We used remote sensing and water quality indices to support fish farming planning and monitoring in the Graminha Reservoir in São Paulo, Brazil. Data collected between January 2020 and May 2024 by the São Paulo State Environmental Agency were used to calculate the Water Quality Index (WQI), Trophic State Index (TSI), and the Water Quality Index for Aquatic Life Protection (WQIALP). Total phosphorus, chlorophyll-a, dissolved oxygen, pH, toxic substances, and thermotolerant coliforms were considered in the calculations. In addition, Sentinel-2/Copernicus satellite images from 2016 to 2025 were analyzed to assess the hydrological dynamics of the reservoir. Finally, in situ measurements from 17 sites across the reservoir included temperature, dissolved oxygen, conductivity, pH, turbidity, alkalinity, orthophosphate (P-PO₄), nitrite (N-NO₂), chlorophyll-a, and total coliform.
The average WQI was 4.4 upstream and 3.6 downstream of the reservoir, showing significant geospatial variation in water quality. The main contributors to this variation were total phosphorus and chlorophyll-a, which are directly related to eutrophication and algal blooms, and thermotolerant coliform levels. Historical data showed a gradual reduction in these variables, likely due to improved sewage treatment. However, phosphorus remains a critical element, with a theoretical maximum load of 142 tons to maintain mesotrophic conditions.
Reservoir volume also strongly influences water quality: drought periods and low water levels concentrate pollutants, whereas sudden refilling events can increase runoff impacts. Satellite images (Sentinel-2/Copernicus) confirmed large fluctuations in the water surface area over time. These spatial and temporal variations affect the suitability of specific reservoir areas for cage farming, potentially impacting its productivity and profitability.
This study highlights the need to keep a close watch on water resources and manage them carefully to protect the environment and support fish farming. The suggested plans include cutting down on pollution, controlling land use around the reservoir, and better planning of fish farming based on water changes. It is also important to adjust fish farming methods to different water quality conditions. Using remote sensing is helpful for planning and checking fish farming activities in reservoirs.
Acknowledgements
We thank FAPESP (Process 2022/09319-9) for the financial support provided to the Semear Digital Project.