Africa accounts for nearly 30% of the discovered world’s mineral reserves, with half of the world’s platinum group metals deposits, 36% of gold, and 20% of cobalt being in Southern Africa (SA). The intensification of heavy-metal production in the SA region has exacerbated negative human and environmental health impacts. In recent years, mining waste generated from industrial and artisanal mining has significantly affected the ecological integrity of SA aquatic ecosystems due to the accelerated introduction and deposition of heavy metals. However, the extent to which heavy-metal pollution associated with mining has impacted the aquatic ecosystems has not been adequately documented, particularly during bioassessments. This review explores the current aquatic ecological impacts on the heavily mined river basins of SA. It also discusses the approaches to assessing the ecological risks, inherent challenges, and potential for developing an integrated ecological risk assessment protocol for aquatic systems in the region. Progress has been made in developing rapid bioassessment schemes (RBS) for SA aquatic ecosystems. Nevertheless, method integration, which also involves heavy-metal pollution monitoring and molecular technology, is necessary to overcome the current challenges of the standardisation of RBS protocols. Citizenry science will also encourage community and stakeholder involvement in sustainable environmental management in SA.
The Upper Chongwe River Catchment has recently been overexploited for water resources with increased complaints by various water users about the deteriorating quality of surface water within the sub-catchment. This study was motivated by the need to investigate and understand the response of surface water quality to land use land cover (LULC) change due to urbanization. Water samples, collected at 9 sampling sites from 2006 to 2017, were analyzed for water quality using the weighted arithmetic water quality index and trend using the Mann-Kendall statistics. LULC change is detected and analyzed in ERDAS Imagine 2014 and ArcGIS 10.4 using 2006 Landsat 5 TM and 2017 Landsat 8 OLI imageries. The relationship between LULC change and water quality was performed with multiple regression analysis and Pearson correlation. The results reveal that Built-up area, Grassland and surface water increased by 5.48%, 13.34% and 0.03% respectively while Agricultural land and Forest Land decreased by −13.41% and −5.42% respectively. The water quality index ranged from 43.04 to 110.40 in 2006 and from 170 to 430 in 2017 indicating a deterioration in the quality of surface water from good to unsuitable for drinking at all the sampled sites.
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