Spatio-temporal assessment of inland surface water quality using remote sensing data in the wake of changing climate

Remote sensing indices have been widely used for mapping water quality parameters such as the suspended material and chlorophyll-a concentration. This study aims at investigating the spatio-temporal performance of spectral indices for mapping suspended sediments in water using Landsat 8 data. The results show that the normalized suspended material index (NSMI) is the most effective index for multi-temporal mapping of suspended solids. The use of other spectral indices in the visible to shortwave infrared also offers reasonable estimation (R-2 > 0.7; p< 0.05) of water quality parameters. It is recommended that the performance of the tested indices be compared with other indices derived from high resolution data such as the Ziyuan-3 and Sentinel-2 satellites for operational monitoring of inland water bodies.