RT Journal Article
T1 Probabilistic Tsunami Hazard Analysis: High Performance Computing for Massive Scale Inundation Simulations
A1 Gibbons, Steven
A1 Lorito, Stefano
A1 Macías-Sánchez, Jorge
A1 Lovholt, Finn
A1 Selva, Jacopo
A1 Volpe, Manuela
A1 Sánchez-Linares, Carlos
A1 Babeyko, Andrey
A1 Brizuela, Beatriz
A1 Cirella, Antonella
A1 Castro, Manuel Jesús
A1 de la Asunción, Marc
A1 Lanucara, Piero
A1 Glimsdal, Sylfest
A1 Lorenzino, Maria Concetta
A1 Nazaria, Massimo
A1 Pizzimenti, Luca
A1 Romano, Fabrizio
A1 Scala, Antonio
A1 Tonini, Roberto
A1 González-Vida, José Manuel
A1 Vöge, Malte
K1 Maremotos
AB Probabilistic Tsunami Hazard Analysis (PTHA) quantifies the probability of exceeding aspecified inundation intensity at a given location within a given time interval. PTHAprovides scientific guidance for tsunami risk analysis and risk management, includingcoastal planning and early warning. Explicit computation of site-specific PTHA, with anadequate discretization of source scenarios combined with high-resolution numericalinundation modelling, has been out of reach with existing models and computingcapabilities, with tens to hundreds of thousands of moderately intensive numericalsimulations being required for exhaustive uncertainty quantification. In recent years, moreefficient GPU-based High-Performance Computing (HPC) facilities, together with efficientGPU-optimized shallow water type models for simulating tsunami inundation, have now madelocal long-term hazard assessment feasible. A workflow has been developed with three mainstages: 1) Site-specific source selection and discretization, 2) Efficient numerical inundationsimulation for each scenario using the GPU-based Tsunami-HySEA numerical tsunamipropagation and inundation model using a system of nested topo-bathymetric grids, and3) Hazard aggregation. We apply this site-specific PTHA workflow here to Catania, Sicily, fortsunamigenic earthquake sources in the Mediterranean. We illustrate the workflows of thePTHA as implemented for High-Performance Computing applications, including preliminarysimulations carried out on intermediate scale GPU clusters. We show how the local hazardanalysis conducted here produces a more fine-grained assessment than is possible with aregional assessment.
PB Frontiers
YR 2020
FD 2020-12-11
LK https://hdl.handle.net/10630/32905
UL https://hdl.handle.net/10630/32905
LA eng
NO Gibbons SJ, Lorito S, Macías J, Løvholt F, Selva J, Volpe M, Sánchez-Linares C, Babeyko A, Brizuela B, Cirella A, Castro MJ, de la Asunción M, Lanucara P, Glimsdal S, Lorenzino MC, Nazaria M, Pizzimenti L, Romano F, Scala A, Tonini R, Manuel González Vida J and Vöge M (2020) Probabilistic Tsunami Hazard Analysis: High Performance Computing for Massive Scale Inundation Simulations. Front. Earth Sci. 8:591549. doi: 10.3389/feart.2020.591549
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 22 ene 2026