Calibration of the 1D shallow water equations: a comparison of Monte Carlo and gradient-based optimization methods

34 Pags.- 14 Figs.- 2 Algorithms. The definitive version is available at: http://jh.iwaponline.com/

Detalles Bibliográficos
Autores: Lacasta Soto, Asier, Morales-Hernández, Mario, Burguete Tolosa, Javier, Brufau, Pilar, García-Navarro, Pilar
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2017
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/149127
Acceso en línea:http://hdl.handle.net/10261/149127
Access Level:acceso abierto
Palabra clave:Calibration
Gradient Method
Monte Carlo
Adjoint method
Shallow
Water Equations
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spelling Calibration of the 1D shallow water equations: a comparison of Monte Carlo and gradient-based optimization methodsLacasta Soto, AsierMorales-Hernández, MarioBurguete Tolosa, JavierBrufau, PilarGarcía-Navarro, PilarCalibrationGradient MethodMonte CarloAdjoint methodShallowWater Equations34 Pags.- 14 Figs.- 2 Algorithms. The definitive version is available at: http://jh.iwaponline.com/The calibration of parameters in complex systems usually requires a large computational effort. Moreover, it becomes harder to perform the calibration when non-linear systems underlie the physical process, and the direction to follow in order to optimize an objective function changes depending on the situation. In the context of shallow water equations (SWE), the calibration of parameters, such as the roughness coefficient or the gauge curve for the outlet boundary condition, is often required. In this work, the SWE are used to simulate an open channel flow with lateral gates. Due to the uncertainty in the mathematical modeling that these lateral discharges may introduce into the simulation, the work is focused on the calibration of discharge coefficients. Thus, the calibration is performed by two different approaches. On the one hand, a classical Monte Carlo method is used. On the other hand, the development and application of an adjoint formulation to evaluate the gradient is presented. This is then used in a gradient-based optimizer and is compared with the stochastic approach. The advantages and disadvantages are illustrated and discussed through different test cases.This research has been partially funded by the Spanish MINECO/FEDER through the Research Project CGL2015-66114-R and by Diputación General de Aragón, DGA, through FEDER funds. The first author was also supported by the Spanish Ministry of Economy and Competitiveness fellowship BES-2012-053691.Peer reviewedMinisterio de Economía y Competitividad (España)Gobierno de AragónConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]201720172017info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Postprintinfo:eu-repo/semantics/acceptedVersionhttp://hdl.handle.net/10261/149127reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Ingléshttp://dx.doi.org/10.2166/hydro.2017.021Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/1491272026-05-22T06:33:51Z
dc.title.none.fl_str_mv Calibration of the 1D shallow water equations: a comparison of Monte Carlo and gradient-based optimization methods
title Calibration of the 1D shallow water equations: a comparison of Monte Carlo and gradient-based optimization methods
spellingShingle Calibration of the 1D shallow water equations: a comparison of Monte Carlo and gradient-based optimization methods
Lacasta Soto, Asier
Calibration
Gradient Method
Monte Carlo
Adjoint method
Shallow
Water Equations
title_short Calibration of the 1D shallow water equations: a comparison of Monte Carlo and gradient-based optimization methods
title_full Calibration of the 1D shallow water equations: a comparison of Monte Carlo and gradient-based optimization methods
title_fullStr Calibration of the 1D shallow water equations: a comparison of Monte Carlo and gradient-based optimization methods
title_full_unstemmed Calibration of the 1D shallow water equations: a comparison of Monte Carlo and gradient-based optimization methods
title_sort Calibration of the 1D shallow water equations: a comparison of Monte Carlo and gradient-based optimization methods
dc.creator.none.fl_str_mv Lacasta Soto, Asier
Morales-Hernández, Mario
Burguete Tolosa, Javier
Brufau, Pilar
García-Navarro, Pilar
author Lacasta Soto, Asier
author_facet Lacasta Soto, Asier
Morales-Hernández, Mario
Burguete Tolosa, Javier
Brufau, Pilar
García-Navarro, Pilar
author_role author
author2 Morales-Hernández, Mario
Burguete Tolosa, Javier
Brufau, Pilar
García-Navarro, Pilar
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Ministerio de Economía y Competitividad (España)
Gobierno de Aragón
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Calibration
Gradient Method
Monte Carlo
Adjoint method
Shallow
Water Equations
topic Calibration
Gradient Method
Monte Carlo
Adjoint method
Shallow
Water Equations
description 34 Pags.- 14 Figs.- 2 Algorithms. The definitive version is available at: http://jh.iwaponline.com/
publishDate 2017
dc.date.none.fl_str_mv 2017
2017
2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Postprint
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/149127
url http://hdl.handle.net/10261/149127
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv http://dx.doi.org/10.2166/hydro.2017.021
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812455

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