Understanding the complexity of climate dynamics is of paramount importance, because climate variability and change significantly affect water cycles and ecosystems. However, recurrent hydrological droughts that have been observed every 10 years on the two primary tributaries of the Congo River (the Ubangui and Kasaï Rivers) since the advent of the 1969 drought lack a plausible explanation for variability or climate change. This study proposes a plausible explanation for recurring hydrological droughts. Given the low rate of human activity and vegetation cover evolution in the Congo Watershed, we propose that climate dynamics play a crucial role in hydrological drought dynamics. By applying the Bayesian approach to a gridded precipitation database, we obtained posterior probability maps for each annual time step during our observational period (1940–2020). This provided a spatiotemporal representation of the areas affected by climatic disturbances, unlike previous studies that were limited to a spatial representation of the temporal location of the disturbances. Our qualitative analysis of the maximum intensity of the climate disturbance signal (CPS) revealed an average cycle of 10 years and eight months of signal migration. However, we observed that every 10 years since the advent of the drought during 1969, the hydrological drought occurrence dates coincided with CPS migration dates. This highlights the influence of this cycle on the hydrological drought dynamics. Nevertheless, because of the monthly scale involved in the propagation time from meteorological to hydrological drought, the error in this cycle was considered to be the propagation time of disturbances. Therefore, we recommend that future research should focus on estimating this time to test this hypothesis. This study underscores the significance of the cyclic dynamics of lengthy transient processes in understanding hydrological drought dynamics.
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