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

Download

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-369', Anonymous Referee #1, 01 Jun 2023
    • CC1: 'Reply on RC1', Rimali Mitra, 29 Jun 2023
    • AC1: 'Reply on RC1', Hajime Naruse, 16 Jul 2023
  • RC2: 'Comment on egusphere-2023-369', Masaki Yamada, 20 Jun 2023
    • CC2: 'Reply on RC2', Rimali Mitra, 29 Jun 2023
    • AC2: 'Reply on RC2', Hajime Naruse, 16 Jul 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Publish subject to minor revisions (review by editor) (30 Sep 2023) by Rachid Omira
AR by Hajime Naruse on behalf of the Authors (27 Nov 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (20 Dec 2023) by Rachid Omira
AR by Hajime Naruse on behalf of the Authors (22 Dec 2023)
Download
Short summary
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.
Altmetrics
Final-revised paper
Preprint