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The southern Kuril Trench is one of the most seismically active regions in the world. In this study, marine surveys and observations were performed to construct fault models for possible outer-rise earthquakes. Seismic and seafloor bathymetric surveys indicated that the dip angle of the outer-rise fault was approximately 50°–80°, with a strike that was slightly oblique to the axis of the Kuril Trench. The maximum fault length was estimated to be ~ 260 km. Based on these findings, we proposed 17 fault models, with moment magnitudes ranging from 7.2 to 8.4. To numerically simulate tsunami, we solved two-dimensional dispersive wave and three-dimensional Euler equations using the outer-rise fault models. The results of both simulations yielded identical predictions for tsunami with short-wavelength components, resulting in significant dispersive deformations in the open ocean. We also found that tsunami generated by outer-rise earthquakes were affected by refraction and diffraction because of the source location beyond the trench axis. These findings can improve future predictions of tsunami hazards. [ABSTRACT FROM AUTHOR]

We present a novel method for coastal tsunami prediction utilizing a denoising autoencoder (DAE) model, one of the deep learning algorithms. Our study focuses on the Tohoku coast, Japan, where dense offshore bottom pressure gauges (OBPGs), called S-net, are installed. To train the model, we generated 800 hypothetical tsunami scenarios by employing stochastic earthquake models (M7.0–8.8). We used synthetic tsunami waveforms at 44 OBPGs as input and the waveforms at four coastal tide gauges as output. Subsequently, we evaluated the model's performance using 200 additional hypothetical and two real tsunami events: the 2016 Fukushima earthquake and 2022 Tonga volcanic tsunamis. Our DAE model demonstrated high accuracy in predicting coastal tsunami waveforms for hypothetical events, achieving an impressive quality index of approximately 90%. Furthermore, it accurately forecasted the maximum amplitude of the 2016 Fukushima tsunami, achieving a quality index of 91.4% at 15 min after the earthquake. However, the prediction of coastal waveforms for the 2022 Tonga volcanic tsunami was not satisfactory. We also assessed the impact of the forecast time window and found that it had limited effects on forecast accuracy. This suggests that our method is suitable for providing rapid forecasts soon after an earthquake occurs. Our research is the first application of an artificial neural network to tsunami prediction using real observations. In the future, we will use more tsunami scenarios for model training to enhance its robustness for different types of tsunamis. [ABSTRACT FROM AUTHOR]

We examined whether it is possible to estimate the tsunami source model of the 2011 Tohoku-Oki earthquake from a comparison of numerical simulations of tsunami propagation and sediment transport, the measured trace heights, and the sediment thickness of tsunami deposits. Twelve models with different subfault numbers were prepared based on a reference model inferred from tsunami waveform inversion. The reference model with 55 subfaults considering rupture propagation and the model with instantaneous slip successfully reproduced both the tsunami trace heights and sediment thickness distribution of tsunami deposits in the Idagawa Lowland and Sendai Plain. Other models with the same moment magnitude but fewer subfaults could not reproduce the observed trace heights, and the reproducibility of sediment thickness distribution strongly depended on the slip distribution. Models with increased slip amounts and moment magnitude could reproduce the trace heights; however, the simulated sediment thickness was underestimated for the Idagawa Lowland while overestimated for the Sendai Plain. Our results indicate that the combination of trace heights, sediment thickness of tsunami deposits, and numerical simulations of tsunami propagation and sediment transport can be used to estimate historical earthquakes and tsunamis. Efforts should be made to increase the number of subfaults for the study of historical events, although the obtained solutions may not be unique because of fewer trace heights or tsunami deposit data. [ABSTRACT FROM AUTHOR]

The island of Sulawesi, Indonesia, is located in a complex and tectonically active region, and has experienced tsunamis in the past. One of the major earthquake and tsunami events was the 23 February 1969 event that struck the Majene region in western Sulawesi Island. Interpretation of the historical accounts revealed that the Mw 7.0 earthquake generated strong intensity up to VIII on the Modified Mercalli Intensity scale. The earthquake was followed by an unusually high tsunami of 4 m that rapidly decayed within 25 km from the highest observation site. Hypocentre and earthquake mechanism analyses confirmed that it was an inland earthquake with a thrust mechanism. Ground motion modelling is able to reproduce the earthquake intensity but earthquake scenarios are unable to reconstruct the tsunami observations. A plausible solution to explain the tsunami report is from a combined scenario of an earthquake and a submarine mass failure of 0.5 km 3 . [ABSTRACT FROM AUTHOR]

High‐frequency (HF) radar monitors the sea surface current velocity and provides information for tsunami early warning. SeaSondeR, an HF ocean radar system in the eastern Tsugaru Strait, Japan, measured the tsunami‐induced current velocity during the 2022 Tonga volcanic tsunami. As an air‐coupled tsunami, the generating mechanism was complex, making it difficult to predict coastal tsunamis using traditional early warning methods. We adopted the tsunami data assimilation (DA) approach, which reconstructs the tsunami wavefield using offshore data and does not require source information, to forecast the coastal tsunami waveforms. Observations from the HF radar and offshore bottom pressure gauges (OBPGs) were used as the input for tsunami DA. The assimilation process started at 09:00 (UTC, hereafter) and forecasts were made at 14:00 and 15:00. The surface current velocity recorded by the HF radar reached the maximum (∼0.25 m/s) at 13:00, which corresponded to a negative phase of ∼2 cm sea level variation observed by OBPGs. We compared the forecasted waveforms with the observed waveforms at Hakodate and Shimokita tide gauges. The assimilation results obtained using HF radar showed a better performance in tsunami forecasting than those using OBPG in this case study. At 14:00, the forecasting accuracy indices were 91% and 67% for the next 2 and 6 hr, respectively. At 15:00, it was 63% and 70% for the next 2 and 6 hr, respectively. We suggest that HF radar could be a good supplement to OBPG for tsunami early warning purposes. Plain Language Summary: On 15 January 2022, the eruption of the Hunga Tonga–Hunga Ha'apai volcano generated a tsunami that arrived in Japan. The tsunami was detected by a high‐frequency (HF) ocean radar system in the eastern Tsugaru Strait. The HF radar recorded the velocity of tsunami‐induced sea surface currents. We used these velocity data to forecast the tsunami waveforms at coastal tide gauge stations. The forecast method, called tsunami data assimilation, does not require tsunami source information but accurately forecasts the coastal tsunami waveforms. We demonstrate that the HF radar data can be successfully applied to tsunami early warning systems. Key Points: High‐frequency (HF) radar observed surface current velocity in the eastern Tsugaru Strait during the 2022 Tonga volcanic tsunamiHF radar observations were used for data assimilation to forecast tsunami waveforms at coastal tide gaugesThe assimilation results using HF radar had an accuracy of over 63% for Hakodate and Shimokita tide gauges [ABSTRACT FROM AUTHOR]

Researchers have developed tsunami inundation models based on nonlinear shallow water equations to estimate tsunami propagation and inundation. However, their empirical results are not in perfect agreement with those of other research institutes, even though the same governing equations are used. Therefore, we quantitatively evaluated the variability of tsunami simulations in this study. Several research institutes have conducted tsunami simulations under the same input conditions using tsunami inundation models adopted for tsunami hazard assessment, resulting in a certain degree of variability among them. By examining the spatial and temporal differences in various physical quantities, we identified the characteristic topography where the variability between tsunami simulations increases. A novel method for calculating statistics from the area integrals of physical quantities was proposed to demonstrate the variability in the overall simulation results. In addition, the effects of different setting parameters and computational environments on the simulation results of a single model were evaluated. The findings of this study are expected to not only serve as a basis to verify the reliability of source codes employed by users of the tsunami inundation model, but also contribute useful technical information to advance probabilistic tsunami hazard assessment in the future. [ABSTRACT FROM AUTHOR]

The ocean floor network system for earthquakes and tsunamis is one of the effective tools for the early detection of large earthquakes on plate boundaries and the tsunamis they generate. The Dense Oceanfloor Network system for Earthquakes and Tsunamis (DONET) was installed in the first rupture areas of the 1944 Tonankai and 1946 Nankai earthquakes. The DONET around the Nankai Trough, a site of huge earthquakes that have caused severe damage, has the potential to detect the genesis of a tsunami. We developed a real-time tsunami prediction system for local communities that takes advantage of the features of DONET, and we have already made it available to several local governments and a commercial company. The outputs of the prediction are the tsunami arrival time, its height, its inundation area, and inundation depth. The system makes real-time monitoring of tsunamis possible. The system should be conceptually applicable to the Nankai Trough area, which has characteristics consistent with the assumptions the system makes about tsunami propagation, crustal activities, and coastal communities. Here, we describe the conceptual basis of the system, the features used to ensure the accuracy of predictions, and the policies used to develop and implement them. [ABSTRACT FROM AUTHOR]

Tsunami-related fires may occur in the inundation area during a huge tsunami disaster, and woody debris produced by the tsunami can cause the fires to spread. To establish a practical method for evaluating tsunami-related fire predictions, we previously developed a method for evaluating the tsunami debris thickness distribution that uses tsunami computation results and static parameters for tsunami numerical analysis. We then used this evaluation method to successfully reproduce the tsunami debris accumulation trend. We then developed an empirical building fragility function that relates the production of debris not only to inundation depth but also to the topographic gradient and the proportion of robust buildings. Using these empirical evaluation models, along with conventional tsunami numerical analysis data, we carried out a practical tsunami debris prediction for Owase City, Mie Prefecture, a potential disaster area for a Nankai Trough mega-earthquake. This prediction analysis method can reveal hazards which go undetected by a conventional tsunami inundation analysis. These results indicate that it is insufficient to characterize the tsunami hazard by inundation area and inundation depth alone when predicting the hazard of a huge tsunami; moreover, more practically, it is necessary to predict the hazard based on the effect of tsunami debris. [ABSTRACT FROM AUTHOR]

We estimated the time difference between the 1854 CE Ansei–Tokai and Ansei–Nankai earthquakes from tidal records of two tide gauge stations (San Francisco and San Diego) on the west coast of North America. The first signals of the Ansei–Tokai tsunami were apparent, whereas those of the Ansei–Nankai tsunami were obscured by the later waves of the Ansei–Tokai tsunami. Waveforms of the Ansei–Nankai tsunami simulated with nonlinear dispersive wave theory by assuming an origin time of 07:00 GMT on 24 December arrived earlier than in the observations. The normalized root mean square and the misfit between the simulated and observed waveforms of the Ansei–Nankai tsunami showed a time difference between them of approximately 0.4 h. This finding suggests that the actual origin time of the Ansei–Nankai tsunami was approximately 07:24 GMT on 24 December. A previous study estimated the origin time of the Ansei–Tokai tsunami to be about 00:30 GMT on 23 December. Thus, we concluded that the time difference between the 1854 CE Ansei–Tokai and Ansei–Nankai tsunamis was 30.9 h. Despite the significant difference in the time resolution between the seasonal timekeeping system used in Japan in 1854 and waveform digitization, our result is roughly in agreement with historical descriptions of the tsunamis, suggesting that such information can be effectively used to determine the origin times of historical earthquakes. [ABSTRACT FROM AUTHOR]

Although tsunamis are dispersive water waves, hazard maps for earthquake-generated tsunamis neglect dispersive effects because the spatial dimensions of tsunamis are much greater than the water depth, and dispersive effects are generally small. Furthermore, calculations that include non-dispersive effects tend to predict higher tsunamis than ones that include dispersive effects. Although non-dispersive models may overestimate the tsunami height, this conservative approach is acceptable in disaster management, where the goal is to save lives and protect property. However, we demonstrate that offshore frequency dispersion amplifies tsunamis caused by outer-rise earthquakes, which displace the ocean bottom downward in a narrow area, generating a dispersive short-wavelength and pulling-dominant (water withdrawn) tsunami. We compared observational evidence and calculations of tsunami for a 1933 Mw 8.3 outer-rise earthquake along the Japan Trench. Dispersive (Boussinesq) calculations predicted significant frequency dispersion in the 1933 tsunami. The dispersive tsunami deformation offshore produced tsunami inundation heights that were about 10% larger than those predicted by non-dispersive (long-wave) calculations. The dispersive tsunami calculations simulated the observed tsunami inundation heights better than did the non-dispersive tsunami calculations. Contrary to conventional practice, we conclude that dispersive calculations are essential when preparing deterministic hazard maps for outer-rise tsunamis. [ABSTRACT FROM AUTHOR]

The detailed understanding of tsunami hazard risk using numerical simulations requires a numerical model that can accurately predict tsunami inundation phenomena on land. In such models, the structural effects are indirectly considered using the variation of bottom roughness as a proxy for the differences in building densities. Only a few studies have conducted intermodel tests to investigate tsunami inundation in complex coastal urban cities. During the tsunami analysis hackathon held in September 2020, eight research groups met to have a detailed discussion on the current urban inundation problems. In this study, we conducted an intermodel comparison of the numerical tsunami models, using the data from physical experiments that were performed on a detailed urban model. Our objective was to investigate the necessary conditions of an accurate numerical model based that can ensure high reproducibility and practicality. It was confirmed that the accuracy of topographic data is an important parameter for tsunami inundation simulations in complex urban areas. Based on the computational cost and accuracy, we suggest that a resolution of 1 cm of topographic data is a sufficient condition for tsunami inundation simulations on 1/250 scale model. [ABSTRACT FROM AUTHOR]

Following the 2011 Tohoku earthquake, coastal forests dissipated the energy of the tsunami and trapped flotsam. Although studies have shown how trees dissipate flow energy and are damaged in the process, the factors determining the trapping of flotsam by lines of trees or their capacity to do so have not been quantitatively examined. Quantitative evaluation of these factors may lead to tree-based strategies for suppressing the secondary damage caused by tsunami flotsam. To increase the ability of trees to mitigate damage, their physical limitations need to be identified. Field surveys revealed that integrated clusters of flotsam were caught by trees even if individual floating objects were smaller than the distance between the trees. Hydraulic experiments revealed relations between physical factors and the capture of flotsam. From these relations, we derived a simple formula for evaluating the trapping capacity of lines of trees. The estimates from our model were consistent with the actual results of the 2011 tsunami in Tagajo city, Miyagi prefecture, where trees did not topple under the forces applied by trapped flotsam. [ABSTRACT FROM AUTHOR]

At 14:46 JST on March 11, 2011 a magnitude 9.0 earthquake (2011 Tohoku Earthquake and Tsunami) occurred off the Pacific Coast of Miyagi Prefecture. This study investigated the extensive changes in beach morphology due to the earthquake and tsunami along the 15 km Northern Sendai Coast using remotely sensed data. The remote sensing analysis on the beach topography and coastal forest demonstrated the following notable characteristics of beach morphological change: erosion of the northern barrier at the mouths of the Nanakitagawa and Natorigawa Rivers; erosion at an old river channel; scour landward of the seawalls in the longshore direction; erosion and deposition in beach areas with detached breakwaters; and deposition in coastal forest areas. Linkage of the deposition in the forest areas with the damage type of coastal forests was observed. The impact of the earthquake and tsunami on the beach morphology was serious; roughly 60% of the study area was degraded by 0.2-0.5 m in elevation mainly due to land subsidence, and a total of 0.4 km2 of beach area was eroded mainly due to erosion of the northern barrier at the mouths of the Nanakitagawa and Natorigawa Rivers. This study explores the geographical changes brought on by a tremendous earthquake and tsunami, which will help to elucidate the mechanisms of coastal forest destruction, beach erosion, and their interaction during tsunami events. [ABSTRACT FROM AUTHOR]

Japan was hit by the tsunami generated by the greatest earthquake in the history of Japan. The authors conducted the post-tsunami field survey in Miyagi prefecture immediately after the event to measure the inundation depth and investigate damaged buildings. Most of the buildings surveyed were wooden houses and could be classified into 4 damage levels. The primary data of inundation depth and damage levels obtained from the field survey were used to create the tsunami fragility curves, which described the degree of structural damage as a function of the hydrodynamic characteristics of tsunami inundation. The developed fragility curves show that damage with more than a 50% chance of occurring is classified as minor damage, moderate damage, major damage and complete damage when the tsunami inundation depth is between 2.5-3.0 m, 3.0-4.0 m and 4.0-4.5 m and greater than 4.5 m, respectively. By comparing the developed tsunami fragility curves, wooden houses in the studied area have higher structural performance than those obtained from historical events in other areas. The new curves suggest that wooden houses will be severely damaged if the inundation depth is greater than 3 m and collapse if the depth is greater than 4 m while wooden houses from historical data can resist only 1-2 m. Moreover, wooden walls in Japan reduce the overall failure of a structural member because a wooden wall is easier to destroy (compared to brick walls in Thailand and Indonesia) and allows the tsunami to pass through, which reduces the pressure at the attacking front of the tsunami. The fragility curves are very important for the loss estimation and reconstruction plans of the city; they are also crucial for reducing the disaster damage from a future tsunami. [ABSTRACT FROM AUTHOR]

We examined the effect of the coastal forest on tsunami sediment movement on the Sendai Plain, Japan, during the 2011 Tohoku tsunami using a numerical simulation of sediment transport. To account for the variable roughness coefficient in the coastal forest, a composite equivalent roughness coefficient was adopted. The simulated mean concentration of suspended sediment, wave height, flow velocity, and inundation limit were significantly reduced by the coastal forest. For fine to medium sand, the volumes of maximum deposition and erosion were reduced to 57–83% of those in the simulation without the coastal forest; these reductions were particularly notable for fine sand. The maximum extent and thickness of the sand layer were also reduced. The simulated sediment thickness and extent with the coastal forest for finer grain sizes roughly agreed with the observations, while the simulated results for coarser sand underestimated the observations. The reduction of sediment transport due to the coastal forest suggests that land use conditions and the vegetation environment at the time of a tsunami should be considered when studying historical and paleo-tsunamis using the geological evidence. [ABSTRACT FROM AUTHOR]

Business continuity plans (BCPs) can be effective and proactive countermeasures to respond flexibly to crises caused by unexpected natural disasters such as large tsunamis. BCP guidelines for fisheries are being issued by the Fisheries Agency (Japan) and the utilization of such BCPs has been spreading in Japan. Despite the need to promote the social implementation of BCPs in the fisheries industry, there is a lack of quantitative criteria for the tsunami damage threshold of various fishing ports and facilities. In this research, we surveyed the damage to the fishing facilities from the tsunami generated by the 2011 Tohoku-oki earthquake. Data were collected on the tsunami damage for various fishery facilities and used to establish criteria for tsunami damage thresholds. In addition, tsunami damage inferred from 1506 scenarios of tsunami computations was predicted probabilistically for a model region as the Nachi Katsu'ura Fishery Port in Wakayama Prefecture. The method we developed in this research makes it possible to assess the probabilistic tsunami damage by combining a tsunami hazard assessment method with criteria for damage occurrence for fishery port facilities and equipment. [ABSTRACT FROM AUTHOR]

The article presents the discussion on earthquake and tsunami causing enormous damage along the coast of northeast Japan in the Tohoku region including afterslip and viscoelastic relaxation of the mantle.

Tsunamis caused by submarine landslides are not accompanied by seismic waves and thus may appear at the coast without warning. In this study, detailed bathymetric surveys with a multi-narrow beam echo sounder were used to map submarine landslides on the continental shelf near Cape Muroto, in the Nankai trough off southwestern Japan. One of the surveyed submarine landslides was selected to supply dimensions for the simulation of a submarine mass movement by a two-layer flow model in which the upper and lower layers correspond to seawater and turbidity currents, respectively. The time series of seafloor deformation during this simulated landslide was used as the boundary condition to drive a tsunami simulation. The results showed strong directivity effects during tsunami generation in which pushing-dominant (positive) tsunami waves propagated seaward, in the direction of the submarine landslide, and pulling-dominant (negative) tsunami waves propagated landward. Both types of waves were strongly modified by frequency dispersion. For pulling-dominant waves, a tsunami simulation that included dispersion (Boussinesq) terms predicted greater maximum tsunami heights than a non-dispersive tsunami simulation. To avoid underestimation of tsunami heights, we recommend including dispersion terms when modeling tsunamis caused by submarine landslides for disaster planning purposes. • Bathymetric survey shows detailed features of the submarine landslide. • Two-layer flow model estimates the submarine mass movement. • Tsunamis caused by the submarine landslide are deeply affected by dispersion effects. [ABSTRACT FROM AUTHOR]

In this study, we considered the accurate calculation of far-field tsunami waveforms by using the shallow water equations and accounting for the effects of Boussinesq dispersion, seawater density stratification, elastic loading, and gravitational potential change in a finite difference scheme. By comparing numerical simulations that included and excluded each of these effects with the observed waveforms of the 2011 Tohoku tsunami, we found that all of these effects are significant and resolvable in the far field by the current generation of deep ocean-bottom pressure gauges. Our calculations using previously published, high-resolution models of the 2011 Tohoku tsunami source exhibited excellent agreement with the observed waveforms to a degree that has previously been possible only with near-field or regional observations. We suggest that the ability to model far-field tsunamis with high accuracy has important implications for tsunami source and hazard studies. [ABSTRACT FROM AUTHOR]