ESTIMATIVA DA TURBIDEZ E ÍNDICE DE ESTADO TRÓFICO EM CORPOS HÍDRICOS LÊNTICOS URBANOS EM RIO VERDE-GO

Abstract

The monitoring of surface waters is a highly relevant activity for water resources management. Among the available monitoring alternatives is the use of spatial tools, such as remote sensing. Thus, this study aimed to test spectral index models, surface turbidity, chlorophyll-a, and the Trophic State Index (TSI) in urban lentic water bodies of Rio Verde, Goiás, for the year 2023. Surface reflectance data obtained by the OLI sensor onboard the Landsat 8 satellite were used, provided by the United States Geological Survey (USGS) and reprojected for the southern hemisphere. The images were acquired through the Google Earth Engine platform. The spectral indices NDTI, NDWI, turbidity, chlorophyll-a, and TSI were calculated from surface reflectance using models widely disseminated in the literature. Data processing was performed using QGIS and R software. Regarding the results, greater variability in the analyzed indices was observed during the dry period, especially in May, along with higher turbidity values in December and lower ones in June, evidencing that climatic conditions directly influence water quality. These variations are associated with increased surface runoff or reduced water volume, which limits the dilution of nutrients and suspended solids, actively contributing to the degradation of aquatic ecosystems. The study areas were identified as eutrophic, according to the classification of the Trophic State Index proposed by Lamparelli (2004), showing moderate nutrient levels and the initial formation of phytoplankton. The applicability of turbidity models to the region was verified, as well as the identification of possible effects of water pollution on water quality. This research demonstrates that the adoption of environmental and water management strategies may be effective for the control and monitoring of water quality in the studied water bodies, particularly in Lago Dona Gercina and Lago Interlagos, which presented high levels of chlorophyll-a and turbidity, respectively. Objective: To test spectral index models, surface turbidity, chlorophyll-a, and the Trophic State Index of urban lentic water bodies in Rio Verde (GO), for the year 2023, using remote sensing techniques.