Horizon 1 1 17 ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES Journal of Hydrology : Regional Studies 101563 [21 ] CENTRAFRIQUE CAMEROUN CONGO ANGOLA ZAMBIE TANZANIE RWANDA BURUNDI CONGO BASSIN 2023 fdi:010089436 ENG Journal of Hydrology : Regional Studies 2214-5818 ISI:001149943800001 10.1016/j.ejrh.2023.101563 https://www.documentation.ird.fr/hor/fdi:010089436 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/2024-02/010089436.pdf 50 Horizon (IRD) 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. 126TELAPP04 UR065 Brésil / République démocratique du Congo