Avaliação da estratificação térmica e química no reservatório da UHE Itumbiara, Bacia do Rio Paranaíba

Detalhes bibliográficos
Ano de defesa: 2023
Autor(a) principal: Silva, Carla Ferreira Borges
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Uberlândia
Brasil
Programa de Pós-graduação em Qualidade Ambiental
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://repositorio.ufu.br/handle/123456789/38045
http://doi.org/10.14393/ufu.di.2023.113
Resumo: Periodic monitoring of ecosystems is necessary to assess the quality of water in hydroelectric reservoirs. Many parameters are analyzed to study mixing and stratification processes, allowing for a better characterization of water quality and more efficient water resource management. Factors like wind, precipitation, and solar radiation can affect the stratification of water layers. In turn, the formation of layers in the water column drives physical, chemical, and biological processes. Therefore, the main objective of this study was to evaluate the thermal and chemical stratification of the Itumbiara Hydroelectric Power Plant reservoir in Goiás, Brazil, between 2018 and 2021 with quarterly sampling. Descriptive statistical analyses were performed to assess the behavior of parameters in the surface layer and establish correlations between them and the influence of climatic and hydrological factors. The results showed that the Itumbiara reservoir remained stratified during the summer months, with a strong stability of the water column, which decreased during the winter, especially in June 2021, when complete mixing of the water column occurred. Climatic conditions (temperature) and water level influenced the mixing process of the water column, and a stronger correlation was found between variations in the profiles of water temperature, dissolved oxygen, pH, and turbidity parameters.