ESTIMATION OF MAIZE PRODUCTIVITY LOSSES IN ALAGOAS FOR FUTURE CLIMATE CHANGE SCENARIOS

Detalhes bibliográficos
Autor(a) principal: de Almeida, Hugo Carvalho
Data de Publicação: 2017
Outros Autores: Gonçalves Nobre, João Pedro, dos Santos Silva, Eli Moisés, dos Santos Silva, Fabrício Daniel
Tipo de documento: Artigo
Idioma: por
Título da fonte: Revista Geama
Texto Completo: https://www.journals.ufrpe.br/index.php/geama/article/view/1515
Resumo: The performance of four global models, together with two scenarios of climate change, was evaluated in five municipalities of the State of Alagoas, for precipitation, minimum and maximum temperature. The input data of the model were obtained through the conventional meteorological stations of the National Institute of Meteorology (INMET), arranged between 1961 and 2016. Estimation of corn yield was obtained through the theoretical model which relates losses in productivity and water deficiency during the phenological phases of the crop. A post-processing technique of global climate model outputs (statistical downscaling) was used, thus, a better visualization in time and space. The precipitation and temperature series were used for the period 2021-2080 estimating the yield losses of maize, comparing to the historical average values of the period 1961-2016, evaluating the impacts of possible climatic changes on crop yield. The scenarios have values of losses very close to and indicate a prediction of increased productivity loss in the period 2021-2080 for Água Branca, Pão de Açúcar and Palmeira dos Índios, and decrease of losses, that is, increase of productivity, for Maceió and Mainly Porto de Pedras. This result is directly associated to the predictions of rainfall reduction in the interior of the State, encompassing the cities of Água Branca, Pão de Açúcar and Palmeira dos Índios, a slight increase in precipitation for Maceió and a more significant increase in precipitation in Porto de Pedras.
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spelling ESTIMATION OF MAIZE PRODUCTIVITY LOSSES IN ALAGOAS FOR FUTURE CLIMATE CHANGE SCENARIOSClimatologyStatistical DownscalingAgrometeorological Model.The performance of four global models, together with two scenarios of climate change, was evaluated in five municipalities of the State of Alagoas, for precipitation, minimum and maximum temperature. The input data of the model were obtained through the conventional meteorological stations of the National Institute of Meteorology (INMET), arranged between 1961 and 2016. Estimation of corn yield was obtained through the theoretical model which relates losses in productivity and water deficiency during the phenological phases of the crop. A post-processing technique of global climate model outputs (statistical downscaling) was used, thus, a better visualization in time and space. The precipitation and temperature series were used for the period 2021-2080 estimating the yield losses of maize, comparing to the historical average values of the period 1961-2016, evaluating the impacts of possible climatic changes on crop yield. The scenarios have values of losses very close to and indicate a prediction of increased productivity loss in the period 2021-2080 for Água Branca, Pão de Açúcar and Palmeira dos Índios, and decrease of losses, that is, increase of productivity, for Maceió and Mainly Porto de Pedras. This result is directly associated to the predictions of rainfall reduction in the interior of the State, encompassing the cities of Água Branca, Pão de Açúcar and Palmeira dos Índios, a slight increase in precipitation for Maceió and a more significant increase in precipitation in Porto de Pedras.Geama Journal - Environmental SciencesRevista Geama2017-09-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.journals.ufrpe.br/index.php/geama/article/view/1515Geama Journal - Environmental Sciences; Volume 3, Número 4 (2017): Revista Geama; 242-251Revista Geama; Volume 3, Número 4 (2017): Revista Geama; 242-2512447-0740reponame:Revista Geamainstname:Universidade Federal Rural de Pernambuco (UFRPE)instacron:UFRPEporhttps://www.journals.ufrpe.br/index.php/geama/article/view/1515/1466Copyright (c) 2017 Revista Geamainfo:eu-repo/semantics/openAccessde Almeida, Hugo CarvalhoGonçalves Nobre, João Pedrodos Santos Silva, Eli Moisésdos Santos Silva, Fabrício Daniel2017-09-04T17:42:35Zoai:ojs.10.0.7.8:article/1515Revistahttps://www.journals.ufrpe.br/index.php/geamaPUBhttps://www.journals.ufrpe.br/index.php/geama/oaijosemachado@ufrpe.br2447-07402447-0740opendoar:2017-09-04T17:42:35Revista Geama - Universidade Federal Rural de Pernambuco (UFRPE)false
dc.title.none.fl_str_mv ESTIMATION OF MAIZE PRODUCTIVITY LOSSES IN ALAGOAS FOR FUTURE CLIMATE CHANGE SCENARIOS
title ESTIMATION OF MAIZE PRODUCTIVITY LOSSES IN ALAGOAS FOR FUTURE CLIMATE CHANGE SCENARIOS
spellingShingle ESTIMATION OF MAIZE PRODUCTIVITY LOSSES IN ALAGOAS FOR FUTURE CLIMATE CHANGE SCENARIOS
de Almeida, Hugo Carvalho
Climatology
Statistical Downscaling
Agrometeorological Model.
title_short ESTIMATION OF MAIZE PRODUCTIVITY LOSSES IN ALAGOAS FOR FUTURE CLIMATE CHANGE SCENARIOS
title_full ESTIMATION OF MAIZE PRODUCTIVITY LOSSES IN ALAGOAS FOR FUTURE CLIMATE CHANGE SCENARIOS
title_fullStr ESTIMATION OF MAIZE PRODUCTIVITY LOSSES IN ALAGOAS FOR FUTURE CLIMATE CHANGE SCENARIOS
title_full_unstemmed ESTIMATION OF MAIZE PRODUCTIVITY LOSSES IN ALAGOAS FOR FUTURE CLIMATE CHANGE SCENARIOS
title_sort ESTIMATION OF MAIZE PRODUCTIVITY LOSSES IN ALAGOAS FOR FUTURE CLIMATE CHANGE SCENARIOS
author de Almeida, Hugo Carvalho
author_facet de Almeida, Hugo Carvalho
Gonçalves Nobre, João Pedro
dos Santos Silva, Eli Moisés
dos Santos Silva, Fabrício Daniel
author_role author
author2 Gonçalves Nobre, João Pedro
dos Santos Silva, Eli Moisés
dos Santos Silva, Fabrício Daniel
author2_role author
author
author
dc.contributor.author.fl_str_mv de Almeida, Hugo Carvalho
Gonçalves Nobre, João Pedro
dos Santos Silva, Eli Moisés
dos Santos Silva, Fabrício Daniel
dc.subject.por.fl_str_mv Climatology
Statistical Downscaling
Agrometeorological Model.
topic Climatology
Statistical Downscaling
Agrometeorological Model.
description The performance of four global models, together with two scenarios of climate change, was evaluated in five municipalities of the State of Alagoas, for precipitation, minimum and maximum temperature. The input data of the model were obtained through the conventional meteorological stations of the National Institute of Meteorology (INMET), arranged between 1961 and 2016. Estimation of corn yield was obtained through the theoretical model which relates losses in productivity and water deficiency during the phenological phases of the crop. A post-processing technique of global climate model outputs (statistical downscaling) was used, thus, a better visualization in time and space. The precipitation and temperature series were used for the period 2021-2080 estimating the yield losses of maize, comparing to the historical average values of the period 1961-2016, evaluating the impacts of possible climatic changes on crop yield. The scenarios have values of losses very close to and indicate a prediction of increased productivity loss in the period 2021-2080 for Água Branca, Pão de Açúcar and Palmeira dos Índios, and decrease of losses, that is, increase of productivity, for Maceió and Mainly Porto de Pedras. This result is directly associated to the predictions of rainfall reduction in the interior of the State, encompassing the cities of Água Branca, Pão de Açúcar and Palmeira dos Índios, a slight increase in precipitation for Maceió and a more significant increase in precipitation in Porto de Pedras.
publishDate 2017
dc.date.none.fl_str_mv 2017-09-04
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.journals.ufrpe.br/index.php/geama/article/view/1515
url https://www.journals.ufrpe.br/index.php/geama/article/view/1515
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://www.journals.ufrpe.br/index.php/geama/article/view/1515/1466
dc.rights.driver.fl_str_mv Copyright (c) 2017 Revista Geama
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2017 Revista Geama
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Geama Journal - Environmental Sciences
Revista Geama
publisher.none.fl_str_mv Geama Journal - Environmental Sciences
Revista Geama
dc.source.none.fl_str_mv Geama Journal - Environmental Sciences; Volume 3, Número 4 (2017): Revista Geama; 242-251
Revista Geama; Volume 3, Número 4 (2017): Revista Geama; 242-251
2447-0740
reponame:Revista Geama
instname:Universidade Federal Rural de Pernambuco (UFRPE)
instacron:UFRPE
instname_str Universidade Federal Rural de Pernambuco (UFRPE)
instacron_str UFRPE
institution UFRPE
reponame_str Revista Geama
collection Revista Geama
repository.name.fl_str_mv Revista Geama - Universidade Federal Rural de Pernambuco (UFRPE)
repository.mail.fl_str_mv josemachado@ufrpe.br
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