Groundwater forms the basis of water supplies across much of Africa and its development is rising as demand for secure water increases. Recharge rates are a key component for assessing groundwater development potential, but have not been mapped across Africa, other than from global models. Here we quantify long-term average (LTA) distributed groundwater recharge rates across Africa for the period 1970–2019 from 134 ground-based estimates and upscaled statistically. Natural diffuse and local focussed recharge, where this mechanism is widespread, are included but discrete leakage from large rivers, lakes or from irrigation are excluded. We find that measurable LTA recharge is found in most environments with average decadal recharge depths in arid and semi-arid areas of 60 mm (30–140 mm) and 200 mm (90–430 mm) respectively. A linear mixed model shows that at the scale of the African continent only LTA rainfall is related to LTA recharge—the inclusion of other climate and terrestrial factors do not improve the model. Kriging methods indicate spatial dependency to 900 km suggesting that factors other than LTA rainfall are important at local scales. We estimate that average decadal recharge in Africa is 15 000 km³ (4900–45 000 km³), approximately 2% of estimated groundwater storage across the continent, but is characterised by stark variability between high-storage/low-recharge sedimentary aquifers in North Africa, and low-storage/high-recharge weathered crystalline-rock aquifers across much of tropical Africa. African water security is greatly enhanced by this distribution, as many countries with low recharge possess substantial groundwater storage, whereas countries with low storage experience high, regular recharge. The dataset provides a first, ground-based approximation of the renewability of groundwater storage in Africa and can be used to refine and validate global and continental hydrological models while also providing a baseline against future change.

Groundwater recharge is a key hydrogeological variable that informs the renewability of groundwater resources. Long-term average (LTA) groundwater recharge provides a measure of replenishment under the prevailing climatic and land-use conditions and is therefore of considerable interest in assessing the sustainability of groundwater withdrawals globally. This study builds on the modelling results by MacDonald et al. (2021), who produced the first LTA groundwater recharge map across Africa using a linear mixed model (LMM) rooted in 134 ground-based studies. Here, continent-wide predictions of groundwater recharge were generated using random forest (RF) regression employing five variables (precipitation, potential evapotranspiration, soil moisture, normalised difference vegetation index (NDVI) and aridity index) at a higher spatial resolution (0.1° resolution) to explore whether an improved model might be achieved through machine learning. Through the development of a series of RF models, we confirm that a RF model is able to generate maps of higher spatial variability than a LMM; the performance of final RF models in terms of the goodness of fit (R²=0.83; 0.88 with residual kriging) is comparable to the LMM (R²=0.86). The higher spatial scale of the predictor data (0.1°) in RF models better preserves small-scale variability from predictor data than the values provided via interpolated LMMs; these may prove useful in testing global- to local-scale models. The RF model remains, nevertheless, constrained by its representation of focused recharge and by the limited range of recharge studies in humid, equatorial Africa, especially in the areas of high precipitation. This confers substantial uncertainty in model estimates.

Radon gas has long been identified as a human carcinogen. The purpose of this study was to understand the occurrence of radon gas in the West Rand region, located west of the city of Johannesburg, South Africa, and to investigate its potential health effects. In this study, the sampling of rocks, tailings, and construction materials was carried out for geochemical analyses. For characterisation of radon, 60 radon monitors (RGMs) were installed in indoor and outdoor environments. The results showed that mine tailings contain high uranium levels, with a maximum of 149.76 ppm and a mean value of 48.87 ppm. The radon levels in the area ranged between 32 Bq/m³ and 1069 Bq/m³ and thus, exceed the typical outdoor radon levels of about 10 Bq/m³. Significantly high values were obtained from gold tailings dams. In indoor environments, radon concentration ranged up to a maximum of 174 Bq/m³, which is above the recommended value of 100 Bq/m³. The effective doses calculated from the obtained radon levels showed a maximum of 16 mSv/y, which is above the recommended value of 1 mSv/y proposed for public exposure. The estimated doses have an enormous potential to pose high lung cancer risks to the populations residing nearby tailings.