the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Understanding flow characteristics from tsunami deposits at Odaka, Joban coast, using a DNN inverse model
Rimali Mitra
Tomoya Abe
Abstract. The 2011 Tohoku-oki tsunami inundated the Joban coastal area in the Odaka region of Minamisoma City, up to 2,818 m from the shoreline. In this study, the flow characteristics of the tsunami were reconstructed from deposits using the DNN (deep neural network) inverse model, suggesting that the tsunami inundation occurred in the Froude-supercritical condition. The DNN inverse model effectively estimated the tsunami flow parameters in the Odaka region, including the maximum inundation distance, flow velocity, maximum flow depth, and sediment concentration. Despite having a few topographical instabilities that caused the flow height to fluctuate greatly, the reconstructed maximum flow depth and flow velocity were reasonable and close to the values reported in the field observations. The reconstructed data around the Odaka region were characterized by an extremely high velocity (12.1 m/s). This study suggests that the large fluctuation of flow depths at the Joban coast compared with the stable flow depths at the Sendai plain can be explained by the inundation in the supercritical flow condition.
Rimali Mitra et al.
Status: open (until 30 Jun 2023)
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RC1: 'Comment on egusphere-2023-369', Anonymous Referee #1, 01 Jun 2023
reply
The authors applied their machine learning approach of tsunami deposit inversion (Mitra et al., 2020a,b) to the data from Odaka region in Fukushima Prefecture, where tsunami flow characteristics were different from that in Sendai Plain, Miyagi Prefecture. The inversion analysis yielded an estimated flow speed of 12.1 m/s and flow depth of 2.4 m, which suggest a supercritical (Fr > 1) flow during tsunami inundation. The authors noted that the results are successful, by comparing with some known flow speeds estimated from field records. Validatation of the inverse model based on field records (deposit data and flow measurements) will improve applicability of the method and will improve our understandings on the flow characteristics during inundaiton of large-scale tsunamis.
My main question is related to the assumption of the inverse modeling and interpretation of the results. In this inverse modeling, as explained in the methodology section, flow velocity is assumed to remain constant (in time and space?). If this can be interpreted as averaged velocity over time or space, comparison to the observed values should be made carefully. In particular, I think comparison to observed local maximum velocity is not appropriate.
Iijima et al. (2021) propvided temporal and spatial changes in flow speed estimated based on forward tsunami inundation modeling along a nearby transect in Odaka region. I suggest careful reviewing and comparison of the findings from the paper.
Please find the attached supplement PDF for specific comments.
Rimali Mitra et al.
Data sets
Odaka_DNN_inverse_2011_tsunami: DNN inverse model for 2011 Tohoku-oki tsunami at Odaka, Japan Rimali Mitra, Hajime Naruse, and Tomoya Abe https://doi.org/10.5281/zenodo.4764153
Model code and software
DNN inverse model for 2011 Tohoku-oki tsunami at Odaka, Japan Rimali Mitra, Hajime Naruse, and Tomoya Abe https://doi.org/10.5281/zenodo.4764153
Rimali Mitra et al.
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