A predictive modelling tool for assessing climate, land use and hydrological change on reservoir quality.

Detalhes bibliográficos
Autor(a) principal: Hughes, Samantha Jane
Data de Publicação: 2012
Outros Autores: Cabecinha, Edna, Santos, João Carlos Andrade dos, Andrade, Cristina Maria Mendes, Lopes, Domingos Manuel Mendes, Trindade, Henrique Manuel da Fonseca, Cabral, João Alexandre, Santos, Mário, Lourenço, José Manuel Martinho, Aranha, José Tadeu Marques, Fernandes, Luís Filipe Sanches, Morais, Maria Manuela, Leite, Maria Solange Mendonça, Oliveira, Paula Cristina Ribeiro Coutinho de, Cortes, Rui Manuel Vitor
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10348/4304
Resumo: Reservoirs are fundamental for water and energy supply but vulnerable to impacts including climate change. This paper outlines the steps in the development of a model to predict how climate, land use and hydrological change could affect the physiochemical and ecological quality of reservoirs in Portugal’s Douro region. Climatic data will be downscaled for subsequent finer spatial scale models to develop scenarios and outputs. Field observations and satellite imagery analysis will create dynamic maps providing data on change in land use and vegetation cover, while Artificial Neural Networks will determine how climate, land use and vegetation cover change may influence catchment hydrology. Data from field surveys of biological indicators, greenhouse gas emissions plus additional research will be applied in the Stochastic Dynamic Methodology, a sequential modelling process based on statistical parameter estimation, developed to predict and model physiochemical and ecological changes in reservoirs. This interdisciplinary approach will provide vital modelling tools for end users essential for water resource management in Portugal and to comply with the EU Water Framework Directive.
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spelling A predictive modelling tool for assessing climate, land use and hydrological change on reservoir quality.PortugalClimate changeLande useHydrologyReservoirPredictive modellingReservoirs are fundamental for water and energy supply but vulnerable to impacts including climate change. This paper outlines the steps in the development of a model to predict how climate, land use and hydrological change could affect the physiochemical and ecological quality of reservoirs in Portugal’s Douro region. Climatic data will be downscaled for subsequent finer spatial scale models to develop scenarios and outputs. Field observations and satellite imagery analysis will create dynamic maps providing data on change in land use and vegetation cover, while Artificial Neural Networks will determine how climate, land use and vegetation cover change may influence catchment hydrology. Data from field surveys of biological indicators, greenhouse gas emissions plus additional research will be applied in the Stochastic Dynamic Methodology, a sequential modelling process based on statistical parameter estimation, developed to predict and model physiochemical and ecological changes in reservoirs. This interdisciplinary approach will provide vital modelling tools for end users essential for water resource management in Portugal and to comply with the EU Water Framework Directive.2015-03-17T14:20:33Z2012-01-01T00:00:00Z2012info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10348/4304eng0004-0894dodoi: 10.1111/j.1475-4762.2012.01114.xmetadata only accessinfo:eu-repo/semantics/openAccessHughes, Samantha JaneCabecinha, EdnaSantos, João Carlos Andrade dosAndrade, Cristina Maria MendesLopes, Domingos Manuel MendesTrindade, Henrique Manuel da FonsecaCabral, João AlexandreSantos, MárioLourenço, José Manuel MartinhoAranha, José Tadeu MarquesFernandes, Luís Filipe SanchesMorais, Maria ManuelaLeite, Maria Solange MendonçaOliveira, Paula Cristina Ribeiro Coutinho deCortes, Rui Manuel Vitorreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-02T12:37:13Zoai:repositorio.utad.pt:10348/4304Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:01:42.047204Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A predictive modelling tool for assessing climate, land use and hydrological change on reservoir quality.
title A predictive modelling tool for assessing climate, land use and hydrological change on reservoir quality.
spellingShingle A predictive modelling tool for assessing climate, land use and hydrological change on reservoir quality.
Hughes, Samantha Jane
Portugal
Climate change
Lande use
Hydrology
Reservoir
Predictive modelling
title_short A predictive modelling tool for assessing climate, land use and hydrological change on reservoir quality.
title_full A predictive modelling tool for assessing climate, land use and hydrological change on reservoir quality.
title_fullStr A predictive modelling tool for assessing climate, land use and hydrological change on reservoir quality.
title_full_unstemmed A predictive modelling tool for assessing climate, land use and hydrological change on reservoir quality.
title_sort A predictive modelling tool for assessing climate, land use and hydrological change on reservoir quality.
author Hughes, Samantha Jane
author_facet Hughes, Samantha Jane
Cabecinha, Edna
Santos, João Carlos Andrade dos
Andrade, Cristina Maria Mendes
Lopes, Domingos Manuel Mendes
Trindade, Henrique Manuel da Fonseca
Cabral, João Alexandre
Santos, Mário
Lourenço, José Manuel Martinho
Aranha, José Tadeu Marques
Fernandes, Luís Filipe Sanches
Morais, Maria Manuela
Leite, Maria Solange Mendonça
Oliveira, Paula Cristina Ribeiro Coutinho de
Cortes, Rui Manuel Vitor
author_role author
author2 Cabecinha, Edna
Santos, João Carlos Andrade dos
Andrade, Cristina Maria Mendes
Lopes, Domingos Manuel Mendes
Trindade, Henrique Manuel da Fonseca
Cabral, João Alexandre
Santos, Mário
Lourenço, José Manuel Martinho
Aranha, José Tadeu Marques
Fernandes, Luís Filipe Sanches
Morais, Maria Manuela
Leite, Maria Solange Mendonça
Oliveira, Paula Cristina Ribeiro Coutinho de
Cortes, Rui Manuel Vitor
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Hughes, Samantha Jane
Cabecinha, Edna
Santos, João Carlos Andrade dos
Andrade, Cristina Maria Mendes
Lopes, Domingos Manuel Mendes
Trindade, Henrique Manuel da Fonseca
Cabral, João Alexandre
Santos, Mário
Lourenço, José Manuel Martinho
Aranha, José Tadeu Marques
Fernandes, Luís Filipe Sanches
Morais, Maria Manuela
Leite, Maria Solange Mendonça
Oliveira, Paula Cristina Ribeiro Coutinho de
Cortes, Rui Manuel Vitor
dc.subject.por.fl_str_mv Portugal
Climate change
Lande use
Hydrology
Reservoir
Predictive modelling
topic Portugal
Climate change
Lande use
Hydrology
Reservoir
Predictive modelling
description Reservoirs are fundamental for water and energy supply but vulnerable to impacts including climate change. This paper outlines the steps in the development of a model to predict how climate, land use and hydrological change could affect the physiochemical and ecological quality of reservoirs in Portugal’s Douro region. Climatic data will be downscaled for subsequent finer spatial scale models to develop scenarios and outputs. Field observations and satellite imagery analysis will create dynamic maps providing data on change in land use and vegetation cover, while Artificial Neural Networks will determine how climate, land use and vegetation cover change may influence catchment hydrology. Data from field surveys of biological indicators, greenhouse gas emissions plus additional research will be applied in the Stochastic Dynamic Methodology, a sequential modelling process based on statistical parameter estimation, developed to predict and model physiochemical and ecological changes in reservoirs. This interdisciplinary approach will provide vital modelling tools for end users essential for water resource management in Portugal and to comply with the EU Water Framework Directive.
publishDate 2012
dc.date.none.fl_str_mv 2012-01-01T00:00:00Z
2012
2015-03-17T14:20:33Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10348/4304
url http://hdl.handle.net/10348/4304
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0004-0894
dodoi: 10.1111/j.1475-4762.2012.01114.x
dc.rights.driver.fl_str_mv metadata only access
info:eu-repo/semantics/openAccess
rights_invalid_str_mv metadata only access
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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