Selection and Ranking the Ground Motion Prediction Equations for Tehran Region

Document Type : Original Article

Authors

1 Assistant Prof., Faculty of Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran

2 Assistant Prof., Faculty of Technology and Mining, Yasouj University, Choram, Iran

3 M.Sc., Civil Engineering, Faculty of Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran.

4 Postdoc student, Faculty of Engineering, University of Kurdistan, Sanandaj,Iran

Abstract

Earthquake wave transmission from the source to the site is modeled by the ground motion prediction equations (GMPEs or attenuation equations). Considering the high contribution of these equations in the variability of the ground motion in the site, the selection of the appropriate relations for the region is of particular importance. The number of prediction equations is large, but there is no specific relationship for many areas, so it is necessary to use criteria to determine the best equations for probabilistic seismic hazard analysis(PSHA). In this paper, 62 relationships used by analysts in Iran and Tehran region are introduced to the three criteria of Rennie divergence, Euclidean distance and likelihood method, are ranked based on similarity with actual occurrence data, and the most suitable relationships for Tehran are introduced. The results show that the relationship of Zare and Sabze Ali (2006) in all three methods has a very good match with the Tehran region earthquakes. Also, some global relations have a better match than the regional relations obtained in Tehran. The results of the sensitivity analysis show a decrease in the effectiveness of the regional PSHA using the ranking. It also shows that relying on the opinion of experts brings more than 90% confidence in the selection of GMPEs, which seems sufficient in some cases. .If this level of accuracy is not sufficient, it is necessary to use the appropriate weighted equations in the analysis based on the physics-based ranking results. Otherwise, the results of the probabilistic seismic hazard analysis will fluctuate and may not have the sufficient reliability.

Keywords

Main Subjects

References

[1] Mirza Goltabar Roshan, A., & Mahdavi Omran, S. (2015). The Dynamic Behavior of a Network of Pipelines and Liquefaction of Soil Caused by the Earthquake Acceleration. Journal of Structural and Construction Engineering, 2(2), 67-76.
[2] Jafari, R., & Alidoost Abadikhah, F. (2019). Seismic Risk Assessment of Mashhad. Journal of Structural and Construction Engineering, 5(4), 128-150.
doi: 10.22065/jsce.2017.81346.1132
[3] Ghadimi Hamzehkolaei, A., Vafaeinezhad, A., & Ghodrati Amiri, G. (2021). Zoning of suitable places for temporary accommodation after an earthquake in Karaj city using fuzzy logic theory. Journal of Structural and Construction Engineering, 8(2), 44-55.
doi: 10.22065/jsce.2019.156425.1709 /jsce.2019.156425.1709
[4] Motaghed, S., Nakhlian, A., Emadali, L., Eftekhari, N., & Mahmudian, H. (2023). Determining the natural frequency of Behbahan city soil using microtremor data analysis. Journal of Geography and Environmental Hazards.‏(in press)
doi: 10.22067/geoeh.2023.80563.1326
[5] Akhani, M., & Pezeshk, S. (2022). Using metaheuristic algorithms to optimize a mixed model-based ground-motion prediction model and associated variance components. Journal of Seismology, 26(3), 483-498.‏
doi.org/10.1007/s10950-022-10091-y
[6] Douglas, J. GMPE compendium. (2022, January 4 – last update). [Online]. Available: http://www.gmpe.org.uk/ [2019, February 3]
[7] Akkar, S., Kale, Ö., Yakut, A., & Ceken, U. (2018). Ground-motion characterization for the probabilistic seismic hazard assessment in Turkey. Bulletin of Earthquake Engineering, 16(8), 3439-3463.‏
doi.org/10.1007/s10518-017-0101-2
[8] Lanzano, G., D’Amico, M., Felicetta, C., Puglia, R., Luzi, L., Pacor, F., & Bindi, D. (2016). Ground‐motion prediction equations for region specific probabilistic seismic-hazard analysis. Bulletin of the Seismological Society of America, 106(1), 73-92.‏
doi.org/10.1785/0120150096
[9] Motaghed, S., Yazdani, A., Nicknam, A., & Khanzadi, M. (2018). Sobol sensitivity generalization for engineering and science applications. Journal of Modeling in Engineering, 16(54), 217-226.‏
[10] Kowsari, M., Halldorsson, B., Hrafnkelsson, B., & Jónsson, S. (2019). Selection of earthquake ground motion models using the deviance information criterion. Soil Dynamics and Earthquake Engineering, 117, 288-299.‏
doi.org/10.1016/j.soildyn.2018.11.014
[11] Zafarani, H., & Soghrat, M. R. (2017). A selected dataset of the Iranian strong motion records. Natural Hazards, 86(3), 1307-1332.‏
doi.org/10.1007/s11069-017-2745-2
[12] Kayhan, A. H., Demir, A., & Palanci, M. (2022). Multi-functional solution model for spectrum compatible ground motion record selection using stochastic harmony search algorithm. Bulletin of Earthquake Engineering, 20(12), 6407-6440.‏
doi.org/10.1007/s10518-022-01450-8
[13] Mardi, Z., Ansari, A. (2014). Ranking of Attenuation Relationships Using Earthquake 11 August 2012 in Ahar- Varzaghan, Research Bulletin of Seismology and Earthquake Engineering, Volume:16 Issue: 3 , 11-20
[14] Scherbaum, F., F. Cotton, and P. Smith (2004). On the use of response spectral-reference data for the selection and ranking of ground-motion models for seismic-hazard analysis in regions of moderate seismicity: The case of rock motion, Bull. Seismol. Soc. Am. no. 6, 2164–2185.
doi:10.1785/0120030147
[15] Kaklamanos, J., and L. G. Baise (2011). Model validations and comparisons of the next generation attenuation of ground motions (NGA–West) project, Bull. Seismol. Soc. Am. no. 1, 160–175.
doi.org/10.1785/0120100038
[16] 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, Earthq. Spectra 1219–1235
doi.org/10.1193/1.3650372
[17]Bindi, D., Luzi, L., Pacor, F., Franceschina, G., & Castro, R. R. (2006). Ground-motion predictions from empirical attenuation relationships versus recorded data: the case of the 1997–1998 Umbria-Marche, central Italy, strong-motion data set. Bulletin of the Seismological Society of America, 96(3), 984-1002.‏
doi.org/10.1785/0120050102
[18] Shoja-Taheri, J., S. Naserieh, and G. Hadi (2010). A test of the applicability of NGA models to the strong ground-motion data in the Iranian plateau, J. Earthq. Eng. 278–292.
doi:10.1080/13632460903086051
19] Scasserra, G., J. P. Stewart, P. Bazzurro, G. Lanzo, and F. Mollaioli (2009).A comparison of NGA ground-motion [prediction equations to Italian data, Bull. Seismol. Soc. Am. no. 5, 2961–2978.
doi.org/10.1785/0120080133
[20] Scherbaum, F., E. Delavaud, and C. Riggelsen (2009). Model selection in seismic hazard analysis: An information–theoretic perspective, Bull. Seismol. Soc. Am. no. 6, 3234–3247.
doi.org/10.1785/0120080347
[21] Kale, Ö., & Akkar, S. (2013). A New Procedure for Selecting and Ranking Ground‐Motion Prediction Equations (GMPEs): The Euclidean Distance-Based Ranking (EDR) Method. Bulletin of the Seismological Society of America, 103(2A), 1069-1084.
doi.org/10.1785/0120120134
[22] Ghasemi, H., Zare, M., & Fukushima, Y. (2008). Ranking of several ground-motion models for seismic hazard analysis in Iran. Journal of Geophysics and Engineering, 5(3), 301.
doi.org/10.1088/1742-2132/5/3/006
[23] Zafarani, H., & Mousavi, M.(2014) Applicability of different ground-motion prediction models for northern Iran. Natural Hazards, 1-30.
doi.org/10.1007/s11069-014-1151-2
[24] Mousavi, M., A. Ansari, H. Zafarani, and A. Azarbakht (2012). Selection of ground motion prediction models for seismic hazard analysis in the Zagros region, Iran, J. Earthq. Eng. 1184–1207.
doi.org/10.1080/13632469.2012.685568
[25] Farajpour, Zoya, et al. "Ranking of Ground‐Motion Models (GMMs) for Use in Probabilistic Seismic Hazard Analysis for Iran Based on an Independent Data Set." Bulletin of the Seismological Society of America 111.1 (2021): 242-257.
doi.org/10.1785/0120200052
[26] Zafarani, H., et al. "Selection and Modification of Ground Motion Prediction Equations in Different Tectonic Regions of Iran considering Declustered and Non-declustered Earthquake Catalogs." Journal of Earthquake Engineering 27.4 (2023): 981-1011.
doi.org/10.1080/13632469.2022.2033361
[27] Yaghmaei-Sabegh, S., Jodat-Saeidabad, A. Ground Motion Records Selection Based on Scalar Frequency-Content Parameters. Iran J Sci Technol Trans Civ Eng 47, 1041–1057 (2023)
doi.org/10.1007/s40996-022-00969-9
[28] Motaghed, S., Khazaee, M., Eftekhari, N., & Mohammadi, M. (2023). A non-extensive approach to probabilistic seismic hazard analysis. Natural Hazards and Earth System Sciences, 23(3), 1117-1124.‏
doi.org/10.5194/nhess-23-1117-2023
[29] Khanzadi, M., Nicknam, A., Yazdani, A., & Motaghed, S. (2014). A Bayesian approach for seismic recurrence parameters estimation. Journal of Vibroengineering, 16(2), 977-986.‏
[30] Yazdani, A., Yazdani, A., Nicknam, A., Khanzadi, M., & Motaghed, S. (2015). An Artificial Statistical Method to Estimate Seismicity Parameter from Incomplete Earthquake Catalogs, a Case Study in Metropolitan Tehran, Iran. Scientia Iranica, 22(2), 400-409.
[31] Moradiyan, Mohammadhosein, Ghasem Pachideh, and Amin Moshtagh. "Study of seismic behavior and development of fragility curves of divergent braced frames under successive earthquakes." Journal of Structural and Construction Engineering 8.Special Issue 4 (2022): 156-175.
doi.org/10.22065/jsce.2021.263292.2315
[32] Pachideh, Ghasem, Majid Gholhaki, and Amir Saedi Daryan. "Analyzing the damage index of steel plate shear walls using pushover analysis." Structures. Vol. 20. Elsevier, 2019.
 doi.org/10.1016/j.istruc.2019.05.005
[33] Gholhaki, Majid, and Ghasem Pachideh. "Investigating of damage indexes results due to presence of shear wall in building with various stories and spans." Int J Rev Life Sci 5.1 (2015): 992-997.
[34] Berberian, M. (2005). The 2003 Bam urban earthquake: a predictable seismotectonic pattern along the western margin of the rigid Lut block, southeast Iran. Earthquake Spectra, 21(1_suppl), 35-99.‏
doi.org/10.1193/1.2127909
[35] USGS (The United States Geological Survey): “Search Earthquake Catalog”, 2020. http://earthquake.usgs.gov/earthquakes/search,
[36] Hintersberger, E., F. Scherbaum, and S. Hainzl (2007). Update of likelihood based ground-motion model selection for seismic hazard analysis in western central Europe, Bull. Earthq. Eng. 1–16.
doi.org/10.1007/s10518-006-9018-x
[37] Stafford, P. J., Strasser, F. O., & Bommer, J. J. (2008). An evaluation of the applicability of the NGA models to ground-motion prediction in the Euro-Mediterranean region. Bulletin of earthquake Engineering, 6(2), 149-177.
doi.org/10.1007/s10518-007-9053-2
[38] Nash, J. E., and J. V. Sutcliffe (1970). River flow forecasting through conceptual models: Part I—A discussion of principles, J. Hydrol. 282–290.
doi.org/10.1016/0022-1694(70)90255-6
[39] Delavaud, E., F. Scherbaum, N. Kuehn, and C. Riggelsen (2009). Information–theoretic selection of ground-motion prediction equations for seismic hazard analysis: An applicability study using Californian data, Bull. Seismol. Soc. Am. no. 6, 3248–3263.
doi.org/10.1785/0120090055
[40] Delavaud, E., F. Scherbaum, N. Kuehn, and T. Allen (2012). Testing the global applicability of ground-motion prediction equations for active shallow crustal regions, Bull. Seismol. Soc. Am. no. 2, 707–721.
doi.org/10.1785/0120110113
[41] Delavaud, E., F. Cotton, S. Akkar, F. Scherbaum, L. Danciu, C. Beauval,S. Drouet, J. Douglas, R. Basili, M. A. Sandıkkaya, M. Segou,E. Faccioli, and N. Theodoulidis (2012b). Toward a ground-motion logic tree for probabilistic seismic hazard assessment in Europe, J. Seismol. 451–473.
doi.org/10.1007/s10950-012-9281-z
[42] Bayari, M. A., Shabakhty, N., & Izadi Zaman Abadi, E. (2021). Assessing the Effects of Record Selection and Ground-Motion’s Spectral Shape on the Collapse Capacity of the Structures. Journal of Structural and Construction Engineering, 8(Special Issue 3), 420-442. doi: 10.22065/jsce.2021.247703.2234
 doi.org/10.22065/jsce.2021.247703.2234

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History

  • Receive Date: 16 April 2023
  • Revise Date: 02 June 2023
  • Accept Date: 05 June 2023

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