Selection Of Ground Motion Prediction Equations Research Articles

Determination of ground motion parameters of urban centers of Balochistan province

Ground motion prediction equations (GMPEs) are cornerstone of Probabilistic Seismic Hazard Assessment. A big pool of GMPEs is available nowadays for active crustal and subduction zone categories which are derived from dataset of different regions including the database of Middle East, Europe (non-NGA) and NGA WEST 2 database. For countries like Pakistan which do not have local GMPEs, selection of GMPE is difficult and is merely based on hit and trial. A Comparative analysis of latest set of GMPEs for these respective categories on seismic hazard of Pakistan is unknown. In this study, Probabilistic Seismic Hazard analysis is conducted on urban centers (Gwadar and Quetta) of Balochistan province, a sample from Pakistan is given their potential to become economic hubs as rapid infrastructure development is expected in the region. The analysis is based on area source approach along with the modelling of major active crustal faults of the region. Three sets of GMPEs are selected where first set consists of GMPEs developed by NGA WEST 2, the second set consists of non-NGA based GMPEs while the third set is a hybrid set in which NGA WEST 2 and non-NGA based GMPEs are used together. Logic tree method is employed in this work to take into consideration of the epistemic uncertainty in different GMPEs for each tectonic zone and the seismic source models as well. For 10% probability of exceedance in 50 years (return period 475 years), updated hazard maps for PGA and spectral acceleration for structural period of 0.1 s, 0.2 s, and 1 s are created. These results can be effectively used to reduce seismic risk, to develop effective disaster mitigation, and management strategies.

Testing Ground-Motion Prediction Equations against Moderate Magnitude Earthquake Data Recorded in Korea

ABSTRACT The selection of ground-motion prediction equations (GMPEs) to perform seismic hazard assessments is challenging for stable continental regions that lack a sufficient number of recordings. In this study, we implement various ranking methods to test the efficiencies of a wide range of GMPEs against the recordings from three of the largest magnitude inland earthquakes that occurred in the Korean Peninsula, which belongs to an intraplate region with low seismicity. In this context, we select a total of 14 GMPEs developed for active shallow crustal zones (Next Generation Attenuation-West2 [NGA-West2] project), stable continental regions, and Korea. Three statistical approaches, including the classical residual, log-likelihood (LLH), and Euclidean distance-based ranking (EDR) methods, are used to evaluate the performance of the GMPEs. The residual analyses show that for the very short spectral period (T≤0.1 s), regionally developed GMPEs perform the best, whereas the NGA-West2 GMPEs outperform other equations for short (0.2≤T≤0.5 s) and medium to long periods (T≥0.75 s). The LLH approach is shown to favor a stable continental region GMPE that has the highest standard deviation. The EDR method, which can account for both aleatory uncertainties and model bias, is found to favor the NGA-West2 and Korean GMPEs. NGA-West2 GMPEs show the lowest model bias, whereas the Korean GMPEs exhibit the lowest residual bias. Five GMPEs selected based on the EDR method are recommended for a probabilistic seismic hazard analysis in Korea. For deterministic hazard assessment, using the Korean GMPEs for the very short spectral period and NGA-West2 GMPEs for short and medium to long periods is recommended. Overall, the stable continental region GMPEs are demonstrated to perform poorly when tested against the earthquakes recorded in Korea.

Probabilistic seismic hazard analysis of Madhya Pradesh (Central India) using alternate source models: a logic tree approach

This study presents the macro-level probabilistic seismic hazard analysis (PSHA) of Madhya Pradesh using the classical Cornell-McGuire method. It investigates the seismic hazard of the region using two different source models—one covering seismogenic sources within 200 km (19–28° N and 72–84° E), and another within 300 km (16–32° N and 69–88° E) from the peripheral boundaries of Madhya Pradesh. It also proposes a new hybrid model that combines the above two models using a logic-tree approach and produces hazard maps and response spectra (bedrock level) for the seven smart cities proposed under the Smart City Mission of the Government of India. Finally, the study’s results are compared with the standard recommendations by IS 1893–2016 (Part-1) and National Disaster Management Authority (NDMA 2010). PSHA is performed using an updated earthquake catalog between 1800 and 2020 compiled from various national and international resources. Standardization of catalog is performed in terms of homogenization of magnitudes to moment magnitudes (Mw), zone-wise catalog division, and declustering using Gardner and Knopoff (1974) algorithm. It utilizes the logic tree approach to address the uncertainties associated with source modeling, source characterization, and selection of ground-motion prediction equations (GMPEs). Ground accelerations corresponding to different parts of the study region are calculated by dividing the region into a 0.2° rectangular grid in orthogonal directions. This study presents the PGA maps for the entire region for the return periods of 475 and 2475 years (equivalent to 10% and 2% probability of exceedance in 50 years, respectively) and first-hand response spectra (bedrock level) for the seven smart cities corresponding to spectral accelerations, SA (T), for periods of 0.1 s, 0.2 s, 0.5 s, 1 s and 2 s on stable firm rock site condition (Vs30 as 760 m/sec) based on the 200 km, 300 km, and hybrid source models. The study finds the 200 km source model's results in fair agreement with the national recommendations, whereas the 300 km source model's results higher than the national recommendations. The results from this study shall render a great help to city planners for designing new structures and also in retrofitting the existing structures.

On computation of conditional mean spectrum in Eastern Canada

This paper investigates the main ingredients required to compute Conditional Mean Spectra (CMS) in Eastern Canada and assesses their effects on the obtained CMS. We particularly address the influence of ground motion prediction equations (GMPEs) and correlations between spectral accelerations. CMS are computed using two approximate methods, and the results are illustrated for three locations with different seismic hazard and risk levels. It is found that selection of GMPEs considerably influences the CMS, particularly at shorter periods. A database of historical records from Eastern Canada is studied to obtain correlation coefficients. The results suggest higher spectral correlations than predicted by a model based on ground motions from Western North America (WNA). The sensitivity of correlation coefficients to magnitude and epicentral distance is also verified, revealing that magnitude has a more significant effect on these coefficients than distance. We also show that the effect of magnitude- or distance-based correlation coefficients on the CMS is (1) generally negligible at long periods and (2) significant at shorter periods particularly when the conditioning period is less than approximately 0.5 s. This work is the first study addressing in detail the ingredients and construction of CMS in Eastern Canada. The methodology and results discussed are expected to enhance the application of CMS in this region.

Comment on "On the Selection of Ground-Motion Prediction Equations for Seismic Hazard Analysis" by Julian J. Bommer, John Douglas, Frank Scherbaum, Fabrice Cotton, Hilmar Bungum, and Donat Fah

The paper by Bommer et al . in Seismological Research Letters 81 (5) (hereafter Bommer et al . 2010) raises the important issue of selection criteria for ground-motion prediction equations (GMPEs) in seismic hazard analysis. Objective selection criteria are needed since many GMPEs have been developed in recent years. I found this discussion timely because of a number of recent and ongoing projects such as next-generation attenuations NGA-West (Power et al . 2006) and NGA-East (http://peer.berkeley.edu/ngaeast/index.html; accessed September 9, 2010). The purpose of this comment is to bring a number of similar issues to the attention of the seismological and earthquake engineering community. Even though I sometimes question the objectivity of reviewers, I agree with Bommer et al . (2010) that GMPEs should be published in peer-reviewed journals. Rephrasing Winston Churchill's quote on democracy so it applies to science, I can say that publishing in a peer-reviewed journal is the worst form of expressing scientific opinion except all the others that have been tried. However, I cannot agree with the approach of Bommer et al . (2010) on this issue. The authors have chosen a formal and not a physical approach to GMPE selection. There are two questions that I would like to raise: The most important features of a physical model are its clarity and physical meaning of the approximation formula, or in terminology used by Bommer et al . (2010), the model's functional form. As was stated by Bolt and Abrahamson (1982), the first critical step in modeling is the selection of an approximation function that best fits ground-motion attenuation with distance. I suggest first …

On the Selection of Ground-Motion Prediction Equations for Seismic Hazard Analysis

A key element in any seismic hazard analysis is the selection of appropriate ground-motion prediction equations (GMPEs). In an earlier paper, focused on the selection and adjustment of ground-motion models for probabilistic seismic hazard analysis (PSHA) in moderately active regions--with limited data and few, if any, indigenous models--Cotton et al. (2006) proposed seven criteria as the basis for selecting GMPEs. Recent experience in applying these criteria, faced with several new GMPEs developed since the Cotton et al. (2006) paper was published and a significantly larger strong-motion database, has led to consideration of how the criteria could be refined and of other conditions that could be included to meet the original objectives of Cotton et al. (2006). In fact, about a dozen new GMPEs are published each year, and this number appears to be increasing. Additionally, Cotton et al. (2006) concluded that the criteria should not be excessively specific, tied to the state-of-the-art in ground-motion modeling at the time of writing and thus remaining static, but rather should be sufficiently flexible to be adaptable to the continuing growth of the global strong-motion database and the continued evolution of GMPEs