Impact of fault parameter uncertainties on earthquake recurrence probability examined by Monte Carlo simulation — an example in Central Taiwan

• Published in: Engineering geology 2012-02, Vol.126, p.67-74
• Main Authors: Wang, Jui-Pin, Lin, Chii-Wen, Taheri, Hamed, Chan, Wen-Shan
• Format: Article
• Language: English
• Subjects: Applied sciences; Buildings. Public works; Computation methods. Tables. Charts; Earth sciences; Earth, ocean, space; Earthquake recurrence probability; Engineering and environment geology. Geothermics; Exact sciences and technology; Geotechnics; Monte Carlo simulation; Natural hazards: prediction, damages, etc; Probabilistic analysis; Structural analysis. Stresses; Structure-soil interaction; Uncertainty
• ISSN: 0013-7952; 1872-6917
• DOI: 10.1016/j.enggeo.2011.12.012

The region around Taiwan is well known for its unique geological setting which has resulted in a high seismicity. The Central Geological Survey, Taiwan (CGST), has launched a series of investigation on characterizing the active faults on the island. The CGST revealed that there are 33 active faults and their fault parameters are suggested in the latest publication in 2010. However, the uncertainties of return period and earthquake magnitude are not provided. The main objective of the paper is to study the impact of “unspecified” parameter uncertainties on recurrence earthquake probabilities. In addition, a numerical approach involving the use of Monte Carlo simulation was proposed to estimate the exceedance probabilities in which the parameter uncertainties were taken into account. The Meishan fault in Central Taiwan with the best-estimate return period of 162years and earthquake magnitude of 7.1 was used as an example. The analyses verified the impact of parameter uncertainties on the exceedance probability in fault-induced earthquake recurrence. When uncertainty is high, the exceedance probability associated with large magnitudes is high. It was also observed that the probabilistic analysis in this study can generate a realistic, continuous distribution of exceedance probabilities that cannot be obtained by a deterministic approach. The best-estimate distribution of exceedance probability was established by enveloping the curves estimated by both deterministic and probabilistic approaches. Accordingly, the best-estimate exceedance probability for a 7.5-magnitude earthquake recurring in 2011–2060 induced by the Meishan fault in Central Taiwan was estimated as 11%.