Mapping hotspots for future water pollution in Africa using SDG indicator 6.3.2

Efficient monitoring and reporting of Sustainable Development Goal (SDG) indicator 6.3.2 is essential for assessing progress toward good ambient water quality. However, data limitations, particularly in developing regions such as Africa, hinder accurate assessment of water quality in rivers. This study addresses this challenge by employing modelling to map progress of the SDG indicator 6.3.2 in Africa for the reporting years 2020, 2030, 2040 and 2050 under three socio-economic scenarios; SSP1-RCP2.6, SSP3-RCP7.0 and SSP5-RCP8.5. This indicator will provide an overview of the state and trends of future water quality in different African regions and identify hotspots of water pollution. We utilize model simulations from two global water quality models; DynQual and SWAT+ to generate water quality indexes (WQIs) using four core parameter groups at level I reporting namely salinity (Total Dissolved solids), nitrogen (Total Nitrogen), phosphorus (Total Phosphorus) and oxygen (Biological Oxygen Demand). Model simulations are compared to target values to derive country and river basin level WQIs. Additionally, we assess the impact of level II parameters on the overall indicator by adding fecal coliform (FC) to the calculation. Lastly, we compute the percentage of population exposed to the deteriorating water quality across these periods and scenarios. This study's robust methodology for SDG mapping significantly enhances our understanding of future water quality dynamics. The findings will inform targeted interventions, policy formulation, and sustainable water resource management, contributing to the achievement of SDG 6 and broader environmental sustainability objectives across the continent.