Long-Term Correlations in São Francisco River Flow: The Influence of Sobradinho Dam
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Brasileira de Meteorologia (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862019000200293 |
Resumo: | Abstract In this work we study the influence of the Sobradinho dam construction on daily streamflow of São Francisco River, Brasil, by analyzing long-range correlations in magnitude and sign time series obtained from streamflow anomalies, using the Detrended Fluctuation Analysis (DFA) method. The magnitude series relates to the nonlinear properties of the original time series, while the sign series relates to the linear properties. The streamflow data recorded during the period 1929-2009, were divided in the periods pre-construction (1929 to 1972) and post-construction (1980 to 2009) of Sobradinho dam and analyzed for small scales (less than 1 year) and for large scales (more than 1 year). In post-construction of Sobradinho dam, DFA-exponents of magnitude series increased at small scales (0.895 to 1.013) and at large scales (0.371 to 0.619) indicating that the memory associated with nonlinear components becames stronger. For sign series, the DFA-exponent increased at small scales (0.596 to 0.692) indicating stronger persistence of flow increments direction, and decreased at large scales (0.381 to 0.259) indicating stronger anti-persistence (positive increments are more likely to be followed by negative increments and vice versa). These results provide new evidence on the hydrological changes in the São Francisco River caused by human activities. |
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Long-Term Correlations in São Francisco River Flow: The Influence of Sobradinho DamstreamflowdamcorrelationsmagnitudesignAbstract In this work we study the influence of the Sobradinho dam construction on daily streamflow of São Francisco River, Brasil, by analyzing long-range correlations in magnitude and sign time series obtained from streamflow anomalies, using the Detrended Fluctuation Analysis (DFA) method. The magnitude series relates to the nonlinear properties of the original time series, while the sign series relates to the linear properties. The streamflow data recorded during the period 1929-2009, were divided in the periods pre-construction (1929 to 1972) and post-construction (1980 to 2009) of Sobradinho dam and analyzed for small scales (less than 1 year) and for large scales (more than 1 year). In post-construction of Sobradinho dam, DFA-exponents of magnitude series increased at small scales (0.895 to 1.013) and at large scales (0.371 to 0.619) indicating that the memory associated with nonlinear components becames stronger. For sign series, the DFA-exponent increased at small scales (0.596 to 0.692) indicating stronger persistence of flow increments direction, and decreased at large scales (0.381 to 0.259) indicating stronger anti-persistence (positive increments are more likely to be followed by negative increments and vice versa). These results provide new evidence on the hydrological changes in the São Francisco River caused by human activities.Sociedade Brasileira de Meteorologia2019-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862019000200293Revista Brasileira de Meteorologia v.34 n.2 2019reponame:Revista Brasileira de Meteorologia (Online)instname:Sociedade Brasileira de Meteorologia (SBMET)instacron:SBMET10.1590/0102-77863340242info:eu-repo/semantics/openAccessBarreto,Ikaro Daniel de CarvalhoXavier Junior,Silvio Fernando AlvesStosic,Tatijanaeng2019-08-22T00:00:00Zoai:scielo:S0102-77862019000200293Revistahttp://www.rbmet.org.br/port/index.phpONGhttps://old.scielo.br/oai/scielo-oai.php||rbmet@rbmet.org.br1982-43510102-7786opendoar:2019-08-22T00:00Revista Brasileira de Meteorologia (Online) - Sociedade Brasileira de Meteorologia (SBMET)false |
dc.title.none.fl_str_mv |
Long-Term Correlations in São Francisco River Flow: The Influence of Sobradinho Dam |
title |
Long-Term Correlations in São Francisco River Flow: The Influence of Sobradinho Dam |
spellingShingle |
Long-Term Correlations in São Francisco River Flow: The Influence of Sobradinho Dam Barreto,Ikaro Daniel de Carvalho streamflow dam correlations magnitude sign |
title_short |
Long-Term Correlations in São Francisco River Flow: The Influence of Sobradinho Dam |
title_full |
Long-Term Correlations in São Francisco River Flow: The Influence of Sobradinho Dam |
title_fullStr |
Long-Term Correlations in São Francisco River Flow: The Influence of Sobradinho Dam |
title_full_unstemmed |
Long-Term Correlations in São Francisco River Flow: The Influence of Sobradinho Dam |
title_sort |
Long-Term Correlations in São Francisco River Flow: The Influence of Sobradinho Dam |
author |
Barreto,Ikaro Daniel de Carvalho |
author_facet |
Barreto,Ikaro Daniel de Carvalho Xavier Junior,Silvio Fernando Alves Stosic,Tatijana |
author_role |
author |
author2 |
Xavier Junior,Silvio Fernando Alves Stosic,Tatijana |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Barreto,Ikaro Daniel de Carvalho Xavier Junior,Silvio Fernando Alves Stosic,Tatijana |
dc.subject.por.fl_str_mv |
streamflow dam correlations magnitude sign |
topic |
streamflow dam correlations magnitude sign |
description |
Abstract In this work we study the influence of the Sobradinho dam construction on daily streamflow of São Francisco River, Brasil, by analyzing long-range correlations in magnitude and sign time series obtained from streamflow anomalies, using the Detrended Fluctuation Analysis (DFA) method. The magnitude series relates to the nonlinear properties of the original time series, while the sign series relates to the linear properties. The streamflow data recorded during the period 1929-2009, were divided in the periods pre-construction (1929 to 1972) and post-construction (1980 to 2009) of Sobradinho dam and analyzed for small scales (less than 1 year) and for large scales (more than 1 year). In post-construction of Sobradinho dam, DFA-exponents of magnitude series increased at small scales (0.895 to 1.013) and at large scales (0.371 to 0.619) indicating that the memory associated with nonlinear components becames stronger. For sign series, the DFA-exponent increased at small scales (0.596 to 0.692) indicating stronger persistence of flow increments direction, and decreased at large scales (0.381 to 0.259) indicating stronger anti-persistence (positive increments are more likely to be followed by negative increments and vice versa). These results provide new evidence on the hydrological changes in the São Francisco River caused by human activities. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-06-01 |
dc.type.driver.fl_str_mv |
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://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862019000200293 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862019000200293 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0102-77863340242 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Meteorologia |
publisher.none.fl_str_mv |
Sociedade Brasileira de Meteorologia |
dc.source.none.fl_str_mv |
Revista Brasileira de Meteorologia v.34 n.2 2019 reponame:Revista Brasileira de Meteorologia (Online) instname:Sociedade Brasileira de Meteorologia (SBMET) instacron:SBMET |
instname_str |
Sociedade Brasileira de Meteorologia (SBMET) |
instacron_str |
SBMET |
institution |
SBMET |
reponame_str |
Revista Brasileira de Meteorologia (Online) |
collection |
Revista Brasileira de Meteorologia (Online) |
repository.name.fl_str_mv |
Revista Brasileira de Meteorologia (Online) - Sociedade Brasileira de Meteorologia (SBMET) |
repository.mail.fl_str_mv |
||rbmet@rbmet.org.br |
_version_ |
1752122085884297216 |