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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/85352
Ver los metadatos del registro completo
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:UNLP2025-09-29T11:16:25Zoai: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:13292025-09-29 11:16:26.242SEDICI (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_ |
1844616037092294656 |
score |
13.070432 |