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Natural Hazards

, Volume 94, Issue 3, pp 1163–1185 | Cite as

Source inversion and numerical simulation of 2017 Mw 8.1 Mexico earthquake tsunami

  • Zhiyuan Ren
  • Xinran Ji
  • Peitao Wang
  • Jingming Hou
  • Di Shan
  • Lianda Zhao
Original Paper
  • 60 Downloads

Abstract

Based on the nonlinear shallow water equations and tsunami measurement, this study has presented the inversion source, which is generated by an earthquake of Mw 8.1 that occurred in Pijijiapan, Mexico, on September 8, 2017. The seafloor deformation induced by the inversed tsunami source reached maximum uplift of 0.5 m and subsidence of − 1.4 m. The numerical results simulated by the inversed source could match well with the measured data. We characterize tsunami propagation scenarios regarding tsunami amplitude and currents. Unlike the feature of tsunami wave amplitude propagation in the deep ocean, the currents induced by the tsunami are confined to shallow coasts, noted as the contour of 400 m water depth. Although most regions endure tsunamigenic currents below 3 knots (1.5 m/s) or in range of 3–6 knots (1.5–3 m/s), which is the threshold from no damage to minor–moderate damage, the duration lasting several hours indicates the potential beach erosion and sediment transport. The eddies of tsunami-induced currents could be identified at the entrance gate of lagoon named Mar Muerto with a finer grid. Finally, the dispersion effect has been investigated on tsunami propagation in the Pacific Ocean.

Keywords

2017 Mexico earthquake of Mw 8.1 Tsunami source inversion Numerical simulation Tsunamigenic coastal currents Dispersion effect 

Notes

Acknowledgements

Discussions with Dr. Yong Wei at NOAA, Associate Professor, Ting Chen at Wuhan University, and Dr. Chao An and Prof. Hua Liu at SJTU are appreciated.

Funding

This research is supported by the National Science and Technology Major Project (Grant No. 2016YFC1401500), the Hainan Provincial Natural Science Foundation of China (Grant No. 517058), the National Natural Science Foundation of China (Grant No. 51709069), the Innovation Program for The Excellent Youth Scholars in Science and Technology of Hainan science and Technology Association (Grant No. QXXM201709), the Opening fund of State Key Laboratory of Coastal and Offshore Engineering (Grant No. LP1607), and the Opening fund of State Key Laboratory of Ocean Engineering (Shanghai Jiao Tong University) (Grant No. 1604).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Human and animal rights

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.National Marine Environmental Forecasting CenterBeijingChina
  2. 2.College of Civil Engineering and ArchitectureHainan UniversityHaikouChina

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