The Congo basin is one of the most hydrologically active and pristine locations with limited understanding of how precipitation changes impacts on stream flow dynamics and variations in catchment stores. Given that the basin is among the three prominent convective regions that dominates global rainfall climatology during transition seasons, historical space-time variability of rainfall (1901-2014) over the basin in relation to river discharge is analysed in order to understand significant hydro-climatic shift. Based on advance multivariate analyses, the total variability of the leading modes (annual variations) of rainfall increased during the 1931-1960 (56.3%) and 1961-1990 (57.3%) periods compared to the 1901-1930 baseline period (51.3%). It varied less between 1991 and 2014 (55.4%) as opposed to the two climatological periods between 1931 and 1990. Furthermore, the total variability in the multi-annual rainfall signals declined from 16.5% at the start of the century (1901-1930) to 13.6% in the 1991-2014 period while the total variability accounted for by other short-term meteorological signals oscillated between 4.0% and 2.7% during the entire period. Between 1995 and 2010 there seems to be a change in the hydrological regimes of the Congo river as the cumulative departures of rainfall and discharge were in opposite directions. The considerable association of discharge with rainfall in catchments characterised by strong annual and seasonal amplitudes in rainfall implies that the wetland hydrology of the basin is largely nourished by rainfall, in addition to possible exchange of fluxes within the Congo floodplain wetlands. Notably, a significant proportion of changes in the dominant rainfall patterns is still not explained by those of river discharge. This information signals the threshold of complex hydrological processes in the region, and perhaps suggest the influence of anthropogenic contributions (e.g., deforestation) and strong multi-scale ocean-atmosphere phenomena as key secondary drivers of hydrologic variability.