Streamflow regionalization for the Mortes River Basin upstream from the Funil Hydropower Plant, MG
Maximum and minimum streamflow are fundamental for water resource management, especially for water rights. However, lack of monitoring and scarce streamflow data limit such studies. Streamflow regionalization is a useful tool to overcome these limitations. The study developed models for regionalizat...
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Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHi)
2020-06-01
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doaj-aaa7bd97328545e4a4d4114716b39c732020-11-25T03:20:36ZengInstituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHi)Revista Ambiente & Água1980-993X2020-06-0115311110.4136/ambi-agua.2495Streamflow regionalization for the Mortes River Basin upstream from the Funil Hydropower Plant, MGJhones da Silva Amorim0https://orcid.org/0000-0001-7012-9465Rubens Junqueira1https://orcid.org/0000-0002-6104-5507Vanessa Alves Mantovani2https://orcid.org/0000-0003-3493-5261Marcelo Ribeiro Viola3https://orcid.org/0000-0002-3910-0987Carlos Rogério de Mello4https://orcid.org/0000-0002-6033-5342Nicole Lopes Bento5https://orcid.org/0000-0002-0432-7655Departamento de Recursos Hídricos e Saneamento. Laboratório de Hidráulica. Universidade Federal de Lavras (UFLA), Caixa Postal 3037, CEP: 37200-900, Lavras, MG, Brazil. Departamento de Recursos Hídricos e Saneamento. Laboratório de Hidráulica. Universidade Federal de Lavras (UFLA), Caixa Postal 3037, CEP: 37200-900, Lavras, MG, Brazil. Departamento de Recursos Hídricos e Saneamento. Laboratório de Hidráulica. Universidade Federal de Lavras (UFLA), Caixa Postal 3037, CEP: 37200-900, Lavras, MG, Brazil. Departamento de Recursos Hídricos e Saneamento. Laboratório de Hidráulica. Universidade Federal de Lavras (UFLA), Caixa Postal 3037, CEP: 37200-900, Lavras, MG, Brazil. Departamento de Engenharia. Universidade Federal de Lavras (UFLA), Caixa Postal 3037, CEP: 37200-900, Lavras, MG, Brazil. Departamento de Engenharia. Universidade Federal de Lavras (UFLA), Caixa Postal 3037, CEP: 37200-900, Lavras, MG, Brazil. Maximum and minimum streamflow are fundamental for water resource management, especially for water rights. However, lack of monitoring and scarce streamflow data limit such studies. Streamflow regionalization is a useful tool to overcome these limitations. The study developed models for regionalization of the maximum and minimum reference streamflows for the Mortes River Basin (MRB) (Water Resources Planning and Management Unit - GD2), Southern Minas Gerais State. The study used long-term streamflow historical series provided by the Brazilian National Water Agency (ANA). Previous exploratory analysis was performed, and it was observed that the streamflow series are stationary according to the Mann-Kendall test. The estimation of the streamflow for different return periods (RP) was performed by fitting Probability Density Functions (PDFs) that were tested by the Anderson-Darling (AD) test. The Generalized Extreme Values (GEV) and Wakeby were the most appropriate PDFs for maximum and minimum streamflows, respectively. The streamflow models were fitted using a power regression procedure, considering the drainage area of the watersheds as inputs. The fittings reached the coefficient of determination (R2) greater than 0.90. Thus, the streamflow regionalization models demonstrated good performance and are a potential tool to be used for water resource management in the studied basin.https://www.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2020000300303&lng=en&nrm=iso&tlng=enprobability density functionsstatistical hydrology |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jhones da Silva Amorim Rubens Junqueira Vanessa Alves Mantovani Marcelo Ribeiro Viola Carlos Rogério de Mello Nicole Lopes Bento |
spellingShingle |
Jhones da Silva Amorim Rubens Junqueira Vanessa Alves Mantovani Marcelo Ribeiro Viola Carlos Rogério de Mello Nicole Lopes Bento Streamflow regionalization for the Mortes River Basin upstream from the Funil Hydropower Plant, MG Revista Ambiente & Água probability density functions statistical hydrology |
author_facet |
Jhones da Silva Amorim Rubens Junqueira Vanessa Alves Mantovani Marcelo Ribeiro Viola Carlos Rogério de Mello Nicole Lopes Bento |
author_sort |
Jhones da Silva Amorim |
title |
Streamflow regionalization for the Mortes River Basin upstream from the Funil Hydropower Plant, MG |
title_short |
Streamflow regionalization for the Mortes River Basin upstream from the Funil Hydropower Plant, MG |
title_full |
Streamflow regionalization for the Mortes River Basin upstream from the Funil Hydropower Plant, MG |
title_fullStr |
Streamflow regionalization for the Mortes River Basin upstream from the Funil Hydropower Plant, MG |
title_full_unstemmed |
Streamflow regionalization for the Mortes River Basin upstream from the Funil Hydropower Plant, MG |
title_sort |
streamflow regionalization for the mortes river basin upstream from the funil hydropower plant, mg |
publisher |
Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHi) |
series |
Revista Ambiente & Água |
issn |
1980-993X |
publishDate |
2020-06-01 |
description |
Maximum and minimum streamflow are fundamental for water resource management, especially for water rights. However, lack of monitoring and scarce streamflow data limit such studies. Streamflow regionalization is a useful tool to overcome these limitations. The study developed models for regionalization of the maximum and minimum reference streamflows for the Mortes River Basin (MRB) (Water Resources Planning and Management Unit - GD2), Southern Minas Gerais State. The study used long-term streamflow historical series provided by the Brazilian National Water Agency (ANA). Previous exploratory analysis was performed, and it was observed that the streamflow series are stationary according to the Mann-Kendall test. The estimation of the streamflow for different return periods (RP) was performed by fitting Probability Density Functions (PDFs) that were tested by the Anderson-Darling (AD) test. The Generalized Extreme Values (GEV) and Wakeby were the most appropriate PDFs for maximum and minimum streamflows, respectively. The streamflow models were fitted using a power regression procedure, considering the drainage area of the watersheds as inputs. The fittings reached the coefficient of determination (R2) greater than 0.90. Thus, the streamflow regionalization models demonstrated good performance and are a potential tool to be used for water resource management in the studied basin. |
topic |
probability density functions statistical hydrology |
url |
https://www.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2020000300303&lng=en&nrm=iso&tlng=en |
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