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The paper presents the use of satellite imagery, GIS applications and in-situ measurements for the estimation of water transparency in reservoirs. Satellite data from the Sentinel-2 sensor and interpolation methods (Kriging, IDW, Natural Neighbour, Spline, Trend) were used for Secchi Disk Transparency (SDT). The results of this study show that the Sentinel-2 blue/red band ratio is a reliable predictor of SDT with the coefficient of determination equal to 0.83 (p< 0.001). The analysis indicates low coefficients of determination between the SDT calculated using interpolation methods based on GIS and in-situ measurements. The SDT modelled on the basis of satellite imagery was further used to indicate parts of the reservoir characterized by the highest uncertainty. The high uncertainty occurs near the shoreline of the reservoir and near the dam, which might be related to spectral reflectance from wooded areas, the overgrowth process or small depth of water. Additionally, it was observed that the highest uncertainty associated with the applied individual regression occurs in the case of limit values of the B2/B4 ratio which were not used during regression model development. The results show that more than 91% of the reservoir is characterized by a standard deviation less than 0.2, while only 0.25% shows values higher than 0.5. The results indicate that the application of remote sensing has important significance for water transparency estimation in reservoirs.