Utilize este identificador para referenciar este registo: https://hdl.handle.net/10316/100864
Título: Can Modeling the Geologic Record Contribute to Constraining the Tectonic Source of the 1755 CE Great Lisbon Earthquake?
Autor: Dourado, F.
Costa, P. J. M. 
La Selle, S.
Andrade, C.
Silva, A. N.
Bosnic, I.
Gelfenbaum, G.
Palavras-chave: Delft3D; numerical modeling; sediment transport; sedimentary signatures; tsunami hazard; tsunami sources
Data: 2021
Projeto: Fulbright Commission for Junior Faculty Member Award (2018) 
Pacific Coastal and Marine Science Center/United State Geological Survey (USGS) 
Foundation for Research Support of the Rio de Janeiro State (FAPERJ) for a Young Scientist of Our State Grant (2016) 
FCT project OnOff – Coupling onshore and offshore tsunami record: complementary tools for a broader perspective on tsunami events – PTDC/CTA-GEO/28941/2017 
Título da revista, periódico, livro ou evento: Earth and Space Science
Volume: 8
Número: 4
Resumo: The precise location of the seismic source of 1755 CE Great Lisbon earthquake is still uncertain. The aim of this work is to use an onland sedimentary record in southern Portugal to test and validate seismic sources for the earthquake. To achieve this, tsunami deposit thicknesses from over 150 cores collected at Salgados in southern Portugal were compared to the results of a tsunami sediment transport model (Delft3D-FLOW) that simulates tsunami propagation, inundation, erosion, and deposition. Five different hypothetical seismic sources were modeled with varying bed roughness coefficients to assess how well they reproduced observed patterns of tsunami deposit thicknesses and dune. Modeled and observed historical tsunami arrival times were also used to test different earthquake sources. Based on these comparisons, three modeled earthquake sources were able to reproduce the observed data, suggesting they should be regarded as somewhat more likely sources for the 1755 earthquake in contrast to four other modeled sources. The fault closest to shore (Marquês de Pombal) yielded the best correlations between model and observations.
URI: https://hdl.handle.net/10316/100864
ISSN: 2333-5084
2333-5084
DOI: 10.1029/2020EA001109
Direitos: openAccess
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