The Eastern Mediterranean Basin (EMB) is under the threat of tsunami events triggered by various causes including earthquakes and landslides. We propose a deployment of Offshore Bottom Pressure Gauges (OBPGs) around Crete Island, which would enable tsunami early warning by data assimilation for disaster mitigation. Our OBPG network consists of 12 gauges distributed around Crete Island. The locations of OBPGs are confirmed by Empirical Orthogonal Function (EOF) analysis of the pre-calculated tsunami scenarios, and most of them are placed at the locations where the most energetic wave dynamics occur. We demonstrate three test cases comprising a hypothetical seismogenic tsunami in east Sicily, a hypothetical landslide tsunami in the Aegean Sea, and the real tsunami event of the May 2020 off the Crete earthquake. Our designed OBPG network achieves a forecasting accuracy of 88.5 % for the hypothetical seismogenic tsunami and 85.3% for the hypothetical landslide tsunami with warning lead times of 10-20 min for both cases. For the real event of May 2020, it predicts the tsunami arrival at tide gauge NOA-04 accurately; the observed and forecasted amplitudes of the first wave are 5.0 cm and 4.5 cm, respectively. The warning lead time for the May 2020 event was ~10 min. Therefore, our results reveal that the assimilation of OBPG data can satisfactorily forecast the amplitudes and arrival times for tsunamis in the EMB. We note that further studies are necessary to examine the relation between the performance of the system and the number of OBPGs or the tsunami characteristics.

An unusual devastating tsunami occurred on 28 September 2018 after a strike-slip faulting earthquake in Sulawesi, Indonesia. The induced tsunami struck Palu city with 4-m wave height and flow depth. We performed a two-step analysis to investigate the source of the tsunami. We first conducted the teleseismic source inversion and obtained the slip distribution of the strike-slip fault. Our tsunami simulation from the coseismic deformation of the seismically-estimated strike-slip faulting produced a tsunami comparable to the leading part of the observation at Pantoloan. We then jointly utilized the tsunami waveform and Synthetic Aperture Radar (SAR) data to reconstruct the detailed slip distribution on the fault plane. Because of the lack of SAR data in the bay, the tsunami data is necessary to constrain the offshore slip distribution, which directly induces the tsunami. The inverted source model shows a strike-slip fault which consists of three segments extending from the epicenter to the south of 1.4°S with two bends and two asperities around Palu city. The joint inversion model accurately reconstructs the observed surface displacements and the leading part of the tsunami waveform. Our result exhibits the significant contribution of the strike-slip faulting to the tsunami, but it also suggests additional tsunami sources, such as landslides, for the high inundations near Palu bay. The result also indicates that regional devastating tsunamis can result from an onshore strike-slip fault with localized large dip slip.