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On the use of AFOSM to estimate major earthquake probabilities in Taiwan

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  • J. Wang
  • H. Kuo-Chen

Abstract

Advanced first-order second-moment (AFOSM) is commonly used to obtain an upper-bound estimate for a probabilistic analysis. This study presents a new AFOSM application to engineering seismology, estimating major earthquake probabilities based on fault length and slip rate, along with an earthquake empirical model subject to a model error of 0.26 M w . The AFOSM analysis shows that the probability could be as high as 64 % for a major earthquake in northern Taiwan to exceed M w 7.0, considering the length and slip rate of the Sanchiao fault are equal to 36 km and 2 ± 1 mm per year. By contrast, the other case study shows that for the Meishan fault in central Taiwan, the probability is “only” 4 % for earthquake magnitude to exceed M w 7.0, given a shorter fault length of 14 km and a larger slip rate of 6 ± 3 mm per year. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • J. Wang & H. Kuo-Chen, 2015. "On the use of AFOSM to estimate major earthquake probabilities in Taiwan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(3), pages 2577-2587, February.
    • Handle: RePEc:spr:nathaz:v:75:y:2015:i:3:p:2577-2587
    DOI: 10.1007/s11069-014-1448-1
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    References listed on IDEAS

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    1. Chi-Hsuan Chen & Jui-Pin Wang & Yih-Min Wu & Chung-Han Chan & Chien-Hsin Chang, 2013. "A study of earthquake inter-occurrence times distribution models in Taiwan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 69(3), pages 1335-1350, December.
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    Cited by:

    1. Yun Xu & J. P. Wang, 2017. "Earthquake recurrence assessment of the active Shanchiao Fault in northern Taiwan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(2), pages 835-851, September.
    2. Jyh-Woei Lin, 2020. "Researching significant earthquakes in Taiwan using two back-propagation neural network models," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 3563-3590, September.

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