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Addressing the epistemic uncertainty in seismic hazard analysis as a basis for seismic design by emphasizing the knowledge aspects and utilizing imprecise probabilities

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Abstract

Epistemic uncertainty in seismic hazard analysis is traditionally addressed by utilizing a logic-tree structure with subjective probabilities for branches. However, many studies have argued that probability is not a suitable choice for addressing epistemic uncertainties; in particular in addressing the background knowledge supporting the probabilities. In this regard, the application of imprecise probability (IP) is investigated. It is discussed that IP could provide a flexible tool for a more objective presentation of experts' knowledge. Moreover, the importance of addressing the strength of knowledge and surprises relative to knowledge in seismic hazard analysis along with methods to do so, are discussed. Then, a method is proposed for providing seismic hazard curves with consideration of IPs for logic-tree branches and addressing the knowledge dimension. It is suggested to consider the worst possible combination of branch probabilities for the expected intensity measures at all return-periods in order to construct the seismic hazard curve. A process is also suggested to demonstrate how the proposed seismic hazard analysis method could be properly used in the seismic design of buildings. The performance of the suggested method was investigated on Uniform California Earthquake Rupture Forecast, Version 2 (UCERF2) logic-tree for two sites in Los Angeles and Oakland, California, US. The results indicate that even with a similar logic-tree, the effects of imprecision in logic-tree weights could be different at different sites.

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No specific data is available form this study. They all could be generated using the procedure described in the manuscript.

References

  • Abrahamson NA, Bommer JJ (2005) Probability and uncertainty in seismic hazard analysis. Earthq Spectra 21(2):603–607

    Article  Google Scholar 

  • Augustin T (2005) Generalized basic probability assignments. Int J Gen Syst 34(4):451–463

    Article  Google Scholar 

  • Augustin T et al (2014) Introduction to imprecise probabilities. John Wiley & Sons, New York

    Book  Google Scholar 

  • Aven T (2008) A semi-quantitative approach to risk analysis, as an alternative to QRAs. Reliab Eng Syst Saf 93(6):790–797

    Article  Google Scholar 

  • Aven T (2010) On the need for restricting the probabilistic analysis in risk assessments to variability. Risk Anal Int J 30(3):354–360

    Article  Google Scholar 

  • Aven T (2013a) On how to deal with deep uncertainties in a risk assessment and management context. Risk Anal 33(12):2082–2091

    Article  Google Scholar 

  • Aven T (2013b) Practical implications of the new risk perspectives. Reliab Eng Syst Saf 115:136–145

    Article  Google Scholar 

  • Aven T (2014) Risk, surprises and black swans: fundamental ideas and concepts in risk assessment and risk management. Routledge

  • Aven T (2015) Implications of black swans to the foundations and practice of risk assessment and management. Reliab Eng Syst Saf 134:83–91

    Article  Google Scholar 

  • Aven T (2017a) Improving the foundation and practice of reliability engineering. Proc Inst Mech Eng Part O J Risk Reliab 231(3):295–305

    Google Scholar 

  • Aven T (2017b) Improving risk characterisations in practical situations by highlighting knowledge aspects, with applications to risk matrices. Reliab Eng Syst Saf 167:42–48

    Article  Google Scholar 

  • Aven T (2019) The cautionary principle in risk management: foundation and practical use. Reliab Eng Syst Saf 191:106585

    Article  Google Scholar 

  • Aven T, Kristensen V (2019) How the distinction between general knowledge and specific knowledge can improve the foundation and practice of risk assessment and risk-informed decision-making. Reliab Eng Syst Saf 191:106553

    Article  Google Scholar 

  • Aven T, Reniers G (2013) How to define and interpret a probability in a risk and safety setting. Saf Sci 51(1):223–231

    Article  Google Scholar 

  • Aven T, Zio E (2011) Some considerations on the treatment of uncertainties in risk assessment for practical decision making. Reliab Eng Syst Saf 96(1):64–74

    Article  Google Scholar 

  • Aven T, Zio E (2018) Knowledge in risk assessment and management. John Wiley & Sons, New York

    Book  Google Scholar 

  • Bard P-Y et al (1988) The Mexico earthquake of September 19, 1985—a theoretical investigation of large-and small-scale amplification effects in the Mexico City Valley. Earthq Spectra 4(3):609–633

    Article  Google Scholar 

  • Beven K et al (2018) Epistemic uncertainties and natural hazard risk assessment-Part 1: a review of different natural hazard areas. Nat Hazard 18(10):2741–2768

    Article  Google Scholar 

  • Bjerga T, Aven T, Zio E (2014) An illustration of the use of an approach for treating model uncertainties in risk assessment. Reliab Eng Syst Saf 125:46–53

    Article  Google Scholar 

  • Bommer JJ (2012) Challenges of building logic trees for probabilistic seismic hazard analysis. Earthq Spectra 28(4):1723–1735

    Article  Google Scholar 

  • Bommer JJ, Scherbaum F (2008) The use and misuse of logic trees in probabilistic seismic hazard analysis. Earthq Spectra 24(4):997–1009

    Article  Google Scholar 

  • Boole G (1854) An investigation of the laws of thought: on which are founded the mathematical theories of logic and probabilities, vol 2. Walton and Maberly, London

    Google Scholar 

  • Boore DM (2003) Simulation of ground motion using the stochastic method. Pure Appl Geophys 160(3):635–676

    Article  Google Scholar 

  • Boore DM, Atkinson GM (2008) Ground-motion prediction equations for the average horizontal component of PGA, PGV, and 5%-damped PSA at spectral periods between 0.01 s and 10.0 s. Earthq Spectra 24(1):99–138

  • Bozorgnia Y et al (2014) NGA-West2 research project. Earthq Spectra 30(3):973–987

    Article  Google Scholar 

  • Budnitz R, Apostolakis G, Boore D (1997) Recommendations for probabilistic seismic hazard analysis: guidance on uncertainty and use of experts. Nuclear Regulatory Commission, Washington, DC (United States)

  • Campbell KW, Bozorgnia Y (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):139–171

  • Chiou B-J, Youngs RR (2008) An NGA model for the average horizontal component of peak ground motion and response spectra. Earthq Spectra 24(1):173–215

    Article  Google Scholar 

  • Dall’Asta A et al (2021) Influence of time-dependent seismic hazard on structural design. Bull Earthq Eng 19(6):2505–2529

    Article  Google Scholar 

  • Dubois D (2007) Uncertainty theories: a unified view. In: IEEE cybernetic systems conference, Dublin, Ireland, Invited Paper

  • Dubois D (2010) Representation, propagation, and decision issues in risk analysis under incomplete probabilistic information. Risk Anal Int J 30(3):361–368

    Article  Google Scholar 

  • Dubois D, Prade H (2012) Possibility theory: an approach to computerized processing of uncertainty. Springer, Berlin

    Google Scholar 

  • Farajpour Z et al (2021) Ranking of ground-motion models (GMMs) for use in probabilistic seismic hazard analysis for Iran based on an independent data set. Bull Seismol Soc Am 111(1):242–257

    Article  Google Scholar 

  • Ferson S, Ginzburg LR (1996) Different methods are needed to propagate ignorance and variability. Reliab Eng Syst Saf 54(2–3):133–144

    Article  Google Scholar 

  • Ferson S et al (2004) Summary from the epistemic uncertainty workshop: consensus amid diversity. Reliab Eng Syst Saf 85(1–3):355–369

    Article  Google Scholar 

  • Field EH, Jordan TH, Cornell CA (2003) OpenSHA: a developing community-modeling environment for seismic hazard analysis. Seismol Res Lett 74(4):406–419

    Article  Google Scholar 

  • Field EH et al (2009) Uniform California earthquake rupture forecast, version 2 (UCERF 2). Bull Seismol Soc Am 99(4):2053–2107

    Article  Google Scholar 

  • Field EH et al (2014) Uniform California earthquake rupture forecast, version 3 (UCERF3)—the time-independent model. Bull Seismol Soc Am 104(3):1122–1180

    Article  Google Scholar 

  • Flage R et al (2014) Concerns, challenges, and directions of development for the issue of representing uncertainty in risk assessment. Risk Anal 34(7):1196–1207

    Article  Google Scholar 

  • Flage R, Dubois D, Aven T (2016) Combined analysis of unique and repetitive events in quantitative risk assessment. Int J Approx Reason 70:68–78

    Article  Google Scholar 

  • Ghasemi H, Zare M, Fukushima Y (2008) Ranking of several ground-motion models for seismic hazard analysis in Iran. J Geophys Eng 5(3):301–310

    Article  Google Scholar 

  • Helton JC, Oberkampf WL (2004) Alternative representations of epistemic uncertainty. Reliab Eng Syst Saf 1(85):1–10

    Article  Google Scholar 

  • Iervolino I (2013) Probabilities and fallacies: why hazard maps cannot be validated by individual earthquakes. Earthq Spectra 29(3):1125–1136

    Article  Google Scholar 

  • Kuznetsov VP (1991) Interval statistical models. Radio i Svyaz, Moscow

    Google Scholar 

  • Lindley DV (2000) The philosophy of statistics. J R Stat Soc Ser D (The Statistician) 49(3):293–337

    Google Scholar 

  • Mahsuli M, Rahimi H, Bakhshi A (2019) Probabilistic seismic hazard analysis of Iran using reliability methods. Bull Earthq Eng 17(3):1117–1143

    Article  Google Scholar 

  • McGuire RK, Cornell CA, Toro GR (2005) The case for using mean seismic hazard. Earthq Spectra 21(3):879–886

    Article  Google Scholar 

  • Mousavi M et al (2012) Selection of ground motion prediction models for seismic hazard analysis in the Zagros region, Iran. J Earthq Eng 16(8):1184–1207

    Article  Google Scholar 

  • Mousavi Bafrouei S et al (2014) Seismic hazard zoning in Iran and estimating peak ground acceleration in provincial capitals. J Earth Space Phys 40(4):15–38

    Google Scholar 

  • Muir-Wood R (2016) The cure for catastrophe: how we can stop manufacturing natural disasters. Basic Books

  • Mulargia F, Stark PB, Geller RJ (2017) Why is probabilistic seismic hazard analysis (PSHA) still used? Phys Earth Planet Inter 264:63–75

    Article  Google Scholar 

  • O’Hagan A (2019) Expert knowledge elicitation: subjective but scientific. Am Stat 73(sup1):69–81

    Article  Google Scholar 

  • O'Hagan A et al (2006) Uncertain judgements: eliciting experts' probabilities, John Wiley & Sons, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England

    Book  Google Scholar 

  • Oxford University Press (OUP) (2020) Definition of robustness. https://www.lexico.com/definition/robustness. [Cited 20 Sept 2020]

  • Paté-Cornell E (2012) On “black swans” and “perfect storms”: risk analysis and management when statistics are not enough. Risk Anal Int J 32(11):1823–1833

    Article  Google Scholar 

  • Petersen MD et al (2008) United States national seismic hazard maps. No. 2008-3018. U.S. Geological Survey, Reston, Virginia, USA

    Google Scholar 

  • Rahimi H, Mahsuli M (2019) Structural reliability approach to analysis of probabilistic seismic hazard and its sensitivities. Bull Earthq Eng 17(3):1331–1359

    Article  Google Scholar 

  • Savage LJ (1954) The foundations of statistics. Jon Wiley and Sons. Inc., New York

    Google Scholar 

  • Shafer G (1976) A mathematical theory of evidence, vol 42. Princeton University Press, Princeton

    Book  Google Scholar 

  • Shahjouei A, Pezeshk S (2016) Alternative hybrid empirical ground-motion model for central and eastern North America using hybrid simulations and NGA-West2 models. Bull Seismol Soc Am 106(2):734–754

    Article  Google Scholar 

  • Shortridge J, Aven T, Guikema S (2017) Risk assessment under deep uncertainty: a methodological comparison. Reliab Eng Syst Saf 159:12–23

    Article  Google Scholar 

  • Stein S, Stein JL (2013) Shallow versus deep uncertainties in natural hazard assessments. EOS Trans Am Geophys Union 94(14):133–134

    Article  Google Scholar 

  • Stein S, Geller RJ, Liu M (2012) Why earthquake hazard maps often fail and what to do about it. Tectonophysics 562:1–25

    Article  Google Scholar 

  • Stucchi M et al (2011) Seismic hazard assessment (2003–2009) for the Italian building code. Bull Seismol Soc Am 101(4):1885–1911

    Article  Google Scholar 

  • Sugawara D et al (2012) Assessing the magnitude of the 869 Jogan tsunami using sedimentary deposits: prediction and consequence of the 2011 Tohoku-oki tsunami. Sediment Geol 282:14–26

    Article  Google Scholar 

  • Taleb NN (2007) The black swan: the impact of the highly improbable, vol 2. Random house, New York

    Google Scholar 

  • Tavakoli B, Ghafory-Ashtiany M (1999) Seismic hazard assessment of Iran

  • Troffaes MC (2007) Decision making under uncertainty using imprecise probabilities. Int J Approx Reason 45(1):17–29

    Article  Google Scholar 

  • Tversky A, Koehler DJ (1994) Support theory: a nonextensional representation of subjective probability. Psychol Rev 101(4):547

    Article  Google Scholar 

  • Van Houtte C, Drouet S, Cotton F (2011) Analysis of the origins of κ (kappa) to compute hard rock to rock adjustment factors for GMPEs. Bull Seismol Soc Am 101(6):2926–2941

    Article  Google Scholar 

  • Walker WE, Marchau VA, Swanson D (2010) Addressing deep uncertainty using adaptive policies: introduction to section 2. Technol Forecast Soc Chang 77(6):917–923

    Article  Google Scholar 

  • Walley P (1991) Statistical reasoning with imprecise probabilities

  • Weatherill G, Cotton F (2020) A ground motion logic tree for seismic hazard analysis in the stable cratonic region of Europe: regionalisation, model selection and development of a scaled backbone approach. Bull Earthq Eng 18(14):6119–6148

    Article  Google Scholar 

  • Woo G (2018) Counterfactual disaster risk analysis. Var J 2:279–291

    Google Scholar 

  • Woo G (2019) Downward counterfactual search for extreme events. Front Earth Sci 7:340

    Article  Google Scholar 

  • Woo G, Mignan A (2018) Counterfactual analysis of runaway earthquakes. Seismol Res Lett 89(6):2266–2273

    Article  Google Scholar 

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  1. Civil Engineering Department, Sharif University of Technology, P O Box: 11155-4313, Tehran, Iran

    Babak Ghods & Fayaz R. Rofooei

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  1. Babak Ghods
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  2. Fayaz R. Rofooei
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We confirm that the manuscript has been read and approved for submission by all the named authors. The authors, B. Ghods and F. R. Rofooei conceived the presented idea. B. Ghods developed the theory and performed the computations. All authors discussed the results and contributed to the final manuscript.

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Correspondence to Fayaz R. Rofooei.

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Ghods, B., Rofooei, F.R. Addressing the epistemic uncertainty in seismic hazard analysis as a basis for seismic design by emphasizing the knowledge aspects and utilizing imprecise probabilities. Bull Earthquake Eng 20, 741–764 (2022). https://doi.org/10.1007/s10518-021-01252-4

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