question is rooted in significant differences between point- source and finite-source stochastic simulation methodologies, specifically as imple- mented in SMSIM (Boore, 2005) and EXSIM (Motazedian and Atkinson, 2005 )t o date. Point-source and finite-fault methodologies differ in general in several important ways: (1) the geometry of the source; (2) the definition and application of duration; and (3) the normalization of finite-source subsource summations. Furthermore, the specific implementation of the methods may differ in their details. The purpose of this article is to provide a brief overview of these differences, their origins, and implica- tions. This sets the stage for a more detailed companion article, Comparing Stochas- tic Point-Source and Finite-Source Ground-Motion Simulations: SMSIM and EXSIM, in which Boore (2009) provides modifications and improvements in the implementations of both programs that narrow the gap and result in closer agreement. These issues are important because both SMSIM and EXSIM have been widely used in the development of ground-motion prediction equations and in modeling the param- eters that control observed ground motions.

Interperiod Dependence of Ground-Motion Prediction Equations: A Copula Perspective

Abstract The conventional approach for developing empirical prediction equations of multivariate ground-motion parameters (e.g., response spectra at a set of vibration periods) is based on regression analysis of the individual parameters; their dependence is subsequently characterized by evaluating the linear correlation coefficient of the logarithm of the ground-motion parameters that are corrected by using a ground-motion prediction equation. A copula technique, which offers a flexible way of describing nonlinear dependence among multivariate data in isolation from their marginal distribution functions, can be used to validate this two-step approach. This new perspective on the multivariate aspects of the development of ground-motion prediction equations is explored through analysis of the strong ground-motion data associated with the Boore and Atkinson (2008) Pacific Earthquake Engineering Research–Next Generation Attenuation of Ground Motions (PEER-NGA) relation. The analysis results demonstrate that multivariate ground-motion parameters can be marginally modeled as a lognormal variate, and their interperiod dependence can be captured by using the normal copula. This finding validates the conventional two-step approach.

Ground-Motion Prediction Equations for Eastern North America from a Referenced Empirical Approach: Implications for Epistemic Uncertainty

Abstract I outline a referenced empirical approach to the development of ground-motion prediction equations (GMPEs). The technique is illustrated by using it to develop GMPEs for eastern North America (ENA). The approach combines the ENA ground-motion database with the empirical prediction equations of Boore and Atkinson (2008) for the reference region of western North America (WNA). The referenced empirical approach provides GMPEs for ENA that are in agreement with regional ground-motion observations, while being constrained to follow the overall scaling behavior of ground motion that is observed in better-instrumented active tectonic regions. They are presented as an alternative to the commonly used stochastic ground-motion relations for ENA. The motivation of the article is not to supplant stochastic GMPEs but is rather to consider other approaches that might shed light on their epistemic uncertainty. Differences between the referenced empirical GMPEs of this study and the stochastic GMPEs of Atkinson and Boore (2006), along with inconsistencies between both of these studies and inferences based on intensity observations, suggest that uncertainty in median ENAGMPEs is about a factor of 1.5–2 for M ≥5 at distances from 10 to 70 km. Uncertainty is greater than a factor of 2 for large events ( M ≥7) at distances within 10 km of the source. It may be that saturation effects not modeled in the stochastic predictions, but inferred from observations in other regions, cause overestimation of near-source amplitudes from large events in Atkinson and Boore (2006). On the other hand, these saturation effects cannot be directly verified in ENA data. Differences in predictions according to the approach taken are also significant at distances from 40 to 150 km, due to uncertainty in the shape of the attenuation function that will be realized in future earthquakes.