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.
Data description paper
| 
12 Jul 2023
Data description paper |
| 12 Jul 2023
| 12 Jul 2023
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
Related authors
Peyman Saemian, Omid Elmi, Molly Stroud, Ryan Riggs, Benjamin M. Kitambo, Fabrice Papa, George H. Allen, and Mohammad J. Tourian
Earth Syst. Sci. Data, 17, 2063–2085, https://doi.org/10.5194/essd-17-2063-2025, https://doi.org/10.5194/essd-17-2063-2025, 2025
Short summary
Short summary
Our study addresses the need for better river discharge data, crucial for water management, by expanding global gauge networks with satellite data. We used satellite altimetry to estimate river discharge for over 8700 stations worldwide, filling gaps in existing records. Our data set, SAEM, supports a better understanding of water systems, helping to manage water resources more effectively, especially in regions with limited monitoring infrastructure.
Benjamin Kitambo, Fabrice Papa, Adrien Paris, Raphael M. Tshimanga, Stephane Calmant, Ayan Santos Fleischmann, Frederic Frappart, Melanie Becker, Mohammad J. Tourian, Catherine Prigent, and Johary Andriambeloson
Hydrol. Earth Syst. Sci., 26, 1857–1882, https://doi.org/10.5194/hess-26-1857-2022, https://doi.org/10.5194/hess-26-1857-2022, 2022
Short summary
Short summary
This study presents a better characterization of surface hydrology variability in the Congo River basin, the second largest river system in the world. We jointly use a large record of in situ and satellite-derived observations to monitor the spatial distribution and different timings of the Congo River basin's annual flood dynamic, including its peculiar bimodal pattern.
Hannes Konrad, Rémy Roca, Anja Niedorf, Stephan Finkensieper, Marc Schröder, Sophie Cloché, Giulia Panegrossi, Paolo Sanò, Christopher Kidd, Rômulo Augusto Jucá Oliveira, Karsten Fennig, Thomas Sikorski, Madeleine Lemoine, and Rainer Hollmann
Earth Syst. Sci. Data, 17, 4097–4124, https://doi.org/10.5194/essd-17-4097-2025, https://doi.org/10.5194/essd-17-4097-2025, 2025
Short summary
Short summary
GIRAFE v1 is a global satellite-based precipitation dataset covering 2002 to 2022. It combines high-accuracy microwave and high-resolution infrared observations for retrieving daily precipitation, a respective sampling uncertainty for a more robust analysis, and monthly means. It is intended and suitable for climate monitoring and research and allows studies on water management, agriculture, and disaster risk reduction. A continuous extension from 2023 onwards will be implemented in 2025.
Anne Springer, Gabriëlle De Lannoy, Matthew Rodell, Yorck Ewerdwalbesloh, Helena Gerdener, Mehdi Khaki, Bailing Li, Fupeng Li, Maike Schumacher, Natthachet Tangdamrongsub, Mohammad J. Tourian, Wanshu Nie, and Jürgen Kusche
EGUsphere, https://doi.org/10.5194/egusphere-2025-2058, https://doi.org/10.5194/egusphere-2025-2058, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
The GRACE and GRACE Follow-On satellites monitor changes in Earth's water storage by observing gravity variations. By integrating these observations into hydrological models through data assimilation, estimates of groundwater, soil moisture, and hydrological trends are improved, helping to monitor droughts, floods, and human water use. This review highlights recent advances in GRACE data assimilation, identifies key challenges, and discusses future directions with upcoming satellite missions.
Peyman Saemian, Omid Elmi, Molly Stroud, Ryan Riggs, Benjamin M. Kitambo, Fabrice Papa, George H. Allen, and Mohammad J. Tourian
Earth Syst. Sci. Data, 17, 2063–2085, https://doi.org/10.5194/essd-17-2063-2025, https://doi.org/10.5194/essd-17-2063-2025, 2025
Short summary
Short summary
Our study addresses the need for better river discharge data, crucial for water management, by expanding global gauge networks with satellite data. We used satellite altimetry to estimate river discharge for over 8700 stations worldwide, filling gaps in existing records. Our data set, SAEM, supports a better understanding of water systems, helping to manage water resources more effectively, especially in regions with limited monitoring infrastructure.
Howlader Mohammad Mehedi Hasan, Petra Döll, Seyed-Mohammad Hosseini-Moghari, Fabrice Papa, and Andreas Güntner
Hydrol. Earth Syst. Sci., 29, 567–596, https://doi.org/10.5194/hess-29-567-2025, https://doi.org/10.5194/hess-29-567-2025, 2025
Short summary
Short summary
We calibrate a global hydrological model using multiple observations to analyse the benefits and trade-offs of multi-variable calibration. We found such an approach to be very important for understanding the real-world system. However, some observations are very essential to the system, in particular, streamflow. We also showed uncertainties in the calibration results, which are often useful for making informed decisions. We emphasize considering observation uncertainty in model calibration.
Thomas Legay, Yoann Aubert, Julien Verdonck, Jérémy Guilhen, Adrien Paris, Jean-Michel Martinez, Sabine Sauvage, Pankyes Datok, Vanessa Dos Santos, José Miquel Sanchez-Perez, Stéphane Bruxelles, Emeric Lavergne, and Franck Mercier
Proc. IAHS, 385, 477–484, https://doi.org/10.5194/piahs-385-477-2024, https://doi.org/10.5194/piahs-385-477-2024, 2024
Short summary
Short summary
Water resources management traditionally relies on the use of in situ data. Spatial altimetry data is a new source of data for water resources monitoring. Through two projects, various partners (BRLi, IRD, CNES, CLS, CNRS, CENEAU) developed a method based on the combination of hydrological models, in-situ and satellite data to enhance the use of spatial altimetry data for water resources management. This article proposes to evaluate the implemented method.
Rodric Mérimé Nonki, Ernest Amoussou, Raphael Muamba Tshimanga, Djan'na Koubodana Houteta, Domiho Japhet Kodja, Franck Eitel Kemgang Ghomsi, and André Lenouo
Proc. IAHS, 385, 319–326, https://doi.org/10.5194/piahs-385-319-2024, https://doi.org/10.5194/piahs-385-319-2024, 2024
Short summary
Short summary
This research aims to evaluate the feasibility of using multiple rainfall-runoff hydrologic models Génie Rural à 4, 5, 6 paramètres Journalier (GR4J, GR5J, and GR6J) in the Upper Benue River (UBR) in Northern Cameroon. By using the Michel's calibration algorithm, we found that the composite criterion is the most sustainable objective function for model optimization. An honest evaluation empirically proves that the GR6J model performs better than the other two models follow by GR5J.
Menaka Revel, Xudong Zhou, Prakat Modi, Jean-François Cretaux, Stephane Calmant, and Dai Yamazaki
Earth Syst. Sci. Data, 16, 75–88, https://doi.org/10.5194/essd-16-75-2024, https://doi.org/10.5194/essd-16-75-2024, 2024
Short summary
Short summary
As satellite technology advances, there is an incredible amount of remotely sensed data for observing terrestrial water. Satellite altimetry observations of water heights can be utilized to calibrate and validate large-scale hydrodynamic models. However, because large-scale models are discontinuous, comparing satellite altimetry to predicted water surface elevation is difficult. We developed a satellite altimetry mapping procedure for high-resolution river network data.
Zhour Najoui, Nellya Amoussou, Serge Riazanoff, Guillaume Aurel, and Frédéric Frappart
Earth Syst. Sci. Data, 14, 4569–4588, https://doi.org/10.5194/essd-14-4569-2022, https://doi.org/10.5194/essd-14-4569-2022, 2022
Short summary
Short summary
Oil spills could have serious repercussions for both the marine environment and ecosystem. The Gulf of Guinea is a very active area with respect to maritime traffic as well as oil and gas exploitation (platforms). As a result, the region is subject to a large number of oil pollution events. This study aims to detect oil slicks in the Gulf of Guinea and analyse their spatial and temporal distribution using satellite data.
Mohammad J. Tourian, Omid Elmi, Yasin Shafaghi, Sajedeh Behnia, Peyman Saemian, Ron Schlesinger, and Nico Sneeuw
Earth Syst. Sci. Data, 14, 2463–2486, https://doi.org/10.5194/essd-14-2463-2022, https://doi.org/10.5194/essd-14-2463-2022, 2022
Short summary
Short summary
HydroSat as a global water cycle database provides estimates of and uncertainty in geometric quantities of the water cycle: (1) surface water extent of lakes and rivers, (2) water level time series of lakes and rivers, (3) terrestrial water storage anomaly, (4) water storage anomaly of lakes and reservoirs, and (5) river discharge estimates for large and small rivers.
P. Zeiger, F. Frappart, and J. Darrozes
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 93–100, https://doi.org/10.5194/isprs-annals-V-3-2022-93-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-93-2022, 2022
Benjamin Kitambo, Fabrice Papa, Adrien Paris, Raphael M. Tshimanga, Stephane Calmant, Ayan Santos Fleischmann, Frederic Frappart, Melanie Becker, Mohammad J. Tourian, Catherine Prigent, and Johary Andriambeloson
Hydrol. Earth Syst. Sci., 26, 1857–1882, https://doi.org/10.5194/hess-26-1857-2022, https://doi.org/10.5194/hess-26-1857-2022, 2022
Short summary
Short summary
This study presents a better characterization of surface hydrology variability in the Congo River basin, the second largest river system in the world. We jointly use a large record of in situ and satellite-derived observations to monitor the spatial distribution and different timings of the Congo River basin's annual flood dynamic, including its peculiar bimodal pattern.
Aurélia Bernard, Nathalie Long, Mélanie Becker, Jamal Khan, and Sylvie Fanchette
Nat. Hazards Earth Syst. Sci., 22, 729–751, https://doi.org/10.5194/nhess-22-729-2022, https://doi.org/10.5194/nhess-22-729-2022, 2022
Short summary
Short summary
This article reviews current scientific literature in order to define vulnerability in the context of coastal Bangladesh facing cyclonic flooding. A new metric, called the socio-spatial vulnerability index, is defined as a function of both the probability of the cyclonic flood hazard and the sensitivity of delta inhabitants. The main result shows that three very densely populated districts, located in the Ganges delta tidal floodplain, are highly vulnerable to cyclonic flooding.
Gil Mahé, Gamal Abdo, Ernest Amoussou, Telesphore Brou, Stephan Dietrich, Ahmed El Tayeb, Henny van Lanen, Mohamed Meddi, Anil Mishra, Didier Orange, Thi Phuong Quynh Le, Raphael Tshimanga, Patrick Valimba, Santiago Yepez, Andrew Ogilvie, and Oula Amrouni
Proc. IAHS, 384, 5–18, https://doi.org/10.5194/piahs-384-5-2021, https://doi.org/10.5194/piahs-384-5-2021, 2021
Short summary
Short summary
The FRIEND-Water program (FWP) is the oldest and the most transverse program within the UNESCO IHP. It allows large communities of hydrologists to collaborate across borders on common shared data and scientific topics, addressed through 8 large world regions. Research priorities evolve according to the projections given by the member States during the IHP councils. FWP further activities follow the IHP IX program with the support of the Montpellier UNESCO Category II Center ICIREWAD.
Sakaros Bogning, Frédéric Frappart, Gil Mahé, Adrien Paris, Raphael Onguene, Fabien Blarel, Fernando Niño, Jacques Etame, and Jean-Jacques Braun
Proc. IAHS, 384, 181–186, https://doi.org/10.5194/piahs-384-181-2021, https://doi.org/10.5194/piahs-384-181-2021, 2021
Short summary
Short summary
This paper investigates links between rainfall variability in the Ogooué River Basin (ORB) and El Niño Southern Oscillation (ENSO) in the Pacific Ocean. Recent hydroclimatology studies of the ORB and surrounding areas resulting in contrasting conclusions about links between rainfall variability and ENSO. Then, this work uses cross-wavelet and wavelet coherence analysis to highlight significant links between ENSO and rainfall in the ORB.
Yves Tramblay, Nathalie Rouché, Jean-Emmanuel Paturel, Gil Mahé, Jean-François Boyer, Ernest Amoussou, Ansoumana Bodian, Honoré Dacosta, Hamouda Dakhlaoui, Alain Dezetter, Denis Hughes, Lahoucine Hanich, Christophe Peugeot, Raphael Tshimanga, and Patrick Lachassagne
Earth Syst. Sci. Data, 13, 1547–1560, https://doi.org/10.5194/essd-13-1547-2021, https://doi.org/10.5194/essd-13-1547-2021, 2021
Short summary
Short summary
This dataset provides a set of hydrometric indices for about 1500 stations across Africa with daily discharge data. These indices represent mean flow characteristics and extremes (low flows and floods), allowing us to study the long-term evolution of hydrology in Africa and support the modeling efforts that aim at reducing the vulnerability of African countries to hydro-climatic variability.
Adam Hastie, Ronny Lauerwald, Philippe Ciais, Fabrice Papa, and Pierre Regnier
Earth Syst. Dynam., 12, 37–62, https://doi.org/10.5194/esd-12-37-2021, https://doi.org/10.5194/esd-12-37-2021, 2021
Short summary
Short summary
We used a model of the Congo Basin to investigate the transfer of carbon (C) from land (vegetation and soils) to inland waters. We estimate that leaching of C to inland waters, emissions of CO2 from the water surface, and the export of C to the coast have all increased over the last century, driven by increasing atmospheric CO2 levels and climate change. We predict that these trends may continue through the 21st century and call for long-term monitoring of these fluxes.
Vinícius B. P. Chagas, Pedro L. B. Chaffe, Nans Addor, Fernando M. Fan, Ayan S. Fleischmann, Rodrigo C. D. Paiva, and Vinícius A. Siqueira
Earth Syst. Sci. Data, 12, 2075–2096, https://doi.org/10.5194/essd-12-2075-2020, https://doi.org/10.5194/essd-12-2075-2020, 2020
Short summary
Short summary
We present a new dataset for large-sample hydrological studies in Brazil. The dataset encompasses daily observed streamflow from 3679 gauges, as well as meteorological forcing for 897 selected catchments. It also includes 65 attributes covering topographic, climatic, hydrologic, land cover, geologic, soil, and human intervention variables. CAMELS-BR is publicly available and will enable new insights into the hydrological behavior of catchments in Brazil.
Cited articles
Albert, J. S., Destouni, G., Duke-Sylvester, S. M., Magurran, A. E., Oberdorff,
T., Reis, R. E., Winemiller, K. O., and Ripple, W. J.: Scientists' warning to
humanity on the freshwater biodiversity crisis, Ambio, 50, 85–94,
https://doi.org/10.1007/s13280-020-01318-8, 2021
Alsdorf, D. E. and Lettenmaier, D. P.: Tracking fresh water from space, Science,
301, 1492–1494, https://doi.org/10.1126/science.1089802, 2003.
Alsdorf, D. E., Rodríguez, E., and Lettenmaier, D. P.: Measuring surface water
from space, Rev. Geophys., 45, RG2002, https://doi.org/10.1029/2006RG000197,
2007.
Beck, H. E., Vergopolan, N., Pan, M., Levizzani, V., van Dijk, A. I. J. M., Weedon, G. P., Brocca, L., Pappenberger, F., Huffman, G. J., and Wood, E. F.: Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling, Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, 2017.
Beck, H. E., Pan, M., Roy, T., Weedon, G. P., Pappenberger, F., van Dijk, A. I. J. M., Huffman, G. J., Adler, R. F., and Wood, E. F.: Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS, Hydrol. Earth Syst. Sci., 23, 207–224, https://doi.org/10.5194/hess-23-207-2019, 2019a.
Beck, H. E., Wood, E. F., Pan, M., Fisher, C. K., Miralles, D. G., van Dijk, A.
I. J. M., McVicar, T. R., and Adler, R. F.: MSWEP V2 Global 3-Hourly
0.1∘ Precipitation: Methodology and Quantitative Assessment, B.
Am. Meteorol. Soc., 100, 473–500,
https://doi.org/10.1175/BAMS-D-17-0138.1, 2019b.
Becker, M., Papa, F., Frappart, F., Alsdorf, D., Calmant, S., da Silva, J.
S., Prigent, C., and Seyler, F.: Satellite-based estimates of surface water
dynamics in the Congo River Basin, Int. J. Appl. Earth Obs., 66,
196–209, https://doi.org/10.1016/j.jag.2017.11.015, 2018.
Biancamaria, S., Lettenmaier, D. P., and Pavelsky, T. M.: The SWOT Mission and
Its Capabilities for Land Hydrology, Surv. Geophys., 37, 307–337,
https://doi.org/10.1007/s10712-015-9346-y, 2016.
Biddulph, G. E., Bocko, Y. E., Bola, P., Crezee, B., Dargie, G. C., Emba,
O., Georgiou, S., Girkin, N., Hawthorne, D., Jonay Jovani-Sancho, A., Joseph
Kanyama, T., Mampouya, W. E., Mbemba, M., Sciumbata, M., and Tyrrell, G.:
Current knowledge on the Cuvette Centrale peatland complex and future
research directions, Bois Forets des Trop., 350, 3–14,
https://doi.org/10.19182/bft2021.350.a36288, 2021.
Boberg, J.: Liquid assets: how demographic changes and water management policies affect freshwater resources, RAND corporation, ISBN 9780833040862, 152 pp., 2005.
Bogning, S., Frappart, F., Blarel, F., Niño, F., Mahé, G., Bricquet,
J. P., Seyler, F., Onguéné, R., Etamé, J., Paiz, M. C., and
Braun, J. J.: Monitoring water levels and discharges using radar altimetry
in an ungauged river basin: The case of the Ogooué, Remote Sens., 10,
350, https://doi.org/10.3390/rs10020350, 2018.
Bricquet, J.-P.: Les écoulements du Congo à Brazzaville et la
spatialisation des apports, in: Grands bassins fluviaux périatlantiques:
Congo, Niger, Amazone, Paris, ORSTOM, edited by: Boulègue, J. and
Olivry, J.-C., Colloques et Séminaires, Grands Bassins Fluviaux
Péri-Atlantiques: Congo, Niger, Amazone, Paris, France, 1993/11/22-24,
27–38, ISBN 2-7099-1245-7, 1995.
Bullock, A. and Acreman, M.: The role of wetlands in the hydrological cycle, Hydrol. Earth Syst. Sci., 7, 358–389, https://doi.org/10.5194/hess-7-358-2003, 2003.
Cazenave, A., Champollion, N., Benveniste, J., Chen, J. Foreword: International Space Science Institute (ISSI) Workshop on Remote Sensing and Water Resources, in: Remote Sensing and Water Resources, edited by: Cazenave, A., Champollion, N., Benveniste, J., and Chen, J., Space Sciences Series of ISSI, Springer, Cham, 55, 1–4, https://doi.org/10.1007/978-3-319-32449-4_1, 2016.
Chahine, M. T.: The hydrological cycle and its influence on climate, Nature,
359, 373–380, https://doi.org/10.1038/359373a0, 1992.
Cooley, S. W., Ryan, J. C., and Smith, L. C.: Human alteration of global surface
water storage variability, Nature, 591, 78–81,
https://doi.org/10.1038/s41586-021-03262-3, 2021.
Cretaux, J., Frappart, F., Papa, F., Calmant, S., Nielsen, K., and
Benveniste, J.: Hydrological Applications of Satellite Altimetry Rivers,
Lakes, Man-Made Reservoirs, Inundated Areas, in: Satellite Altimetry over
Oceans and Land Surfaces, edited by: Stammer, D. C. and Cazenave, A., Taylor
& Francis Group, New York, 459–504, ISBN 9781315151779,
https://doi.org/10.1201/9781315151779, 2017.
Crezee, B., Dargie, G. C., Ewango, C. E. N., Mitchard, E. T. A., B, O. E., T, J. K., Bola, P., Ndjango, J. N., Girkin, N. T., Bocko, Y. E., Ifo, S. A., Hubau, W., Seidensticker, D., Batumike, R., Wotzka, H., Bean, H., Baker, T. R., Baird, A. J., Boom, A., Morris, P. J., Page, S. E., Lawson, I. T., and Lewis, S. L.: Mapping peat thickness and carbon stocks of the central Congo Basin using field data, Nat. Geosci., 15, 639–644, https://doi.org/10.1038/s41561-022-00966-7, 2022.
Crowley, J. W., Mitrovica, J. X., Bailey, R. C., Tamisiea, M. E., and Davis, J. L.: Land water storage within the Congo Basin inferred from GRACE satellite gravity data, Geophys. Res. Lett., 33, L19402, https://doi.org/10.1029/2006GL027070, 2006.
Da Silva, J., Calmant, S., Seyler, F., Corrêa, O., Filho, R.,
Cochonneau, G., and João, W.: Water levels in the Amazon basin derived
from the ERS 2 and ENVISAT radar altimetry missions, Remote Sens. Environ.,
114, 2160–2181, https://doi.org/10.1016/j.rse.2010.04.020, 2010.
Datok, P., Fabre, C., Sauvage, S., N'kaya, G. D. M., Paris, A., Santos, V. D., Laraque, A., and Sánchez-Pérez, J.-M.: Investigating the Role of the Cuvette Centrale in the Hydrology of the Congo River Basin, in: Congo Basin Hydrology, Climate, and Biogeochemistry, edited by: Tshimanga, R. M., N'kaya, G. D. M., and Alsdorf, D., 247–273, https://doi.org/10.1002/9781119657002.ch14, 2022.
Decharme, B., Alkama, R., Papa, F., Faroux, S., Douville, H., and Prigent,
C.: Global off-line evaluation of the ISBA-TRIP flood model, Clim. Dynam.,
38, 1389–1412, https://doi.org/10.1007/s00382-011-1054-9, 2011.
de Marsily, G.: Eaux continentales, C. R. Geosci., 337, 1–7, https://doi.org/10.1016/j.crte.2004.11.002, 2005.
Dubayah, R., Blair, J. B., Goetz, S., Fatoyinbo, L., Hansen, M., Healey, S.,
Hofton, M., Hurtt, G., Kellner, J., and Luthcke, S.: The global ecosystem
dynamics investigation: high-resolution laser ranging of the Earth's forests
and topography, Sci. Remote Sens., 1, 100002,
https://doi.org/10.1016/j.srs.2020.100002, 2020a.
Fassoni-Andrade, A. C., Fleischmann, A. S., Papa, F., Paiva, R. C. D. d., Wongchuig, S., Melack, J. M., Moreira, A. A., Paris, A., Ruhoff, A., Barbosa, C., Maciel, D. A., T Novo, E., Durand, F., Frappart, F., Aires, F., Medeiros Abrahão, G., Ferreira-Ferreira, J., Espinoza, J. C., Laipelt, L., Costa, M. H., Espinoza-Villar, R., Calmant, S., and Pellet, V.: Amazon hydrology from space: Scientific advances and future challenges, Rev. Geophys., 59, e2020RG000728, https://doi.org/10.1029/2020RG000728, 2021.
Frappart, F., Calmant, S., Cauhopé, M., Seyler, F., and Cazenave, A.:
Preliminary results of ENVISAT RA-2-derived water levels validation over the
Amazon basin, Remote Sens. Environ., 100, 252–264,
https://doi.org/10.1016/j.rse.2005.10.027, 2006.
Frappart, F., Papa, F., Famiglietti, J., Prigent, C., Rossow, W. B., and Seyler,
F.: Interannual variations of river water storage from a multiple satellite
approach: A case study for the Rio Negro River basin, J. Geophys. Res., 113,
113, https://doi.org/10.1029/2007JD009438, 2008.
Frappart, F., Papa, F., Güntner, A., Werth, S., Ramillien, G., Prigent, C., Rossow, W. B., and Bonnet, M.-P.: Interannual variations of the terrestrial water storage in the Lower Ob' Basin from a multisatellite approach, Hydrol. Earth Syst. Sci., 14, 2443–2453, https://doi.org/10.5194/hess-14-2443-2010, 2010.
Frappart, F., Papa, F., Güntner, A., Werth, S., Santos da Silva, J.,
Tomasella, J., Seyler, F., Prigent, C., Rossow, W. B., Calmant, S., and
Bonnet, M. P.: Satellite-based estimates of groundwater storage variations in
large drainage basins with extensive floodplains, Remote Sens. Environ.,
115, 1588–1594, https://doi.org/10.1016/j.rse.2011.02.003, 2011.
Frappart, F., Papa, F., Da Silva, J. S., Ramillien, G., Prigent, C., Seyler,
F., and Calmant, S.: Surface freshwater storage and dynamics in the Amazon basin
during the 2005 exceptional drought, Environ. Res. Lett., 7, 7,
https://doi.org/10.1088/1748-9326/7/4/044010, 2012.
Frappart, F., Papa, F., Malbéteau, Y., Leon, J. G., Ramillien, G.,
Prigent, C., Seoane, L., Seyler, F., and Calmant, S.: Surface freshwater storage
variations in the Orinoco floodplains using multi-satellite observations,
Remote Sens., 7, 89–110, https://doi.org/10.3390/rs70100089, 2015a.
Frappart, F., Papa, F., Marieu, V., Malbeteau, Y., Jordy, F., Calmant, S.,
Durant, F., and Bala, S.: Preliminary assessment of SARAL/AltiKa observations
over the Ganges-Brahmaputra and Irrawaddy Rivers, Marine Geodesy, 38,
568–580, https://doi.org/10.1080/01490419.2014.990591, 2015b.
Frappart, F., Legrésy, B., Nino, F., Blarel, F., Fuller, N., Fleury, S.,
Birol, F., and Calmant, S.: An ERS-2 altimetry reprocessing compatible with
ENVISAT for long-term land and ice sheets studies, Remote Sens.
Environ., 184, 558–581, https://doi.org/10.1016/j.rse.2016.07.037, 2016.
Frappart, F., Biancamaria, S., Normandin, C., Blarel, F., Bourrel, L., Aumont, M., Azemar, P., Vu, P.-L., Le Toan, T., Lubac, B., and Darrozes, J.: Influence of recent climatic events on the surface water storage of the Tonle Sap Lake, Sci. Total Environ., 636, 1520–1533, https://doi.org/10.1016/j.scitotenv.2018.04.326, 2018.
Frappart, F., Papa, F., Güntner, A., Tomasella, J., Pfeffer, J.,
Ramillien, G., Emilio, T., Schietti, J., Seoane, L., da Silva Carvalho, J.,
Medeiros Moreira, D., Bonnet, M. P., and Seyler, F.: The spatio-temporal
variability of groundwater storage in the Amazon River Basin, Adv. Water
Resour., 124, 41–52, https://doi.org/10.1016/j.advwatres.2018.12.005, 2019.
Frappart, F., Blarel, F., Fayad, I., Bergé-Nguyen, M., Crétaux, J.
F., Shu, S., Schregenberger, J., and Baghdadi, N.: Evaluation of the performances
of radar and lidar altimetry missions for water level retrievals in
mountainous environment: The case of the Swiss lakes, Remote
Sensing, 13, 2196, https://doi.org/10.3390/rs13112196, 2021.
Gasse, F., Ledee, V., Massauh, M., and Fontes, J.: Water-level fluctuations
of Lake Tanganyika in phase with oceanic changes during the last glaciation
and deglaciation, Nature, 342, 57–59,
https://doi.org/10.1038/342057a0, 1989.
Good, S. P., Noone, D., and Bowen, G.: Hydrologic connectivity constrains
partitioning of global terrestrial water fluxes, Science, 349, 175–177,
https://doi.org/10.1126/science.aaa5931, 2015.
Guth, P. L., Van Niekerk, A., Grohmann, C. H., Muller, J. P., Hawker, L.,
Florinsky, I. V., Gesch, D., Reuter, H. I., Herrera-Cruz, V., Riazanoff, S.,
López-Vázquez, C., Carabajal, C. C., Albinet, C., and Strobl, P.: Digital
elevation models: Terminology and definitions, Remote Sens., 13, 1–19,
https://doi.org/10.3390/rs13183581, 2021.
Harrison, I. J., Brummett, R., and Stiassny, M. L. J.: The Congo River Basin,
in: The Wetland Book (1), edited by: Finlayson, C. M., van Dam, A. A., Irvine, K., Everard, M., McInnes, R. J., Middleton, B.
A., and Davidson, N. C., Springer
Science + Business Media, Dordrecht,
https://doi.org/10.1007/978-94-007-6173-5, 2016.
Hastie, A., Lauerwald, R., Ciais, P., Papa, F., and Regnier, P.: Historical and future contributions of inland waters to the Congo Basin carbon balance, Earth Syst. Dynam., 12, 37–62, https://doi.org/10.5194/esd-12-37-2021, 2021.
Hawker, L. and Neal, J.: FABDEM V1-0, University of Bristol [data set], https://doi.org/10.5523/bris.25wfy0f9ukoge2gs7a5mqpq2j7, 2021.
Hawker, L., Neal, J., and Bates, P.: Accuracy assessment of the TanDEM-X 90
Digital Elevation Model for selected floodplain sites, Remote Sens.
Environ., 232, https://doi.org/10.1016/j.rse.2019.111319, 2019.
Hawker, L., Uhe, P., Paulo, L., Sosa, J., Savage, J., Sampson, C., and Neal, J.:
A 30 m global map of elevation with forests and buildings removed, Environ.
Res. Lett., 17, https://doi.org/10.1088/1748-9326/ac4d4f, 2022.
Hua, W., Zhou, L., Chen, H., Nicholson, S. E., Raghavendra, A., and Jiang, Y.: Possible causes of the Central Equatorial African long-term drought Possible causes of the Central Equatorial African long-term drought, Environ. Res. Lett., 11, 124002, https://doi.org/10.1088/1748-9326/11/12/124002, 2016.
Inogwabini, B.-I.: The changing water cycle: Freshwater in the Congo, WIREs
Water, 7, e1410, https://doi.org/10.1002/wat2.1410, 2020.
Jiang, L., Nielsen, K., Dinardo, S., Andersen, O. B., and Bauer-Gottwein, P.:
Evaluation of Sentinel-3 SRAL SAR altimetry over Chinese rivers, Remote
Sens. Environ., 237, 111546,
https://doi.org/10.1016/j.rse.2019.111546, 2020.
Kao, H., Kuo, C., Tseng, K., Shum, C. K., Tseng, T.-P., Jia, Y.-Y., Yang,
T.-Y., Ali, T. A., Yi, Y., and Hussain, D.: Assessment of Cryosat-2 and
SARAL/AltiKa altimetry for measuring inland water and coastal sea level
variations: A case study on Tibetan Plateau Lake and Taiwan Coast, Mar.
Geod., 42, 327–343, https://doi.org/10.1080/01490419.2019.1623352, 2019.
Kitambo, B., Papa, F., Paris, A., Tshimanga, R. M., Calmant, S., Fleischmann, A. S., Frappart, F., Becker, M., Tourian, M. J., Prigent, C., and Andriambeloson, J.: A combined use of in situ and satellite-derived observations to characterize surface hydrology and its variability in the Congo River basin, Hydrol. Earth Syst. Sci., 26, 1857–1882, https://doi.org/10.5194/hess-26-1857-2022, 2022a.
Kitambo, B., Papa, F., Paris, A., Tshimanga, R. M., Frappart, F., Calmant,
S., Elmi, O., Fleischmann, A. S., Becker, M., Tourian, M. J., Jucá
Oliveira, R. A., and Wongchuig, S.: A long-term monthly surface water storage
dataset for the Congo basin from 1992 to 2015, Zenodo [data set],
https://doi.org/10.5281/zenodo.7299823, 2022b.
Kitambo, B., Papa, F., and Paris, A.: Surface Water Storage computation (1.0),
Zenodo [code], https://doi.org/10.5281/zenodo.8011607, 2023.
Kittel, C. M. M., Jiang, L., Tøttrup, C., and Bauer-Gottwein, P.: Sentinel-3 radar altimetry for river monitoring – a catchment-scale evaluation of satellite water surface elevation from Sentinel-3A and Sentinel-3B, Hydrol. Earth Syst. Sci., 25, 333–357, https://doi.org/10.5194/hess-25-333-2021, 2021.
Laraque, A., Bricquet, J. P., Pandi, A., and Olivry, J. C.: A review of
material transport by the Congo River and its tributaries, Hydrol. Process.,
23, 3216–3224, https://doi.org/10.1002/hyp.7395, 2009.
Laraque, A., Bellanger, M., Adele, G., Guebanda, S., Gulemvuga, G., Pandi,
A., Paturel, J. E., Robert, A., Tathy, J. P., and Yambele, A.: Evolutions
récentes des débits du Congo, de l'Oubangui et de la Sangha,
Geo-Eco-Trop., 37, 93–100, 2013.
Laraque, A., N'kaya, G. D. M., Orange, D., Tshimanga, R., Tshitenge, J. M., Mahé, G., Nguimalet, C. R., Trigg, M. A., Yepez, S., and Gulemvuga, G.: Recent budget of hydroclimatology and hydrosedimentology of the congo river in central Africa, Water, 12, 2613, https://doi.org/10.3390/w12092613, 2020.
Lee, H., Beighley, R. E., Alsdorf, D., Chul, H., Shum, C. K., Duan, J., Guo,
J., Yamazaki, D., and Andreadis, K.: Remote Sensing of Environment
Characterization of terrestrial water dynamics in the Congo Basin using
GRACE and satellite radar altimetry, Remote Sens. Environ., 115, 3530–3538,
https://doi.org/10.1016/j.rse.2011.08.015, 2011.
Mcphaden, M. J.: El Nino and La Nina: Causes and Global Consequences, in:
Encyclopedia of Global Environmental Change (1), 1–17, ISBN
0-471-97796-9, https://www.pmel.noaa.gov/gtmba/files/PDF/pubs/ElNinoLaNina.pdf (last access: 17 May 2023), 2002.
Mekonnen, M. M. and Hoekstra, A. Y.: Sustainability: Four billion people facing
severe water scarcity, Sci. Adv., 2, e1500323, https://doi.org/10.1126/sciadv.1500323,
2016.
Melack, J. M. and Forsberg, B. R.: Biogeochemistry of Amazon floodplain lakes and
associated wetlands, in: The Bio-Geochemistry of the Amazon Basin, edited by: McClain,
M. E., Victoria, R. L., and Richey, J. E., Oxford University Press: New York,
NY, USA, 235–274, https://doi.org/10.1093/oso/9780195114317.001.0001, 2001.
Ndehedehe, C. E., Awange, J. L., Agutu, N. O., and Okwuashi, O.: Changes in
hydro-meteorological conditions over tropical West Africa (1980–2015)
and links to global climate, Glob. Planet. Change, 162, 321–341,
https://doi.org/10.1016/j.gloplacha.2018.01.020, 2018.
Ndehedehe, C. E., Anyah, R. O., Alsdorf, D., Agutu, N. O., and Ferreira, V.
G.: Modelling the impacts of global multi-scale climatic drivers on
hydro-climatic extremes (1901–2014) over the Congo basin, Sci. Total
Environ., 651, 1569–1587, https://doi.org/10.1016/j.scitotenv.2018.09.203,
2019.
Ndehedehe, C. E. and Agutu, N. O.: Historical Changes in Rainfall Patterns
over the Congo Basin and Impacts on Runoff (1903–2010), in:
Tshimanga, R. M., N'kaya, G. D. M., and Alsdorf, D., Congo Basin Hydrology,
Climate, and Biogeochemistry A Foundation for the Future, American
Geophysical Union and John Wiley and Sons, Inc.,
https://doi.org/10.1002/9781119657002.ch9, 2022.
Normandin, C., Frappart, F., Lubac, B., Bélanger, S., Marieu, V., Blarel, F., Robinet, A., and Guiastrennec-Faugas, L.: Quantification of surface water volume changes in the Mackenzie Delta using satellite multi-mission data, Hydrol. Earth Syst. Sci., 22, 1543–1561, https://doi.org/10.5194/hess-22-1543-2018, 2018.
O'Connell, E.: Towards Adaptation ofWater Resource Systems to Climatic and
Socio-Economic Change, Water Resour. Manag., 31, 2965–2984,
https://doi.org/10.1007/s11269-017-1734-2, 2017.
Oki, T. and Kanae, S.: Global Hydrological Cycles and WorldWater Resources,
Science, 313, 1068–1072, https://doi.org/10.1126/science.1128845, 2006.
O'Loughlin, F. E., Paiva, R. C. D., Durand, M., Alsdorf, D. E., and Bates, P. D.:
A multi-sensor approach towards a global vegetation corrected SRTM DEM
product, Remote Sens. Environ., 182, 49–59,
https://doi.org/10.1016/j.rse.2016.04.018, 2016.
Papa, F. and Frappart, F.: SurfaceWater Storage in Rivers and Wetlands Derived
from Satellite
Observations: A Review of Current Advances and Future Opportunities for
Hydrological Sciences, Remote Sens., 13, 4162, https://doi.org/10.3390/rs13204162, 2021.
Papa, F., Gu, A., Frappart, F., Prigent, C., and Rossow, W. B.: Variations of
surface water extent and water storage in large river basins: A comparison
of different global data sources, Geophys. Res. Lett., 35, 1–5,
https://doi.org/10.1029/2008GL033857, 2008.
Papa, F., Prigent, C., Aires, F., Jimenez, C., Rossow, W. B., and Matthews,
E.: Interannual variability of surface water extent at the global scale,
1993–2004, J. Geophys. Res.-Atmos., 115, 1–17,
https://doi.org/10.1029/2009JD012674, 2010.
Papa, F., Frappart, F., Güntner, A., Prigent, C., Aires, F., Getirana,
A. C. V., and Maurer, R.: Surface freshwater storage and variability in the
Amazon basin from multi-satellite observations, 1993–2007, J. Geophys.
Res.-Atmos., 118, 11951–11965, https://doi.org/10.1002/2013JD020500, 2013.
Papa, F., Frappart, F., Malbeteau, Y., Shamsudduha, M., Vuruputur, V.,
Sekhar, M., Ramillien, G., Prigent, C., Aires, F., Pandey, R. K., Bala, S.,
and Calmant, S.: Satellitederived surface and sub-surface water storage in
the Ganges- Brahmaputra River Basin, J. Hydrol. Reg. Stud., 4, 15–35,
https://doi.org/10.1016/j.ejrh.2015.03.004, 2015.
Papa, F., Crétaux, J.-F., Grippa, M., Robert, E., Trigg, M., Tshimanga, R. M., Kitambo, B., Paris, A., Carr, A., Fleischmann, A. S., de Fleury, M., Gbetkom, P. G., Calmettes, B., Calmant, S. Water Resources in Africa under Global Change: Monitoring Surface Waters from Space, Surv. Geophys., 44, 43–93, https://doi.org/10.1007/s10712-022-09700-9, 2022.
Paris, A., Calmant, S., Gosset, M., Fleischmann, A. S., Conchy, T. S. X.,
Garambois, P.-A., Bricquet, J.-P., Papa, F., Tshimanga, R. M., Guzanga, G.
G., Siqueira, V. A., Tondo, B.-L., Paiva, R., da Silva, J. S., and Laraque,
A.: Monitoring Hydrological Variables from Remote Sensing and Modeling in
the Congo River Basin, in: Congo Basin Hydrology, Climate, and
Biogeochemistry, edited by: Tshimanga, R. M., N'kaya, G. D. M., and Alsdorf,
D., AGU, https://doi.org/10.1002/9781119657002.ch18, 2022.
Pervez, M. S. and Henebry, G. M.: Spatial and seasonal responses of precipitation in the Ganges and Brahmaputra river basins to ENSO and Indian Ocean dipole modes: implications for flooding and drought, Nat. Hazards Earth Syst. Sci., 15, 147–162, https://doi.org/10.5194/nhess-15-147-2015, 2015.
Pham-duc, B., Papa, F., Prigent, C., Aires, F., Biancamaria, S., and Frappart,
F.: Variations of Surface and Subsurface Water Storage in the Lower Mekong
Basin (Vietnam and Cambodia) from Multisatellite Observations, Water,
11, 1–17, https://doi.org/10.3390/w11010075, 2019.
Pham-Duc, B., Sylvestre, F., Papa, F., Frappart, F., Bouchez, C.,
and Crétaux, J.-F.: The Lake Chad hydrology under current climate change,
Sci. Rep., 10, 5498, https://doi.org/10.1038/s41598-020-62417-w, 2020.
Potapov, P., Li, X., Hernandez-Serna, A., Tyukavina, A., Hansen, M. C., Kommareddy, A., Pickens, A., Turubanova, S., Tang, H., Silva, C. E., Armston, J., Dubayah, R., Blair, J. B., and Hofton, M.: Mapping global forest canopy height through integration of GEDI and Landsat data, Remote Sens. Environ., 253, 112165, https://doi.org/10.1016/j.rse.2020.112165, 2020.
Prigent, C., Papa, F., Aires, F., Rossow, W. B., and Matthews, E.:
Global inundation dynamics inferred from multiple satellite observations,
1993–2000, J. Geophys. Res.-Atmos., 112, 1993–2000,
https://doi.org/10.1029/2006JD007847, 2007.
Prigent, C., Jimenez, C., and Bousquet, P.: Satellite-derived global surface
water extent and dynamics over the last 25 years (GIEMS-2), J. Geophys. Res.-Atmos., 125, e2019JD030711, https://doi.org/10.1029/2019JD030711, 2020.
Raymond, P. A., Hartmann, J., Lauerwald, R., Sobek, S., Mc- Donald, C., Hoover, M., Butman, D., Striegl, R., Mayorga, E., Humborg, C., Kortelainen, P., Dürr, H., Meybeck, M., Ciais, P., and Guth, P.: Global carbon dioxide emissions from inland waters, Nature, 503, 355–359, https://doi.org/10.1038/nature12760, 2013.
Reis, V., Hermoso, V., Hamilton, S. K., Ward, D., Fluet-Chouinard, E.,
Lehner, B., and Linke, S.: A Global Assessment of Inland Wetland Conservation
Status, Bioscience, 67, 523–533, https://doi.org/10.1093/biosci/bix045,
2017.
Richey, J. E., Melack, J. M., Aufdenkampe, A., Ballester, V. M., and Hess, L. L.:
Outgassing from Amazonian rivers and wetlands as a large tropical source of
atmospheric CO2, Nature, 416, 617–620, https://doi.org/10.1038/416617a,
2002.
Richey, A. S., Thomas, B. F., Lo, M. H., Reager, J. T., Famiglietti, J. S.,
Voss, K., Swenson, S., and Rodell, M.: Quantifying renewable groundwater stress
with GRACE, Water Resour. Res., 51, 5217–5237,
https://doi.org/10.1002/2015WR017349, 2015.
Rodell, M., Beaudoing, H. K., L’Ecuyer, T. S., Olson, W. S., Famiglietti, J., Houser, P. R., Adler, R., Bosilovich, M. G., Clayson, C. A., Chambers, D., Clark, E., Fetzer, E. J., Gao, X., Gu, G., Hilburn, K., Huffman, G. J., Lettenmaier, D. P., Liu, W. T., Robertson, F. R., Schlosser, C. A., Sheffield, J., and Wood, E. F.: The Observed State of the Water Cycle in the Early Twenty-First Century, J. Climate, 28, 8289–8318, https://doi.org/10.1175/JCLI-D-14-00555.1, 2015.
Runge, J.: The Congo River, Central Africa, in: Large Rivers: Geomorphology and Management, edited by: Gupta, A., John Wiley and Sons, 293–309,
https://doi.org/10.1002/9780470723722.ch14, 2007.
Scanlon, B. R., Zhang, Z., Rateb, A., Sun, A., Wiese, D., Save, H.,
Beaudoing, H., Lo, M. H., Müller-Schmied, H., Döll, P., Beek, R.
van, Swenson, S., Lawrence, D., Croteau, M., and Reedy, R. C.: Tracking Seasonal
Fluctuations in Land Water Storage Using Global Models and GRACE Satellites,
Geophys. Res. Lett., 46, 5254–5264,
https://doi.org/10.1029/2018GL081836, 2019.
Shelton, M. L.: Hydroclimatology, Perspectives and applications, Cambridge
University Press, New York,
https://assets.cambridge.org/97805218/48886/frontmatter/9780521848886_frontmatter.pdf (last access: 17 May 2023), 2009.
Sridhar, V., Kang, H., Ali, S. A., Bola, G. B., Tshimanga, M. R., and Lakshmi,
V.: Bilan hydrique et sechéresse dans les conditions ctuelles et futures
dans le bassin du fleuve Congo, in: Congo Basin Hydrology, Climate, and
Biogeochemistry, edited by: Tshimanga, R. M., N'kaya, G. D. M., and Alsdorf,
D., AGU, https://doi.org/10.1002/9781119657002.ch18, 2022.
Stephens, G. L., Slingo, J. M., Rignot, E., Reager, J. T., Hakuba, M. Z.,
Durack, P. J., Worden, J., and Rocca, R.: Earth's water reservoirs in a changing
climate, P. Roy. Soc. A, 476, 20190458,
https://doi.org/10.1098/rspa.2019.0458, 2020.
Steffen, W., Richardson, K., Rockström, J., Cornell, S. E., Fetzer, I., Bennett, E. M., Biggs, R., Carpenter, S. R., Vries, W. De, Wit, C. A. De, Folke, C., Gerten, D., Heinke, J., Mace, G. M., Persson, L. M., Ramanathan, V., Reyers, B., and Sörlin, S.: Planetary boundaries: Guiding human development on a changing planet, Science, 347, 6223, https://doi.org/10.1126/science.1259855, 2015.
Tapley, B. D., Bettadpur, S., Watkins, M., and Reigber, C.: The gravity recovery and climate experiment: Mission overview and early results, Geophys. Res. Lett., 31, L09607, https://doi.org/10.1029/2004GL019920, 2004.
Tapley, B. D., Watkins, M. M., Flechtner, F., Reigber, C., Bettadpur, S., Rodell, M., Sasgen, I., Famiglietti, J. S., Landerer, F. W., Chambers, D. P., Reager, J. T., Gardner, A. S., Save, H., Ivins, E. R., Swenson, S. C., Boening, C., Dahle, C., Wiese, D. N., Dobslaw, H., Tamisiea, M. E., and Velicogna, I.: Contributions of GRACE to understanding climate change, Nat. Clim. Change, 9, 358–369, https://doi.org/10.1038/s41558-019-0456-2, 2019.
Tourian, M. J., Reager, J. T., and Sneeuw, N.: The Total Drainable Water Storage of
the Amazon River Basin: A First Estimate Using GRACE, Water Resour. Res.,
54, 3290–3312, https://doi.org/10.1029/2017WR021674, 2018.
Tourian, M. J., Elmi, O., Shafaghi, Y., Behnia, S., Saemian, P., Schlesinger, R., and Sneeuw, N.: HydroSat: geometric quantities of the global water cycle from geodetic satellites, Earth Syst. Sci. Data, 14, 2463–2486, https://doi.org/10.5194/essd-14-2463-2022, 2022.
Tourian, M. J., Papa, F., Elmi, O., Sneeuw, N., Kitambo, B., Tshimanga, R.,
Paris, A., and Calmant, S.: Current availability and distribution of Congo
Basin's freshwater resources, Commun. Earth Environ., 4, 174,
https://doi.org/10.1038/s43247-023-00836-z, 2023.
Trenberth, K. E., Smith, L., Qian, T., Dai, A., and Fasullo, J.: Estimates of the
global water budget and its annual cycle using observational and model data,
J. Hydrometeorol., 8, 758–769, https://doi.org/10.1175/JHM600.1, 2007.
Trenberth, K. E., Fasullo, J., and Mackaro, J.: Atmospheric Moisture Transports
from Ocean to Land and Global Energy Flows in Reanalyses, J. Climate, 24,
4907–4924, https://doi.org/10.1175/2011JCLI4171.1, 2011.
Tshimanga, R. M., N'kaya, G. D. M., and Alsdorf, D.: Congo Basin Hydrology, Climate, and Biogeochemistry A Foundation for the Future, edited by: Tshimanga, R. M., N'kaya, G. D. M., and Alsdorf, D., American Geophysical Union and JohnWiley and Sons, Inc., ISBN 9781119656999, 2022.
Ummenhofer, C. C., England, M. H., Mcintosh, P. C., Meyers, G. A., Pook, M.
J., Risbey, J. S., and Gupta, A. S.: What causes southeast Australia's
worst droughts?, Geophys. Res. Lett., 36, 1–5,
https://doi.org/10.1029/2008GL036801, 2009.
Verhegghen, A., Mayaux, P., de Wasseige, C., and Defourny, P.: Mapping Congo Basin vegetation types from 300 m and 1 km multi-sensor time series for carbon stocks and forest areas estimation, Biogeosciences, 9, 5061–5079, https://doi.org/10.5194/bg-9-5061-2012, 2012.
Vörösmarty, C. J., McIntyre, P. B., Gessner, M. O., Dudgeon, D., Prusevich, A., Green, P., Glidden, S., Bunn, S. E., Sullivan, C. A., Liermann, C. R., and Davies, P. M.: Global threats to human water security and river biodiversity, Nature, 467, 555–561, https://doi.org/10.1038/nature09440, 2010.
Ward, N. D., Bianchi, T. S., Medeiros, P. M., Seidel, M., Richey, J. E., Keil, R. G., and Sawakuchi, H. O.: Where Carbon Goes When Water Flows: Carbon Cycling across the Aquatic Continuum. Front. Mar. Sci., 4, 2296–7745, https://doi.org/10.3389/fmars.2017.00007, 2017.
Watkins, M. M., Wiese, D. N., Yuan, D.-N., Boening, C., and Landerer, F. W.: Improved methods for observing Earth's time variable mass distribution with GRACE using spherical cap mascons, J. Geophys. Res.-Sol. Ea., 120, 2648–2671, https://doi.org/10.1002/2014JB011547, 2015.
White, L. J. T., Masudi, E. B., Ndongo, J. D., Matondo, R., Soudan-Nonault,
A., Ngomanda, A., Averti, I. S., Ewango, C. E. N., Sonké, B., and Lewis,
S. L.: Congo Basin rainforest – invest US$150 million in science, Nature,
598, 411–414, https://doi.org/10.1038/d41586-021-02818-7, 2021.
Wiese, D. N., Landerer, F. W., and Watkins, M. M.: Quantifying and reducing
leakage errors in the JPL RL05M GRACE mascon solution, Water Resour. Res.,
52, 7490–7502, https://doi.org/10.1002/2016WR019344, 2016.
Wiese, D. N., Yuan, D.-N., Boening, C., Landerer, F. W., and Watkins, M. M.: JPL GRACE
Mascon Ocean, Ice, and Hydrology Equivalent Water Height Release 06 Coastal
Resolution Improvement (CRI) Filtered Version 1.0. Ver. 1.0, PO.DAAC, CA,
USA [data set], https://doi.org/10.5067/TEMSC-3MJC6,
2018.
Wohl, E.: An Integrative Conceptualization of Floodplain Storage, Rev.
Geophys., 59, e2020RG000724, https://doi.org/10.1029/2020RG000724, 2021.
Yamazaki, D., Ikeshima, D., Tawatari, R., Yamaguchi, T., O'Loughlin, F.,
Neal, J. C., Sampson, C. C., Kanae, S., and Bates, P. D.: A high accuracy map of
global terrain elevations, Geophys. Res. Lett., 44, 5844–5853, https://doi.org/10.1002/2017GL072874, 2017.
Yuan, T., Lee, H., Jung, C. H., Aierken, A., Beighley, E., Alsdorf, D. E., Tshimanga, R. M., and Kim,
D.: Absolute water storages in the Congo River floodplains from integration
of InSAR and satellite radar altimetry, Remote Sens. Environ., 201, 57–72,
https://doi.org/10.1016/j.rse.2017.09.003, 2017.
Zhou, T., Nijssen, B., Gao, H., and Lettenmaier, D. P.: The Contribution of
Reservoirs to Global Land Surface Water Storage Variations, J.
Hydrometeorol., 17, 309–325, https://doi.org/10.1175/JHM-D-15-0002.1, 2016.
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,...
Altmetrics
Final-revised paper
Preprint