Machine Learning-Based Assessment of Regional Groundwater Recharge Variability and its Implications for Sustainable Water Supply in Renewable Energy Projects Across Africa

Abstract

Water is a precious resource in Africa. The sustainable management of this resource is important for our everyday lives, as well as for renewable energy applications such as green hydrogen production. Especially in desert regions, this water is mainly groundwater. This study assesses how land surface characteristics affect groundwater recharge across Africa, in addition to the dominant impact of precipitation. A combination of correlation analysis, principal component analysis (PCA), and machine learning models (Random Forest and Gradient Boosting) interpreted with Shapley additive exPlanations (SHAP) was applied across eight African regions. These methods were used to analyse the Community Land Model (CLM) simulated datasets for different African land surface characteristics. The findings of the analysis indicate that precipitation is the main factor affecting variations in recharge. However, its effectiveness is significantly impacted by factors such as soil depth, slope, vegetation, organic matter, and soil texture. Three dominant recharge regimes were identified. These are runoff-limited regimes, evapotranspiration-limited regimes, and precipitation-constrained regimes (e.g., Sahara and Mediterranean). The runoff-limited regimes are characterized by shallow soils and steep terrain that restrict infiltration despite high rainfall. The evapotranspiration-limited regimes are characterized by vegetation and organic-rich soils that drive moisture losses. The precipitation-limited regimes are characterized by low rainfall that dominates recharge regardless of land characteristics. Random Forest models outperformed Gradient Boosting in predictive accuracy (R² up to 0.98), and SHAP analysis provided quantifications of variable importance. These findings highlight the critical role of land-surface heterogeneity in shaping groundwater availability and its implications for water-energy planning. In renewable energy strategies that involve groundwater, policies should consider recharge variability. They should also manage soil and slopes in runoff-limited regions. And they should assess the balance between the water needs for energy production and competing demands such as drinking water and environmental needs. The study emphasises the importance of adapting region-specific approaches to groundwater management. These are needed to support Africa’s renewable energy transition.