ESTIMATION OF MAIZE PRODUCTIVITY LOSSES IN ALAGOAS FOR FUTURE CLIMATE CHANGE SCENARIOS
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , |
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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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 |
_version_ |
1809218600385380352 |