Tsunami inundation, sediment transport, and deposition process of tsunami deposits on coastal lowland inferred from the Tsunami Sand Transport Laboratory Experiment (TSTLE)

Yoshii, Takumi; Tanaka, Shiro; Matsuyama, Masafumi

doi:10.1016/j.margeo.2018.03.007

Cited by 35 publications

(13 citation statements)

References 41 publications

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“…The balance between erosion and deposition was examined also by flume experiments (e.g., Hasegawa et al 2001;Yoshii et al 2017Yoshii et al , 2018. Hasegawa et al (2001) carried out the flume experiment with land slope of 50‰ and found that approx.…”

Section: Relations Among Topography Tsunami Behavior and Sedimentary Processmentioning

confidence: 99%

“…60% of onshore depositional volume, which was transported by run-up flow, was discharged into the sea by return flow. Yoshii et al (2017Yoshii et al ( , 2018 performed the flume experiment with three cases of land slope (0‰, 10‰, 20‰) and showed that land slope plays an important role in balance between sediment supply resulting from inflow and sediment remigration attributed to outflow. The role of tsunami as a geomorphological agent, which is reflected to patterns of tsunami-induced erosion and deposition, can sometimes be very different between valleys and coastal plains.…”

Section: Relations Among Topography Tsunami Behavior and Sedimentary Processmentioning

confidence: 99%

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Spatial distribution and sources of tsunami deposits in a narrow valley setting - insight from 2011 Tohoku-oki tsunami deposits in northeastern Japan

Abe

Goto

Sugawara

2020

Prog Earth Planet Sci

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Sedimentary processes and spatial distributions of tsunami deposits in valleys have poorly been understood despite many paleo-tsunami deposits have recently been discovered from sedimentary sequences in valleys. We conducted an exhaustive investigation of 2011 Tohoku-oki tsunami deposits in a narrow valley at the south end of Sendai Plain, northeastern Japan, to collect sedimentological data of the tsunami deposits in the valley and to correlate them with tsunami inundation and associated sedimentary processes. The tsunami deposits were investigated at 174 sites to cover the entire inundation area of the narrow valley. We analyzed thickness, sedimentary structures, and grain size of the tsunami deposits to correlate their spatial variation with tsunami flow hydrodynamics and topographic features. The tsunami deposits, composed of sand and mud layers, were found to be 0–40 cm thick. Sand thickness generally decreased inland with local fluctuation. The sand layer was mostly composed of single unit on the upper main valley and sub-valleys, although it was mainly composed of 2–6 sub-units on the lower main valley and in the pond. Mud thickness is strongly controlled by local sources, namely, the rice paddy and the pond. The depositional area of the mud layer coincides with the distribution of the rice paddies and the pond location. The mud layer also considerably thicker in and around the pond. These results indicate that sediment thickness and sedimentary structures are highly varied on a local scale, but they are generally controlled by local topography. Sediment budget in the valley was estimated, and it may provide implications to general sedimentary process. Total depositional volume of the tsunami sand deposited on land is half of the volume of sediments disappeared from the sandy beach and sand dune, suggesting the rest must have been discharged into the sea by the backwash. Spatial distribution of sediment thickness and sedimentary structures as well as sedimentary processes inferred from 2011 Tohoku-oki tsunami deposits will benefit searching and identification of paleo-tsunami deposits in valleys of other coastal environments.

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Section: Relations Among Topography Tsunami Behavior and Sedimentary Processmentioning

confidence: 99%

Section: Relations Among Topography Tsunami Behavior and Sedimentary Processmentioning

confidence: 99%

Spatial distribution and sources of tsunami deposits in a narrow valley setting - insight from 2011 Tohoku-oki tsunami deposits in northeastern Japan

Abe

Goto

Sugawara

2020

Prog Earth Planet Sci

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“…In an attempt to contribute to the paleo tsunami research, Johnson et al (2016) studied deposits left by a breaking bore and concluded that an existing advection-settling model was able to predict flow depths within a factor two and velocities within a factor 1.5, thus showing a reasonable performance of one of the paleo tsunami inverse models. Yoshii et al (2017Yoshii et al ( , 2018 studied experimentally tsunami deposits in their 205 m long flume for a range of topographies. They concluded that the majority of the deposits came from the onshore flow.…”

Section: Introductionmentioning

confidence: 99%

Full-scale CFD simulation of tsunamis. Part 2: Boundary layers and bed shear stresses

Larsen

Fuhrman

2019

Coastal Engineering

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This paper presents results from numerical simulations of the propagation and run-up of full scale tsunamis, using a Reynolds-Averaged Navier-Stokes model, with emphasis on the resulting boundary layers and bed shear stresses. Spatial distributions of the Shields and Rouse parameters during run-up and draw-down show that for the tsunamis considered, with a sediment grain size corresponding to medium sand, considerable sediment transport (Shields parameter O(10)-O(100)) can be expected during run-up and that the sediment transport can be expected to be dominated by suspended load. The results likewise show that the expected sediment transport during draw-down will similarly be considerable and dominated by suspension. The tsunami-induced boundary layers are monitored in time, and the observed boundary layer thickness ranges from spanning only a small fraction of the water depth to spanning the entire depth. The velocity profiles beneath the tsunamis are shown to have good correspondence with a logarithmic profile within the boundary layer. Similarly, the bed shear stresses beneath the tsunamis are investigated and a new and simple engineering model is developed for predicting the temporal variation of the bed shear stress based only on a free-stream velocity signal. The new engineering model is shown give better predictions for the bed shear stress than a standard Manning approach, and is likewise shown (in the Appendix) to produce reasonable predictions for shorter (wind scale) waves. It is finally also shown how the temporal evolution of the boundary layer thickness can be predicted based on the free-stream velocity signal alone. The results presented here are Part 2 of a larger study, where Part 1 presents the model validation and detailed descriptions of the run-up process.

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“…To reconstruct quantitative values of tsunami characteristics from the deposits, various numerical forward and in-verse models which incorporate sediment dynamics as well as transport and depositional equations have been established (Li et al, 2012;Sugawara and Goto, 2012;Jaffe et al, 2012;Johnson et al, 2016;Yoshii et al, 2018). Recently, the deep neural network (DNN) inverse model was proposed (Mitra et al, 2020) and was proven to be effective for reconstructing flow conditions via an examination of the deposits of the 2011 Tohoku-oki tsunami.…”

Section: Introductionmentioning

confidence: 99%

Reconstruction of flow conditions from 2004 Indian Ocean tsunami deposits at the Phra Thong island using a deep neural network inverse model

Mitra

Naruse

Fujino

2021

Nat. Hazards Earth Syst. Sci.

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Abstract. The 2004 Indian Ocean tsunami caused significant economic losses and a large number of fatalities in the coastal areas. The estimation of tsunami flow conditions using inverse models has become a fundamental aspect of disaster mitigation and management. Here, a case study involving the Phra Thong island, which was affected by the 2004 Indian Ocean tsunami, in Thailand was conducted using inverse modeling that incorporates a deep neural network (DNN). The DNN inverse analysis reconstructed the values of flow conditions such as maximum inundation distance, flow velocity and maximum flow depth, as well as the sediment concentration of five grain-size classes using the thickness and grain-size distribution of the tsunami deposit from the post-tsunami survey around Phra Thong island. The quantification of uncertainty was also reported using the jackknife method. Using other previous models applied to areas in and around Phra Thong island, the predicted flow conditions were compared with the reported observed values and simulated results. The estimated depositional characteristics such as volume per unit area and grain-size distribution were in line with the measured values from the field survey. These qualitative and quantitative comparisons demonstrated that the DNN inverse model is a potential tool for estimating the physical characteristics of modern tsunamis.

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Tsunami inundation, sediment transport, and deposition process of tsunami deposits on coastal lowland inferred from the Tsunami Sand Transport Laboratory Experiment (TSTLE)

Cited by 35 publications

References 41 publications

Spatial distribution and sources of tsunami deposits in a narrow valley setting - insight from 2011 Tohoku-oki tsunami deposits in northeastern Japan

Spatial distribution and sources of tsunami deposits in a narrow valley setting - insight from 2011 Tohoku-oki tsunami deposits in northeastern Japan

Full-scale CFD simulation of tsunamis. Part 2: Boundary layers and bed shear stresses

Reconstruction of flow conditions from 2004 Indian Ocean tsunami deposits at the Phra Thong island using a deep neural network inverse model

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