Minimum streamflow regionalization in a Brazilian watershed under different clustering approaches
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Anais da Academia Brasileira de Ciências (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652021000801703 |
Resumo: | Abstract Estimating the minimum streamflows in rivers is essential to solving problems related to water resources. In gauged watersheds, this task is relatively easy. However, the spatial and temporal insufficiency of gauged watercourses in Brazil makes researchers rely on the hydrological regionalization technique. This study’s objective was to compare different hierarchical and non-hierarchical clustering approaches for the delimitation of hydrologically homogeneous regions in the state of Rio Grande do Sul, Brazil, aiming to regionalize the minimum streamflow that is equaled or exceeded in 90% of the time (Q90). The methodological development for the regionalization of Q90 consisted of using regression analysis supported by multivariate statistics. With respect to independent variables for regionalization, this study considered the morphoclimatic attributes of 100 watersheds located in southern Brazil. The results of this study highlighted that: (i) the clustering techniques had the potential to define hydrologically homogeneous regions, in the context of Q90 in the Rio Grande do Sul State, mostly the Ward algorithm associated with the Manhattan distance; (ii) drainage area, perimeter, centroids X and Y, and mean annual total rainfall aggregated important information that increased the accuracy of the cluster; and (iii) the refined mathematical models provided excellent performance and can be used to estimate Q90 in ungauged rivers. |
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Minimum streamflow regionalization in a Brazilian watershed under different clustering approachesdrought indicatorhydrological regionalizationmultivariate statisticsRio Grande do Sul Stateungauged watershedsAbstract Estimating the minimum streamflows in rivers is essential to solving problems related to water resources. In gauged watersheds, this task is relatively easy. However, the spatial and temporal insufficiency of gauged watercourses in Brazil makes researchers rely on the hydrological regionalization technique. This study’s objective was to compare different hierarchical and non-hierarchical clustering approaches for the delimitation of hydrologically homogeneous regions in the state of Rio Grande do Sul, Brazil, aiming to regionalize the minimum streamflow that is equaled or exceeded in 90% of the time (Q90). The methodological development for the regionalization of Q90 consisted of using regression analysis supported by multivariate statistics. With respect to independent variables for regionalization, this study considered the morphoclimatic attributes of 100 watersheds located in southern Brazil. The results of this study highlighted that: (i) the clustering techniques had the potential to define hydrologically homogeneous regions, in the context of Q90 in the Rio Grande do Sul State, mostly the Ward algorithm associated with the Manhattan distance; (ii) drainage area, perimeter, centroids X and Y, and mean annual total rainfall aggregated important information that increased the accuracy of the cluster; and (iii) the refined mathematical models provided excellent performance and can be used to estimate Q90 in ungauged rivers.Academia Brasileira de Ciências2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652021000801703Anais da Academia Brasileira de Ciências v.93 suppl.4 2021reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765202120210538info:eu-repo/semantics/openAccessBORK,CARINA K.GUEDES,HUGO A.S.BESKOW,SAMUELFRAGA,MICAEL DE S.TORMAM,MYLENA F.eng2021-11-23T00:00:00Zoai:scielo:S0001-37652021000801703Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2021-11-23T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false |
dc.title.none.fl_str_mv |
Minimum streamflow regionalization in a Brazilian watershed under different clustering approaches |
title |
Minimum streamflow regionalization in a Brazilian watershed under different clustering approaches |
spellingShingle |
Minimum streamflow regionalization in a Brazilian watershed under different clustering approaches BORK,CARINA K. drought indicator hydrological regionalization multivariate statistics Rio Grande do Sul State ungauged watersheds |
title_short |
Minimum streamflow regionalization in a Brazilian watershed under different clustering approaches |
title_full |
Minimum streamflow regionalization in a Brazilian watershed under different clustering approaches |
title_fullStr |
Minimum streamflow regionalization in a Brazilian watershed under different clustering approaches |
title_full_unstemmed |
Minimum streamflow regionalization in a Brazilian watershed under different clustering approaches |
title_sort |
Minimum streamflow regionalization in a Brazilian watershed under different clustering approaches |
author |
BORK,CARINA K. |
author_facet |
BORK,CARINA K. GUEDES,HUGO A.S. BESKOW,SAMUEL FRAGA,MICAEL DE S. TORMAM,MYLENA F. |
author_role |
author |
author2 |
GUEDES,HUGO A.S. BESKOW,SAMUEL FRAGA,MICAEL DE S. TORMAM,MYLENA F. |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
BORK,CARINA K. GUEDES,HUGO A.S. BESKOW,SAMUEL FRAGA,MICAEL DE S. TORMAM,MYLENA F. |
dc.subject.por.fl_str_mv |
drought indicator hydrological regionalization multivariate statistics Rio Grande do Sul State ungauged watersheds |
topic |
drought indicator hydrological regionalization multivariate statistics Rio Grande do Sul State ungauged watersheds |
description |
Abstract Estimating the minimum streamflows in rivers is essential to solving problems related to water resources. In gauged watersheds, this task is relatively easy. However, the spatial and temporal insufficiency of gauged watercourses in Brazil makes researchers rely on the hydrological regionalization technique. This study’s objective was to compare different hierarchical and non-hierarchical clustering approaches for the delimitation of hydrologically homogeneous regions in the state of Rio Grande do Sul, Brazil, aiming to regionalize the minimum streamflow that is equaled or exceeded in 90% of the time (Q90). The methodological development for the regionalization of Q90 consisted of using regression analysis supported by multivariate statistics. With respect to independent variables for regionalization, this study considered the morphoclimatic attributes of 100 watersheds located in southern Brazil. The results of this study highlighted that: (i) the clustering techniques had the potential to define hydrologically homogeneous regions, in the context of Q90 in the Rio Grande do Sul State, mostly the Ward algorithm associated with the Manhattan distance; (ii) drainage area, perimeter, centroids X and Y, and mean annual total rainfall aggregated important information that increased the accuracy of the cluster; and (iii) the refined mathematical models provided excellent performance and can be used to estimate Q90 in ungauged rivers. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01 |
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=S0001-37652021000801703 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652021000801703 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0001-3765202120210538 |
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 |
Academia Brasileira de Ciências |
publisher.none.fl_str_mv |
Academia Brasileira de Ciências |
dc.source.none.fl_str_mv |
Anais da Academia Brasileira de Ciências v.93 suppl.4 2021 reponame:Anais da Academia Brasileira de Ciências (Online) instname:Academia Brasileira de Ciências (ABC) instacron:ABC |
instname_str |
Academia Brasileira de Ciências (ABC) |
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ABC |
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ABC |
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Anais da Academia Brasileira de Ciências (Online) |
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Anais da Academia Brasileira de Ciências (Online) |
repository.name.fl_str_mv |
Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC) |
repository.mail.fl_str_mv |
||aabc@abc.org.br |
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1754302871291035648 |