An Empirical Spectral Ground-Motion Model for Iran Using Truncated Iranian Strong-Motion Database Enriched by Near-Field Records

References

• Abrahamson, N., and W. Silva. 2008. Summary of the Abrahamson & Silva NGA ground-motion relations. Earthquake Spectra 24 (1):67–97. doi:10.1193/1.2924360.
   Web of Science ®Google Scholar
• Abrahamson, N. A., W. J. Silva, and R. Kamai. 2014. Summary of the ASK14 ground motion relation for active crustal regions. Earthquake Spectra 30 (3):1025–55. doi:10.1193/070913EQS198M.
   Web of Science ®Google Scholar
• Abrahamson, N. A., and R. R. Youngs. 1992. A stable algorithm for regression analyses using the random effects model. Bulletin of the Seismological Society of America 82 (1):505–10. doi:10.1785/BSSA0820010505.
   Web of Science ®Google Scholar
• Akkar, S., and J. J. Bommer. 2010. Empirical equations for the prediction of PGA, PGV, and spectral accelerations in Europe, the Mediterranean region, and the Middle East. Seismological Research Letters 81 (2):195–206. doi:10.1785/gssrl.81.2.195.
   Web of Science ®Google Scholar
• Akkar, S., Z. Çağnan, E. Yenier, Ö. Erdoğan, M. A. Sandıkkaya, and P. Gülkan. 2010. The recently compiled Turkish strong motion database: Preliminary investigation for seismological parameters. Journal of Seismology 14 (3):457–79. doi:10.1007/s10950-009-9176-9.
   Web of Science ®Google Scholar
• Akkar, S., M. A. Sandıkkaya, and J. J. Bommer. 2014. Empirical ground-motion models for point-and extended-source crustal earthquake scenarios in Europe and the Middle East. Bulletin of Earthquake Engineering 12 (1):359–87. doi:10.1007/s10518-013-9461-4.
   Web of Science ®Google Scholar
• Ancheta, T. D., R. B. Darragh, J. P. Stewart, E. Seyhan, W. J. Silva, B. S. J. Chiou, and J. L. Donahue, R. W. Graves, A. R. Kottke, D. M. Boore. 2014. NGA-West2 database. Earthquake Spectra 30 (3):989–1005. doi:10.1193/070913EQS197M.
   Web of Science ®Google Scholar
• Ansari, A., A. Noorzad, H. Zafarani, and H. Vahidifard. 2010. Correction of highly noisy strong motion records using a modified wavelet de-noising method. Soil Dynamics and Earthquake Engineering 30 (11):1168–81. doi:10.1016/j.soildyn.2010.04.025.
   Web of Science ®Google Scholar
• Atik, L. A., N. Abrahamson, J. J. Bommer, F. Scherbaum, F. Cotton, and N. Kuehn. 2010. The variability of ground-motion prediction models and its components. Seismological Research Letters 81 (5):794–801. doi:10.1785/gssrl.81.5.794.
   Web of Science ®Google Scholar
• Barani, S., D. Albarello, M. Massa, and D. Spallarossa. 2017. Influence of twenty years of research on ground-motion prediction equations on probabilistic seismic hazard in Italy. Bulletin of the Seismological Society of America 107 (1):240–55. doi:10.1785/0120150276.
   Web of Science ®Google Scholar
• Beauval, C., P. Y. Bard, and L. Danciu. 2020. The influence of source-and ground-motion model choices on probabilistic seismic hazard levels at 6 sites in France. Bulletin of Earthquake Engineering 18 (10):4551–80. doi:10.1007/s10518-020-00879-z.
   Web of Science ®Google Scholar
• Bindi, D., M. Massa, L. Luzi, G. Ameri, F. Pacor, R. Puglia, and P. Augliera. 2014. Pan-European ground-motion prediction equations for the average horizontal component of PGA, PGV, and 5%-damped PSA at spectral periods up to 3.0 s using the RESORCE dataset. Bulletin of Earthquake Engineering 12 (1):391–430. doi:10.1007/s10518-013-9525-5.
   Web of Science ®Google Scholar
• Bindi, D., F. Pacor, L. Luzi, R. Puglia, M. Massa, G. Ameri, and R. Paolucci. 2011. Ground motion prediction equations derived from the Italian strong motion database. Bulletin of Earthquake Engineering 9 (6):1899–920. doi:10.1007/s10518-011-9313-z.
   Web of Science ®Google Scholar
• Bommer, J. J. 2012. Challenges of building logic trees for probabilistic seismic hazard analysis. Earthquake Spectra 28 (4):1723–35. doi:10.1193/1.4000079.
   Web of Science ®Google Scholar
• Bommer, J. J., J. Douglas, F. Scherbaum, F. Cotton, H. Bungum, and D. Fäh. 2010. On the selection of ground-motion prediction equations for seismic hazard analysis. Seismological Research Letters 81 (5):783–93. doi:10.1785/gssrl.81.5.783.
   Web of Science ®Google Scholar
• Bommer, J. J., and F. Scherbaum. 2008. The use and misuse of logic trees in probabilistic seismic hazard analysis. Earthquake Spectra 24 (4):997–1009. doi:10.1193/1.2977755.
   Web of Science ®Google Scholar
• Bommer, J. J., F. Scherbaum, H. Bungum, F. Cotton, F. Sabetta, and N. A. Abrahamson. 2005. On the use of logic trees for ground-motion prediction equations in seismic-hazard analysis. Bulletin of the Seismological Society of America 95 (2):377–89. doi:10.1785/0120040073.
   Web of Science ®Google Scholar
• Boore, D. M. 2010. Orientation-independent, nongeometric-mean measures of seismic intensity from two horizontal components of motion. Bulletin of the Seismological Society of America 100 (4):1830–35. doi:10.1785/0120090400.
   Web of Science ®Google Scholar
• Boore, D. M., and G. M. Atkinson. 2008. Ground-motion prediction equations for the average horizontal component of PGA, PGV, and 5%-damped PSA at spectral periods between 0.01 s and0.0 s. Earthquake Spectra 24 (1):99–138. doi:10.1193/1.2830434.
   Web of Science ®Google Scholar
• Boore, D. M., and T. Kishida. 2017. Relations between some horizontal‐component ground-motion intensity measures used in practice. Bulletin of the Seismological Society of America 107 (1):334–43. doi:10.1785/0120160250.
   Web of Science ®Google Scholar
• Boore, D. M., J. P. Stewart, E. Seyhan, and G. M. Atkinson. 2014. NGA-West2 equations for predicting PGA, PGV, and 5% damped PSA for shallow crustal earthquakes. Earthquake Spectra 30 (3):1057–85. doi:10.1193/070113EQS184M.
   Web of Science ®Google Scholar
• Bozorgnia, Y., J. P. Stewart, and N. A. Abrahamson (2020). Data resources for NGA-Subduction project. PEER No. Report 2020, 2.
   Google Scholar
• Bragato, P. L. 2004. Regression analysis with truncated samples and its application to ground-motion attenuation studies. Bulletin of the Seismological Society of America 94 (4):1369–78. doi:10.1785/012003083.
   Web of Science ®Google Scholar
• Budnitz, R. J., G. Apostolakis, and D. M. Boore (1997). Recommendations for probabilistic seismic hazard analysis: Guidance on uncertainty and use of experts. (No. NUREG/CR-6372-Vol.; UCRL-ID-122160), Nuclear Regulatory Commission, Washington, DC (United States). Div. of Engineering Technology; Lawrence Livermore National Lab., CA (United States); Electric Power Research Inst., Palo Alto, CA (United States); USDOE, Washington, DC (United States).
   Google Scholar
• Building and Housing Research Center. 2012. Iranian code of practice for seismic resistant design of buildings, standard No. 2800. 4th ed. Tehran, Iran: Building and Housing Research Center.
   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 to0 s. Earthquake Spectra 24 (1):139–71. doi:10.1193/1.2857546.
   Web of Science ®Google Scholar
• Campbell, K. W., and Y. Bozorgnia. 2014. NGA-West2 ground motion model for the average horizontal components of PGA, PGV, and 5% damped linear acceleration response spectra. Earthquake Spectra 30 (3):1087–115. doi:10.1193/062913EQS175M.
   Web of Science ®Google Scholar
• Cauzzi, C., and E. Faccioli. 2018. Anatomy of sigma of a global predictive model for ground motions and response spectra. Bulletin of Earthquake Engineering 16 (5):1887–905. doi:10.1007/s10518-017-0278-4.
   Web of Science ®Google Scholar
• Chao, S. H., and Y. H. Chen. 2019. A novel regression analysis method for randomly truncated strong-motion data. Earthquake Spectra 35 (2):977–1001. doi:10.1193/022218EQS044M.
   Web of Science ®Google Scholar
• Chiou, B. S. J., and R. R. Youngs. 2014. Update of the Chiou and Youngs NGA model for the average horizontal component of peak ground motion and response spectra. Earthquake Spectra 30 (3):1117–53. doi:10.1193/072813EQS219M.
   Web of Science ®Google Scholar
• Contreras, V., J. P. Stewart, T. Kishida, R. B. Darragh, B. S. J. Chiou, S. Mazzoni, N. Kuehn, S. K. Ahdi, K. Wooddell, R. R. Youngs, et al. 2020. Chapter 4: Source and path metadata. In Data resources for NGA-subduction project, PEER report 2020/02, ed. J. Stewart. California: UC Berkeley (Headquarters): Pacific Earthquake Engineering Research Center.
   Google Scholar
• Coppersmith, K. J., J. J. Bommer, K. Hanson, R. Coppersmith, J. R. Unruh, L. Wolf, and V. Montaldo-Falero (2014). Hanford sitewide probabilistic seismic hazard analysis, PNNL-23361. Richland, WA: Pacific Northwest National Laboratory. http://www.hanford.gov/page.cfm/OfficialDocuments/HSPSHA.
   Google Scholar
• Darzi, A., M. R. Zolfaghari, C. Cauzzi, and D. Fäh. 2019. An empirical ground‐motion model for horizontal PGV, PGA, and 5% damped elastic response spectra (0.01–10 s) in IranAn empirical ground‐motion model. Bulletin of the Seismological Society of America 109 (3):1041–57. doi:10.1785/0120180196.
   Web of Science ®Google Scholar
• Douglas, J. 2020. Ground motion prediction equations964-2020, 670. Glaskow, UK: Dept. Civil Environ. Eng., Univ Strathclyde.
   Google Scholar
• Douglas, J., and B. Edwards. 2016. Recent and future developments in earthquake ground motion estimation. Earth-Science Reviews 160:203–19. doi:10.1016/j.earscirev.2016.07.005.
   Web of Science ®Google Scholar
• Eskandarinejad, A., H. Zafarani, and M. Jahanandish. 2018. Local site effect of a clay site in Shiraz based on seismic hazard of Shiraz Plain. Natural Hazards 90 (3):1115–35. doi:10.1007/s11069-017-3086-x.
   Web of Science ®Google Scholar
• Farajpour, Z., S. Pezeshk, and M. Zare. 2019. A new empirical ground‐motion model for Iran. Bulletin of the Seismological Society of America 109 (2):732–44. doi:10.1785/0120180139.
   Web of Science ®Google Scholar
• Fukushima, Y. 1997. Comment on “Ground motion attenuation relations for subduction zones”. Seismological Research Letters 68 (6):947–49. doi:10.1785/gssrl.68.6.947.
   Google Scholar
• Fukushima, Y., and T. Tanaka. 1990. A new attenuation relation for peak horizontal acceleration of strong earthquake ground motion in Japan. Bulletin of the Seismological Society of America 80 (4):757–83.
   Web of Science ®Google Scholar
• Gao, J. C., C. H. Chan, and C. T. Lee. 2021. Site-dependent ground-motion prediction equations and uniform hazard response spectra. Engineering Geology 292:106241. doi:10.1016/j.enggeo.2021.106241.
   Web of Science ®Google Scholar
• Ghasemi, H., M. Zare, Y. Fukushima, and K. Koketsu. 2009a. An empirical spectral ground-motion model for Iran. Journal of Seismology 13 (4):499–515. doi:10.1007/s10950-008-9143-x.
   Web of Science ®Google Scholar
• Ghasemi, H., M. Zare, Y. Fukushima, and F. Sinaeian. 2009b. Applying empirical methods in site classification, using response spectral ratio (H/V): A case study on Iranian strong motion network (ISMN). Soil Dynamics and Earthquake Engineering 29 (1):121–32. doi:10.1016/j.soildyn.2008.01.007.
   Web of Science ®Google Scholar
• Gülerce, Z., B. Kargoığlu, and N. A. Abrahamson. 2016. Turkey-adjusted NGA-W1 horizontal ground motion prediction models. Earthquake Spectra 32 (1):75–100. doi:10.1193/022714EQS034M.
   Web of Science ®Google Scholar
• Joyner, W. B., and D. M. Boore. 1981. Peak horizontal acceleration and velocity from strong-motion records including records from the979 Imperial Valley, California, earthquake. Bulletin of the Seismological Society of America 71 (6):2011–38. doi:10.1785/BSSA0710062011.
   Web of Science ®Google Scholar
• Joyner, W. B., and D. M. Boore. 1993. Methods for regression analysis of strong-motion data. Bulletin of the Seismological Society of America 83 (2):469–87. doi:10.1785/BSSA0830020469.
   Web of Science ®Google Scholar
• Kaklamanos, J., L. G. Baise, and D. M. Boore. 2011. Estimating unknown input parameters when implementing the NGA ground-motion prediction equations in engineering practice. Earthquake Spectra 27 (4):1219–35. doi:10.1193/1.3650372.
   Web of Science ®Google Scholar
• Kale, Ö., S. Akkar, A. Ansari, and H. Hamzehloo. 2015. A ground‐motion predictive model for Iran and Turkey for horizontal PGA, PGV, and 5% damped response spectrum: Investigation of possible regional effects. Bulletin of the Seismological Society of America 105 (2A):963–80. doi:10.1785/0120140134.
   Web of Science ®Google Scholar
• Kanno, T., A. Narita, N. Morikawa, and Y. A. J. Fukushima. July, 2006. New Attenuation Relation for Strong Ground Motion in Japan Based on Recorded Data. Bulletin of the Seismological Society of America 96 (3):879–97. doi:10.1785/0120050138.
   Web of Science ®Google Scholar
• Khodaverdian, A., H. Zafarani, M. Rahimian, and V. Dehnamaki. 2016a. Seismicity parameters and spatially smoothed seismicity model for Iran. Bulletin of the Seismological Society of America 106 (3):1133–50. doi:10.1785/0120150178.
   Web of Science ®Google Scholar
• Khodaverdian, A., H. Zafarani, K. W. Schultz, and M. Rahimian. 2016b. Recurrence time distributions of large earthquakes in Eastern Iran. Bulletin of the Seismological Society of America 106 (6):2624–39. doi:10.1785/0120160077.
   Web of Science ®Google Scholar
• Kuehn, N. M., T. Kishida, M. AlHamaydeh, G. Lavrentiadis, and Y. Bozorgnia. 2020. A Bayesian model for truncated regression for the estimation of empirical ground-motion models. Bulletin of Earthquake Engineering 18 (14):6149–79. doi:10.1007/s10518-020-00943-8.
   Web of Science ®Google Scholar
• McGuire, R. K. 1978. FRISK: Computer program for seismic risk analysis using faults as earthquake sources (No. 78-1007). US Geological Survey. doi:10.3133/ofr781007.
   Google Scholar
• Mirzaei, N., G. Mengtan, and C. Yuntai. 1998. Seismic source regionalization for seismic zoning of Iran: Major seismotectonic provinces. Journal of Earthquake Prediction Research 7:465–95.
   Google Scholar
• Mousavi, M., H. Zafarani, A. Noorzad, A. Ansari, and K. Bargi. 2007. Analysis of Iranian strong-motion data using the specific barrier model. Journal of Geophysics and Engineering 4 (4):415–28.
   Web of Science ®Google Scholar
• Mousavi, M., H. Zafarani, S. Rahpeyma, and A. Azarbakht. 2014. Test of goodness of the NGA ground-motion equations to predict the strong motions of the 2012 Ahar–Varzaghan dual earthquakes in northwestern Iran. Bulletin of the Seismological Society of America 104 (5):2512–28. doi:10.1785/0120130302.
   Web of Science ®Google Scholar
• Nissen, E., A. Ghods, E. Karasözen, J. R. Elliott, W. D. Barnhart, E. A. Bergman, and L. Chen, M. Jamal‐Reyhani, M. Nemati, F. Tan. 2019. The2 November 2017 M w 7.3 Ezgeleh‐Sarpolzahab (Iran) earthquake and active tectonics of the Lurestan Arc. Journal of Geophysical Research: Solid Earth 124 (2):2124–52. doi:10.1029/2018JB016221.
   Web of Science ®Google Scholar
• Nowroozi, A. A. 1976. Seismotectonic provinces of Iran. Bulletin of the Seismological Society of America 66 (4):1249–76.
   Web of Science ®Google Scholar
• Power, M., B. Chiou, N. Abrahamson, Y. Bozorgnia, T. Shantz, and C. Roblee. 2008. An overview of the NGA project. Earthquake Spectra 24, 3–21.
   Web of Science ®Google Scholar
• Saffari, H., Y. Kuwata, S. Takada, and A. Mahdavian. 2012. Updated PGA, PGV, and spectral acceleration attenuation relations for Iran. Earthquake Spectra 28 (1):257–76. doi:10.1193/1.3673622.
   Web of Science ®Google Scholar
• Sandıkkaya, M. A., S. Akkar, and P. Y. Bard. 2013. A nonlinear site-amplification model for the next pan-European ground-motion prediction equations. Bulletin of the Seismological Society of America 103 (1):19–32. doi:10.1785/0120120008.
   Web of Science ®Google Scholar
• Shahvar, M. P., E. Farzanegan, A. Eshaghi, and H. Mirzaei. 2021. I1‐net: The Iran strong motion network. Seismological Research Letters 92 (4):1–9. doi:10.1785/0220200417.
   Web of Science ®Google Scholar
• Shahvar, M. P., M. Zare, and S. Castellaro. 2013. A unified seismic catalog for the Iranian plateau (1900–2011). Seismological Research Letters 84 (2):233–49. doi:10.1785/0220120144.
   Web of Science ®Google Scholar
• Soghrat, M. R., N. Khaji, and H. Zafarani. 2012. Simulation of strong ground motion in northern Iran using the specific barrier model. Geophysical Journal International 188 (2):645–79. doi:10.1111/j.1365-246X.2011.05287.x.
   Web of Science ®Google Scholar
• Soghrat, M. R., and M. Ziyaeifar. 2016. A predictive equation for vertical‐to‐horizontal response spectral ratios in Northern Iran. Bulletin of the Seismological Society of America 106 (1):123–40. doi:10.1785/0120150227.
   Web of Science ®Google Scholar
• Talebi, M., M. Zare, E. N. Farsangi, M. R. Soghrat, V. Maleki, and S. Esmaeili. 2021. Development of risk-targeted seismic hazard maps for the Iranian plateau. Soil Dynamics and Earthquake Engineering 141:106506. doi:10.1016/j.soildyn.2020.106506.
   Web of Science ®Google Scholar
• Vahidifard, H., H. Zafarani, and S. R. Sabbagh-Yazdi. 2017a. Hybrid broadband simulation of strong-motion records from the September6,978, Tabas, Iran, earthquake (Mw 7.4). Natural Hazards 87 (1):57–81. doi:10.1007/s11069-017-2753-2.
   Web of Science ®Google Scholar
• Vahidifard, H., H. Zafarani, S. R. Sabbagh-Yazdi, and M. A. Hadian. 2017b. Seismic hazard analysis using simulated ground-motion time histories: The case of the Sefidrud dam, Iran. Soil Dynamics and Earthquake Engineering 99:20–34. doi:10.1016/j.soildyn.2017.04.017.
   Web of Science ®Google Scholar
• Wang, J. P., and Y. H. Lin. 2021. Application of Bayesian calculation to determine logic-tree weights for ground motion prediction equations: Seismological case studies in Taiwan. Engineering Geology 294:106347. doi:10.1016/j.enggeo.2021.106347.
   Web of Science ®Google Scholar
• Wells, D. L., and K. J. Coppersmith. 1994. New empirical relationships among magnitude, rupture length, rupture width, rupture area, and surface displacement. Bulletin of the Seismological Society of America 84 (4):974–1002.
   Web of Science ®Google Scholar
• Zafarani, H., S. M. M. Ghafoori, M. R. Adlparvar, P. Rajaeian, and A. Hasankhani. 2015. Application of time-and magnitude-predictable model for long-term earthquake prediction in Iran. Natural Hazards 78:155–78. doi:10.1007/s11069-015-1708-8.
   Web of Science ®Google Scholar
• Zafarani, H., L. Luzi, G. Lanzano, and M. R. Soghrat. 2018. Empirical equations for the prediction of PGA and pseudo spectral accelerations using Iranian strong-motion data. Journal of Seismology 22 (1):263–85. doi:10.1007/s10950-017-9704-y.
   Web of Science ®Google Scholar
• Zafarani, H., M. Mousavi, A. S. Noorzad, and A. Ansari. 2008. Calibration of the specific barrier model to Iranian plateau earthquakes and development of physically based attenuation relationships for Iran. Soil Dynamics and Earthquake Engineering 28 (7):550–76. doi:10.1016/j.soildyn.2007.08.001.
   Web of Science ®Google Scholar
• Zafarani, H., A. Noorzad, A. Ansari, and K. Bargi. 2009. Stochastic modeling of Iranian earthquakes and estimation of ground motion for future earthquakes in Greater Tehran. Soil Dynamics and Earthquake Engineering 29 (4):722–41. doi:10.1016/j.soildyn.2008.08.002.
   Web of Science ®Google Scholar
• Zafarani, H., and M. Soghrat. 2012. Simulation of ground motion in the Zagros region of Iran using the specific barrier model and the stochastic method. Bulletin of the Seismological Society of America 102 (5):2031–45. doi:10.1785/0120110315.
   Web of Science ®Google Scholar
• Zafarani, H., and M. R. Soghrat. 2017. A selected dataset of the Iranian strong motion records. Natural Hazards 86 (3):1307–32. doi:10.1007/s11069-017-2745-2.
   Web of Science ®Google Scholar
• Zarrineghbal, A., H. Zafarani, and M. Rahimian. 2021. Towards an Iranian national risk-targeted model for seismic hazard mapping. Soil Dynamics and Earthquake Engineering 141:106495. doi:10.1016/j.soildyn.2020.106495.
   Web of Science ®Google Scholar
• Zhao, J. X., et al. January, 2006. Attenuation relations of strong ground motion in Japan using site classification based on predominant period. Bulletin of the Seismological Society of America 96 (3):898–913.
   Web of Science ®Google Scholar