Remote sensing-based water quality monitoring in African reservoirs, potential and limitations of sensors and algorithms: A systematic review

Abstract

Accurate spatial and temporal water quality data can enable advanced management of water resources, which are increasingly threatened as a result of climate change, rapid population growth and a rise in the demand of freshwater sources. Recently, there has been remarkable efforts in blending in-situ samples and remotely sensed data for implicit analysis of water quality indicators (WQIs) such as turbidity, chlorophyll-a (Chl-a), coloured dissolved organic matter (CDOM), clarity and temperature in reservoirs. This review quantitatively assessed the spectral, spatial and temporal variables of frequently used remote sensing sensors in water quality monitoring. The review also identifies the prevailing challenges and prospective direction in assessing water quality using remotely sensed data in African inland reservoirs. The results indicated that Chl-a and total suspended solids (TSS) are the most widely researched WQIs in Africa using multispectral sensors including Landsat series and Sentinel-2. The utilisation of remote sensing approaches in water quality studies has increased significantly in Africa. However, the geographical distribution of the studies is unbalanced. This could be attributed to the high costs incurred during the collection of in situ samples to parameterise and validate models, plus a general lack of research interests in the subject. In conclusion, substantial advancements in temporal, spectral and spatial resolutions of sensors utilised, WQI list and model inversion accuracy is needed.