The Zambezi River basin is the fourth largest basin in Africa and the largest in southern Africa, comprising 5% of the total area of the continent. The basin is extremely vulnerable to climate change effects due to its highly variable climate. The purpose of this study was to evaluate the impact of climate change on streamflow in one of the sub-basins, the Kabombo basin. The multi- global climate model projections were used as input to the Soil Water Assessment Tool (SWAT) hydrological model for simulation of streamflow under RCP 4.5 and RCP 8.5 climate scenarios. The model predicted an annual streamflow increase of 85% and 6% for high uncertainty and strong consensus, respectively, under RCP 8.5. The model predicted a slightly reduced annual streamflow of less than 3% under RCP 4.5. The majority of simulations indicated that intra-annual and inter-annual streamflow variability will increase in the future for RCP 8.5 while it will reduce for the RCP 4.5 scenario. The predicted high and moderate rise in streamflow for RCP 8.5 suggests the need for adaptation plans and mitigation strategies. In contrast, the streamflow predicted for RCP 4.5 indicates that there may be a need to review the current management strategies of the water resources in the basin.

Groundwater resources are largely used in rural communities of river basins due to their acceptable water quality and reliability for domestic purposes where little or no treatment is required. However, groundwater resources have been affected by changes in land use, mining activities, agricultural practices, industrial effluent, and urbanisation among anthropogenic influences while climate change impacts and volcanic eruptions have affected its involvement among the natural phenomena. The purpose of the study was to assess groundwater potential in the basin with the use of Analytical Hierarchy Process (AHP), remote sensing, GIS techniques, and groundwater occurrence and movement influencing factors. These factors were used to produce seven thematic maps, which were then assigned weights and scale using an AHP tool, based on their degree of influence on groundwater occurrence and movement. A weighted groundwater potential map was produced with four zones denoted as 0.4% (317 km²) for very good potential; 27% (19,170 km²) for good potential; 61% (43,961 km²) for moderate potential and 12% (8639 km²) for poor potential. Validation, using existing boreholes, showed that 89% were overlain on moderate to very good potential zones and henceforth considered to be a novel approach which is useful for groundwater resources assessment and integrated water management in the basin.

In developing countries with data scarcity challenges, an integrated approach is required to enhance the estimation of streamflow variability for the design of water supply systems, hydropower generation, environmental flows, water allocation and pollution studies. The Flow Duration Curve (FDC) was adopted as a tool that is influenced by topography, land use land cover, discharge and climate change. The data from Global Climate Model (GCM) projections, based on Representative Concentration Pathways (RCP) 4.5 and RCP 8.5 climate scenarios, were used as input data for the SWAT model for the simulation of streamflow. The FDCs were then derived from the simulated streamflow. The FDC for RCP 4.5 showed insignificant differences, whilst for RCP 8.5 it showed an increase of 5–10% in FDC from the baseline period, which is likely to increase the hydropower generation potential with some considerable streamflow variability. The integrated approach of utilizing FDC, GIS and SWAT for the estimation of flow variability and hydropower generation potential could be useful in data scarce regions.

Generating a high resolution climate scenario using regional climate models is highly useful to study climate change. Southern African like other global regions is prone to climate extremes and needs better investigation and understanding. This article, therefore, demonstrates the usefulness of downscaling large scale climate scenarios over this region for climate change impact studies. Four experiments were conducted to downscale the GCM HadGEM2-ES model under three climate scenarios, namely the baseline, and Representative Concentration Pathways (RCP) 4.5 and 8.5. The predictions under both RCP4.5 and RCP8.5 climate scenarios indicate that seasonal rainfall will increase in magnitude by 1 to 65% and 1 to 37%, respectively. The coverage area with increased rainfall varies from 33% to 77% and 49% to 58% for RCP4.5 and RCP8.5, respectively. Temperatures are also predicted to increase under RCP4.5 and RCP8.5. In general, the results are indicative of the potential future climate change impact in the region and may be used for devising adaptation and mitigation strategies.