Hydro-climatic Variability, Change, and Extremes Across South America and Sub-Saharan Africa: Insights from Multi-Catchment, Multi-Dataset Analyses

South America and Sub-Saharan Africa host some of the world’s most dynamic and societally critical terrestrial water cycles, yet their hydro-climatic responses to ongoing climate warming remain incompletely understood. Here, we assess spatial patterns, temporal trends, and hydrological extremes of precipitation, runoff, evapotranspiration, and water storage change across 222 hydrological catchments (95 in South America and 127 in Sub-Saharan Africa) over the period 1980–2010, based on and comparing four widely used global datasets.

Across both regions, the datasets robustly indicate widespread warming over the study period. For the mean water fluxes of precipitation, runoff, and evapotranspiration, most datasets show weak and often statistically insignificant trends. Among the datasets, ERA5 implications emerge as systematically anomalous, yielding strongly divergent results of persistent water-storage depletion driven by physically unrealistic evapotranspiration behavior.

Analyses of hydrological drought- and flood-related water-flux extremes reveal both shared and contrasting regional signals. In South America, wet-season high-flux extremes increase in magnitude in the Amazon Basin, indicating heightened flood risk, while the magnitudes of dry-season low-flux extremes decrease across much of the continent, indicating increasing drought risk, particularly in the La Plata Basin. In Sub-Saharan Africa, the highest 5% of monthly precipitation and runoff extremes intensify in the wettest season, whereas severe drought hazards, characterized by zero precipitation and runoff, persist in the driest season. Regional variability is pronounced, with catchments in Namibia showing wetting trends, yet still experiencing severe drought extremes.

Together, these results underscore the multi-faceted and region-specific nature of terrestrial hydro-climatic change in the Global South. They highlight the importance of comparative multi-dataset analyses combined with integrated water-balance diagnostics across many catchments to improve process understanding, distinguish physically plausible long-term change signals and extreme short-term variations, and more robustly assess changing flood and drought risks in a warming climate.