Spatial and sectoral water demand assessment for the African continent
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Updated: Oct 30, 2026

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Davy Vanham1, Dahami Gunathilake2, Bhawani Gunasekara2
1International Water Management Institute (IWMI), Colombo, Sri Lanka. davy.vanham@yahoo.de.
Abstract:
Water demand is the volume of water required by a sector to satisfy its needs1,2. Across Africa, these demands are frequently unmet3, yet their spatial and sectoral distribution remains incompletely characterized, limiting informed water-management decisions4. Here, we provide an Africa-wide estimate of water demand for 2020 across six sectors and multiple subsectors at high spatial resolution. Because the analysis integrates heterogeneous datasets and modelling assumptions, the resulting values should be interpreted as harmonized estimates rather than direct observations of realized water use. We estimate total annual water demand at 347 km3, comprising 60 km3 (17%) for municipalities (57-64 km3, with ±20% key parameters variations), 225 km3 (65%) for irrigation (214-233 km3, 95% confidence interval, with ±20% variations in irrigation efficiency), 11 km3 (3%) for livestock, 15 km3 (4%) for manufacturing, 33 km3 (10%) for electricity including hydropower and 3 km3 (1%) for mining (3-4 km3, with annual production variations). Estimated demand increased by 26% between 2010 and 2020. The dominant water-demand sector varies across regions and river basins, broadly reflecting established geographical and socioeconomic patterns. In parts of northern and southern Africa, estimated demand exceeds water availability, although results depend on assumptions regarding environmental-flow protection5. Elsewhere, water availability exceeds aggregate demand despite limited access to piped drinking water, indicating that physical availability alone does not determine water security. Our analysis therefore provides a spatially and sectorally resolved baseline for identifying water-demand pressures and access constraints rather than establishing a new causal mechanism of water insecurity. Local estimates should be interpreted cautiously given uncertainties in the underlying datasets.
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