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Suitability Analysis of Ground Motion Prediction Equations for Western and Central Himalayas and Indo-Gangetic Plains
Geophysics · Submitted 8 Oct 2024
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim Different suites of GMPEs are shown suitable for different periods of interest.
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The abstract, sentence by sentence
Ground motion prediction equations (GMPEs) play a key role in seismic hazard assessment (SHA). Considering the seismo-tectonic, geophysical and geotectonic characteristics of a target region, all the GMPEs may not be suitable in predicting the observed ground motion effectively. With a fairly large number of published GMPEs, the selection and ranking of suitable GMPEs for the design of logic trees in SHA for a particular target region has become a necessity of late. This paper presents a detailed quantitative evaluation of performance of 16 GMPEs against recorded ground motion data in two target regions, characterized by distinct seismo-tectonic, geophysical and geotectonical nature. The data set comprises of 465 three-component spectral accelerograms corresponding to 122 earthquake events. The suitability of a GMPE is tested by two widely accepted data-driven statistical methods, namely, likelihood (LH) and log-likelihood (LLH) method. Different suites of GMPEs are shown suitable for different periods of interest. The results will be useful to scientists and engineers for microzonation and estimation of seismic design parameters for the design of earthquake-resistant structures in these regions.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | Ground motion prediction equations (GMPEs) play a key role in seismic hazard assessment (SHA). | background 1.00 | 0.04 | 0.02 | asserted 1.00 |
| s1 | Considering the seismo-tectonic, geophysical and geotectonic characteristics of a target region, all the GMPEs may not be suitable in predicting the observed ground motion effectively. | background 0.92 | 0.06 | 0.06 | hedged possibility 0.99 |
| s2 | With a fairly large number of published GMPEs, the selection and ranking of suitable GMPEs for the design of logic trees in SHA for a particular target region has become a necessity of late. | background 0.88 | 0.05 | 0.03 | asserted 0.99 |
| s3 | This paper presents a detailed quantitative evaluation of performance of 16 GMPEs against recorded ground motion data in two target regions, characterized by distinct seismo-tectonic, geophysical and geotectonical nature. | contribution 1.00 | 0.94 | 0.08 | asserted 0.99 |
| s4 | The data set comprises of 465 three-component spectral accelerograms corresponding to 122 earthquake events. | method 0.99 | 0.75 | 0.02 | asserted 1.00 |
| s5 | The suitability of a GMPE is tested by two widely accepted data-driven statistical methods, namely, likelihood (LH) and log-likelihood (LLH) method. | method 1.00 | 0.69 | 0.04 | asserted 1.00 |
| s6 | Different suites of GMPEs are shown suitable for different periods of interest. | result 1.00 | 0.88 | 0.38 | asserted 1.00 |
| s7 | The results will be useful to scientists and engineers for microzonation and estimation of seismic design parameters for the design of earthquake-resistant structures in these regions. | interpretation 0.94 | 0.22 | 0.15 | asserted 0.80 |
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Original abstract
Ground motion prediction equations (GMPEs) play a key role in seismic hazard assessment (SHA). Considering the seismo-tectonic, geophysical and geotectonic characteristics of a target region, all the GMPEs may not be suitable in predicting the observed ground motion effectively. With a fairly large number of published GMPEs, the selection and ranking of suitable GMPEs for the design of logic trees in SHA for a particular target region has become a necessity of late. This paper presents a detailed quantitative evaluation of performance of 16 GMPEs against recorded ground motion data in two target regions, characterized by distinct seismo-tectonic, geophysical and geotectonical nature. The data set comprises of 465 three-component spectral accelerograms corresponding to 122 earthquake events. The suitability of a GMPE is tested by two widely accepted data-driven statistical methods, namely, likelihood (LH) and log-likelihood (LLH) method. Different suites of GMPEs are shown suitable for different periods of interest. The results will be useful to scientists and engineers for microzonation and estimation of seismic design parameters for the design of earthquake-resistant structures in these regions.
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