Computing, a powerful tool for improving the parameters simulation quality in flood prediction

Autores
Gaudiani, Adriana Angélica; Luque Fadón, Emilio; García, Pablo; Re, Mariano; Naiouf, 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 Paraná River in Argentina, and the percentage of improvement over the original simulator values ranges from 33 to 60%.
Facultad de Informática
Materia
Ciencias Informáticas
Flood prediction
Flood simulation improvement
High performance computing in flood simulation
Parametric simulation
Tuning simulation
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/85352
Acceder
id SEDICI_b7aab8318f18ff82c0ee118c7b95ba03
oai_identifier_str oai:sedici.unlp.edu.ar:10915/85352
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Computing, a powerful tool for improving the parameters simulation quality in flood predictionGaudiani, Adriana AngélicaLuque Fadón, EmilioGarcía, PabloRe, MarianoNaiouf, MarceloDe Giusti, Armando EduardoCiencias InformáticasFlood predictionFlood simulation improvementHigh performance computing in flood simulationParametric simulationTuning simulationFloods 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 Paraná River in Argentina, and the percentage of improvement over the original simulator values ranges from 33 to 60%.Facultad de Informática2014info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf299-309http://sedici.unlp.edu.ar/handle/10915/85352enginfo:eu-repo/semantics/altIdentifier/issn/1877-0509info:eu-repo/semantics/altIdentifier/doi/10.1016/j.procs.2014.05.027info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T16:57:17Zoai:sedici.unlp.edu.ar:10915/85352Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:57:17.855SEDICI (UNLP) - Universidad Nacional de La Platafalse
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
Ciencias Informáticas
Flood prediction
Flood simulation improvement
High performance computing in flood simulation
Parametric simulation
Tuning 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
Luque Fadón, Emilio
García, Pablo
Re, Mariano
Naiouf, Marcelo
De Giusti, Armando Eduardo
author Gaudiani, Adriana Angélica
author_facet Gaudiani, Adriana Angélica
Luque Fadón, Emilio
García, Pablo
Re, Mariano
Naiouf, Marcelo
De Giusti, Armando Eduardo
author_role author
author2 Luque Fadón, Emilio
García, Pablo
Re, Mariano
Naiouf, Marcelo
De Giusti, Armando Eduardo
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Flood prediction
Flood simulation improvement
High performance computing in flood simulation
Parametric simulation
Tuning simulation
topic Ciencias Informáticas
Flood prediction
Flood simulation improvement
High performance computing in flood simulation
Parametric simulation
Tuning simulation
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 Paraná River in Argentina, and the percentage of improvement over the original simulator values ranges from 33 to 60%.
Facultad de Informática
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 Paraná 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
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
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://sedici.unlp.edu.ar/handle/10915/85352
url http://sedici.unlp.edu.ar/handle/10915/85352
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/1877-0509
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.procs.2014.05.027
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
299-309
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1846783185171513344
score 12.982451

Publicaciones similares