Water quality monitoring in slightly-polluted inland water body through remote sensing —A case study in Guanting Reservoir, Beijing, China

This study focused on water quality for Guanting Reservoir, the possible auxiliary drinking water source of Beijing. Through remote sensing (RS) approach, water quality retrieval models were established and analyzed for eight common concerned water quality variables, including algae content, turbidity, and concentrations of chemical oxygen demand, total nitrogen, ammonia nitrogen, nitrate nitrogen, total phosphorus, and dissolved phosphorus, by using Landsat 5 Thematic Mapper (TM) data. The results showed that there existed a statistical significant correlation between each water quality variable and remote sensing data in the slightly-polluted inland water body with fairly weak spectral radiation. With appropriate method of sampling pixel digital numbers and multiple regression algorithms, algae content, turbidity, and nitrate nitrogen concentration could be retrieved within 10% mean relative error, concentrations of total nitrogen and dissolved phosphorus within 20%, concentrations of ammonia nitrogen and total phosphorus within 30% while chemical oxygen demand had no effective retrieval method. These accuracies were acceptable for the practical applications of routine monitoring and early warning on water quality safety with some support of precise traditional monitoring. The results showed that it was possible and effective to perform most traditional routine monitoring tasks of water quality on relatively clean inland water bodies by RS.