RT Journal Article
T1 Pseudo-Probabilistic Design for High-Resolution Tsunami Simulations in the Southwestern Spanish Coast
A1 González, Alejandro
A1 Fernández Hernández, Marta
A1 Llorente Isidro, Miguel
K1 Maremotos
AB The application of simulation software has proven to be a crucial tool for tsunami hazardassessment studies. Understanding the potentially devastating effects of tsunamis leads to thedevelopment of safety and resilience measures, such as the design of evacuation plans or the planningof the economic investment necessary to quickly mitigate their consequences. This article introducesa pseudo-probabilistic seismic-triggered tsunami simulation approach to investigate the potentialimpact of tsunamis in the southwestern coast of Spain, in the provinces of Huelva and Cádiz. Selectedfaults, probabilistic distributions and sampling methods are presented as well as some results for thenearly 900 Atlantic-origin tsunamis computed along the 250 km-long coast.
PB MPDI
YR 2022
FD 2022-05-23
LK https://hdl.handle.net/10630/24273
UL https://hdl.handle.net/10630/24273
LA eng
NO González A, Fernández M, Llorente M, Macías J, Sánchez-Linares C, García-Mayordomo J, Paredes C. Pseudo-Probabilistic Design for High-Resolution Tsunami Simulations in the Southwestern Spanish Coast. GeoHazards. 2022; 3(2):294-322. https://doi.org/10.3390/geohazards3020016González A, Fernández M, Llorente M, Macías J, Sánchez-Linares C, García-Mayordomo J, Paredes C. Pseudo-Probabilistic Design for High-Resolution Tsunami Simulations in the Southwestern Spanish Coast. GeoHazards. 2022; 3(2):294-322. https://doi.org/10.3390/geohazards3020016
NO This work has being carried out under a project funded by a public mutual agreement ofunderstanding between the CN-IGME (CSIC) and the CCS (Law reference: BOE 103, 30/04/2019).This project is supported by an agreement of understanding between CN-IGME and UMA, creating acooperative entity INGEA (Law reference: BOE 332, 22/12/2020). The numerical results presented inthis work have been performed with the computational resources allocated by the Spanish Networkfor Supercomputing (RES) grants AECT-2020-3-0023 and AECT-2021-2-0018. Further support has alsobeen received from the Spanish Government research project MEGAFLOW (RTI2018-096064-B-C21)and ChEESE project (EU Horizon 2020, grant agreement No. 823844, https://cheese-coe.eu/) due tothe synergies found between the projects. Partial funding for open access charge: Universidad de Málaga
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026