Few studies have assessed mining-associated water pollution using spectral characteristics. We used high-resolution multispectral
data acquired by unmanned aerial drones combined with in situ chemical data to assess water quality parameters
in 12 relatively small water bodies located in the Tharsis complex, an abandoned mining area in the Iberian pyrite belt
(SW Spain). The spectral bands of Micasense RedEdge-MX Dual and spectral band combinations were used jointly with
physicochemical data to estimate water quality parameters and develop reliable empirical models using regression analysis.
Physicochemical parameters including pH, ORP, EC, Al, Cu, Fe, Mn, S, Si, and Zn were estimated with high accuracy levels
(0.81 < R2
< 0.99, 4 < RMSE% < 75, 0.01 < MAPE < 0.97). In contrast, the observed and modelled values for Ba, Ca, and
Mg did not agree well (0.42 < R2
< 0.70). The best-fitted models were used to generate spatial distribution maps, providing
information on water quality patterns. This study demonstrated that using empirical models to generate spatial distribution
maps can be an effective and easy way to monitor acid mine drainage.