Understanding flow characteristics from tsunami deposits at Odaka, Joban coast, using a DNN inverse model

Abstract

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.

A Medium‐Sized Paleo‐Tsunami Reconstruction by a Deep Neural Network Processing Sedimentary Deposits

“…The combination of forward 2D models with deep neural network (DNN) models has been successfully used to reconstruct the characteristics of the 2011 Tohoku‐oki (Mitra et al., 2020; Naruse & Abe, 2017), 2004 Indian Ocean (Mitra et al., 2021) and other tsunamis (e.g., Mitra et al., 2023). The direct observation of the events and the rapid sampling of the tsunami deposits validated the model results.…”