Most pollutants found in rivers come from the discharge of raw sewage from both point and nonpoint sources. So, monitoring the pollution levels in surface water sources is essential. River pollution monitoring is a real challenge. Using remote sensing, precise outcomes can be achieved with the help of the selection of the right combination of satellite images and algorithms. Generally, established available algorithms are site-specific, indicating that they may not work at all areas on Earth's surface due to differences in altitude, cloud cover, and sun glint. The present work determined Chlorophyll-a concentrations in the Tapi River at various locations using Landsat-8 satellite images and Acolite software from 2017 to 2021 Period. The outcomes reveal that applying the dark spectrum fitting with sun glint correction when processing Landsat-8 satellite images is needed. In the present study, water quality results were obtained very precisely for the months of January, February, November, and December after processing and analysing satellite images. Due to factors such as sun glare, cloud cover, cloud shadow, and haze, the desired effect could not be achieved in the remaining months of the study period. This research provides a solid foundation for estimating the impact of eutrophication in the water body by estimating chlorophyll-a concentration from satellite images.

Eutrophication of the urban water bodies is one the biggest challenge causing severe ecological and economic loss. Urban ponds are more prone to eutrophication due to their small size and polluted catchment areas. Biomonitoring using phytoplankton provides cost-effective estimation of the level of eutrophication. Ten urban ponds in different areas of the Mumbai city were chosen to investigate the phytoplankton community structure, and level of eutrophication. We assessed the 3 algal indices viz. Shannon-Wiener indices, Palmer and Nygard's (Myxophycean and diatom) indices. Linear relationship of these indices was tested against Carlson trophic state indices in order to assess the effectiveness of these indices to measure the degree of eutrophication in urban lakes. All ten lakes were found to be eutrophic, of which two were very low eutrophic (TSI – 53.74-53.95), four were low-mid eutrophic (TSI – 55.18 – 57.5), and four lakes were mid eutrophic (TSI 61.4 – 62.2). Shannon-Wiener indices (r= -0.73) and Myxophycean indices (r= 0.77) showed strong correlation with TSI whereas Diatom indices (r= -0.12) and Palmer’s Algal Pollution Indices (r= - 0.47) showed weak correlation with TSI. Thus study found that Shannon-Wiener indices and Myxophycean indices are reliable and cost effective means to assess the eutrophication of urban ponds in Mumbai.