Streamflow regionalization for the Mortes River Basin upstream from the Funil Hydropower Plant, MG

• Published in: Revista ambiente & água 2020, Vol.15 (3), p.1-11
• Main Authors: Amorim, Jhones Da Silva, Junqueira, Rubens, Mantovani, Vanessa Alves, Viola, Marcelo Ribeiro, Mello, Carlos Rogério de, Bento, Nicole Lopes
• Format: Article
• Language: English
• Subjects: Basins; Drainage area; ENGINEERING, ENVIRONMENTAL; Environmental monitoring; Extreme values; Fittings; Hydroelectric plants; Hydroelectric power; Hydroelectric power plants; Hydrologic data; Hydrology; Precipitation; Probability density functions; Probability theory; Regression analysis; Resource management; River basins; Rivers; Statistical analysis; statistical hydrology; Stream discharge; Stream flow; Studies; Water management; Water resources; Water resources management; Water rights; Watersheds
• ISSN: 1980-993X; 1980-993X
• DOI: 10.4136/ambi-agua.2495

 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.