Typhoon Jebi in 2018 caused severe damage along areas of Osaka Bay, Japan. After the storm, a Japan Society of Civil Engineers (JSCE) coastal survey group surveyed the coastal impacts and recorded watermarks inside Osaka Bay and along the Pacific. The maximum storm tide recorded by a tide gauge was 3.29 m at the Osaka Tide Station, which is a historical high for Osaka Bay. Coastal flooding consisted of both storm surge and wave run-up in almost all locations, with flooding exceeding 5 m and 12 m in elevation from mean sea level in the inner parts of Osaka Bay and along the Pacific coast, respectively. Coastal damage was severe in areas located outside of coastal barriers, such as ports and harbors, while residential areas were mainly well protected and spared due to coastal protection systems. In addition, some inland flooding occurred in the Kobe-Ashiya regions due to the storm surge propagating up several small rivers. This survey report summarizes the findings of the post-event survey by JSCE and analyzes the relation between maximum water level and resulting damage.

This study investigated how the synthetic aperture radar (SAR) parameters and natural conditions affect the spatial distribution of backscattering coefficient of SAR images around the shoreline. Primary findings of this study are summarized as follows: (i) the HH polarization mode is the best mode for shoreline detection; (ii) SAR scenes with incident angle ranging from 30° to 50° under sea-to-land observation direction are recommended for shoreline detection; (iii) clear contrast of the backscattering coefficient between the beach and sea is expected when the nearshore significant wave height is smaller than 0.5 m for L-band SAR scenes; and (iv) X-band SAR scenes may be preferred to L-band SAR scenes for shoreline detection especially where the grain size of the beach material is relatively fine.

On 1 January 2024, a massive earthquake struck the Noto Peninsula in Japan, and the resulting tsunami significantly damaged the nearby coasts. This study focuses on Iida Bay, located on the peninsula that suffered severe coastal damage. We observed a tsunami waveform in Iida Bay from video analysis owing to the lack of instrument data. This, combined with the waveform observed outside the bay, was used to correct the initial sea‐surface displacements produced by a prior source model. We successfully reproduced the observed waveforms with corrected displacements and investigated how the tsunami propagated and amplified in the bay. Alongshore wave propagation and superposition were identified as crucial factors in this tsunami event.

For Japanese coastal communities along the Japan Sea, where the risk of earthquake-induced tsunamis is deemed lower than that along the Pacific Ocean, tsunami disaster mitigation strategies have not been sufficiently developed. This study estimated the tsunami inundation characteristics for three major Japanese coastal cities along the Japan Sea. Based on tsunami simulations for representative coastal areas, we aimed to identify common vulnerabilities, which included those suggested by previous studies and local governments, to develop disaster mitigation strategies. Comprehensive simulations for tsunami propagation and inundation were performed for coastal areas in Akita City, Sakata City, and Niigata City based on earthquake and tsunami source scenarios developed by the Japanese Government for the Japan Sea area. To demonstrate the effectiveness of the estimated inundation characteristics, tsunami inundation was simulated for each coastal area under varying tsunami source conditions (including excessive tsunami magnitude) with a high resolution of the topography and infrastructure. Natural sand dunes, ports with man-made breakwaters, and rivers with levees are typical topographical features found in urbanized and densely populated areas along the Japan Sea coastline. According to the simulated results, the dunes and port breakwaters contribute significantly to decreasing the total amount of tsunami inundation for the areas behind them. However, the presence of the breakwaters also increases the tsunami heights in the areas immediately beyond the ports. Additionally, even the areas protected by the dunes might be exposed to an inundation risk in which the tsunamis invade a river channel, causing it to overflow. These findings were common to the coastal areas, and could be generally applicable to tsunami inundation for all coastal areas along the Japan Sea. Based on these results, the enhancement of existing infrastructure such as breakwaters and river levees should be the priority measure within tsunami risk-mitigation strategies; these, combined with natural resources such as dunes, can effectively mitigate tsunami disasters. Graphical Abstract

A dense cabled observation network, called the seafloor observation network for earthquakes and tsunami along the Japan Trench (S-net), was installed in Japan. This study aimed to develop a near-real time tsunami source estimation technique using the ocean bottom pressure data observed at those sensors in S-net. Synthetic pressure waveforms at those sensors were computed for 64 earthquake tsunami scenarios with magnitude ranging between M8.0 and M8.8. The pressure waveforms within a time window of 500 s after an earthquake were classified into three types. Type 1 has the following pressure waveform characteristic: the pressure decreases and remains low; sensors exhibiting waveforms associated with Type 1 are located inside a co-seismic uplift area. The pressure waveform characteristic of Type 2 is that one up-pulse of a wave is within the time window; sensors exhibiting waveforms associated with Type 2 are located at the edge of the co-seismic uplift area. The other pressure waveforms are classified as Type 3. Subsequently, we developed a method to estimate the uplift area using those three classifications of pressure waveforms at sensors in S-net and a method to estimate earthquake magnitude from the estimated uplift area using a regression line. We systematically applied those methods for two cases of previous large earthquakes: the 1952 Tokachi-oki earthquake (Mw8.2) and the 1968 Tokachi-oki earthquake (Mw8.1). The locations of the large computed uplift areas of the earthquakes were well defined by the estimated ones. The estimated magnitudes of the 1952 and 1968 Tokachi-oki earthquakes from the estimated uplift area were 8.2 and 7.9, respectively; they are almost consistent with the moment magnitudes derived from the source models. Those results indicate that the tsunami source estimation method developed in this study can be used for near-real time tsunami forecasts.