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  • 标题:Regionalização de vazões para a bacia hidrográfica do Rio das Mortes a montante da Usina Hidrelétrica do Funil, MG
  • 其他标题:Streamflow regionalization for the Mortes River Basin upstream from the Funil Hydropower Plant, MG
  • 本地全文:下载
  • 作者:Amorim, Jhones da Silva ; Junqueira, Rubens ; Mantovani, Vanessa Alves
  • 期刊名称:Revista Ambiente & Água
  • 印刷版ISSN:1980-993X
  • 出版年度:2020
  • 卷号:15
  • 期号:3
  • 页码:1-11
  • DOI:10.4136/ambi-agua.2495
  • 出版社:Instituto de Pesquisas Ambientais em Bacias Hidrográficas
  • 摘要: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.
  • 关键词:funções densidade de probabilidade;gestão dos recursos hídricos;hidrologia estatística
  • 其他关键词:probability density functions;statistical hydrology;water resource management
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