<?xml version="1.0"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Improved modeling of Congo's hydrology for floods and droughts analysis and ENSO teleconnections</dc:title>
  <dc:creator>Wongchuig, S.</dc:creator>
  <dc:creator>Kitambo, B.</dc:creator>
  <dc:creator>/Papa, Fabrice</dc:creator>
  <dc:creator>Paris, A.</dc:creator>
  <dc:creator>Fleischmann, A.S.</dc:creator>
  <dc:creator>Gal, L.</dc:creator>
  <dc:creator>/Boucharel, Julien</dc:creator>
  <dc:creator>Paiva, R.</dc:creator>
  <dc:creator>/Juca Oliveira, Romulo Augusto</dc:creator>
  <dc:creator>Tshimanga, R.M.</dc:creator>
  <dc:creator>Calmant, St&#xE9;phane</dc:creator>
  <dc:description>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 Ni&#xF1;o-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 Ni&#xF1;o 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 Ni&#xF1;o and La Ni&#xF1;a 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.</dc:description>
  <dc:date>2023</dc:date>
  <dc:type>text</dc:type>
  <dc:identifier>https://www.documentation.ird.fr/hor/fdi:010089436</dc:identifier>
  <dc:identifier>fdi:010089436</dc:identifier>
  <dc:identifier>Wongchuig S., Kitambo B., Papa Fabrice, Paris A., Fleischmann A.S., Gal L., Boucharel Julien, Paiva R., Juca Oliveira Romulo Augusto, Tshimanga R.M., Calmant St&#xE9;phane. Improved modeling of Congo's hydrology for floods and droughts analysis and ENSO teleconnections. 2023, 50, 101563 [21 ]</dc:identifier>
  <dc:language>EN</dc:language>
  <dc:coverage>CENTRAFRIQUE</dc:coverage>
  <dc:coverage>CAMEROUN</dc:coverage>
  <dc:coverage>CONGO</dc:coverage>
  <dc:coverage>ANGOLA</dc:coverage>
  <dc:coverage>ZAMBIE</dc:coverage>
  <dc:coverage>TANZANIE</dc:coverage>
  <dc:coverage>RWANDA</dc:coverage>
  <dc:coverage>BURUNDI</dc:coverage>
</oai_dc:dc>
