Auteur:  Sly Wongchuig

Co-Auteur:  Benjamin M.Kitambo, Fabrice Papa, Adrien Paris, AyanSantos Fleischmann, Laetitia Gal,

Julien Boucharel, Rodrigo Paiva, RômuloJucá Oliveira, Tshimanga, R.M., Stéphane Calmant 

Review :  Journal of Hydrology: Regional Studies.

Lien: https://www.sciencedirect.com/science/article/pii/S2214581823002501 

Abstract

Study region

The Congo River basin (CRB), the world's second-largest river system, is subject to extreme hydrological events that strongly impact its ecosystems and population.

Study focus

Here we present an improved 40-year (1981–2020) hydrological reanalysis of daily CRB discharge and analyze the spatiotemporal dynamics of recent major CRB floods and droughts, and their teleconnection with El Niño-Southern Oscillation (ENSO), the dominant driver of tropical precipitation. We employ a large-scale hydrologic-hydrodynamic model (MGB) with lake storage dynamics representation and a data assimilation (DA) technique using in-situ and remote sensing observations.

New Hydrological Insights

The MGB model demonstrates satisfactory performance, with Kling-Gupta efficiency metric of 0.84 and 0.71 for calibration and validation, respectively. Incorporating lake representation substantially enhances simulations, increasing the Pearson correlation coefficient from 0.3 to 0.63. Additionally, DA yields a ∼13% reduction in discharge errors via cross-validation. We find that the 1997–1998 flood impacting the south and central CRB is statistically linked to a major El Niño event during that period. However, no such association is found for the 2019–2020 flood. Severe droughts in 1983–1984 and 2011–2012, affecting northern and southern CRB respectively, exhibit strong correlation with preceding El Niño and La Niña events, with a ∼10–12 months lag. This study advances understanding of the intricate interplay between spatiotemporal hydrological variability in CRB and large-scale climate phenomena like ENSO.

Keywords : Hydrological reanalysis, Hydrological-hydrodynamic modeling, Lakes storage,Dynamics,Data assimilation,Congo River basin,Hydrological extreme events