Variação espaço-temporal da temperatura da água e suas relações com a ocorrência de florações algais do reservatório de Itaipu, PR, Brasil

• Ano de defesa: 2021
• Autor(a) principal: Kramer, Gisieli
• Orientador(a): Pereira Filho, Waterloo
• Banca de defesa: Cassol, Roberto, Cabral, João Batista Pereira, Carvalho, Lino Augusto Sander de, Trindade , Patricia Michele Pereira
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Centro de Ciências Naturais e Exatas
• Programa de Pós-Graduação: Programa de Pós-Graduação em Geografia
• Departamento: Geografia
• País: Brasil
• Palavras-chave em Português: Temperatura; Florações algais; Reservatório
• Palavras-chave em Inglês: Temperature; Algal blooms; Reservoir
• Área do conhecimento CNPq: CNPQ::CIENCIAS HUMANAS::GEOGRAFIA
• Link de acesso: http://repositorio.ufsm.br/handle/1/22251

The study on the dynamics of water temperature by remote sensing can provide an understanding of metabolic changes in large water bodies. Hence, the objective of the present research was to identify the spatiotemporal variation in water temperature and its effect on areas of algal bloom recurrence. The study area comprised the water compartments São Francisco Verdadeiro (SFV), Ocoí, and the central area of the Itaipu Reservoir, on the Paraná River, located in the western region of the State of Paraná, Brasil. The research methodology gathered four data production fronts: 1) on water surface temperature in the SFV water compartment registered in situ (TSAi) and satellite images (TSAs) from 2015 to 2017 for the development and validation of a mathematical model for estimating (TSAe); 2) application of this model and identification of TSAe, in the study areas between 2013 and 2020; and 3) occurrence of thermal plumes and their relationship with algal blooms. TSA estimates were generated from Landsat 8 satellite image data, Thermal Infrared Sensor (TIRS), and processed in Envi 5.5 softwares, using the Band Math tool and the QGIS 2.14, and employing the Planck Equation method, which is in the Land Surface Temperature (LST) plugin. Given the implementation of the model in the study area, with statistically significant performance (RMSE of 0.8°C), the variation in TSAe indicated average estimates between 18 and 27°C from 2013 to 2020. However, statistically significant changes in TSAe were noted between periods of presence and absence of blooms with mean differences > 0, which occurred for all seasons of the year, with greater frequency for the autumn and winter periods. These changes raised the maximum average temperatures in the blooming sites with 28°C in autumn, 26°C in winter, 27.91°C in spring, and 31.79°C in summer. The Ocoí aquatic compartment showed the highest frequency of blooming in June and August, while the highest for SFV was in May. Mostly, the highest recurrence of the previously mentioned blooms in 2019 and 2020 was noticeable. Furthermore, these were the years with the highest average maximum air temperatures. This fact possibly favored the warming of the waters and resulted in the intensification of algae bloom episodes. It was observed that, under the same period of analysis, in 2019, in the water column, the presence of blooms and the heating of the TSAe in the SFV provided differences in the thermal gradient concerning the Ocoí, which can determine the beginning and duration of the thermal stratification. The temperature variation observed in the water compartments was greater than in the reservoir area, where no episode of algal bloom was identified. Reservoirs with this scenario and history of blooms tend to be more susceptible, in the future, to increased frequency and severity of algal blooms, unless other variables, such as nutrient availability, are not sufficient to support their growth.