Articles | Volume 21, issue 5
https://doi.org/10.5194/nhess-21-1667-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-21-1667-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
31 May 2021
Research article |
| 31 May 2021
| 31 May 2021
Reconstruction of flow conditions from 2004 Indian Ocean tsunami deposits at the Phra Thong island using a deep neural network inverse model
Division of Earth and Planetary Sciences, Graduate School of Science, Kyoto University, Kitashirakawa Oiwakecho, Kyoto, 606-8502, Japan
Hajime Naruse
Division of Earth and Planetary Sciences, Graduate School of Science, Kyoto University, Kitashirakawa Oiwakecho, Kyoto, 606-8502, Japan
Shigehiro Fujino
Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8572, Japan
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Short summary
A case study on the 2004 Indian Ocean tsunami was conducted at the Phra Thong island, Thailand, using a deep neural network (DNN) inverse model. The model estimated tsunami characteristics from the deposits at Phra Thong island. The uncertainty quantification of the result was evaluated. The predicted flow conditions and the depositional characteristics were compared with the reported observed values. This DNN model can serve as an essential tool for tsunami hazard mitigation at coastal cities.
A case study on the 2004 Indian Ocean tsunami was conducted at the Phra Thong island, Thailand,...
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