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Bayesian seismic hazard analysis

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Abstract

The Bayesian approach aims to obtain an inference utilizing indirect data as the prior information and direct data (or samples) as the observation. This paper presents a new Bayesian approach to estimate the annual rate of PGA exceedance (or SA: spectral acceleration), based on several sources of indirect data (e.g., ground motion prediction equations, seismic source models, and earthquake catalogs) and the directly recorded PGA data. In addition to the methodology, three case studies in Taiwan were also conducted. Like other Bayesian calculations, the case studies show that the Bayesian estimate is in between the estimate sorely based on the indirect data and the estimate sorely based on the PGA records (direct data), demonstrating the new Bayesian approach for estimating the annual rate of PGA exceedance (also known as seismic hazard) is fundamentally robust.

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source model used in a PSHA study for Taipei (Taiwan); the value in the parenthesis is the b-value of the Gutenberg-Richter recurrence law (after Wang et al. 2013)

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References

  • Akeju OV, Senetakis K, Wang Y (2019) Bayesian parameter identification and model selection for normalized modulus reduction curves of soils. J Earthquake Eng 23:305–333

    Article  Google Scholar 

  • Anbazhagan P, Vinod JS, Sitharam TG (2009) Probabilistic seismic hazard analysis of Bangalore. Nat Hazards 48(2):145–166

    Article  Google Scholar 

  • Ang AHS, Tang WH (2007) Probability concepts in engineering; emphasis on applications to civil and environmental engineering. John Wiley & Sons, New Jersey

    Google Scholar 

  • Bommer JJ, Scherbaum F (2008) The use and misuse of logic trees in probabilistic seismic hazard analysis. Earthq Spectra 70:165–168

    Google Scholar 

  • Cao Z, Wang Y (2014) Bayesian model comparison and characterization of undrained shear strength. J Geotech Geoenviron Eng 140(6):04014018

    Article  Google Scholar 

  • Castanos H, Lomnitz C (2002) PSHA: is it science? Eng Geol 66:315–317

    Article  Google Scholar 

  • Central Weather Bureau of Taiwan (CWB): https://scweb.cwb.gov.tw/zh-tw/page/disaster/ . (access on 15 Jan 2022)

  • Cheng CT, Chiou SJ, Lee CT, Tsai YB (2007) Study on probabilistic seismic hazard maps of Taiwan after Chi-Chi earthquake. J GeoEngineering 2:19–28

    Google Scholar 

  • Ching J, Phoon KK, Chen YC (2010) Reducing shear strength uncertainties in clay by multivariate correlations. Can Geotech J 47(1):16–33

    Article  Google Scholar 

  • Cornell CA (1968) Engineering seismic risk analysis. Bull Seis Soc Am 58(5):1583–1606

    Article  Google Scholar 

  • Hapke C, Plant N (2010) Predicting coastal cliff erosion using a Bayesian probabilistic model. Mar Geol 278(1):140–149

    Article  Google Scholar 

  • Kolathayar S, Sitharam TG (2012) Comprehensive probabilistic seismic hazard analysis of the Andaman-Nicobar Regions. Bull Seis Soc Am 102:2063–2076

    Article  Google Scholar 

  • Kramer SL (1996) Geotechnical earthquake engineering. Prentice Hall Inc., New Jersey

    Google Scholar 

  • Krinitzsky EL (2002) Epistematic and aleatory uncertainty: a new shtick for probabilistic seismic hazard analysis. Eng Geol 66:157–157

    Article  Google Scholar 

  • Lin PS, Lee CT, Cheng CT, Sung CH (2011) Response spectral attenuation relations for shallow crustal earthquakes in Taiwan. Eng Geol 121:150–164

    Article  Google Scholar 

  • Musson RMW (2012a) PSHA validated by quasi observational means. Seismol Res Lett 83:130–134

    Article  Google Scholar 

  • Musson RMW (2012b) Probability in PSHA: reply to comment on “PSHA validated by quasi observational means” by Z. Wang Seismol Res Lett 83:717–719

    Article  Google Scholar 

  • Ng IT, Yuen KV, Lao NK (2016) Probabilistic characterization of cyclic shear modulus reduction for normally to moderately over-consolidated clays. Earthq Eng Eng Vib 15:495–508

    Article  Google Scholar 

  • Pan YX, Ventura CE, Tannert T (2020) Damage index fragility assessment of low-rise light-frame wood buildings under long duration subduction earthquakes. Struct Saf 84:101940

    Article  Google Scholar 

  • Petersen MD, Dewey J, Hartzell S, Mueller C, Harmsen S, Frankel A, Rukstales K (2004) Probabilistic seismic hazard analysis for Sumatra, Indonesia and across the Southern Malaysian Peninsula. Tectonophysics 390:141–158

    Article  Google Scholar 

  • Phoon KK, Kulhawy FH (1999) Characterization of geotechnical variability. Can Geotech J 36(4):612–624

    Article  Google Scholar 

  • Stirling M, Litchfield N, Gerstenberger M, Clark D, Bradley B, Beavan J, McVerry G, Van Dissen R, Nicol A, Wallace L, Buxton R (2011) Preliminary probabilistic seismic hazard analysis of the CO2CRC Otway project site, Victoria, Australia. Bull Seis Soc Am 101:2726–2736

    Article  Google Scholar 

  • USNRC (2007) A performance-based approach to define the site-specific earthquake ground motion. Regulatory Guide 1.208. United States Nuclear Regulatory Commission

  • Wang JP, Chang SC, Xu Y (2016) Best-estimate return period of the Sanchiao fault in Taipei: Bayesian approach. Natural Hazards Review ASCE 17(1):06015001

    Article  Google Scholar 

  • Wang JP, Huang D, Cheng CT, Shao KS, Wu YC, Chang CW (2013) Seismic hazard analysis for Taipei City including deaggregation, design spectra, and time history with Excel applications. Comput Geosci 52:146–154

    Article  Google Scholar 

  • Wang JP, Xu Y (2015) Estimating the standard deviation of soil properties with limited samples through the Bayesian approach. Bull Eng Geol Env 74:271–278

    Article  Google Scholar 

  • Wang JP, Xu Y, Kuochen H, Wu YM (2018) CAV site-effect assessment: a case study of Taipei Basin. Soil Dyn Earthq Eng 108:142–149

    Article  Google Scholar 

  • Wang JP, Lin YH (2021) Application of Bayesian calculation to determine logic-tree weights for ground motion prediction equations: seismological case studies in Taiwan. Eng Geol 294:106347

    Article  Google Scholar 

  • Wang Z (2012) Comment on “PSHA validated by quasi observational means” by R.M.W Musson. Seismol Res Lett 83:714–716

    Article  Google Scholar 

  • Wu MH, Wang JP (2020) Relationship between earthquake magnitude and fault length for Taiwan: Bayesian approach. J GeoEng 15(2):69–76

    Google Scholar 

  • Wu YM, Shin TC, Chang CH (2001) Neal real-time mapping of peak ground acceleration and peak ground velocity following a strong earthquake. Bull Seis Soc Am 91:1218–1228

    Article  Google Scholar 

  • Xu Y, Wang JP, Wu YM, Kuochen H (2019) Prediction models and seismic hazard assessment: a case study from Taiwan. Soil Dyn Earthq Eng 122:94–106

    Article  Google Scholar 

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Acknowledgements

The authors appreciate the editors and reviewers for their constructive comments, improving the paper in so many aspects

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Authors and Affiliations

  1. Department of Civil Engineering, National Central University, Taoyuan, Taiwan

    J. P. Wang & Chia-Ying Sung

  2. Department of Earth Sciences, the University of Hong Kong, Pok Fu Lam, Hong Kong

    Su-Chin Chang

  3. Research Center for Hazard Mitigation and Prevention, National Central University, Taoyuan, Taiwan

    J. P. Wang

Authors
  1. J. P. Wang
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  2. Chia-Ying Sung
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  3. Su-Chin Chang
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Corresponding author

Correspondence to J. P. Wang.

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Wang, J.P., Sung, CY. & Chang, SC. Bayesian seismic hazard analysis. Bull Eng Geol Environ 81, 265 (2022). https://doi.org/10.1007/s10064-022-02768-y

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