In this paper, we model the full range of possible local impacts of future tsunamis in the Makran subduction zone (MSZ) at Karachi port, Pakistan. For the first time, the 3-D subduction geometry Slab2 is employed in the MSZ, in conjunction with the most refined rupture segmentation to date for this region, to improve the earthquake source definition. Motivated by the massive sediment layer over the MSZ, we also introduce to tsunami modeling the application of the sediment amplification formula, resulting in enhancements of seabed deformation up to 60% locally. Furthermore, we design a new unstructured mesh algorithm for our GPU-accelerated tsunami code in order to efficiently represent flow velocities, including vortices, down to a resolution of 10m in the vicinity of the port. To afford to compute very large number of high resolution tsunami scenarios, for the granularity and extent of the range of magnitudes (occurrence ratios of 1:100,000 implied by the Gutenberg-Richter relation) and locations of source, we create a statistical surrogate (i.e. emulator) of the tsunami model. Our main contribution is hence the largest set of emulated predictions using any realistic tsunami code to date: 1 million per location. We go on to obtain probabilistic representations of maximum tsunami velocities and heights at around 200 locations in the port area of Karachi. Amongst other findings, we discover substantial local variations of currents and heights. Hence we argue that an end-to-end synthesis of advanced physical, numerical and statistical modeling is instrumental in coastal engineering to comprehensively model local impacts of tsunamis.

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.