Assessing the utility of using current generation high-resolution satellites (Sentinel 2 and Landsat 8) to monitor large water supply dam in South Africa

Abstract

The Vaal Dam is one of the largest impounded water resources in South Africa with a capacity of 2330 × 106 m3 and surface area of 321.07 km2. The Dam is part of the Vaal river system with a catchment area of about 37 100 km2 and is designed to supply water to the large metropolitan city of Johannesburg in the north and the surrounding areas in the Gauteng Province serving approximately 13 million people. The Dam is biologically productive and experiences frequent algal blooms especially during summer months (February to April). Recent studies have indicated the presence of toxic cyanobacteria genera such as Anabaena, Lyngbya, and Microcystis and these can be of great concern for ecosystem health as well as biodiversity. Currently, ground-based methods are employed to assess and monitor the water quality of the Dam. This method is costly and lacks the temporal and spatial resolution. Therefore, a more efficient observation tools are required for effective monitoring. Satellite remote sensing is an efficient tool that can allow accurate and timely detection of harmful algal blooms (HABs) such as the toxic cyanobacteria genera and other algal types. This study focuses on assessing the utility of using current generation Satellites (Sentinel 2 and Landsat 8) to characterize the water quality and estimate concentrations of chlorophyll a as a proxy for HABs and the total suspended matter (TSM). The optimal correlation between in-situ and chlorophyll a retrieved from blue-green band ratio of Landsat 8 [Rrs (560)/Rrs (443)], and red/NIR of Sentinel 2 [Rrs (705)/Rrs (665)] were found to be the best indices for Chl-a retrieval in the Vaal Dam. Results for Landsat OLI dataset (R2 = 0.89; RMSE = 0.36 μg/L, P < 0.05) and Sentinel MSI dataset (R2 = 0.75; RMSE = 0.48 μg/L, P < 0.05) show high degree of accuracy. Models developed in this study will significantly improve near-real time and long-term water quality monitoring of the Vaal Dam and will effectively help to address public health issues related to water quality.