Articles | Volume 24, issue 2
https://doi.org/10.5194/nhess-24-429-2024
https://doi.org/10.5194/nhess-24-429-2024
Research article
 | 
08 Feb 2024
Research article |  | 08 Feb 2024

Understanding flow characteristics from tsunami deposits at Odaka, Joban Coast, using a deep neural network (DNN) inverse model

Rimali Mitra, Hajime Naruse, and Tomoya Abe

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Cited articles

Abe, T., Goto, K., and Sugawara, D.: Relationship between the maximum extent of tsunami sand and the inundation limit of the 2011 Tohoku-oki tsunami on the Sendai Plain, Japan, Sediment. Geol., 282, 142–150, https://doi.org/10.1016/j.sedgeo.2012.05.004, 2012. a, b
Ali Hasan Muhammad, R. and Tanaka, N.: Energy reduction of a tsunami current through a hybrid defense system comprising a sea embankment followed by a coastal forest, Geosci., 9, 247, https://doi.org/10.3390/geosciences9060247, 2019. a
Charvet, I., Macabuag, J., and Rossetto, T.: Estimating tsunamiinduced building damage through fragility functions: critical review and research needs, Front. Built Environ., 3, 36, 2017. a
Choowong, M., Murakoshi, N., Hisada, K. I., Charusiri, P., Charoentitirat, T., Chutakositkanon, V., Jankaew, K., Kanjanapayont, P., and Phantuwongraj, S.: 2004 Indian Ocean tsunami inflow and outflow at Phuket, Thailand, Mar. Geol., 248, 179–192, https://doi.org/10.1016/j.margeo.2007.10.011, 2008. a, b
Fritz, H. M., Borrero, J. C., Synolakis, C. E., and Yoo, J.: 2004 Indian Ocean tsunami flow velocity measurements from survivor videos, Geophys. Res. Lett., 33, https://doi.org/10.1029/2006GL026784, 2006. a
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This study estimates the behavior of the 2011 Tohoku-oki tsunami from its deposit distributed in the Joban coastal area. In this study, the flow characteristics of the tsunami were reconstructed using the DNN (deep neural network) inverse model, suggesting that the tsunami inundation occurred in the very high-velocity condition.
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