<p>Effective water pollution assessment is essential for promoting sustainable development, especially in mining regions, where water resources are frequently degraded. Unmanned Aerial Vehicles (UAVs) and satellite imagery offer valuable tools for monitoring and evaluating surface water quality. This study aimed to compare the results of on-site water sampling with data obtained from multispectral images captured by UAVs and Sentinel-2 satellites, while also identifying the limitations of these methods. A total of 54 water samples were collected from two locations in the Sokolov coal basin in the Czech Republic during two field campaigns, in spring and autumn 2020. Concurrently, multispectral images were taken on-site using UAVs, and satellite images from Sentinel-2 satellites were also analyzed. The water samples were examined using atomic spectrometry to measure concentrations of iron, manganese, and sulfate ions. Statistically significant correlations were observed between sulfate (SO₄²⁻) concentrations and all spectral bands of the Parrot Sequoia multispectral drone camera (positive correlation), as well as between total nitrogen (TN) and the B1 and B2 spectra (green and red) (negative correlation). This study has confirmed the effectiveness of remote sensing methods as faster and more cost-efficient tools for assessing the quality of surface water impacted by open-pit coal mining. UAVs were found to be more suitable for monitoring smaller areas (units of km²) due to their superior spatial resolution compared to satellite imagery, which makes them a valuable resource for detecting water pollution in localized environments.</p>