Regional Ground Motion Prediction Equation Developed for the Korean Peninsula Using Recorded and Simulated Ground Motions

References

• Aki, K. 1967. Scaling law of seismic spectrum. Journal of Geophysical Research Atmospheres 72: 1217–31. doi: 10.1029/JZ072i004p01217.
   Web of Science ®Google Scholar
• Anbazhagan, P., M. Sreenivas, B. Ketan, S. S. R. Moustafa, and N. S. N. Al-Arifi. 2016. Selection of ground motion prediction equations for seismic hazard analysis of Peninsular India. Journal of Earthquake Engineering 20 (5): 699–737. doi: 10.1080/13632469.2015.1104747.
   Web of Science ®Google Scholar
• Anderson, J. G., and J. N. Brune. 1999. Probabilistic seismic hazard analysis without the ergodic assumption. Seismological Research Letters 70 (1): 19–28. doi: 10.1029/JZ072i004p01217.
   Google Scholar
• Anderson, J. G., and S. Hough. 1984. A model for the shape of the Fourier amplitude spectrum at high frequencies. Bulletin of the Seismological Society of America 74 (1969–1993). http://bssa.geoscienceworld.org/content/74/5/1969.abstract
   Google Scholar
• Atkinson, G. M., and D. M. Boore. 1998. Evaluation of models for earthquake source spectra in Eastern North America. Bulletin of Seismological Society of America 88 (4): 917–934.
   Web of Science ®Google Scholar
• Atkinson, G. M., and D. M. Boore. 1995. Ground-motion relations for Eastern North America. Bulletin of the Seismological Society of America 85 (1): 17–30.
   Web of Science ®Google Scholar
• Atkinson, G. M., and D. M. Boore. 2006. Earthquake ground-motion prediction equations for Eastern North America. Bulletin of the Seismological Society of America 96 (6): 2181–205. doi: 10.1785/0120050245.
   Web of Science ®Google Scholar
• Atkinson, G. M., and D. M. Boore. 2014. The attenuation of fourier amplitudes for rock sites in Eastern North America. Bulletin of the Seismological Society of America 104 (1): 513–28. doi: 10.1785/0120130136.
   Web of Science ®Google Scholar
• Atkinson, G. M., and J. Adams. 2013. Ground motion prediction equations for application to the 2015 Canadian national seismic hazard maps. Canadian Journal of Civil Engineering 40 (10): 1–30. doi: 10.1139/cjce-2012-0544.
   Web of Science ®Google Scholar
• Atkinson, G. M., and J. F. Cassidy. 2000. Integrated use of seismograph and strong-motion data to determine soil amplification: Response of the Fraser River Delta to the Duvall and Georgia Strait Earthquakes. Bulletin of the Seismological Society of America 90 (4): 1028–40. doi: 10.1785/0119990098.
   Web of Science ®Google Scholar
• Atkinson, G. M., and R. F. Mereu. 1992. The shape of ground motion attenuation curves in Southeastern Canada. Bulletin of the Seismological Society of America 82 (5): 2014–31.
   Web of Science ®Google Scholar
• Boatwright, J., and G. L. Choy. 1992. Acceleration source spectra anticipated for large earthquakes in Northeastern North America. Bulletin of the Seismological Society of America 82 (2): 660–82.
   Web of Science ®Google Scholar
• Boore, D. M. 1983. Stochastic simulation of high-frequency ground motions based on seismological models of the radiated spectra. Bulletin of the Seismological Society of America 73 (6A): 1865–94.
   Google Scholar
• Boore, D. M. 2003. Simulation of ground motion using the stochastic method. Pure and Applied Geophysics 160 (3–4): 635–76. doi: 10.1007/PL00012553.
   Web of Science ®Google Scholar
• Boore, D. M., and G. M. Atkinson. 1987. Stochastic prediction of ground motion and spectral response parameters at hard-rock sites in Eastern North America. Bulletin of the Seismological Society of America 77 (2): 440–67.
   Web of Science ®Google Scholar
• Boore, D. M., and J. Boatwright. 1984. Average body-wave radiation coefficients. Bulletin of the Seismological Society of America 74 (5): 1615–21.
   Web of Science ®Google Scholar
• Bora, S. S., F. Scherbaum, N. Kuehn, and P. Stafford. 2016. On the relationship between Fourier and response spectra: Implications for the adjustment of empirical ground-motion prediction equations (GMPEs). Bulletin of the Seismological Society of America 106 (3): 1235–53. doi: 10.1785/0120150129.
   Web of Science ®Google Scholar
• Bozorgnia, Y., and K. W. Campbell. 2016. Vertical ground motion model for PGA, PGV, and linear response spectra using the NGA-West2 database. Earthquake Spectra 32 (2): 979–1004. (BC2016V). doi: 10.1193/072814eqs121m.
   Web of Science ®Google Scholar
• Brune, J. 1970. Tectonic stress and the spectra of seismic shear waves. Journal of Geophysical Research Atmospheres 75: 4997–5009. doi: 10.1029/JB075i026p04997.
   Web of Science ®Google Scholar
• Brune, J. 1971. Correction: tectonic stress and the spectra of seismic shear waves. Journal of Geophysical Research Atmospheres 76: 5002. doi: 10.1029/JB076i020p05002.
   Web of Science ®Google Scholar
• Campbell, K. W. 2003. Prediction of strong ground motion using the hybrid empirical method and its use in the development of ground-motion (attenuation) relations in Eastern North America. Bulletin of the Seismological Society of America 93: 1012–33. doi: 10.1785/0120020002.
   Web of Science ®Google Scholar
• Campbell, K. W. 2011. Ground motion simulation using the hybrid empirical method: Issues and insights, in earthquake data in engineering seismology: Predictive models, data management and networks. Geotechnical, Geological and Earthquake Engineering 14: 81–95. doi: 10.1007/978-94-007-0152-6_7.
   Google Scholar
• Campbell, K. W., and Y. Bozorgnia. 2008. NGA ground motion model for the geometric mean horizontal component of PGA, PGV, PGD and 5% damped linear elastic response spectra for periods ranging from 0.01 to 10 s. Earthq Spectra 24 (1): 139–71. doi: 10.1193/1.2857546.
   Web of Science ®Google Scholar
• Douglas, J., H. Bungum, and F. Scherbaum. 2006. Ground-motion prediction equations for Southern Spain and Southern Norway obtained using the composite model perspective. Journal of Earthquake Engineering 10 (1): 33–72. doi: 10.1080/13632460609350587.
   Web of Science ®Google Scholar
• Drouet, S., and F. Cotton. 2015. Regional stochastic GMPEs in low-seismicity areas: Scaling and aleatory variability analysis—application to the french alps. Bulletin of the Seismological Society of America 105 (4). doi: 10.1785/0120140240.
   Web of Science ®Google Scholar
• Gülerce, Z., R. Kamai, N. A. Abrahamson, and W. J. Silva. 2017. Ground motion prediction equations for the vertical ground motion component based on the NGA-W2 database. Earthquake Spectra 33 (2): 499–528. doi: 10.1193/121814EQS213M.
   Web of Science ®Google Scholar
• Han, S. W., T.-O. Kim, D. H. Kim, and S.-J. Baek. 2017. Seismic collapse performance of special moment steel frames with torsional irregularities. Engineering Structures 141: 482–94. doi: 10.1016/j.engstruct.2017.03.045.
   Web of Science ®Google Scholar
• Hanks, T. C., and H. Kanamori. 1979. A moment magnitude scale. Journal of Geophysical Research Atmospheres 84 (B5): 2348–50. doi: 10.1029/JB084iB05p02348.
   Web of Science ®Google Scholar
• Hung, T. V., and O. Kiyomiya. 2013. Source parameter estimation and stochastic ground motion simulation based on recorded accelerograms in Northwestern Vietnam. Journal of Earthquake Engineering 17 (3): 304–22. doi: 10.1080/13632469.2012.719484.
   Web of Science ®Google Scholar
• Jee, H. W., and S. W. Han. 2020. Estimation of path attenuation effect from ground motion in the Korean Peninsula using stochastic point-source model. Journal of the Earthquake Engineering Society of Korea 24 (1): 9–17. [in Korean). doi:10.5000/EESK.2020.24.1.009.
   Google Scholar
• Johnston, A. C. 1996. Seismic moment assessment of earthquakes in stable continental regions - I. Instrumental seismicity. Geophysical Journal International 124: 381–414. doi: 10.1111/j.1365-246X.1996.tb07028.x.
   Web of Science ®Google Scholar
• Joshi, A. 2006. Use of acceleration spectra for determining the frequency-dependent attenuation coefficient and Source Parameters. Bulletin of the Seismological Society of America 96 (6): 2165–80. doi: 10.1785/0120050095.
   Web of Science ®Google Scholar
• Joshi, A., M. Tomer, S. Lal, S. Chopra, S. Singh, S. Prajapati, M. L. Sharma, and Sandeep. 2016. Estimation of the source parameters of the Nepal Earthquake from strong motion data. Natural Hazards 83: 867–83. doi: 10.1007/s11069-016-2351-8.
   Web of Science ®Google Scholar
• Kalkan, E. 2016. An automatic P-phase arrival-time picker. Bulletin of the Seismological Society of America 106 (3). doi: 10.1785/0120150111.
   Web of Science ®Google Scholar
• Kim, S. K. 1995. A study on the crustal structure of the Korean Peninsula. Journal of the Geological Society of Korea 8: 393–403. [in Korean].
   Google Scholar
• KMA. 2018. Investigation of the 2017 Pohang earthquake. Korea Meteorological Administration, Seoul, Korea [in Korean). pp. 48.
   Google Scholar
• Kong, Q., D. Trugman, Z. E. Ross, M. J. Bianco, B. J. Meade, and P. Gerstoft. 2018. Machine learning in seismology: Turning data into insights. Seismological Research Letters 90 (1). doi: 10.1785/0220180259.
   Web of Science ®Google Scholar
• Konno, K., and T. Ohmachi. 1998. Ground-motion characteristics estimated from spectral ratio between horizontal and vertical components of microtremor. Bulletin of the Seismological Society of America 88 (1): 228–41.
   Web of Science ®Google Scholar
• Moon, K. H., S. W. Han, T. S. Lee, and S. W. Seok. 2012. Approximate MPA-based method for performing incremental dynamic analysis. Nonlinear Dynamics 67 (4): 2865–88. doi: 10.1007/s11071-011-0195-z.
   Web of Science ®Google Scholar
• Nabilah, A. B., and T. Balendra. 2012. Seismic hazard analysis for Kuala Lumpur, Malaysia. Journal of Earthquake Engineering 16 (7): 1076–94. doi: 10.1080/13632469.2012.685208.
   Web of Science ®Google Scholar
• Nakamura, Y. 1989. A method for dynamic characteristics estimation of subsurface using microtremor on the ground surface. Quarterly Report of Railway Technical Research Institute 30 (1): 25–33.
   Google Scholar
• Papazafeiropoulos, G., and V. Plevris. 2018. OpenSeismoMatlab: A new open-source software for strong ground motion data processing. Heliyon 4 (9): e00784. doi: 10.1016/j.heliyon.2018.e00784.
   PubMed Web of Science ®Google Scholar
• Papoulia, J., Y. M. Fahjan, L. Hutchings, and T. Novikova. 2015. PSHA for broad-band strong ground-motion hazards in the Saronikos Gulf, Greece, from Potential Earthquake with synthetic ground motions. Journal of Earthquake Engineering 19 (4): 624–48. doi: 10.1080/13632469.2014.991977.
   Web of Science ®Google Scholar
• Pezeshk, S., A. Zandieh, and B. Tavakoli. 2011. Hybrid empirical ground-motion prediction equations for Eastern North America using NGA models and updated seismological parameters. Bulletin of the Seismological Society of America 101 (4): 1859–70. doi: 10.1785/0120100144.
   Web of Science ®Google Scholar
• Pezeshk, S., A. Zandieh, K. W. Campbell, and B. Tavakoli. 2018. Ground-motion prediction equations for central and Eastern North America using the hybrid empirical method and NGA-West2 empirical ground-motion models. Bulletin of the Seismological Society of America 108 (4): 2278–304. doi: 10.1785/0120170179.
   Web of Science ®Google Scholar
• Rathje, E. M., A. R. Kottke, and M. C. Ozbey. 2005. “Using inverse random vibration theory to develop input Fourier amplitude spectra for use in site response,” Proceedings of 16th International Conference on Soil Mechanics and Geotechnical Engineering, TC4 Earthquake Geotechnical Engineering Satellite Conference, 160–66. Osaka, Japan. DOI: 10.13140/2.1.3695.3920.
   Google Scholar
• Rietbrock, A., F. Strasser, and B. Edwards. 2013. A stochastic earthquake ground-motion prediction model for the United Kingdom. Bulletin of the Seismological Society of America 103 (1): 57–77. doi: 10.1785/0120110231.
   Web of Science ®Google Scholar
• Saragoni, G. R., and G. C. Hart. 1974. Simulation of artificial earthquakes. Earthquake Engineering and Structural Dynamics 2: 249–67. doi: 10.1002/eqe.4290020305.
   Google Scholar
• Schulte, S. M., and W. D. Mooney. 2005. An updated global earthquake catalogue for stable continental regions: Reassessing the correlation with ancient rifts. Geophysical Journal International 161 (3): 707–21. doi: 10.1111/j.1365-246X.2005.02554.x.
   Web of Science ®Google Scholar
• Sharma, N., and V. Convertito. 2018. Update, comparison, and interpretation of the ground-motion prediction equation for “The Geysers” geothermal area in the light of new data. Bulletin of the Seismological Society of America 108 (6): 3645–55. doi: 10.1785/0120170350.
   Web of Science ®Google Scholar
• Stewart, J. P., D. M. Boore, E. Seyhan, and G. M. Atkinson. 2016. NGA-West2 equations for predicting vertical-component PGA, PGV, and 5%-damped PSA from Shallow crustal earthquakes. Earthquake Spectra 32 (2): 1005–31. doi: 10.1193/072114eqs116m.
   Web of Science ®Google Scholar
• Tavakoli, B., and S. Pezeshk. 2005. Empirical-stochastic ground-motion prediction for Eastern North America. Bulletin of the Seismological Society of America 95 (6): 2283–96. doi: 10.1785/0120050030.
   Web of Science ®Google Scholar
• Wen, Y. K., K. R. Collins, S. W. Han, and K. J. Elwood. 1996. Dual-level designs of buildings under seismic loads. Structural Safety 18 (2–3): 195–224. doi: 10.1016/0167-4730(96)00011-2.
   Web of Science ®Google Scholar
• Yang, D., and J. Zhou. 2015. A stochastic model and synthesis for near-fault impulsive ground motions. Earthquake Engineering and Structural Dynamics 44 (2). doi: 10.1002/eqe.2468.
   Web of Science ®Google Scholar
• Yenier, E., and G. M. Atkinson. 2015. An equivalent point-source model for stochastic simulation of earthquake ground motions in California. Bulletin of the Seismological Society of America 105 (3): 1435–55. doi: 10.1785/0120140254.
   Web of Science ®Google Scholar
• Zafarani, H., B. Hajimohammadi, and S. M. Jalalalhosseini. 2019. Earthquake hazard in the tehran region based on the characteristic earthquake model. Journal of Earthquake Engineering 23 (9): 1485–511. doi: 10.1080/13632469.2017.1387189.
   Web of Science ®Google Scholar
• Zandieh, A., and S. Pezeshk. 2010. Investigation of geometrical spreading and quality factor functions in the New Madrid Seismic Zone. Bulletin of the Seismological Society of America 100: 2185–95. doi: 10.1785/0120090209.
   Web of Science ®Google Scholar
• Zhao, J. X., K. Irikura, J. Zhang, F. Yoshimitsu, P. G. Somerville, A. Asano, Y. Ohno, T. Oouchi, T. Takahashi, and H. Ogawa. 2006. An empirical site-classification method for strong-motion stations in Japan using H/V response spectral ratio. Bulletin of the Seismological Society of America 96 (3): 914–25. doi: 10.1785/0120050124.
   Web of Science ®Google Scholar