Natural Hazards

, Volume 71, Issue 3, pp 1749–1769 | Cite as

Bayesian probabilities of earthquake occurrences in Shanxi rift system (China)

  • Ying Wang
  • Qinglong Zhang
  • Chao Liu
Original Paper


China has a long history of earthquake records. The Shanxi rift system (SRS) is situated along the axial zone of the domal uplift of the Shanxi Highlands and is the boundary between the Ordos block and the North China Plain block. Strong earthquakes in the SRS have been recorded since the thirteenth century. In our work, we applied the Bayesian probability method using extreme value distribution of earthquake occurrences to estimate the seismic hazard in the SRS. The seismic moment, slip rate, earthquake recurrence rate, and magnitude were considered as the basic parameters for computing the Bayesian prior estimates of the seismicity. These estimates were then updated in terms of Bayes’ theorem and historical estimates of seismicity in the SRS. The probability of occurrence of \(M_{\text{s}} = 5.0\) for Z1, Z2, and Z3 is less than 0.3, 0.1, and 0.6, respectively (T = 5 years). The probability of the occurrence of M \(\ge\) 8.0 is small for the whole SRS. The selection of upper bound magnitude probably influences the result, and the upper bound magnitude of Z1, Z2, and Z3 may be 7.5, 7.0, and 8.5, respectively. We obtained the values of the magnitude of completeness M c (3.2) and the Gutenberg–Richter b value before applying the Bayesian extreme value distribution of earthquake occurrences method.


Central North China Bayesian probabilities Seismic hazard assessment Earthquake occurrences 



This work is financially supported by the National Natural Science Foundation of China (ID 40634021) and the National Science and Technology Major Project of China (ID 2008ZX05035-006-001). Ph.D. candidate Hong Ye and Ph.D. candidate Cai Deng offered their help in completing the manuscript. We are also indebted to the two anonymous reviewers, who provided valuable comments and that significantly improved the original manuscript.


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.School of Earth Sciences and EngineeringNanjing UniversityNanjingChina
  2. 2.Exploration and Production Research InstituteSWPB of SinopecChengduChina
  3. 3.Jinma Oilfield Development CompanyLiaohe Oilfield of CNPCPanjinChina

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