Intervalo de tempo de máxima previsibilidade no acoplamento de modelos climáticos e hidrológico para gerenciamento de reservatório

Detalhes bibliográficos
Ano de defesa: 2014
Autor(a) principal: Cabral, Samuellson Lopes
Orientador(a): Campos, José Nilson Bezerra
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Recursos hídricos
Reservatórios
Regiões áridas
Link de acesso: http://www.repositorio.ufc.br/handle/riufc/11381
Resumo: This work seeks to integrate climatic, hydrologic, and reservoir operation models in order to optimize available water volume in the Brazilian Northeast. The global ECHAM 4.5 climate model was used to feed the RAMS regional climate model for the Alto Jaguaribe hydrographic basin. Resulting precipitation values were calibrated by the probability density function (PDF) correction of simulated data compared with average daily precipitation data using the Thiessen method for the period 1979-2009. The Heidke Skill Score (HSS) was used to evaluate model performance in the Maximum Predictable Time Interval (ITEMP) of the atmospheric model. These PDF-corrected precipitation data, both observed and RAMS-simulated, were inserted in the hydrologic Soil Moisture Account (SMA) model from the Hydrologic Engineering Center – Hydrologic Modeling System (HEC-HMS) to determine modeled flows. These flows were then compared with median observed flows. To calibrate and validate the SMA, an iterative method was used to minimize percentage error of volume. The data returned by this cascade model was applied to assisting policy-makers determine water releases from the Orós reservoir. Three different scenarios were compared, the first based on observed flows, the second flows simulated by SMA with observed precipitation, and the third by flows simulated by SMA driven by the RAMS-PDF precipitation data. The RAMS model showed optimal efficiency in precipitation prediction on a 30 to 45 day interval, with HSS values of 0.56. The SMA model showed satisfactory performance with Nash-Sutcliffe values of 0.89 in the calibration phase and 0.67 in the validation phase, demonstrating its capacity to assist hydrological modeling in the semi-arid. This cascade model showed potential in accurately representing median inflows for the reservoir and as such can be used as a hydrologic tool, assisting reservoir operation decisions to meet the region’s demand. Keywords: Soil Moisture Account; hydrologic
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spelling Cabral, Samuellson LopesCampos, José Nilson Bezerra2015-04-16T10:35:06Z2015-04-16T10:35:06Z2014CABRAL, S. L. Intervalo de tempo de máxima previsibilidade no acoplamento de modelos climáticos e hidrológico para gerenciamento de reservatório. 2014. 139 f. Tese (Doutorado em Engenharia Civil: Recursos Hídricos)-Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2014.http://www.repositorio.ufc.br/handle/riufc/11381This work seeks to integrate climatic, hydrologic, and reservoir operation models in order to optimize available water volume in the Brazilian Northeast. The global ECHAM 4.5 climate model was used to feed the RAMS regional climate model for the Alto Jaguaribe hydrographic basin. Resulting precipitation values were calibrated by the probability density function (PDF) correction of simulated data compared with average daily precipitation data using the Thiessen method for the period 1979-2009. The Heidke Skill Score (HSS) was used to evaluate model performance in the Maximum Predictable Time Interval (ITEMP) of the atmospheric model. These PDF-corrected precipitation data, both observed and RAMS-simulated, were inserted in the hydrologic Soil Moisture Account (SMA) model from the Hydrologic Engineering Center – Hydrologic Modeling System (HEC-HMS) to determine modeled flows. These flows were then compared with median observed flows. To calibrate and validate the SMA, an iterative method was used to minimize percentage error of volume. The data returned by this cascade model was applied to assisting policy-makers determine water releases from the Orós reservoir. Three different scenarios were compared, the first based on observed flows, the second flows simulated by SMA with observed precipitation, and the third by flows simulated by SMA driven by the RAMS-PDF precipitation data. The RAMS model showed optimal efficiency in precipitation prediction on a 30 to 45 day interval, with HSS values of 0.56. The SMA model showed satisfactory performance with Nash-Sutcliffe values of 0.89 in the calibration phase and 0.67 in the validation phase, demonstrating its capacity to assist hydrological modeling in the semi-arid. This cascade model showed potential in accurately representing median inflows for the reservoir and as such can be used as a hydrologic tool, assisting reservoir operation decisions to meet the region’s demand. Keywords: Soil Moisture Account; hydrologicO presente trabalho visa o acoplamento de modelo atmosférico, hidrológico e de operação de reservatório com vistas à otimização da liberação de águas no semiárido do nordeste brasileiro. O modelo atmosférico regional RAMS foi forçado pelo modelo atmosférico global ECHAM 4.5, na bacia hidrográfica do Alto Jaguaribe, e em seguida, aplicada a correção probability density function (PDF) nos dados simulados e comparado com dados diário de precipitação média observada pelo método de Thiessen no período de 1979-2009. Foi utilizando o Heidke Skill Score (HSS) como métrica principal para avaliar o desempenho da previsão em busca do Intervalo de Tempo de Máxima Previsibilidade (ITEMP) do modelo atmosférico. Os dados de precipitações observados e simulados pelo RAMS com correções PDFs foram inseridos no modelo hidrológico Soil Moisture Account (SMA) do Hydrologic Engineering Center - Hydrologic Modeling System (HEC-HMS), e comparado com as vazões médias observadas. Para a calibração e validação do SMA, foi realizado um método interativo para minimizar uma função objetivo, com base no erro percentual do volume. Por fim foi desenvolvido e avaliado um modelo de cascata a fim de comparar as decisões operacionais de liberação do reservatório Orós com diferentes cenários com base nas vazões observadas, vazões simuladas pelo SMA com a precipitação observada e vazões simuladas pelo SMA forçada com o RAMS-PDF. O modelo RAMS mostrou melhor eficiência na previsão da precipitação no intervalo de 30 a 45 dias, com valores de HSS = 0,56. O modelo SMA mostrou desempenho satisfatório com valores de Nash-Sutcliffe de 0,89 na fase de calibração e 0,67 na fase de validação, mostrando ser uma nova alternativa de utilização de modelo hidrológico no semiárido. O modelo de cascata mostrou potencial em representar bem as afluências médias do reservatório, podendo tornar uma ferramenta hidrológica, auxiliando as decisões de operação dos reservatórios, atendendo as demandas da regiãoRecursos hídricosReservatóriosRegiões áridasIntervalo de tempo de máxima previsibilidade no acoplamento de modelos climáticos e hidrológico para gerenciamento de reservatórioTime interval of maximum predictability in coupled climate and hydrological models for reservoir managementinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisporreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFCinfo:eu-repo/semantics/openAccessORIGINAL2014_tese_slcabral.pdf2014_tese_slcabral.pdfapplication/pdf4808746http://repositorio.ufc.br/bitstream/riufc/11381/1/2014_tese_slcabral.pdf0db5af5aa3dae7c70268fccfdf360f87MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81786http://repositorio.ufc.br/bitstream/riufc/11381/2/license.txt8c4401d3d14722a7ca2d07c782a1aab3MD52riufc/113812021-07-22 12:27:14.135oai:repositorio.ufc.br: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Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2021-07-22T15:27:14Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false
dc.title.pt_BR.fl_str_mv Intervalo de tempo de máxima previsibilidade no acoplamento de modelos climáticos e hidrológico para gerenciamento de reservatório
dc.title.en.pt_BR.fl_str_mv Time interval of maximum predictability in coupled climate and hydrological models for reservoir management
title Intervalo de tempo de máxima previsibilidade no acoplamento de modelos climáticos e hidrológico para gerenciamento de reservatório
spellingShingle Intervalo de tempo de máxima previsibilidade no acoplamento de modelos climáticos e hidrológico para gerenciamento de reservatório
Cabral, Samuellson Lopes
Recursos hídricos
Reservatórios
Regiões áridas
title_short Intervalo de tempo de máxima previsibilidade no acoplamento de modelos climáticos e hidrológico para gerenciamento de reservatório
title_full Intervalo de tempo de máxima previsibilidade no acoplamento de modelos climáticos e hidrológico para gerenciamento de reservatório
title_fullStr Intervalo de tempo de máxima previsibilidade no acoplamento de modelos climáticos e hidrológico para gerenciamento de reservatório
title_full_unstemmed Intervalo de tempo de máxima previsibilidade no acoplamento de modelos climáticos e hidrológico para gerenciamento de reservatório
title_sort Intervalo de tempo de máxima previsibilidade no acoplamento de modelos climáticos e hidrológico para gerenciamento de reservatório
author Cabral, Samuellson Lopes
author_facet Cabral, Samuellson Lopes
author_role author
dc.contributor.author.fl_str_mv Cabral, Samuellson Lopes
dc.contributor.advisor1.fl_str_mv Campos, José Nilson Bezerra
contributor_str_mv Campos, José Nilson Bezerra
dc.subject.por.fl_str_mv Recursos hídricos
Reservatórios
Regiões áridas
topic Recursos hídricos
Reservatórios
Regiões áridas
description This work seeks to integrate climatic, hydrologic, and reservoir operation models in order to optimize available water volume in the Brazilian Northeast. The global ECHAM 4.5 climate model was used to feed the RAMS regional climate model for the Alto Jaguaribe hydrographic basin. Resulting precipitation values were calibrated by the probability density function (PDF) correction of simulated data compared with average daily precipitation data using the Thiessen method for the period 1979-2009. The Heidke Skill Score (HSS) was used to evaluate model performance in the Maximum Predictable Time Interval (ITEMP) of the atmospheric model. These PDF-corrected precipitation data, both observed and RAMS-simulated, were inserted in the hydrologic Soil Moisture Account (SMA) model from the Hydrologic Engineering Center – Hydrologic Modeling System (HEC-HMS) to determine modeled flows. These flows were then compared with median observed flows. To calibrate and validate the SMA, an iterative method was used to minimize percentage error of volume. The data returned by this cascade model was applied to assisting policy-makers determine water releases from the Orós reservoir. Three different scenarios were compared, the first based on observed flows, the second flows simulated by SMA with observed precipitation, and the third by flows simulated by SMA driven by the RAMS-PDF precipitation data. The RAMS model showed optimal efficiency in precipitation prediction on a 30 to 45 day interval, with HSS values of 0.56. The SMA model showed satisfactory performance with Nash-Sutcliffe values of 0.89 in the calibration phase and 0.67 in the validation phase, demonstrating its capacity to assist hydrological modeling in the semi-arid. This cascade model showed potential in accurately representing median inflows for the reservoir and as such can be used as a hydrologic tool, assisting reservoir operation decisions to meet the region’s demand. Keywords: Soil Moisture Account; hydrologic
publishDate 2014
dc.date.issued.fl_str_mv 2014
dc.date.accessioned.fl_str_mv 2015-04-16T10:35:06Z
dc.date.available.fl_str_mv 2015-04-16T10:35:06Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv CABRAL, S. L. Intervalo de tempo de máxima previsibilidade no acoplamento de modelos climáticos e hidrológico para gerenciamento de reservatório. 2014. 139 f. Tese (Doutorado em Engenharia Civil: Recursos Hídricos)-Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2014.
dc.identifier.uri.fl_str_mv http://www.repositorio.ufc.br/handle/riufc/11381
identifier_str_mv CABRAL, S. L. Intervalo de tempo de máxima previsibilidade no acoplamento de modelos climáticos e hidrológico para gerenciamento de reservatório. 2014. 139 f. Tese (Doutorado em Engenharia Civil: Recursos Hídricos)-Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2014.
url http://www.repositorio.ufc.br/handle/riufc/11381
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da Universidade Federal do Ceará (UFC)
instname:Universidade Federal do Ceará (UFC)
instacron:UFC
instname_str Universidade Federal do Ceará (UFC)
instacron_str UFC
institution UFC
reponame_str Repositório Institucional da Universidade Federal do Ceará (UFC)
collection Repositório Institucional da Universidade Federal do Ceará (UFC)
bitstream.url.fl_str_mv http://repositorio.ufc.br/bitstream/riufc/11381/1/2014_tese_slcabral.pdf
http://repositorio.ufc.br/bitstream/riufc/11381/2/license.txt
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repository.name.fl_str_mv Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)
repository.mail.fl_str_mv bu@ufc.br || repositorio@ufc.br
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