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Modelling of surface river plume using set-up and input data files of Delft-3D model

This data article presents set-up and input data files to model a surface river plume through curvilinear nested grid in double-way mode. The hydrodynamic modelling in river deltas with intense transport processes and complex bathymetry such as the Magdalena River delta, requires a mesh grid that ea...

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Autores principales: Rueda-Bayona, Juan Gabriel, Horrillo-Caraballo, José, Chaparro, Tatiana R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334385/
https://www.ncbi.nlm.nih.gov/pubmed/32642515
http://dx.doi.org/10.1016/j.dib.2020.105899
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author Rueda-Bayona, Juan Gabriel
Horrillo-Caraballo, José
Chaparro, Tatiana R.
author_facet Rueda-Bayona, Juan Gabriel
Horrillo-Caraballo, José
Chaparro, Tatiana R.
author_sort Rueda-Bayona, Juan Gabriel
collection PubMed
description This data article presents set-up and input data files to model a surface river plume through curvilinear nested grid in double-way mode. The hydrodynamic modelling in river deltas with intense transport processes and complex bathymetry such as the Magdalena River delta, requires a mesh grid that ease the natural river discharge into the ocean. The aforementioned may be challenging due to the numerical scheme and stability restrictions of the numerical models that difficult having efficient and effective validated simulations. This dataset files are a reference to perform analysis of the hydrodynamic river deltas, meaningful for optimizing time and resources, easing the planning of measurement campaigns what reduce risks of the personnel and instrumentation during equipment deployment and field work .The application of the set-up and input data files of this data article is shown in Rueda-Bayona et al. [1].
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spelling pubmed-73343852020-07-07 Modelling of surface river plume using set-up and input data files of Delft-3D model Rueda-Bayona, Juan Gabriel Horrillo-Caraballo, José Chaparro, Tatiana R. Data Brief Engineering This data article presents set-up and input data files to model a surface river plume through curvilinear nested grid in double-way mode. The hydrodynamic modelling in river deltas with intense transport processes and complex bathymetry such as the Magdalena River delta, requires a mesh grid that ease the natural river discharge into the ocean. The aforementioned may be challenging due to the numerical scheme and stability restrictions of the numerical models that difficult having efficient and effective validated simulations. This dataset files are a reference to perform analysis of the hydrodynamic river deltas, meaningful for optimizing time and resources, easing the planning of measurement campaigns what reduce risks of the personnel and instrumentation during equipment deployment and field work .The application of the set-up and input data files of this data article is shown in Rueda-Bayona et al. [1]. Elsevier 2020-06-23 /pmc/articles/PMC7334385/ /pubmed/32642515 http://dx.doi.org/10.1016/j.dib.2020.105899 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Engineering
Rueda-Bayona, Juan Gabriel
Horrillo-Caraballo, José
Chaparro, Tatiana R.
Modelling of surface river plume using set-up and input data files of Delft-3D model
title Modelling of surface river plume using set-up and input data files of Delft-3D model
title_full Modelling of surface river plume using set-up and input data files of Delft-3D model
title_fullStr Modelling of surface river plume using set-up and input data files of Delft-3D model
title_full_unstemmed Modelling of surface river plume using set-up and input data files of Delft-3D model
title_short Modelling of surface river plume using set-up and input data files of Delft-3D model
title_sort modelling of surface river plume using set-up and input data files of delft-3d model
topic Engineering
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334385/
https://www.ncbi.nlm.nih.gov/pubmed/32642515
http://dx.doi.org/10.1016/j.dib.2020.105899
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