Verification of inflow into hydropower reservoirs using ensemble forecasts of the TIGGE database for large scale basins in Brazil
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/247012 |
Resumo: | Study region This paper describes a major ensemble-forecasts verification effort for inflows of three large-scale river basins of Brazil: Upper São Francisco, Doce, and Tocantins Rivers. Study focus In experimental scenarios, inflow forecasts were generated forcing one hydrological model with quantitative precipitation forecasts (QPF) from three selected models of the TIGGE database. This study provides information on the regional ensemble performance and also evaluates how different QPF models respond for the different basins and what happens with the use of combined QPF in a greater ensemble. New hydrological insights for the region This work presents one of the first extensive efforts to evaluate ensemble forecasts for large-scale basins in South America using TIGGE archive data. Results from these scenarios provide validation criteria and confirm that ensemble forecasts depend on the particular EPS used to run the hydrological model and on the basin studied. Furthermore, the use of the Super Ensemble seems to be a good strategy in terms of performance and robustness. The importance of the TIGGE database is also highlighted. |
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Fan, Fernando MainardiSchwanenberg, DirkCollischonn, WalterWeerts, Albrecht2022-08-16T04:47:51Z20152214-5818http://hdl.handle.net/10183/247012000992061Study region This paper describes a major ensemble-forecasts verification effort for inflows of three large-scale river basins of Brazil: Upper São Francisco, Doce, and Tocantins Rivers. Study focus In experimental scenarios, inflow forecasts were generated forcing one hydrological model with quantitative precipitation forecasts (QPF) from three selected models of the TIGGE database. This study provides information on the regional ensemble performance and also evaluates how different QPF models respond for the different basins and what happens with the use of combined QPF in a greater ensemble. New hydrological insights for the region This work presents one of the first extensive efforts to evaluate ensemble forecasts for large-scale basins in South America using TIGGE archive data. Results from these scenarios provide validation criteria and confirm that ensemble forecasts depend on the particular EPS used to run the hydrological model and on the basin studied. Furthermore, the use of the Super Ensemble seems to be a good strategy in terms of performance and robustness. The importance of the TIGGE database is also highlighted.application/pdfengJournal of Hydrology : regional studies. Amsterdam : Elsevier B.V. Vol. 4 (2015), p. 196-227Previsao de vazoesPrevisão hidrológicaReservatóriosUsinas hidrelétricasSão Francisco, Rio, BaciaDoce, Rio, Bacia (MG e ES)Tocantins, Rio, BaciaEnsemble forecastingTIGGE databaseInflow forecastingVerification of inflow into hydropower reservoirs using ensemble forecasts of the TIGGE database for large scale basins in BrazilEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT000992061.pdf.txt000992061.pdf.txtExtracted Texttext/plain102727http://www.lume.ufrgs.br/bitstream/10183/247012/2/000992061.pdf.txt44527fec0f59bb478a5203a8b204c728MD52ORIGINAL000992061.pdfTexto completo (inglês)application/pdf6859203http://www.lume.ufrgs.br/bitstream/10183/247012/1/000992061.pdf7f3439d34c28bcc0eb39fda5e6af5d6fMD5110183/2470122024-03-27 06:39:03.092286oai:www.lume.ufrgs.br:10183/247012Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2024-03-27T09:39:03Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Verification of inflow into hydropower reservoirs using ensemble forecasts of the TIGGE database for large scale basins in Brazil |
title |
Verification of inflow into hydropower reservoirs using ensemble forecasts of the TIGGE database for large scale basins in Brazil |
spellingShingle |
Verification of inflow into hydropower reservoirs using ensemble forecasts of the TIGGE database for large scale basins in Brazil Fan, Fernando Mainardi Previsao de vazoes Previsão hidrológica Reservatórios Usinas hidrelétricas São Francisco, Rio, Bacia Doce, Rio, Bacia (MG e ES) Tocantins, Rio, Bacia Ensemble forecasting TIGGE database Inflow forecasting |
title_short |
Verification of inflow into hydropower reservoirs using ensemble forecasts of the TIGGE database for large scale basins in Brazil |
title_full |
Verification of inflow into hydropower reservoirs using ensemble forecasts of the TIGGE database for large scale basins in Brazil |
title_fullStr |
Verification of inflow into hydropower reservoirs using ensemble forecasts of the TIGGE database for large scale basins in Brazil |
title_full_unstemmed |
Verification of inflow into hydropower reservoirs using ensemble forecasts of the TIGGE database for large scale basins in Brazil |
title_sort |
Verification of inflow into hydropower reservoirs using ensemble forecasts of the TIGGE database for large scale basins in Brazil |
author |
Fan, Fernando Mainardi |
author_facet |
Fan, Fernando Mainardi Schwanenberg, Dirk Collischonn, Walter Weerts, Albrecht |
author_role |
author |
author2 |
Schwanenberg, Dirk Collischonn, Walter Weerts, Albrecht |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Fan, Fernando Mainardi Schwanenberg, Dirk Collischonn, Walter Weerts, Albrecht |
dc.subject.por.fl_str_mv |
Previsao de vazoes Previsão hidrológica Reservatórios Usinas hidrelétricas São Francisco, Rio, Bacia Doce, Rio, Bacia (MG e ES) Tocantins, Rio, Bacia |
topic |
Previsao de vazoes Previsão hidrológica Reservatórios Usinas hidrelétricas São Francisco, Rio, Bacia Doce, Rio, Bacia (MG e ES) Tocantins, Rio, Bacia Ensemble forecasting TIGGE database Inflow forecasting |
dc.subject.eng.fl_str_mv |
Ensemble forecasting TIGGE database Inflow forecasting |
description |
Study region This paper describes a major ensemble-forecasts verification effort for inflows of three large-scale river basins of Brazil: Upper São Francisco, Doce, and Tocantins Rivers. Study focus In experimental scenarios, inflow forecasts were generated forcing one hydrological model with quantitative precipitation forecasts (QPF) from three selected models of the TIGGE database. This study provides information on the regional ensemble performance and also evaluates how different QPF models respond for the different basins and what happens with the use of combined QPF in a greater ensemble. New hydrological insights for the region This work presents one of the first extensive efforts to evaluate ensemble forecasts for large-scale basins in South America using TIGGE archive data. Results from these scenarios provide validation criteria and confirm that ensemble forecasts depend on the particular EPS used to run the hydrological model and on the basin studied. Furthermore, the use of the Super Ensemble seems to be a good strategy in terms of performance and robustness. The importance of the TIGGE database is also highlighted. |
publishDate |
2015 |
dc.date.issued.fl_str_mv |
2015 |
dc.date.accessioned.fl_str_mv |
2022-08-16T04:47:51Z |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10183/247012 |
dc.identifier.issn.pt_BR.fl_str_mv |
2214-5818 |
dc.identifier.nrb.pt_BR.fl_str_mv |
000992061 |
identifier_str_mv |
2214-5818 000992061 |
url |
http://hdl.handle.net/10183/247012 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Journal of Hydrology : regional studies. Amsterdam : Elsevier B.V. Vol. 4 (2015), p. 196-227 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFRGS instname:Universidade Federal do Rio Grande do Sul (UFRGS) instacron:UFRGS |
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UFRGS |
reponame_str |
Repositório Institucional da UFRGS |
collection |
Repositório Institucional da UFRGS |
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Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS) |
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