Computing, a Powerful Tool for Improving the Parameters Simulation Quality in Flood Prediction

Autores
Gaudiani, Adriana Angélica; Luquet, Emilio; García, Pablo; Re, Mariano; Naiouf, Ricardo Marcelo; de Giusti, Armando Eduardo
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Floods have caused widespread damage throughout the world. Modelling and simulation provide solutions and tools which enable us to forecast and make necessary steps toward prevention. One problem that must be handled by physical systems simulators is the parameters uncertainty and their impact on output results, causing prediction errors. In this paper, we address input parameter uncertainty toward providing a methodology to tune a flood simulator and achieve lower error between simulated and observed results. The tuning methodology, through a parametric simulation technique, implements a first stage to find an adjusted set of critical parameters which will be used to validate the predictive capability of the simulator in order to reduce the disagreement between observed data and simulated results. We concentrate our experiments in three significant monitoring stations, located at the lower basin of the Parańa River in Argentina, and the percentage of improvement over the original simulator values ranges from 33 to 60%.
Fil: Gaudiani, Adriana Angélica. Universidad Nacional de General Sarmiento; Argentina
Fil: Luquet, Emilio. Universitat Autònoma de Barcelona; España
Fil: García, Pablo. Instituto Nacional del Agua; Argentina
Fil: Re, Mariano. Instituto Nacional del Agua; Argentina
Fil: Naiouf, Ricardo Marcelo. Universidad Nacional de la Plata. Facultad de Informatica. Instituto de Investigación En Informatica Lidi; Argentina
Fil: de Giusti, Armando Eduardo. Universidad Nacional de la Plata. Facultad de Informatica. Instituto de Investigación En Informatica Lidi; Argentina
Materia
Parametric Simulation
Tuning Simulation
Flood Prediction
Flood Simulation Improvement
High Performance Computing in Flood Simulation
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/32575
Acceder
id CONICETDig_c0eb8ae08c053874c0b94499d5135a8e
oai_identifier_str oai:ri.conicet.gov.ar:11336/32575
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Computing, a Powerful Tool for Improving the Parameters Simulation Quality in Flood PredictionGaudiani, Adriana AngélicaLuquet, EmilioGarcía, PabloRe, MarianoNaiouf, Ricardo Marcelode Giusti, Armando EduardoParametric SimulationTuning SimulationFlood PredictionFlood Simulation ImprovementHigh Performance Computing in Flood Simulationhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Floods have caused widespread damage throughout the world. Modelling and simulation provide solutions and tools which enable us to forecast and make necessary steps toward prevention. One problem that must be handled by physical systems simulators is the parameters uncertainty and their impact on output results, causing prediction errors. In this paper, we address input parameter uncertainty toward providing a methodology to tune a flood simulator and achieve lower error between simulated and observed results. The tuning methodology, through a parametric simulation technique, implements a first stage to find an adjusted set of critical parameters which will be used to validate the predictive capability of the simulator in order to reduce the disagreement between observed data and simulated results. We concentrate our experiments in three significant monitoring stations, located at the lower basin of the Parańa River in Argentina, and the percentage of improvement over the original simulator values ranges from 33 to 60%.Fil: Gaudiani, Adriana Angélica. Universidad Nacional de General Sarmiento; ArgentinaFil: Luquet, Emilio. Universitat Autònoma de Barcelona; EspañaFil: García, Pablo. Instituto Nacional del Agua; ArgentinaFil: Re, Mariano. Instituto Nacional del Agua; ArgentinaFil: Naiouf, Ricardo Marcelo. Universidad Nacional de la Plata. Facultad de Informatica. Instituto de Investigación En Informatica Lidi; ArgentinaFil: de Giusti, Armando Eduardo. Universidad Nacional de la Plata. Facultad de Informatica. Instituto de Investigación En Informatica Lidi; ArgentinaElsevier Science2014-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/32575Luquet, Emilio; García, Pablo; Re, Mariano; de Giusti, Armando Eduardo; Naiouf, Ricardo Marcelo; Gaudiani, Adriana Angélica; et al.; Computing, a Powerful Tool for Improving the Parameters Simulation Quality in Flood Prediction; Elsevier Science; Procedia Computer Science; 29; 6-2014; 299-3091877-0509CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.procs.2014.05.027info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S187705091400204Xinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:13:53Zoai:ri.conicet.gov.ar:11336/32575instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:13:54.081CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Computing, a Powerful Tool for Improving the Parameters Simulation Quality in Flood Prediction
title Computing, a Powerful Tool for Improving the Parameters Simulation Quality in Flood Prediction
spellingShingle Computing, a Powerful Tool for Improving the Parameters Simulation Quality in Flood Prediction
Gaudiani, Adriana Angélica
Parametric Simulation
Tuning Simulation
Flood Prediction
Flood Simulation Improvement
High Performance Computing in Flood Simulation
title_short Computing, a Powerful Tool for Improving the Parameters Simulation Quality in Flood Prediction
title_full Computing, a Powerful Tool for Improving the Parameters Simulation Quality in Flood Prediction
title_fullStr Computing, a Powerful Tool for Improving the Parameters Simulation Quality in Flood Prediction
title_full_unstemmed Computing, a Powerful Tool for Improving the Parameters Simulation Quality in Flood Prediction
title_sort Computing, a Powerful Tool for Improving the Parameters Simulation Quality in Flood Prediction
dc.creator.none.fl_str_mv Gaudiani, Adriana Angélica
Luquet, Emilio
García, Pablo
Re, Mariano
Naiouf, Ricardo Marcelo
de Giusti, Armando Eduardo
author Gaudiani, Adriana Angélica
author_facet Gaudiani, Adriana Angélica
Luquet, Emilio
García, Pablo
Re, Mariano
Naiouf, Ricardo Marcelo
de Giusti, Armando Eduardo
author_role author
author2 Luquet, Emilio
García, Pablo
Re, Mariano
Naiouf, Ricardo Marcelo
de Giusti, Armando Eduardo
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Parametric Simulation
Tuning Simulation
Flood Prediction
Flood Simulation Improvement
High Performance Computing in Flood Simulation
topic Parametric Simulation
Tuning Simulation
Flood Prediction
Flood Simulation Improvement
High Performance Computing in Flood Simulation
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Floods have caused widespread damage throughout the world. Modelling and simulation provide solutions and tools which enable us to forecast and make necessary steps toward prevention. One problem that must be handled by physical systems simulators is the parameters uncertainty and their impact on output results, causing prediction errors. In this paper, we address input parameter uncertainty toward providing a methodology to tune a flood simulator and achieve lower error between simulated and observed results. The tuning methodology, through a parametric simulation technique, implements a first stage to find an adjusted set of critical parameters which will be used to validate the predictive capability of the simulator in order to reduce the disagreement between observed data and simulated results. We concentrate our experiments in three significant monitoring stations, located at the lower basin of the Parańa River in Argentina, and the percentage of improvement over the original simulator values ranges from 33 to 60%.
Fil: Gaudiani, Adriana Angélica. Universidad Nacional de General Sarmiento; Argentina
Fil: Luquet, Emilio. Universitat Autònoma de Barcelona; España
Fil: García, Pablo. Instituto Nacional del Agua; Argentina
Fil: Re, Mariano. Instituto Nacional del Agua; Argentina
Fil: Naiouf, Ricardo Marcelo. Universidad Nacional de la Plata. Facultad de Informatica. Instituto de Investigación En Informatica Lidi; Argentina
Fil: de Giusti, Armando Eduardo. Universidad Nacional de la Plata. Facultad de Informatica. Instituto de Investigación En Informatica Lidi; Argentina
description Floods have caused widespread damage throughout the world. Modelling and simulation provide solutions and tools which enable us to forecast and make necessary steps toward prevention. One problem that must be handled by physical systems simulators is the parameters uncertainty and their impact on output results, causing prediction errors. In this paper, we address input parameter uncertainty toward providing a methodology to tune a flood simulator and achieve lower error between simulated and observed results. The tuning methodology, through a parametric simulation technique, implements a first stage to find an adjusted set of critical parameters which will be used to validate the predictive capability of the simulator in order to reduce the disagreement between observed data and simulated results. We concentrate our experiments in three significant monitoring stations, located at the lower basin of the Parańa River in Argentina, and the percentage of improvement over the original simulator values ranges from 33 to 60%.
publishDate 2014
dc.date.none.fl_str_mv 2014-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/32575
Luquet, Emilio; García, Pablo; Re, Mariano; de Giusti, Armando Eduardo; Naiouf, Ricardo Marcelo; Gaudiani, Adriana Angélica; et al.; Computing, a Powerful Tool for Improving the Parameters Simulation Quality in Flood Prediction; Elsevier Science; Procedia Computer Science; 29; 6-2014; 299-309
1877-0509
CONICET Digital
CONICET
url http://hdl.handle.net/11336/32575
identifier_str_mv Luquet, Emilio; García, Pablo; Re, Mariano; de Giusti, Armando Eduardo; Naiouf, Ricardo Marcelo; Gaudiani, Adriana Angélica; et al.; Computing, a Powerful Tool for Improving the Parameters Simulation Quality in Flood Prediction; Elsevier Science; Procedia Computer Science; 29; 6-2014; 299-309
1877-0509
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.procs.2014.05.027
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S187705091400204X
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1844614060951207936
score 13.070432

Publicaciones similares