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
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In this study, we present a dataset for the Dischma catchment in eastern Switzerland, which represents a typical high-alpine watershed in the European Alps. Accurate monitoring and reliable forecasting of snow and water resources in such basins are crucial for a wide range of applications. Our dataset is valuable for improving physics-based snow, land surface, and hydrological models, with potential applications in similar high-alpine catchments.
Nikunj K. Mangukiya, Kanneganti Bhargav Kumar, Pankaj Dey, Shailza Sharma, Vijaykumar Bejagam, Pradeep P. Mujumdar, and Ashutosh Sharma
Earth Syst. Sci. Data, 17, 461–491, https://doi.org/10.5194/essd-17-461-2025, https://doi.org/10.5194/essd-17-461-2025, 2025
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We introduce CAMELS-IND (Catchment Attributes and MEteorology for Large-sample Studies – India), which provides daily hydrometeorological time series and static catchment attributes representing the location, topography, climate, hydrological signatures, land use, land cover, soil, geology, and anthropogenic influences for 472 catchments in Peninsular India to foster large-sample hydrological studies in India and promote the inclusion of Indian catchments in global hydrological research.
Bennett J. McAfee, Aanish Pradhan, Abhilash Neog, Sepideh Fatemi, Robert T. Hensley, Mary E. Lofton, Anuj Karpatne, Cayelan C. Carey, and Paul C. Hanson
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-27, https://doi.org/10.5194/essd-2025-27, 2025
Revised manuscript accepted for ESSD
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LakeBeD-US is a dataset of lake water quality data collected by multiple long-term monitoring programs around the United States. This dataset is designed to foster collaboration between lake scientists and computer scientists to improve predictions of water quality. By offering a way for computer models to be tested against real-world lake data, LakeBeD-US offers opportunities for both sciences to grow and to give new insights into the causes of water quality changes.
Aloïs Tilloy, Dominik Paprotny, Stefania Grimaldi, Goncalo Gomes, Alessandra Bianchi, Stefan Lange, Hylke Beck, Cinzia Mazzetti, and Luc Feyen
Earth Syst. Sci. Data, 17, 293–316, https://doi.org/10.5194/essd-17-293-2025, https://doi.org/10.5194/essd-17-293-2025, 2025
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This article presents a reanalysis of Europe's river streamflow for the period 1951–2020. Streamflow is estimated through a state-of-the-art hydrological simulation framework benefitting from detailed information about the landscape, climate, and human activities. The resulting Hydrological European ReAnalysis (HERA) can be a valuable tool for studying hydrological dynamics, including the impacts of climate change and human activities on European water resources and flood and drought risks.
Daniel Kovacek and Steven Weijs
Earth Syst. Sci. Data, 17, 259–275, https://doi.org/10.5194/essd-17-259-2025, https://doi.org/10.5194/essd-17-259-2025, 2025
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We made a dataset for British Columbia describing the terrain, soil, land cover, and climate of over 1 million watersheds. The attributes are often used in hydrology because they are related to the water cycle. The data are meant to be used for water resources problems that can benefit from lots of watersheds and their attributes. The data and instructions needed to build the dataset from scratch are freely available. The permanent home for the data is https://doi.org/10.5683/SP3/JNKZVT.
Andrea Galletti, Soroush Zarghami Dastjerdi, and Bruno Majone
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-521, https://doi.org/10.5194/essd-2024-521, 2025
Revised manuscript accepted for ESSD
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We propose IAR-HP, a detailed inventory of large hydropower systems in Italy's Alpine Region, aimed at improving hydrological modeling for climate impact studies by providing the most relevant information with a consistent level of detail. It includes structural, geographical, and operational data for over 300 hydropower plants and their related reservoirs and water intakes. Validated through modeling, IAR-HP accurately reproduces observed hydropower, capturing 96.2 % of actual production.
Bennet Juhls, Anne Morgenstern, Jens Hölemann, Antje Eulenburg, Birgit Heim, Frederieke Miesner, Hendrik Grotheer, Gesine Mollenhauer, Hanno Meyer, Ephraim Erkens, Felica Yara Gehde, Sofia Antonova, Sergey Chalov, Maria Tereshina, Oxana Erina, Evgeniya Fingert, Ekaterina Abramova, Tina Sanders, Liudmila Lebedeva, Nikolai Torgovkin, Georgii Maksimov, Vasily Povazhnyi, Rafael Gonçalves-Araujo, Urban Wünsch, Antonina Chetverova, Sophie Opfergelt, and Pier Paul Overduin
Earth Syst. Sci. Data, 17, 1–28, https://doi.org/10.5194/essd-17-1-2025, https://doi.org/10.5194/essd-17-1-2025, 2025
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The Siberian Arctic is warming fast: permafrost is thawing, river chemistry is changing, and coastal ecosystems are affected. We aimed to understand changes in the Lena River, a major Arctic river flowing to the Arctic Ocean, by collecting 4.5 years of detailed water data, including temperature and carbon and nutrient contents. This dataset records current conditions and helps us to detect future changes. Explore it at https://doi.org/10.1594/PANGAEA.913197 and https://lena-monitoring.awi.de/.
Ralf Loritz, Alexander Dolich, Eduardo Acuña Espinoza, Pia Ebeling, Björn Guse, Jonas Götte, Sibylle K. Hassler, Corina Hauffe, Ingo Heidbüchel, Jens Kiesel, Mirko Mälicke, Hannes Müller-Thomy, Michael Stölzle, and Larisa Tarasova
Earth Syst. Sci. Data, 16, 5625–5642, https://doi.org/10.5194/essd-16-5625-2024, https://doi.org/10.5194/essd-16-5625-2024, 2024
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The CAMELS-DE dataset features data from 1582 streamflow gauges across Germany, with records spanning from 1951 to 2020. This comprehensive dataset, which includes time series of up to 70 years (median 46 years), enables advanced research on water flow and environmental trends and supports the development of hydrological models.
Einara Zahn and Elie Bou-Zeid
Earth Syst. Sci. Data, 16, 5603–5624, https://doi.org/10.5194/essd-16-5603-2024, https://doi.org/10.5194/essd-16-5603-2024, 2024
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Quantifying water and CO2 exchanges through transpiration, evaporation, net photosynthesis, and soil respiration is essential for understanding how ecosystems function. We implemented five methods to estimate these fluxes over a 5-year period across 47 sites. This is the first dataset representing such large spatial and temporal coverage of soil and plant exchanges, and it has many potential applications, such as examining the response of ecosystems to weather extremes and climate change.
Lauranne Alaerts, Jonathan Lambrechts, Ny Riana Randresihaja, Luc Vandenbulcke, Olivier Gourgue, Emmanuel Hanert, and Marilaure Grégoire
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-529, https://doi.org/10.5194/essd-2024-529, 2024
Revised manuscript accepted for ESSD
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We created the first comprehensive, high-resolution, and easily-accessible bathymetry dataset for the three main branches of the Danube Delta. By combining four data sources, we obtained a detailed representation of the riverbed, with resolutions ranging from 2 to 100 m. This dataset will support future studies on water and nutrient exchanges between the Danube and the Black Sea, and provide insights into the Delta’s buffer role within the understudied Danube-Black Sea continuum.
Sanchit Minocha and Faisal Hossain
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-470, https://doi.org/10.5194/essd-2024-470, 2024
Revised manuscript accepted for ESSD
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Trustworthy and independently verifiable information on declining storage capacity or sedimentation rates around the world is sparse and suffers from inconsistent metadata and curation to allow global-scale archiving and analyses. Global Reservoir Inventory of Lost Storage by Sedimentation (GRILSS) dataset addresses this challenge by providing organized, well-curated and open-source data on sedimentation rates and capacity loss for 1,015 reservoirs in 75 major river basins across 54 countries.
Juliette Godet, Pierre Nicolle, Nabil Hocini, Eric Gaume, Philippe Davy, Frederic Pons, Pierre Javelle, Pierre-André Garambois, Dimitri Lague, and Olivier Payrastre
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-472, https://doi.org/10.5194/essd-2024-472, 2024
Revised manuscript accepted for ESSD
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This paper describes a dataset that includes input, output, and validation data for the simulation of flash flood hazards and three specific flash flood events in the French Mediterranean region. This dataset is particularly valuable as flood mapping methods often lack sufficient benchmark data. Additionally, we demonstrate how the hydraulic method we used, named Floodos, produces highly satisfactory results.
Ling Zhang, Yanhua Xie, Xiufang Zhu, Qimin Ma, and Luca Brocca
Earth Syst. Sci. Data, 16, 5207–5226, https://doi.org/10.5194/essd-16-5207-2024, https://doi.org/10.5194/essd-16-5207-2024, 2024
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This study presented new annual maps of irrigated cropland in China from 2000 to 2020 (CIrrMap250). These maps were developed by integrating remote sensing data, irrigation statistics and surveys, and an irrigation suitability map. CIrrMap250 achieved high accuracy and outperformed currently available products. The new irrigation maps revealed a clear expansion of China’s irrigation area, with the majority (61%) occurring in the water-unsustainable regions facing severe to extreme water stress.
Dominik Paprotny, Paweł Terefenko, and Jakub Śledziowski
Earth Syst. Sci. Data, 16, 5145–5170, https://doi.org/10.5194/essd-16-5145-2024, https://doi.org/10.5194/essd-16-5145-2024, 2024
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Knowledge about past natural disasters can help adaptation to their future occurrences. Here, we present a dataset of 2521 riverine, pluvial, coastal, and compound floods that have occurred in 42 European countries between 1870 and 2020. The dataset contains available information on the inundated area, fatalities, persons affected, or economic loss and was obtained by extensive data collection from more than 800 sources ranging from news reports through government databases to scientific papers.
Paulina Bartkowiak, Bartolomeo Ventura, Alexander Jacob, and Mariapina Castelli
Earth Syst. Sci. Data, 16, 4709–4734, https://doi.org/10.5194/essd-16-4709-2024, https://doi.org/10.5194/essd-16-4709-2024, 2024
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This paper presents the Two-Source Energy Balance evapotranspiration (ET) product driven by Copernicus Sentinel-2 and Sentinel-3 imagery together with ERA5 climate reanalysis data. Daily ET maps are available at 100 m spatial resolution for the period 2017–2021 across four Mediterranean basins: Ebro (Spain), Hérault (France), Medjerda (Tunisia), and Po (Italy). The product is highly beneficial for supporting vegetation monitoring and sustainable water management at the river basin scale.
Fanny J. Sarrazin, Sabine Attinger, and Rohini Kumar
Earth Syst. Sci. Data, 16, 4673–4708, https://doi.org/10.5194/essd-16-4673-2024, https://doi.org/10.5194/essd-16-4673-2024, 2024
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Nitrogen (N) and phosphorus (P) contamination of water bodies is a long-term issue due to the long history of N and P inputs to the environment and their persistence. Here, we introduce a long-term and high-resolution dataset of N and P inputs from wastewater (point sources) for Germany, combining data from different sources and conceptual understanding. We also account for uncertainties in modelling choices, thus facilitating robust long-term and large-scale water quality studies.
Shanti Shwarup Mahto, Simone Fatichi, and Stefano Galelli
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-441, https://doi.org/10.5194/essd-2024-441, 2024
Revised manuscript accepted for ESSD
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The MSEA-Res database offers an open-access dataset tracking absolute water storage for 185 large reservoirs across Mainland Southeast Asia from 1985–2023. It provides valuable insights into how reservoir storage has grown by 130 % between 2008 and 2017, driven by dams in key river basins. Our data also reveal how droughts, like the 2019–2020 event, significantly impacted water reservoirs. This resource can aid water management, drought planning, and research globally.
Haiguang Cheng, Kaiheng Hu, Shuang Liu, Xiaopeng Zhang, Hao Li, Qiyuan Zhang, Lan Ning, Manish Raj Gouli, Pu Li, Anna Yang, and Peng Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-382, https://doi.org/10.5194/essd-2024-382, 2024
Revised manuscript accepted for ESSD
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After reviewing 2,519 literature and media reports, we compiled the first comprehensive global dataset of 555 debris flow barrier dams (DFBDs) from 1800 to 2023. Our dataset meticulously documents 36 attributes of DFBDs, and we have utilized Google Earth for validation. Additionally, we discussed the applicability of landslide dam stability and peak discharge models to DFBDs. This dataset offers a rich foundation of data for future studies on DFBDs.
Karl Nicolaus van Zweel, Laurent Gourdol, Jean François Iffly, Loïc Léonard, François Barnich, Laurent Pfister, Erwin Zehe, and Christophe Hissler
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-259, https://doi.org/10.5194/essd-2024-259, 2024
Revised manuscript accepted for ESSD
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Our study monitored groundwater in a Luxembourg forest over a year to understand water and chemical changes. We found seasonal variations in water chemistry, influenced by rainfall and soil interactions. This data helps predict environmental responses and manage water resources better. By measuring key parameters like pH and dissolved oxygen, our research provides valuable insights into groundwater behavior and serves as a resource for future environmental studies.
Rohit Mukherjee, Frederick Policelli, Ruixue Wang, Elise Arellano-Thompson, Beth Tellman, Prashanti Sharma, Zhijie Zhang, and Jonathan Giezendanner
Earth Syst. Sci. Data, 16, 4311–4323, https://doi.org/10.5194/essd-16-4311-2024, https://doi.org/10.5194/essd-16-4311-2024, 2024
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Global water resource monitoring is crucial due to climate change and population growth. This study presents a hand-labeled dataset of 100 PlanetScope images for surface water detection, spanning diverse biomes. We use this dataset to evaluate two state-of-the-art mapping methods. Results highlight performance variations across biomes, emphasizing the need for diverse, independent validation datasets to enhance the accuracy and reliability of satellite-based surface water monitoring techniques.
Lei Huang, Yong Luo, Jing M. Chen, Qiuhong Tang, Tammo Steenhuis, Wei Cheng, and Wen Shi
Earth Syst. Sci. Data, 16, 3993–4019, https://doi.org/10.5194/essd-16-3993-2024, https://doi.org/10.5194/essd-16-3993-2024, 2024
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Timely global terrestrial evapotranspiration (ET) data are crucial for water resource management and drought forecasting. This study introduces the VISEA algorithm, which integrates satellite data and shortwave radiation to provide daily 0.05° gridded near-real-time ET estimates. By employing a vegetation index–temperature method, this algorithm can estimate ET without requiring additional data. Evaluation results demonstrate VISEA's comparable accuracy with accelerated data availability.
Sibylle Kathrin Hassler, Rafael Bohn Reckziegel, Ben du Toit, Svenja Hoffmeister, Florian Kestel, Anton Kunneke, Rebekka Maier, and Jonathan Paul Sheppard
Earth Syst. Sci. Data, 16, 3935–3948, https://doi.org/10.5194/essd-16-3935-2024, https://doi.org/10.5194/essd-16-3935-2024, 2024
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Agroforestry systems (AFSs) combine trees and crops within the same land unit, providing a sustainable land use option which protects natural resources and biodiversity. Introducing trees into agricultural systems can positively affect water resources, soil characteristics, biomass and microclimate. We studied an AFS in South Africa in a multidisciplinary approach to assess the different influences and present the resulting dataset consisting of water, soil, tree and meteorological variables.
Keirnan J. A. Fowler, Ziqi Zhang, and Xue Hou
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-263, https://doi.org/10.5194/essd-2024-263, 2024
Revised manuscript accepted for ESSD
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This paper presents Version 2 of the Australian edition of the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS v2 comprises data for an increased number (561) of catchments, each with with long-term monitoring, combining hydrometeorological time series with attributes related to geology, soil, topography, land cover, anthropogenic influence and hydroclimatology. It is freely downloadable from https://zenodo.org/doi/10.5281/zenodo.12575680.
Kaihao Zheng, Peirong Lin, and Ziyun Yin
Earth Syst. Sci. Data, 16, 3873–3891, https://doi.org/10.5194/essd-16-3873-2024, https://doi.org/10.5194/essd-16-3873-2024, 2024
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We develop a globally applicable thresholding scheme for DEM-based floodplain delineation to improve the representation of spatial heterogeneity. It involves a stepwise approach to estimate the basin-level floodplain hydraulic geometry parameters that best respect the scaling law while approximating the global hydrodynamic flood maps. A ~90 m resolution global floodplain map, the Spatial Heterogeneity Improved Floodplain by Terrain analysis (SHIFT), is delineated with demonstrated superiority.
Yuzhong Yang, Qingbai Wu, Xiaoyan Guo, Lu Zhou, Helin Yao, Dandan Zhang, Zhongqiong Zhang, Ji Chen, and Guojun Liu
Earth Syst. Sci. Data, 16, 3755–3770, https://doi.org/10.5194/essd-16-3755-2024, https://doi.org/10.5194/essd-16-3755-2024, 2024
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We present the temporal data of stable isotopes in different waterbodies in the Beiluhe Basin in the hinterland of the Qinghai–Tibet Plateau (QTP) produced between 2017 and 2022. In this article, the first detailed stable isotope data of 359 ground ice samples are presented. This first data set provides a new basis for understanding the hydrological effects of permafrost degradation on the QTP.
Pragnaditya Malakar, Aatish Anshuman, Mukesh Kumar, Georgios Boumis, T. Prabhakar Clement, Arik Tashie, Hitesh Thakur, Nagaraj Bhat, and Lokendra Rathore
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-324, https://doi.org/10.5194/essd-2024-324, 2024
Revised manuscript accepted for ESSD
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Groundwater dynamics depend on groundwater recharge, but daily benchmark data of recharge is scarce. Here we present a daily groundwater recharge per unit specified yield (RpSy) data at 485 US groundwater monitoring wells. RpSy can be used to validate temporal consistency of recharge products from land surface and hydrologic models and facilitate assessment of recharge-driver functional relationships in them.
Jun Liu, Julian Koch, Simon Stisen, Lars Troldborg, Anker Lajer Højberg, Hans Thodsen, Mark F. T. Hansen, and Raphael J. M. Schneider
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-292, https://doi.org/10.5194/essd-2024-292, 2024
Revised manuscript accepted for ESSD
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We developed a CAMELS-style dataset in Denmark, which contains hydrometeorological time series and landscape attributes for 3,330 catchments. Many of the catchments in CAMELS-DK are small and located at low elevations. The dataset provides information on groundwater characteristics and dynamics, as well as quantities related to human impact on the hydrological system in Denmark. The dataset is especially relevant for developing data-driven and hybrid physically-informed modeling frameworks.
Bernhard Lehner, Mira Anand, Etienne Fluet-Chouinard, Florence Tan, Filipe Aires, George H. Allen, Pilippe Bousquet, Josep G. Canadell, Nick Davidson, C. Max Finlayson, Thomas Gumbricht, Lammert Hilarides, Gustaf Hugelius, Robert B. Jackson, Maartje C. Korver, Peter B. McIntyre, Szabolcs Nagy, David Olefeldt, Tamlin M. Pavelsky, Jean-Francois Pekel, Benjamin Poulter, Catherine Prigent, Jida Wang, Thomas A. Worthington, Dai Yamazaki, and Michele Thieme
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-204, https://doi.org/10.5194/essd-2024-204, 2024
Revised manuscript accepted for ESSD
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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 million km2, equivalent to 13.4 % of total global land area.
Hordur Bragi Helgason and Bart Nijssen
Earth Syst. Sci. Data, 16, 2741–2771, https://doi.org/10.5194/essd-16-2741-2024, https://doi.org/10.5194/essd-16-2741-2024, 2024
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LamaH-Ice is a large-sample hydrology (LSH) dataset for Iceland. The dataset includes daily and hourly hydro-meteorological time series, including observed streamflow and basin characteristics, for 107 basins. LamaH-Ice offers most variables that are included in existing LSH datasets and additional information relevant to cold-region hydrology such as annual time series of glacier extent and mass balance. A large majority of the basins in LamaH-Ice are unaffected by human activities.
Chengcheng Hou, Yan Li, Shan Sang, Xu Zhao, Yanxu Liu, Yinglu Liu, and Fang Zhao
Earth Syst. Sci. Data, 16, 2449–2464, https://doi.org/10.5194/essd-16-2449-2024, https://doi.org/10.5194/essd-16-2449-2024, 2024
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To fill the gap in the gridded industrial water withdrawal (IWW) data in China, we developed the China Industrial Water Withdrawal (CIWW) dataset, which provides monthly IWWs from 1965 to 2020 at a spatial resolution of 0.1°/0.25° and auxiliary data including subsectoral IWW and industrial output value in 2008. This dataset can help understand the human water use dynamics and support studies in hydrology, geography, sustainability sciences, and water resource management and allocation in China.
Nehar Mandal, Prabal Das, and Kironmala Chanda
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-109, https://doi.org/10.5194/essd-2024-109, 2024
Revised manuscript accepted for ESSD
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Optimal features among hydroclimatic variables and land surface model (LSM) outputs are selected using a novel Bayesian network (BN) approach for simulating Terrestrial Water Storage Anomalies (TWSA). TWSA is simulated using ML models (CNN, SVR, ETR, and Stacking Ensemble Regression), and gridwise leader models are identified globally. TWSA is reconstructed (BNML_TWSA) with the selected leader models from January 1960 to December 2022 to generate a continuous global gridded dataset.
Pierre-Antoine Versini, Leydy Alejandra Castellanos-Diaz, David Ramier, and Ioulia Tchiguirinskaia
Earth Syst. Sci. Data, 16, 2351–2366, https://doi.org/10.5194/essd-16-2351-2024, https://doi.org/10.5194/essd-16-2351-2024, 2024
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Nature-based solutions (NBSs), such as green roofs, have appeared as relevant solutions to mitigate urban heat islands. The evapotranspiration (ET) process allows NBSs to cool the air. To improve our knowledge about ET assessment, this paper presents some experimental measurement campaigns carried out during three consecutive summers. Data are available for three different (large, small, and point-based) spatial scales.
Ralph Bathelemy, Pierre Brigode, Vazken Andréassian, Charles Perrin, Vincent Moron, Cédric Gaucherel, Emmanuel Tric, and Dominique Boisson
Earth Syst. Sci. Data, 16, 2073–2098, https://doi.org/10.5194/essd-16-2073-2024, https://doi.org/10.5194/essd-16-2073-2024, 2024
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The aim of this work is to provide the first hydroclimatic database for Haiti, a Caribbean country particularly vulnerable to meteorological and hydrological hazards. The resulting database, named Simbi, provides hydroclimatic time series for around 150 stations and 24 catchment areas.
Changming Li, Ziwei Liu, Wencong Yang, Zhuoyi Tu, Juntai Han, Sien Li, and Hanbo Yang
Earth Syst. Sci. Data, 16, 1811–1846, https://doi.org/10.5194/essd-16-1811-2024, https://doi.org/10.5194/essd-16-1811-2024, 2024
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Using a collocation-based approach, we developed a reliable global land evapotranspiration product (CAMELE) by merging multi-source datasets. The CAMELE product outperformed individual input datasets and showed satisfactory performance compared to reference data. It also demonstrated superiority for different plant functional types. Our study provides a promising solution for data fusion. The CAMELE dataset allows for detailed research and a better understanding of land–atmosphere interactions.
Yuhan Guo, Hongxing Zheng, Yuting Yang, Yanfang Sang, and Congcong Wen
Earth Syst. Sci. Data, 16, 1651–1665, https://doi.org/10.5194/essd-16-1651-2024, https://doi.org/10.5194/essd-16-1651-2024, 2024
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We have provided an inaugural version of the hydrogeomorphic dataset for catchments over the Tibetan Plateau. We first provide the width-function-based instantaneous unit hydrograph (WFIUH) for each HydroBASINS catchment, which can be used to investigate the spatial heterogeneity of hydrological behavior across the Tibetan Plateau. It is expected to facilitate hydrological modeling across the Tibetan Plateau.
Chang Liao, Darren Engwirda, Matthew Cooper, Mingke Li, and Yilin Fang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-398, https://doi.org/10.5194/essd-2023-398, 2024
Revised manuscript accepted for ESSD
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Discrete Global Grid systems, or DGGs, are digital frameworks that help us organize information about our planet. Although scientists have used DGGs in areas like weather and nature, using them in the water cycle has been challenging because some core datasets are missing. We created a way to generate these datasets. We then developed the datasets in the Amazon Basin, which plays an important role in our planet's climate. These datasets may help us improve our water cycle models.
Lingbo Li, Hong-Yi Li, Guta Abeshu, Jinyun Tang, L. Ruby Leung, Chang Liao, Zeli Tan, Hanqin Tian, Peter Thornton, and Xiaojuan Yang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-43, https://doi.org/10.5194/essd-2024-43, 2024
Revised manuscript accepted for ESSD
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We have developed a new map that reveals how organic carbon from soil leaches into headwater streams over the contiguous United States. We use advanced artificial intelligence techniques and a massive amount of data, including observations at over 2,500 gauges and a wealth of climate and environmental information. The map is a critical step in understanding and predicting how carbon moves through our environment, hence a useful tool for tackling climate challenges.
Ziyun Yin, Peirong Lin, Ryan Riggs, George H. Allen, Xiangyong Lei, Ziyan Zheng, and Siyu Cai
Earth Syst. Sci. Data, 16, 1559–1587, https://doi.org/10.5194/essd-16-1559-2024, https://doi.org/10.5194/essd-16-1559-2024, 2024
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Large-sample hydrology (LSH) datasets have been the backbone of hydrological model parameter estimation and data-driven machine learning models for hydrological processes. This study complements existing LSH studies by creating a dataset with improved sample coverage, uncertainty estimates, and dynamic descriptions of human activities, which are all crucial to hydrological understanding and modeling.
Pierluigi Claps, Giulia Evangelista, Daniele Ganora, Paola Mazzoglio, and Irene Monforte
Earth Syst. Sci. Data, 16, 1503–1522, https://doi.org/10.5194/essd-16-1503-2024, https://doi.org/10.5194/essd-16-1503-2024, 2024
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FOCA (Italian FlOod and Catchment Atlas) is the first systematic collection of data on Italian river catchments. It comprises geomorphological, soil, land cover, NDVI, climatological and extreme rainfall catchment attributes. FOCA also contains 631 peak and daily discharge time series covering the 1911–2016 period. Using this first nationwide data collection, a wide range of applications, in particular flood studies, can be undertaken within the Italian territory.
Wei Jing Ang, Edward Park, Yadu Pokhrel, Dung Duc Tran, and Ho Huu Loc
Earth Syst. Sci. Data, 16, 1209–1228, https://doi.org/10.5194/essd-16-1209-2024, https://doi.org/10.5194/essd-16-1209-2024, 2024
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Dams have burgeoned in the Mekong, but information on dams is scattered and inconsistent. Up-to-date evaluation of dams is unavailable, and basin-wide hydropower potential has yet to be systematically assessed. We present a comprehensive database of 1055 dams, a spatiotemporal analysis of the dams, and a total hydropower potential of 1 334 683 MW. Considering projected dam development and hydropower potential, the vulnerability and the need for better dam management may be highest in Laos.
Chuanqi He, Ci-Jian Yang, Jens M. Turowski, Richard F. Ott, Jean Braun, Hui Tang, Shadi Ghantous, Xiaoping Yuan, and Gaia Stucky de Quay
Earth Syst. Sci. Data, 16, 1151–1166, https://doi.org/10.5194/essd-16-1151-2024, https://doi.org/10.5194/essd-16-1151-2024, 2024
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The shape of drainage basins and rivers holds significant implications for landscape evolution processes and dynamics. We used a global 90 m resolution topography to obtain ~0.7 million drainage basins with sizes over 50 km2. Our dataset contains the spatial distribution of drainage systems and their morphological parameters, supporting fields such as geomorphology, climatology, biology, ecology, hydrology, and natural hazards.
Jingyu Lin, Peng Wang, Jinzhu Wang, Youping Zhou, Xudong Zhou, Pan Yang, Hao Zhang, Yanpeng Cai, and Zhifeng Yang
Earth Syst. Sci. Data, 16, 1137–1149, https://doi.org/10.5194/essd-16-1137-2024, https://doi.org/10.5194/essd-16-1137-2024, 2024
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Our paper provides a repository comprising over 330 000 observations encompassing daily, weekly, and monthly records of surface water quality spanning the period 1980–2022. It included 18 distinct indicators, meticulously gathered at 2384 monitoring sites, ranging from inland locations to coastal and oceanic areas. This dataset will be very useful for researchers and decision-makers in the fields of hydrology, ecological studies, climate change, policy development, and oceanography.
Ana M. Ricardo, Rui M. L. Ferreira, Alberto Rodrigues da Silva, Jacinto Estima, Jorge Marques, Ivo Gamito, and Alexandre Serra
Earth Syst. Sci. Data, 16, 375–385, https://doi.org/10.5194/essd-16-375-2024, https://doi.org/10.5194/essd-16-375-2024, 2024
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Floods are among the most common natural disasters responsible for severe damages and human losses. Agueda.2016Flood, a synthesis of locally sensed data and numerically produced data, allows complete characterization of the flood event that occurred in February 2016 in the Portuguese Águeda River. The dataset was managed through the RiverCure Portal, a collaborative web platform connected to a validated shallow-water model.
Jiawei Hou, Albert I. J. M. Van Dijk, Luigi J. Renzullo, and Pablo R. Larraondo
Earth Syst. Sci. Data, 16, 201–218, https://doi.org/10.5194/essd-16-201-2024, https://doi.org/10.5194/essd-16-201-2024, 2024
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The GloLakes dataset provides historical and near-real-time time series of relative (i.e. storage change) and absolute (i.e. total stored volume) storage for more than 27 000 lakes worldwide using multiple sources of satellite data, including laser and radar altimetry and optical remote sensing. These data can help us understand the influence of climate variability and anthropogenic activities on water availability and system ecology over the last 4 decades.
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
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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.
Marvin Höge, Martina Kauzlaric, Rosi Siber, Ursula Schönenberger, Pascal Horton, Jan Schwanbeck, Marius Günter Floriancic, Daniel Viviroli, Sibylle Wilhelm, Anna E. Sikorska-Senoner, Nans Addor, Manuela Brunner, Sandra Pool, Massimiliano Zappa, and Fabrizio Fenicia
Earth Syst. Sci. Data, 15, 5755–5784, https://doi.org/10.5194/essd-15-5755-2023, https://doi.org/10.5194/essd-15-5755-2023, 2023
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CAMELS-CH is an open large-sample hydro-meteorological data set that covers 331 catchments in hydrologic Switzerland from 1 January 1981 to 31 December 2020. It comprises (a) daily data of river discharge and water level as well as meteorologic variables like precipitation and temperature; (b) yearly glacier and land cover data; (c) static attributes of, e.g, topography or human impact; and (d) catchment delineations. CAMELS-CH enables water and climate research and modeling at catchment level.
Peter Burek and Mikhail Smilovic
Earth Syst. Sci. Data, 15, 5617–5629, https://doi.org/10.5194/essd-15-5617-2023, https://doi.org/10.5194/essd-15-5617-2023, 2023
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We address an annoying problem every grid-based hydrological model must solve to compare simulated and observed river discharge. First, station locations do not fit the high-resolution river network. We update the database with stations based on a new high-resolution network. Second, station locations do not work with a coarser grid-based network. We use a new basin shape similarity concept for station locations on a coarser grid, reducing the error of assigning stations to the wrong basin.
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,...
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