Articles | Volume 15, issue 7
https://doi.org/10.5194/essd-15-2957-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-2957-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A long-term monthly surface water storage dataset for the Congo basin from 1992 to 2015
Benjamin M. Kitambo
CORRESPONDING AUTHOR
Laboratoire d'Etudes en Géophysique et Océanographie Spatiales
(LEGOS), Université de Toulouse, CNES/CNRS/IRD/UT3, Toulouse, France
Congo Basin Water Resources Research Center (CRREBaC) & the
Regional School of Water, University of Kinshasa (UNIKIN), Kinshasa,
Democratic Republic of the Congo
Faculty of Sciences, Department of Geology, University of Lubumbashi
(UNILU), Route Kasapa, Lubumbashi, Democratic Republic of the Congo
Fabrice Papa
Laboratoire d'Etudes en Géophysique et Océanographie Spatiales
(LEGOS), Université de Toulouse, CNES/CNRS/IRD/UT3, Toulouse, France
Institute of Geosciences, Campus Universitario Darcy Ribeiro,
Universidade de Brasília (UnB), 70910-900 Brasilia (DF), Brazil
Adrien Paris
Hydro Matters, 1 Chemin de la Pousaraque, 31460 Le Faget, France
Laboratoire d'Etudes en Géophysique et Océanographie Spatiales
(LEGOS), Université de Toulouse, CNES/CNRS/IRD/UT3, Toulouse, France
Raphael M. Tshimanga
Congo Basin Water Resources Research Center (CRREBaC) & the
Regional School of Water, University of Kinshasa (UNIKIN), Kinshasa,
Democratic Republic of the Congo
Frederic Frappart
INRAE, Bordeaux Sciences Agro, UMR1391 ISPA, 71 Avenue Edouard
Bourlaux, 33882 CEDEX Villenave d'Ornon, France
Stephane Calmant
Laboratoire d'Etudes en Géophysique et Océanographie Spatiales
(LEGOS), Université de Toulouse, CNES/CNRS/IRD/UT3, Toulouse, France
Omid Elmi
Institute of Geodesy, University of Stuttgart, Stuttgart, Germany
Ayan Santos Fleischmann
Instituto de Desenvolvimento Sustentável Mamirauá, Tefé (AM), Brazil
Melanie Becker
LIENSs/CNRS, UMR 7266, ULR/CNRS, 2 Rue Olympe de Gouges, La Rochelle,
France
Mohammad J. Tourian
Institute of Geodesy, University of Stuttgart, Stuttgart, Germany
Rômulo A. Jucá Oliveira
Laboratoire d'Etudes en Géophysique et Océanographie Spatiales
(LEGOS), Université de Toulouse, CNES/CNRS/IRD/UT3, Toulouse, France
Sly Wongchuig
Laboratoire d'Etudes en Géophysique et Océanographie Spatiales
(LEGOS), Université de Toulouse, CNES/CNRS/IRD/UT3, Toulouse, France
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Cited
5 citations as recorded by crossref.
- Decadal Variations in Equatorial Ellipticity and Principal Axis of the Earth from Satellite Laser Ranging/GRACE M. Cheng 10.1007/s10712-024-09852-w
- First results of the surface water ocean topography (SWOT) observations to rivers elevation profiles in the Cuvette Centrale of the Congo Basin C. Normandin et al. 10.3389/frsen.2024.1466695
- Quantification of surface water extent and volume in the Inner Niger Delta (IND) over 2000–2022 using multispectral imagery and radar altimetry C. Normandin et al. 10.1080/10106049.2024.2311203
- A long-term monthly surface water storage dataset for the Congo basin from 1992 to 2015 B. Kitambo et al. 10.5194/essd-15-2957-2023
- Mapping Water Levels across a Region of the Cuvette Centrale Peatland Complex S. Georgiou et al. 10.3390/rs15123099
3 citations as recorded by crossref.
- Decadal Variations in Equatorial Ellipticity and Principal Axis of the Earth from Satellite Laser Ranging/GRACE M. Cheng 10.1007/s10712-024-09852-w
- First results of the surface water ocean topography (SWOT) observations to rivers elevation profiles in the Cuvette Centrale of the Congo Basin C. Normandin et al. 10.3389/frsen.2024.1466695
- Quantification of surface water extent and volume in the Inner Niger Delta (IND) over 2000–2022 using multispectral imagery and radar altimetry C. Normandin et al. 10.1080/10106049.2024.2311203
Latest update: 06 Dec 2024
Short summary
The surface water storage (SWS) in the Congo River basin (CB) remains unknown. In this study, the multi-satellite and hypsometric curve approaches are used to estimate SWS in the CB over 1992–2015. The results provide monthly SWS characterized by strong variability with an annual mean amplitude of ~101 ± 23 km3. The evaluation of SWS against independent datasets performed well. This SWS dataset contributes to the better understanding of the Congo basin’s surface hydrology using remote sensing.
The surface water storage (SWS) in the Congo River basin (CB) remains unknown. In this study,...
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