論文

査読有り
2020年

Uncertainty of probabilistic tsunami hazard assessment of Zihuatanejo (Mexico) due to the representation of tsunami variability

Coastal Engineering Journal
  • Miyashita, T.
  • ,
  • Mori, N.
  • ,
  • Goda, K.

62
3
開始ページ
413
終了ページ
428
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1080/21664250.2020.1780676
出版者・発行元
Informa {UK} Limited

This study conducts a probabilistic tsunami hazard assessment (PTHA) and compares two approaches to representing earthquake source variability in the PTHA. The target region is the coast of Zihuatanejo in the State of Guerrero, Mexico. First, numerous synthetic fault slip distributions are generated using a stochastic random-phase process. The moment magnitude ranges from 7.8 to 8.6. A numerical tsunami simulation is implemented for each earthquake fault slip. The result of the Monte Carlo simulation indicates the tsunami heights at the nearshore of city areas tend to be higher. Then, the exceedance probabilities of tsunami height are estimated and compared using two different PTHA approaches: the random phase approach and the logic tree approach. The logic tree can generally incorporate many types of uncertainty, but this study focuses on the earthquake source uncertainty for comparison. The comparison result indicates significant differences between the two tsunami hazard models. Additionally, the logic tree approach is used to investigate the possible ranges in tsunami heights for extreme events by assuming that a sizable epistemic uncertainty exists in a given region. The tsunami heights for a 1,000-year event vary significantly when the weighting values for the paths in the logic tree are changed.

リンク情報
DOI
https://doi.org/10.1080/21664250.2020.1780676
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000549075000001&DestApp=WOS_CPL
URL
http://www.scopus.com/inward/record.url?eid=2-s2.0-85087958977&partnerID=MN8TOARS
ID情報
  • DOI : 10.1080/21664250.2020.1780676
  • ISSN : 2166-4250
  • eISSN : 1793-6292
  • ORCIDのPut Code : 79565228
  • SCOPUS ID : 85087958977
  • Web of Science ID : WOS:000549075000001

エクスポート
BibTeX RIS