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Machine learning-based tsunami inundation prediction derived from offshore observations. [PDF]
Nat Commun, 2022 The world’s largest and densest tsunami observing system gives us the leverage to develop a method for a real-time tsunami inundation prediction based on machine learning.
Mulia IE +4 more
europepmc +2 more sources
Frontiers in Earth Science, 2020 Probabilistic Tsunami Hazard Analysis (PTHA) quantifies the probability of exceeding a specified inundation intensity at a given location within a given time interval.
Jacopo Selva +2 more
exaly +4 more sources
Early forecasting of tsunami inundation from tsunami and geodetic observation data with convolutional neural networks. [PDF]
Nat Commun, 2021 Rapid and accurate hazard forecasting is important for prompt evacuations and reducing casualties during natural disasters. In the decade since the 2011 Tohoku tsunami, various tsunami forecasting methods using real-time data have been proposed. However,
Makinoshima F +4 more
europepmc +2 more sources
Earth, Planets and Space, 2022 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.
Yusuke Yamanaka, Takenori Shimozono
doaj +2 more sources
Palaeo-tsunami inundation distances deduced from roundness of gravel particles in tsunami deposits. [PDF]
Sci Rep, 2019 Information on palaeo-tsunami magnitude is scientifically and socially essential to mitigate tsunami risk. However, estimating palaeo-tsunami parameters (e.g., inundation distance) from sediments is not simple because tsunami deposits reflect complex ...
Ishimura D, Yamada K.
europepmc +2 more sources
Stochastic Environmental Research and Risk Assessment, 2023 Probabilistic tsunami inundation assessment ordinarily requires many inundation simulations that consider various uncertainties; thus, the computational cost is very high.
Tomohiro Yasuda +2 more
exaly +2 more sources
Journal of Geophysical Research: Oceans, 2021 This study presents an innovative probabilistic tsunami inundation assessment for an earthquake scenario to randomly generate tsunami inundation depth distributions by quantitatively evaluating the spatial correlation of tsunami inundation depths using ...
Kenjiro Terada, Yu Otake, Yo Fukutani
exaly +2 more sources
Tsunami inundation modeling for western Sumatra. [PDF]
Proc Natl Acad Sci U S A, 2006 A long section of the Sunda megathrust south of the great tsunamigenic earthquakes of 2004 and 2005 is well advanced in its seismic cycle and a plausible candidate for rupture in the next few decades. Our computations of tsunami propagation and inundation yield model flow depths and inundations consistent with sparse historical accounts for the last ...
Borrero JC +3 more
europepmc +6 more sources
Simulating Tsunami Inundation and Soil Response in a Large Centrifuge. [PDF]
Sci Rep, 2019 AbstractTsunamis are rare, extreme events and cause significant damage to coastal infrastructure, which is often exacerbated by soil instability surrounding the structures. Simulating tsunamis in a laboratory setting is important to further understand soil instability induced by tsunami inundation processes. Laboratory simulations are difficult because
Exton M +4 more
europepmc +6 more sources
Physics-informed neural networks for tsunami inundation modeling [PDF]
Journal of Computational PhysicsWe use physics-informed neural networks for solving the shallow-water equations for tsunami modeling. Physics-informed neural networks are an optimization based approach for solving differential equations that is completely meshless. This substantially simplifies the modeling of the inundation process of tsunamis. While physics-informed neural networks
Rüdiger Brecht +2 more
openaire +5 more sources