Articles | Volume 26, issue 7
https://doi.org/10.5194/hess-26-1857-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-1857-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A combined use of in situ and satellite-derived observations to characterize surface hydrology and its variability in the Congo River basin
Benjamin 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), Department of Natural Resources Management, University of Kinshasa (UNIKIN), Kinshasa, Democratic Republic of the Congo
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), Brazi
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), Department of Natural Resources Management, University of Kinshasa (UNIKIN), Kinshasa, Democratic Republic of the Congo
Stephane Calmant
Laboratoire d'Etudes en Géophysique et Océanographie Spatiales (LEGOS), Université de Toulouse, CNES/CNRS/IRD/UT3, Toulouse, France
Ayan Santos Fleischmann
Instituto de Pesquisas Hidráulicas (IPH), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brasil
Instituto de Desenvolvimento Sustentável Mamirauá, Tefé, AM, Brazil
Frederic Frappart
Laboratoire d'Etudes en Géophysique et Océanographie Spatiales (LEGOS), Université de Toulouse, CNES/CNRS/IRD/UT3, Toulouse, France
INRAE, Bordeaux Sciences Agro, UMR1391 ISPA, 71 Avenue Edouard Bourlaux, 33882 CEDEX Villenave d'Ornon, France
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
Catherine Prigent
LERMA, Observatoire de Paris, Sorbonne Université, CNRS, Université PSL, Paris, France
Johary Andriambeloson
Laboratoire de Géophysique de l'Environnement et de Télédétection (LGET), Institut et Observatoire de Géophysique d'Antananarivo (IOGA), Université d'Antananarivo, Antananarivo, Madagascar
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 M. Kitambo, Fabrice Papa, Adrien Paris, Raphael M. Tshimanga, Frederic Frappart, Stephane Calmant, Omid Elmi, Ayan Santos Fleischmann, Melanie Becker, Mohammad J. Tourian, Rômulo A. Jucá Oliveira, and Sly Wongchuig
Earth Syst. Sci. Data, 15, 2957–2982, https://doi.org/10.5194/essd-15-2957-2023, https://doi.org/10.5194/essd-15-2957-2023, 2023
Short summary
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.
Nils Risse, Mario Mech, Catherine Prigent, Joshua Jeremias Müller, and Susanne Crewell
EGUsphere, https://doi.org/10.5194/egusphere-2025-3311, https://doi.org/10.5194/egusphere-2025-3311, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
Clouds play a crucial role in the Arctic climate system, particularly cloud liquid water droplets. However, there is currently a measurement gap for cloud liquid water over sea ice. We present a method to estimate cloud liquid water over Arctic sea ice using airborne passive microwave observations from the HALO-(𝒜𝒞)3 campaign. Evaluation with other airborne sensors highlights both the limitations and potential of the retrieval. This approach is promising for future applications to satellites.
Juliette Bernard, Catherine Prigent, Carlos Jimenez, Etienne Fluet-Chouinard, Bernhard Lehner, Elodie Salmon, Philippe Ciais, Zhen Zhang, Shushi Peng, and Marielle Saunois
Earth Syst. Sci. Data, 17, 2985–3008, https://doi.org/10.5194/essd-17-2985-2025, https://doi.org/10.5194/essd-17-2985-2025, 2025
Short summary
Short summary
Wetlands are responsible for about a third of global emissions of methane, a potent greenhouse gas. We have developed the Global Inundation Extent from Multi-Satellites-MethaneCentric (GIEMS-MC) dataset to represent the dynamics of wetland extent on a global scale (0.25° × 0.25° resolution, monthly time step). This updated resource combines satellite data and existing wetland databases, covering 1992 to 2020. Consistent maps of other methane-emitting surface waters (lakes, rivers, reservoirs, rice paddies) are also provided.
Bernhard Lehner, Mira Anand, Etienne Fluet-Chouinard, Florence Tan, Filipe Aires, George H. Allen, Philippe Bousquet, Josep G. Canadell, Nick Davidson, Meng Ding, C. Max Finlayson, Thomas Gumbricht, Lammert Hilarides, Gustaf Hugelius, Robert B. Jackson, Maartje C. Korver, Liangyun Liu, Peter B. McIntyre, Szabolcs Nagy, David Olefeldt, Tamlin M. Pavelsky, Jean-Francois Pekel, Benjamin Poulter, Catherine Prigent, Jida Wang, Thomas A. Worthington, Dai Yamazaki, Xiao Zhang, and Michele Thieme
Earth Syst. Sci. Data, 17, 2277–2329, https://doi.org/10.5194/essd-17-2277-2025, https://doi.org/10.5194/essd-17-2277-2025, 2025
Short summary
Short summary
The Global Lakes and Wetlands Database (GLWD) version 2 distinguishes a total of 33 non-overlapping wetland classes, providing a static map of the world’s inland surface waters. It contains cell fractions of wetland extents per class at a grid cell resolution of ~500 m. The total combined extent of all classes including all inland and coastal waterbodies and wetlands of all inundation frequencies – that is, the maximum extent – covers 18.2 × 106 km2, equivalent to 13.4 % of total global land area.
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.
Léa Elise Bonnefoy, Catherine Prigent, Ghislain Picard, Clément Soriot, Alice Le Gall, Lise Kilic, and Carlos Jimenez
EGUsphere, https://doi.org/10.5194/egusphere-2024-3972, https://doi.org/10.5194/egusphere-2024-3972, 2025
Short summary
Short summary
Microwave radiometry senses the thermal emission from a target, whereas its active counterpart, radar, sends a signal to the target and measures the signal reflected back. We simultaneously model radar and radiometry over the East Antarctic ice sheet, which we propose as an analog for icy moons: we can reproduce most data with a unique model. Saturn's moons' radar brightness cannot be reproduced and must be caused by processes unaccounted for in the model and less active in the Antarctic.
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.
Nils Risse, Mario Mech, Catherine Prigent, Gunnar Spreen, and Susanne Crewell
The Cryosphere, 18, 4137–4163, https://doi.org/10.5194/tc-18-4137-2024, https://doi.org/10.5194/tc-18-4137-2024, 2024
Short summary
Short summary
Passive microwave observations from satellites are crucial for monitoring Arctic sea ice and atmosphere. To do this effectively, it is important to understand how sea ice emits microwaves. Through unique Arctic sea ice observations, we improved our understanding, identified four distinct emission types, and expanded current knowledge to include higher frequencies. These findings will enhance our ability to monitor the Arctic climate and provide valuable information for new satellite missions.
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.
Benjamin M. Kitambo, Fabrice Papa, Adrien Paris, Raphael M. Tshimanga, Frederic Frappart, Stephane Calmant, Omid Elmi, Ayan Santos Fleischmann, Melanie Becker, Mohammad J. Tourian, Rômulo A. Jucá Oliveira, and Sly Wongchuig
Earth Syst. Sci. Data, 15, 2957–2982, https://doi.org/10.5194/essd-15-2957-2023, https://doi.org/10.5194/essd-15-2957-2023, 2023
Short summary
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.
Danny M. Leung, Jasper F. Kok, Longlei Li, Gregory S. Okin, Catherine Prigent, Martina Klose, Carlos Pérez García-Pando, Laurent Menut, Natalie M. Mahowald, David M. Lawrence, and Marcelo Chamecki
Atmos. Chem. Phys., 23, 6487–6523, https://doi.org/10.5194/acp-23-6487-2023, https://doi.org/10.5194/acp-23-6487-2023, 2023
Short summary
Short summary
Desert dust modeling is important for understanding climate change, as dust regulates the atmosphere's greenhouse effect and radiation. This study formulates and proposes a more physical and realistic desert dust emission scheme for global and regional climate models. By considering more aeolian processes in our emission scheme, our simulations match better against dust observations than existing schemes. We believe this work is vital in improving dust representation in climate models.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
Short summary
Short summary
As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
Toby R. Marthews, Simon J. Dadson, Douglas B. Clark, Eleanor M. Blyth, Garry D. Hayman, Dai Yamazaki, Olivia R. E. Becher, Alberto Martínez-de la Torre, Catherine Prigent, and Carlos Jiménez
Hydrol. Earth Syst. Sci., 26, 3151–3175, https://doi.org/10.5194/hess-26-3151-2022, https://doi.org/10.5194/hess-26-3151-2022, 2022
Short summary
Short summary
Reliable data on global inundated areas remain uncertain. By matching a leading global data product on inundation extents (GIEMS) against predictions from a global hydrodynamic model (CaMa-Flood), we found small but consistent and non-random biases in well-known tropical wetlands (Sudd, Pantanal, Amazon and Congo). These result from known limitations in the data and the models used, which shows us how to improve our ability to make critical predictions of inundation events in the future.
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.
Ronny Meier, Edouard L. Davin, Gordon B. Bonan, David M. Lawrence, Xiaolong Hu, Gregory Duveiller, Catherine Prigent, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2365–2393, https://doi.org/10.5194/gmd-15-2365-2022, https://doi.org/10.5194/gmd-15-2365-2022, 2022
Short summary
Short summary
We revise the roughness of the land surface in the CESM climate model. Guided by observational data, we increase the surface roughness of forests and decrease that of bare soil, snow, ice, and crops. These modifications alter simulated temperatures and wind speeds at and above the land surface considerably, in particular over desert regions. The revised model represents the diurnal variability of the land surface temperature better compared to satellite observations over most regions.
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.
Adama Telly Diepkilé, Flavien Egon, Fabien Blarel, Eric Mougin, and Frédéric Frappart
Proc. IAHS, 384, 31–35, https://doi.org/10.5194/piahs-384-31-2021, https://doi.org/10.5194/piahs-384-31-2021, 2021
Martina Klose, Oriol Jorba, María Gonçalves Ageitos, Jeronimo Escribano, Matthew L. Dawson, Vincenzo Obiso, Enza Di Tomaso, Sara Basart, Gilbert Montané Pinto, Francesca Macchia, Paul Ginoux, Juan Guerschman, Catherine Prigent, Yue Huang, Jasper F. Kok, Ron L. Miller, and Carlos Pérez García-Pando
Geosci. Model Dev., 14, 6403–6444, https://doi.org/10.5194/gmd-14-6403-2021, https://doi.org/10.5194/gmd-14-6403-2021, 2021
Short summary
Short summary
Mineral soil dust is a major atmospheric airborne particle type. We present and evaluate MONARCH, a model used for regional and global dust-weather prediction. An important feature of the model is that it allows different approximations to represent dust, ranging from more simplified to more complex treatments. Using these different treatments, MONARCH can help us better understand impacts of dust in the Earth system, such as its interactions with radiation.
Zhen Zhang, Etienne Fluet-Chouinard, Katherine Jensen, Kyle McDonald, Gustaf Hugelius, Thomas Gumbricht, Mark Carroll, Catherine Prigent, Annett Bartsch, and Benjamin Poulter
Earth Syst. Sci. Data, 13, 2001–2023, https://doi.org/10.5194/essd-13-2001-2021, https://doi.org/10.5194/essd-13-2001-2021, 2021
Short summary
Short summary
The spatiotemporal distribution of wetlands is one of the important and yet uncertain factors determining the time and locations of methane fluxes. The Wetland Area and Dynamics for Methane Modeling (WAD2M) dataset describes the global data product used to quantify the areal dynamics of natural wetlands and how global wetlands are changing in response to climate.
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.
Song Shu, Hongxing Liu, Richard A. Beck, Frédéric Frappart, Johanna Korhonen, Minxuan Lan, Min Xu, Bo Yang, and Yan Huang
Hydrol. Earth Syst. Sci., 25, 1643–1670, https://doi.org/10.5194/hess-25-1643-2021, https://doi.org/10.5194/hess-25-1643-2021, 2021
Short summary
Short summary
This study comprehensively evaluated 11 satellite radar altimetry missions (including their official retrackers) for lake water level retrieval and developed a strategy for constructing consistent long-term water level records for inland lakes. It is a two-step bias correction and normalization procedure. First, we use Jason-2 as the initial reference to form a consistent TOPEX/Poseidon–Jason series. Then, we use this as the reference to remove the biases with other radar altimetry missions.
Lise Kilic, Catherine Prigent, Carlos Jimenez, and Craig Donlon
Ocean Sci., 17, 455–461, https://doi.org/10.5194/os-17-455-2021, https://doi.org/10.5194/os-17-455-2021, 2021
Short summary
Short summary
The Copernicus Imaging Microwave Radiometer (CIMR) is one of the high-priority satellite missions of the Copernicus program within the European Space Agency. It is designed to respond to the European Union Arctic policy. Its channels, incidence angle, precisions, and spatial resolutions have been selected to observe the Arctic Ocean with the recommendations expressed by the user communities.
In this note, we present the sensitivity analysis that has led to the choice of the CIMR channels.
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.
Samuel Favrichon, Carlos Jimenez, and Catherine Prigent
Atmos. Meas. Tech., 13, 5481–5490, https://doi.org/10.5194/amt-13-5481-2020, https://doi.org/10.5194/amt-13-5481-2020, 2020
Short summary
Short summary
Long-term monitoring of satellite-derived variables is necessary for a better understanding of the evolution of Earth parameters at global scale. However different instruments' observations used over the years need to be inter-calibrated with each other to provide meaningful information. This paper describes how a linear correction can improve the observations from the Scanning Multichannel Microwave Radiometer over continental surfaces to be more consistent with more recent radiometers.
Cited articles
Aires, F., Papa, F., and Prigent, C.: Along-term, high-resolution wetland
dataset over the Amazon basin, downscaled from a multiwavelength retrieval
using SAR data, J. Hydrometeorol., 14, 594–607, https://doi.org/10.1175/JHM-D-12-093.1, 2013.
Aloysius, N. and Saiers, J.: Simulated hydrologic response to projected
changes in precipitation and temperature in the Congo River basin, Hydrol.
Earth Syst. Sci., 21, 4115–4130, https://doi.org/10.5194/hess-21-4115-2017, 2017.
Alsdorf, D., Beighley, E., Laraque, A., Lee, H., Tshimanga, R., O'Loughlin,
F., Mahé, G., Dinga, B., Moukandi, G., and Spencer, R. G. M.: Opportunities for hydrologic research in the Congo Basin, Rev. Geophys., 54,
378–409, https://doi.org/10.1002/2016RG000517, 2016.
Andriambeloson, J. A., Paris, A., Calmant, S., and Rakotondraompiana, S.:
Re-initiating depth-discharge monitoring in small-sized ungauged watersheds by combining remote sensing and hydrological modelling: a case study in
Madagascar, Hydrolog. Sci. J., 65, 2709-2728, https://doi.org/10.1080/02626667.2020.1833013, 2020.
Becker, M., Santos, J., Calmant, S., Robinet, V., Linguet, L., and Seyler, F.: Water Level Fluctuations in the Congo Basin Derived from ENVISAT
Satellite Altimetry, Remote Sens., 6, 9340–9358, https://doi.org/10.3390/rs6109340, 2014.
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. Geoinf., 66,
196–209, https://doi.org/10.1016/j.jag.2017.11.015, 2018.
Bele, Y., Mulotwa, E., Bokoto de Semboli, B., Sonwa, D., and Tiani, A.: Afrique centrale: Les effets du changement climatique dans le Bassin du
Congo: la nécessité de soutenir les capacités adaptatives
locales, CRDI/CIFOR, Canada, 5 pp., https://idl-bnc-idrc.dspacedirect.org/bitstream/handle/10625/45639/132108.pdf (last access; 6 April 2022), 2010.
Betbeder, J., Gond, V., Frappart, F., Baghdadi, N. N., Briant, G., and
Bartholomé, E.: Mapping of Central Africa forested wetlands using remote
sensing, IEEE J. Select. Top. Appl. Earth Obs. Remote Sens., 7, 531–542,
https://doi.org/10.1109/JSTARS.2013.2269733, 2014.
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.
Bonnefond, P., Verron, J., Aublanc, J., Babu, K., Bergé-Nguyen, M., Cancet, M., Chaudhary, A., Crétaux, J.-F., Frappart, F., Haines, B., Laurain, O., Ollivier, A., Poisson, J.-C., Prandi, P., Sharma, R., Thibaut, P., and Watson, C.: The Benefits of the Ka-Band as Evidenced from the SARAL/AltiKa AltimetricMission: Quality Assessment and Unique Characteristics of AltiKa Data, Remote Sens., 10, 83, https://doi.org/10.3390/rs10010083, 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, ISSN 0767-2896, 1995
Burnett, M. W., Quetin, G. R., and Konings, A. G.: Data-driven estimates of evapotranspiration and its controls in the Congo Basin, Hydrol. Earth Syst. Sci., 24, 4189–4211, https://doi.org/10.5194/hess-24-4189-2020, 2020.
Bwangoy, J. R. B., Hansen, M. C., Roy, D. P., De Grandi, G., and Justice, C.
O.: Wetland mapping in the Congo Basin using optical and radar remotely sensed data and derived topographical indices, Remote Sens. Environ., 114,
73–86, 2010.
Carr, A. B., Trigg, M. A., Tshimanga, R. M., Borman, D. J., and Smith, M.
W.: Greater water surface variability revealed by new Congo River field data: Implications for satellite altimetry measurements of large rivers, Geophys. Res. Lett., 46, 8093–8101, https://doi.org/10.1029/2019GL083720, 2019.
Corbari, C., Huber, C., Yesou, H., Huang, Y., and Su, Z.: Multi-Satellite Data of Land Surface Temperature, Lakes Area, and Water Level for Hydrological Model Calibration and Validation in the Yangtze River Basin,
Water, 11, 2621, https://doi.org/10.3390/w11122621, 2019.
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.
Crowhurst, D., Dadson, S., Peng, J., and Washington, R.: Contrasting controls on Congo Basin evaporation at the two rainfall peaks, Clim. Dynam., 56, 1609–1624, https://doi.org/10.1007/s00382-020-05547-1, 2021.
Dargie, G. C., Lewis, S. L., Lawson, I. T., Mitchard, E. T. A., Page, S. E.,
Bocko, Y. E., and Ifo, S. A.: Age, extent and carbon storage of the central
Congo Basin peatland complex, Nature, 542, 86–90, https://doi.org/10.1038/nature21048, 2017.
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., AGU, https://doi.org/10.1002/9781119657002.ch14, 2022.
Decharme, B., Douville, H., Prigent, C., Papa, F., and Aires, F.: A new river flooding scheme for global climate applications: Off-line evaluation over South America, J. Geophys. Res.-Atmos., 113, 1–11, https://doi.org/10.1029/2007JD009376, 2008.
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 Paiva, R. C. D., Buarque, D. C., Collischonn, W., Bonnet, M., Frappart, F., Calmant, S., and Mendes, C. A. B.: Large-scale hydrologic and hydrodynamic modeling of the Amazon River basin, Water Resour. Res., 49,
1226–1243, https://doi.org/10.1002/wrcr.20067, 2013.
Fan, L., Wigneron, J.-P., Ciais, P., Chave, J., Brandt, M., Fensholt, R.,
Saatchi, S. S., Bastos, A., Al-Yaari, A., Hufkens, K., Qin, Y., Xiao, X.,
Chen, C., Myneni, R. B., Fernandez-Moran, R., Mialon, A., Rodriguez-Fernandez, N. J., Kerr, Y., Tian, F., and Penuelas, J.: Satellite-observed pantropical carbon dynamics, Nat. Plants, 5, 944–951,
https://doi.org/10.1038/s41477-019-0478-9, 2019.
Fatras, C., Parrens, M., Peña Luque, S., and Al Bitar, A.: Hydrological
Dynamics of the Congo Basin From Water Surfaces Based on L-Band Microwave,
Water Resour. Res., 57, e2020WR027259, https://doi.org/10.1029/2020wr027259, 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., Malbeteau, Y., León, 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.,
Durand, F. and Bala, S.: Preliminary assessment of SARAL/AltiKa observations
over the Ganges-Brahmaputra and Irrawaddy Rivers, Mar. Geod., 38, 568–580,
https://doi.org/10.1080/01490419.2014.990591, 2015b.
Frappart, F., Zeiger, P., Betbeder, J., Gond, V., Bellot, R., Baghdadi, N.,
Blarel, F., Darrozes, J., Bourrel, L., and Seyler, F.: Automatic Detection of
Inland Water Bodies along Altimetry Tracks for Estimating Surface Water Storage Variations in the Congo Basin, Remote Sens., 13, 3804, https://doi.org/10.3390/rs13193804, 2021a.
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 Sens., 13, 2196, https://doi.org/10.3390/rs13112196, 2021b.
Garambois, P. A., Calmant, S., Roux, H., Paris, A., Monnier, J., Finaud-Guyot, P., Samine Montazem, A., and da Silva, J. S.: Hydraulic visibility: Using satellite altimetry to parameterize a hydraulic model of an ungauged reach of a braided river, Hydrol. Process., 31, 756–767, https://doi.org/10.1002/hyp.11033, 2017.
Hastenrath, S.: Climate and circulation of the tropics, D. Reidel Publishing
Company, Holland, https://doi.org/10.1007/978-94-009-5388-8, 1985.
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.
Hess, L. L., Melack, J. M., Novo, E., Barbosa, C., and Gastil, M.: Dual-season mapping of wetland inundation and vegetation for the central
Amazon basin, Remote Sens. Environ., 87, 404–428, https://doi.org/10.1016/j.rse.2003.04.001, 2003.
Hydroweb: http://hydroweb.theia-land.fr/, last access: 6 April 2022.
Ingram, V., Tieguhong, J. C., Schure, J., Nkamgnia, E., and Tadjuidje, M.
H.: Where artisanal mines and forest meet: Socio-economic and environmental
impacts in the Congo Basin, Nat. Resour. Forum, 35, 304–320, https://doi.org/10.1111/j.1477-8947.2011.01408.x, 2011.
Inogwabini, B.-I.: The changing water cycle: Freshwater in the Congo, WIREs
Water, 7, e1410, https://doi.org/10.1002/wat2.1410, 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.
Kim, D., Lee, H., Laraque, A., Tshimanga, R. M., Yuan, T., Jung, H. C., Beighley, E., and Chang, C.-H.: Mapping spatio-temporal water level variations over the central Congo River using PALSAR ScanSAR and Envisat altimetry data, Int. J. Remote Sens., 38, 7021–7040, https://doi.org/10.1080/01431161.2017.1371867, 2017.
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, Alain, 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, Alain, 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.
Leon, J. G., Calmant, S., Seyler, F., Bonnet, M. P., Cauhopé, M., Frappart, F., Filizola, N., and Fraizy, P.: Rating curves and estimation of
average water depth at the upper Negro River based on satellite altimeter
data and modeled discharges, J. Hydrol., 328, 481–496, https://doi.org/10.1016/j.jhydrol.2005.12.006, 2006.
Mcphaden, M. J.: El Niño and La Niña: Causes and Global Consequences, in: Encyclopedia of Global Environmental Change, edited by: MacCracken, M. C. and Perry, J. S., USA, 353–370, ISBN 0-471-97796-9,
https://www.pmel.noaa.gov/gtmba/files/PDF/pubs/ElNinoLaNina.pdf (last access: 6 April 2022), 2002.
Moreira, D. M., Calmant, S., Perosanz, F., Xavier, L., Rotunno Filho, O. C.,
Seyler, F., and Monteiro, A. C.: Comparisons of observed and modeled elastic
responses to hydrological loading in the Amazon basin, Geophys. Res. Lett.,
43, 9604–9610, https://doi.org/10.1002/2016GL070265, 2016.
Munzimi, Y. A., Hansen, M. C., and Asante, K. O.: Estimating daily streamflow in the Congo Basin using satellite-derived data and a semi-distributed hydrological model, Hydrolog. Sci. J., 64, 1472–1487, https://doi.org/10.1080/02626667.2019.1647342, 2019.
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.
Nogherotto, R., Coppola, E., Giorgi, F., and Mariotti, L.: Impact of Congo
Basin deforestation on the African monsoon, Atmos. Sci. Lett., 14, 45–51,
https://doi.org/10.1002/asl2.416, 2013.
Normandin, C., Frappart, F., Diepkilé, A. T., Marieu, V., Mougin, E.,
Blarel, F., Lubac, B., Braquet, N., and Ba, A.: Evolution of the performances of radar altimetry missions from ERS-2 to Sentinel-3A over the Inner Niger Delta, Remote Sens., 10, 833, https://doi.org/10.3390/rs10060833, 2018.
O'Loughlin, F., Trigg, M. A., Schumann, G. J.-P., and Bates, P. D. : Hydraulic characterization of the middle reach of the Congo River, Water Resour. Res., 49, 5059–5070, https://doi.org/10.1002/wrcr.20398, 2013.
O'Loughlin, F., Neal, J., Schumann, G. J., Beighley, R. E., and Bates, P. D.: A LISFLOOD-FP hydraulic model of the middle reach of the Congo, J. Hydrol., 580, 124203, https://doi.org/10.1016/j.jhydrol.2019.124203, 2019.
OMM: CONGO-HYCOS, Organisation météorologique mondiale, 101 pp.,
https://library.wmo.int/doc_num.php?explnum_id=4883 (last access: 6 April 2022), 2010.
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., Bala, S. K., Pandey, R. K., Durand, F., Gopalakrishna, V. V, Rahman, A., and Rossow, W. B.: Ganga-Brahmaputra river discharge from Jason-2 radar altimetry: An update to the long-term satellite-derived estimates of continental freshwater forcing flux into the Bay of Bengal, J. Geophys. Res., 117, C11021, https://doi.org/10.1029/2012JC008158, 2012.
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.: Satellite-derived 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.
Paris, Adrien, De Paiva, R. D., Da Silva, J. S., Moreira, D. M., Calmant, S., Garambois, P.-A., Collischonn, W., Bonnet, M., and Seyler, F.: Stage-discharge rating curves based on satellite altimetry and modeled discharge in the Amazon basin, Water Resour. Res., 52, 3787–3814,
https://doi.org/10.1002/2014WR016618, 2016.
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.
Park, E.: Characterizing channel–floodplain connectivity using satellite
altimetry: Mechanism, hydrogeomorphic control, and sediment budget, Remote
Sens. Environ., 243, 111783, https://doi.org/10.1016/j.rse.2020.111783, 2020.
Parrens, M., Al Bitar, A., Frappart, F., Papa, F., Wigneron, J.-P., and Kerr, Y.: Mapping dynamic water fraction under the tropical rain forests of the Amazonian basin from L-band brightness temperature, Water, 9, 350, https://doi.org/10.3390/w9050350, 2017.
Pekel, J.-F., A. Cottam, N. Gorelick, and Belward, A. S.: High-resolution mapping of global surface water and its long-term changes, Nature, 540,
418–422, https://doi.org/10.1038/nature20584, 2016.
Plisnier, P. D., Nshombo, M., Mgana, H., and Ntakimazi, G.: Monitoring climate change and anthropogenic pressure at Lake Tanganyika, J. Great Lakes
Res., 44, 1194–1208, https://doi.org/10.1016/j.jglr.2018.05.019, 2018.
Prigent, Catherine, 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, 1–21, https://doi.org/10.1029/2019JD030711, 2020.
Pujol, L., Garambois, P. A., Finaud-Guyot, P., Monnier, J., Larnier, K.,
Mosé, R., Biancamaria, S., Yesou, H., Moreira, D., Paris, A., and Calmant, S.: Estimation of multiple inflows and effective channel by
assimilation of multi-satellite hydraulic signatures: The ungauged anabranching Negro river, J. Hydrol., 591, 125331, https://doi.org/10.1016/j.jhydrol.2020.125331, 2020.
Raney, R. K.: The delay/Doppler radar altimeter, IEEE T. Geosci. Remote, 36, 1578–1588, https://doi.org/10.1109/36.718861, 1998.
Rosenqvist, Å. and Birkett, C. M.: Evaluation of JERS-1 SAR mosaics for
hydrological applications in the Congo River basin, Int. J. Remote Sens., 23, 1283–1302, https://doi.org/10.1080/01431160110092902, 2002.
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.
Seyler, F., Calmant, S., Silva, J., Filizola, N., Roux, E., Cochonneau, G.,
Vauchel, P., and Bonnet, M.: Monitoring water level in large trans-boundary
ungauged basins with altimetry: the example of ENVISAT over the Amazon basin, in: 6th SPIE Asia Pacific Remote Sensing Conference, November 2008, Nouméa, France, https://doi.org/10.1117/12.813258, 2008.
Stammer, D. and Cazenave, A.: Satellite Altimetry over Oceans and Land
Surfaces, Taylor and Francis Group, Boca Raton, London, New York, 645 pp.,
2017.
Sun, W., Ishidaira, H., and Bastola, S.: Calibration of hydrological models in ungauged basins based on satellite radar altimetry observations of river
water level, Hydrol. Process., 26, 3524–3537, https://doi.org/10.1002/hyp.8429, 2012.
Tshimanga, R. M.: Two decades of hydrologic modeling and predictions in the
Congo River Basin: Progress and prospect for future investigations, Under
press, in: Congo Basin Hydrology, Climate, and Biogeochemistry: A Foundation
for the Future, edited by: Alsdorf, D., Tshimanga, R. M., and Moukandi, G. N., Wiley-AGU, ISBN 9781119656975, 2021.
Tshimanga, R. M. and Hughes, D. A.: Climate change and impacts on the hydrology of the Congo Basin: the case of the northern sub-basins of the
Oubangui and Sangha Rivers, Phys. Chem. Earth, 50–52, 72–83, https://doi.org/10.1016/j.pce.2012.08.002, 2012.
Tshimanga, R. M. and Hughes, D. A.: Basin-scale performance of a semi-distributed rainfall-runoff model for hydrological predictions and
water resources assessment of large rivers: the Congo River, Water Resour.
Res., 50, 1174–1188, https://doi.org/10.1002/2013WR014310, 2014.
Tshimanga, R. M., Hughes, D. A., and Kapangaziwiri, E.: Initial calibration of a semi-distributed rainfall runoff model for the Congo River basin, Phys.
Chem. Earth, 36, 761–774, https://doi.org/10.1016/j.pce.2011.07.045, 2011.
Ummenhofer, C. C., England, M. H., Mcintosh, P. C., Meyers, G. A., Pook, M.
J., Risbey, J. S., and Gupta, A. S., and Taschetto, A. S.: What causes
southeast Australia's worst droughts?, Geophys. Res. Lett., 36, L04706, 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.
Zakharova, E., Nielsen, K., Kamenev, G., and Kouraev, A.: River discharge
estimation from radar altimetry: Assessment of satellite performance, river
scales and methods, J. Hydrol., 583, 124561, https://doi.org/10.1016/j.jhydrol.2020.124561, 2020.
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.
This study presents a better characterization of surface hydrology variability in the Congo...