Articles | Volume 24, issue 5
https://doi.org/10.5194/hess-24-2207-2020
© Author(s) 2020. 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-24-2207-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 May 2020
Research article |
| 06 May 2020
| 06 May 2020
Assimilation of wide-swath altimetry water elevation anomalies to correct large-scale river routing model parameters
Charlotte Marie Emery
CORRESPONDING AUTHOR
LEGOS, 16 Avenue Edouard Belin, 31400 Toulouse, France
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
now at: CS-Group, Space Business Unit, 31500 Toulouse, France
Sylvain Biancamaria
LEGOS, 16 Avenue Edouard Belin, 31400 Toulouse, France
Aaron Boone
CNRM-GAME, Meteo-France, 42 Avenue Gaspard Coriolis, 31000 Toulouse, France
Sophie Ricci
CECI, Université de Toulouse, CERFACS, CNRS, 42 Avenue Gaspard Coriolis, 31057 Toulouse CEDEX 1, France
Mélanie C. Rochoux
CECI, Université de Toulouse, CERFACS, CNRS, 42 Avenue Gaspard Coriolis, 31057 Toulouse CEDEX 1, France
Vanessa Pedinotti
Magellium, 1 Rue Ariane, 31520 Ramonville-Saint-Agne, France
Cédric H. David
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Related authors
Charlotte Marie Emery, Adrien Paris, Sylvain Biancamaria, Aaron Boone, Stéphane Calmant, Pierre-André Garambois, and Joecila Santos da Silva
Hydrol. Earth Syst. Sci., 22, 2135–2162, https://doi.org/10.5194/hess-22-2135-2018, https://doi.org/10.5194/hess-22-2135-2018, 2018
Short summary
Short summary
This study uses remotely sensed river discharge data to correct river storage and discharge in a large-scale hydrological model. The method is based on an ensemble Kalman filter and also introduces an additional technique that allows for better constraint of the correction (called localization). The approach is applied over the entire Amazon basin. Results show that the method is able to improve river discharge and localization to produce better results along main tributaries.
Malak Sadki, Gaëtan Noual, Simon Munier, Vanessa Pedinotti, Kaushlendra Verma, Clément Albergel, Sylvain Biancamaria, and Alice Andral
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-328, https://doi.org/10.5194/hess-2024-328, 2024
Preprint under review for HESS
Short summary
Short summary
This study explores how 20 years of remote-sensed discharge data from the ESA CCI improve large-scale hydrological models, CTRIP and MGB, through data assimilation. Using an EnKF framework across the Niger and Congo basins, it shows how assimilating denser temporal discharge data reduces biases and improves flow variability, enhancing accuracy. These findings underscore the role of long-term discharge data in refining models for climate assessments, water management, and forecasting.
Tanguy Lunel, Maria Antonia Jimenez, Joan Cuxart, Daniel Martinez-Villagrasa, Aaron Boone, and Patrick Le Moigne
Atmos. Chem. Phys., 24, 7637–7666, https://doi.org/10.5194/acp-24-7637-2024, https://doi.org/10.5194/acp-24-7637-2024, 2024
Short summary
Short summary
During the summer in Catalonia, a cool wind, the marinada, blows into the eastern Ebro basin in the afternoon. This study investigates its previously unclear dynamics using observations and a meteorological model. It is found to be driven by a cool marine air mass that flows over the mountains into the basin. The study shows how the sea breeze, upslope winds, larger weather patterns and irrigation play a prominent role in the formation and characteristics of the marinada.
Sophie Barthelemy, Bertrand Bonan, Miquel Tomas-Burguera, Gilles Grandjean, Séverine Bernardie, Jean-Philippe Naulin, Patrick Le Moigne, Aaron Boone, and Jean-Christophe Calvet
EGUsphere, https://doi.org/10.5194/egusphere-2024-1079, https://doi.org/10.5194/egusphere-2024-1079, 2024
Short summary
Short summary
A drought index is developed that quantifies drought on an annual scale for deciduous broadleaf vegetation, making it applicable to monitoring clay shrinkage damage to buildings, agriculture or forestry. It is found that significant soil moisture drought events occurred in France in 2003, 2018, 2019, 2020 and 2022. Particularly high index values are observed throughout the country in 2022. It is also found that droughts will become more severe in the future.
Théo Defontaine, Sophie Ricci, Corentin J. Lapeyre, Arthur Marchandise, and Etienne Le Pape
EGUsphere, https://doi.org/10.5194/egusphere-2023-2621, https://doi.org/10.5194/egusphere-2023-2621, 2024
Short summary
Short summary
This work presents how machine learning models predict discharge and outperforms the 6 h lead-time empirical model used operationally in Toulouse. The 40 k points database includes discharge and rainfall data, for 36 flood events. The approach also provides a reliable solution for extended 8 h lead-time. The scarcity and the heterogeneity of the data, especially in presence of outliers, heavily weigh on the learning strategy. Rainfall data processing increases the predictive performances.
Jari-Pekka Nousu, Matthieu Lafaysse, Giulia Mazzotti, Pertti Ala-aho, Hannu Marttila, Bertrand Cluzet, Mika Aurela, Annalea Lohila, Pasi Kolari, Aaron Boone, Mathieu Fructus, and Samuli Launiainen
The Cryosphere, 18, 231–263, https://doi.org/10.5194/tc-18-231-2024, https://doi.org/10.5194/tc-18-231-2024, 2024
Short summary
Short summary
The snowpack has a major impact on the land surface energy budget. Accurate simulation of the snowpack energy budget is difficult, and studies that evaluate models against energy budget observations are rare. We compared predictions from well-known models with observations of energy budgets, snow depths and soil temperatures in Finland. Our study identified contrasting strengths and limitations for the models. These results can be used for choosing the right models depending on the use cases.
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.
Malak Sadki, Simon Munier, Aaron Boone, and Sophie Ricci
Geosci. Model Dev., 16, 427–448, https://doi.org/10.5194/gmd-16-427-2023, https://doi.org/10.5194/gmd-16-427-2023, 2023
Short summary
Short summary
Predicting water resource evolution is a key challenge for the coming century.
Anthropogenic impacts on water resources, and particularly the effects of dams and reservoirs on river flows, are still poorly known and generally neglected in global hydrological studies. A parameterized reservoir model is reproduced to compute monthly releases in Spanish anthropized river basins. For global application, an exhaustive sensitivity analysis of the model parameters is performed on flows and volumes.
Jaime Gaona, Pere Quintana-Seguí, María José Escorihuela, Aaron Boone, and María Carmen Llasat
Nat. Hazards Earth Syst. Sci., 22, 3461–3485, https://doi.org/10.5194/nhess-22-3461-2022, https://doi.org/10.5194/nhess-22-3461-2022, 2022
Short summary
Short summary
Droughts represent a particularly complex natural hazard and require explorations of their multiple causes. Part of the complexity has roots in the interaction between the continuous changes in and deviation from normal conditions of the atmosphere and the land surface. The exchange between the atmospheric and surface conditions defines feedback towards dry or wet conditions. In semi-arid environments, energy seems to exceed water in its impact over the evolution of conditions, favoring drought.
Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
Geosci. Model Dev., 14, 4465–4494, https://doi.org/10.5194/gmd-14-4465-2021, https://doi.org/10.5194/gmd-14-4465-2021, 2021
Short summary
Short summary
The subseasonal prediction of extreme hydroclimate events such as droughts/floods has remained stubbornly low for years. This paper presents a new international initiative which, for the first time, introduces spring land surface temperature anomalies over high mountains to improve precipitation prediction through remote effects of land–atmosphere interactions. More than 40 institutions worldwide are participating in this effort. The experimental protocol and preliminary results are presented.
Thibault Guinaldo, Simon Munier, Patrick Le Moigne, Aaron Boone, Bertrand Decharme, Margarita Choulga, and Delphine J. Leroux
Geosci. Model Dev., 14, 1309–1344, https://doi.org/10.5194/gmd-14-1309-2021, https://doi.org/10.5194/gmd-14-1309-2021, 2021
Short summary
Short summary
Lakes are of fundamental importance in the Earth system as they support essential environmental and economic services such as freshwater supply. Despite the impact of lakes on the water cycle, they are generally not considered in global hydrological studies. Based on a model called MLake, we assessed both the importance of lakes in simulating river flows at global scale and the value of their level variations for water resource management.
Michel Le Page, Younes Fakir, Lionel Jarlan, Aaron Boone, Brahim Berjamy, Saïd Khabba, and Mehrez Zribi
Hydrol. Earth Syst. Sci., 25, 637–651, https://doi.org/10.5194/hess-25-637-2021, https://doi.org/10.5194/hess-25-637-2021, 2021
Short summary
Short summary
In the context of major changes, the southern Mediterranean area faces serious challenges with low and continuously decreasing water resources mainly attributed to agricultural use. A method for projecting irrigation water demand under both anthropogenic and climatic changes is proposed. Time series of satellite imagery are used to determine a set of semiempirical equations that can be easily adapted to different future scenarios.
Adrien Napoly, Aaron Boone, and Théo Welfringer
Geosci. Model Dev., 13, 6523–6545, https://doi.org/10.5194/gmd-13-6523-2020, https://doi.org/10.5194/gmd-13-6523-2020, 2020
Short summary
Short summary
Accurate modeling of snow impact on surface energy and mass fluxes is required from land surface models. This new version of the SURFEX model improves the representation of the snowpack. In particular, it prevents its ablation from occurring too early in the season, which also leads to better soil temperatures and energy fluxes toward the atmosphere. This was made possible with a more explicit and distinct representation of each layer that constitutes the surface (soil, snow, and vegetation).
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
Short summary
Short summary
Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
Patrick Le Moigne, François Besson, Eric Martin, Julien Boé, Aaron Boone, Bertrand Decharme, Pierre Etchevers, Stéphanie Faroux, Florence Habets, Matthieu Lafaysse, Delphine Leroux, and Fabienne Rousset-Regimbeau
Geosci. Model Dev., 13, 3925–3946, https://doi.org/10.5194/gmd-13-3925-2020, https://doi.org/10.5194/gmd-13-3925-2020, 2020
Short summary
Short summary
The study describes how a hydrometeorological model, operational at Météo-France, has been improved. Particular emphasis is placed on the impact of climatic data, surface, and soil parametrizations on the model results. Model simulations and evaluations carried out on a variety of measurements of river flows and snow depths are presented. All improvements in climate, surface data, and model physics have a positive impact on system performance.
Ghizlane Aouade, Lionel Jarlan, Jamal Ezzahar, Salah Er-Raki, Adrien Napoly, Abdelfattah Benkaddour, Said Khabba, Gilles Boulet, Sébastien Garrigues, Abdelghani Chehbouni, and Aaron Boone
Hydrol. Earth Syst. Sci., 24, 3789–3814, https://doi.org/10.5194/hess-24-3789-2020, https://doi.org/10.5194/hess-24-3789-2020, 2020
Short summary
Short summary
Our objective is to question the representation of the energy budget in surface–vegetation–atmosphere transfer models for the prediction of the convective fluxes in crops with complex structures (row) and under transient hydric regimes due to irrigation. The main result is that a coupled multiple energy balance approach is necessary to properly predict surface exchanges for these complex crops. It also points out the need for other similar studies on various crops with different sparsity levels.
Alexandra Giese, Aaron Boone, Patrick Wagnon, and Robert Hawley
The Cryosphere, 14, 1555–1577, https://doi.org/10.5194/tc-14-1555-2020, https://doi.org/10.5194/tc-14-1555-2020, 2020
Short summary
Short summary
Rocky debris on glacier surfaces is known to affect the melt of mountain glaciers. Debris can be dry or filled to varying extents with liquid water and ice; whether debris is dry, wet, and/or icy affects how efficiently heat is conducted through debris from its surface to the ice interface. Our paper presents a new energy balance model that simulates moisture phase, evolution, and location in debris. ISBA-DEB is applied to West Changri Nup glacier in Nepal to reveal important physical processes.
Wafa Chebbi, Vincent Rivalland, Pascal Fanise, Aaron Boone, Lionel Jarlan, Hechmi Chehab, Zohra Lili Chabaane, Valérie Le Dantec, and Gilles Boulet
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-104, https://doi.org/10.5194/hess-2020-104, 2020
Publication in HESS not foreseen
Heloisa Ehalt Macedo, Ralph Edward Beighley, Cédric H. David, and John T. Reager
Hydrol. Earth Syst. Sci., 23, 3269–3277, https://doi.org/10.5194/hess-23-3269-2019, https://doi.org/10.5194/hess-23-3269-2019, 2019
Short summary
Short summary
The water stored under the surface is very important for defining the amount of water available for human and environmental applications; however, it is still a challenge to obtain such measurements. NASA's GRACE satellites provide information on total terrestrial water storage based on observations of gravity changes. Here, we relate GRACE data to streamflow measurements, providing estimations of the fraction of baseflow and total drainable storage for the Mississippi River basin.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
Short summary
Short summary
This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Charlotte Marie Emery, Adrien Paris, Sylvain Biancamaria, Aaron Boone, Stéphane Calmant, Pierre-André Garambois, and Joecila Santos da Silva
Hydrol. Earth Syst. Sci., 22, 2135–2162, https://doi.org/10.5194/hess-22-2135-2018, https://doi.org/10.5194/hess-22-2135-2018, 2018
Short summary
Short summary
This study uses remotely sensed river discharge data to correct river storage and discharge in a large-scale hydrological model. The method is based on an ensemble Kalman filter and also introduces an additional technique that allows for better constraint of the correction (called localization). The approach is applied over the entire Amazon basin. Results show that the method is able to improve river discharge and localization to produce better results along main tributaries.
Antoine Colmet-Daage, Emilia Sanchez-Gomez, Sophie Ricci, Cécile Llovel, Valérie Borrell Estupina, Pere Quintana-Seguí, Maria Carmen Llasat, and Eric Servat
Hydrol. Earth Syst. Sci., 22, 673–687, https://doi.org/10.5194/hess-22-673-2018, https://doi.org/10.5194/hess-22-673-2018, 2018
Short summary
Short summary
Here, the first assessment of future changes in extreme precipitation in small Mediterranean watersheds is done through three watersheds frequently subjected to flash floods. Collaboration between Spanish and French laboratories enabled us to conclude that the intensity of high precipitation will increase at the end of the century. A high degree of confidence results from the multi-model approach used here with eight regional climate models (RCMs) developed in the Med and Euro-CORDEX project.
Judith Eeckman, Pierre Chevallier, Aaron Boone, Luc Neppel, Anneke De Rouw, Francois Delclaux, and Devesh Koirala
Hydrol. Earth Syst. Sci., 21, 4879–4893, https://doi.org/10.5194/hess-21-4879-2017, https://doi.org/10.5194/hess-21-4879-2017, 2017
Short summary
Short summary
The central part of the Himalayan Range presents tremendous heterogeneity in terms of topography and climatology, but the representation of hydro-climatic processes for Himalayan catchments is limited due to a lack of knowledge in such poorly instrumented environments. The proposed approach is to characterize the effect of altitude on precipitation by considering ensembles of acceptable altitudinal factors. Ensembles of acceptable values for the components of the water cycle are then provided.
Judith Eeckman, Santosh Nepal, Pierre Chevallier, Gauthier Camensuli, Francois Delclaux, Aaron Boone, and Anneke De Rouw
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-401, https://doi.org/10.5194/hess-2017-401, 2017
Preprint retracted
Short summary
Short summary
This paper compares the simulation of water cycle obtained using two different hydrological models
in two small mountainous Himalayan catchments. The reliability of the simulations for evapotranspiration, discharge can therefore be considered as satisfactory. The differences in the structure and results of the two models mainly concern the water storages and flows in the soil, in particular in high-mountain environment.
Adrien Napoly, Aaron Boone, Patrick Samuelsson, Stefan Gollvik, Eric Martin, Roland Seferian, Dominique Carrer, Bertrand Decharme, and Lionel Jarlan
Geosci. Model Dev., 10, 1621–1644, https://doi.org/10.5194/gmd-10-1621-2017, https://doi.org/10.5194/gmd-10-1621-2017, 2017
Short summary
Short summary
This paper is the second part of a new parameterization for canopy representation that has been developed in the Interactions between the Surface Biosphere Atmosphere model (ISBA). A module for the explicit representation of the litter bellow forest canopies has been added. Then, the first evaluation of these new developments is performed at local scale among three well-instrumented sites and then at the global scale using the FLUXNET network.
Aaron Boone, Patrick Samuelsson, Stefan Gollvik, Adrien Napoly, Lionel Jarlan, Eric Brun, and Bertrand Decharme
Geosci. Model Dev., 10, 843–872, https://doi.org/10.5194/gmd-10-843-2017, https://doi.org/10.5194/gmd-10-843-2017, 2017
Short summary
Short summary
Land surface models describe the different exchanges of mass, heat, and momentum with the atmosphere. They are pushing towards improved realism owing to an increasing number of in situ observations, improving satellite data-sets and increasing computing resources. As a part of the trend, a new parameterization has been developed called the Interactions between the Surface Biosphere Atmosphere-Multi-Energy Budget model. This technical paper describes model equations and theoretical background.
Bertrand Decharme, Eric Brun, Aaron Boone, Christine Delire, Patrick Le Moigne, and Samuel Morin
The Cryosphere, 10, 853–877, https://doi.org/10.5194/tc-10-853-2016, https://doi.org/10.5194/tc-10-853-2016, 2016
Short summary
Short summary
We analyze how snowpack processes and soil properties impact the soil temperature profiles over northern Eurasian regions using a land surface model. A correct representation of snow compaction is critical in winter while snow albedo is dominant in spring. In summer, soil temperature is more affected by soil organic carbon content, which strongly influences the maximum thaw depth in permafrost regions. This work was done to improve the representation of boreal region processes in climate models.
M. C. Rochoux, C. Emery, S. Ricci, B. Cuenot, and A. Trouvé
Nat. Hazards Earth Syst. Sci., 15, 1721–1739, https://doi.org/10.5194/nhess-15-1721-2015, https://doi.org/10.5194/nhess-15-1721-2015, 2015
Short summary
Short summary
This paper, the second part in a series of two articles, aims at presenting a data-driven modeling strategy for forecasting
wildfire spread scenarios based on the assimilation of the observed
fire front location and on the sequential correction of model parameters
or model state. The objective here is to sequentially update the fire front location in order to provide a more reliable initial condition for further model integration and forecast.
V. Pedinotti, A. Boone, S. Ricci, S. Biancamaria, and N. Mognard
Hydrol. Earth Syst. Sci., 18, 4485–4507, https://doi.org/10.5194/hess-18-4485-2014, https://doi.org/10.5194/hess-18-4485-2014, 2014
M. C. Rochoux, S. Ricci, D. Lucor, B. Cuenot, and A. Trouvé
Nat. Hazards Earth Syst. Sci., 14, 2951–2973, https://doi.org/10.5194/nhess-14-2951-2014, https://doi.org/10.5194/nhess-14-2951-2014, 2014
Short summary
Short summary
This paper presents a data-driven wildfire simulator for forecasting wildfire spread scenarios at a reduced computational cost that is consistent with operational systems. A wildfire spread simulator combined with an ensemble-based data assimilation algorithm is indeed a promising approach to reduce uncertainties in the forecast location of the fire front and to introduce a paradigm shift in the wildfire emergency response.
F. Habets, E. Philippe, E. Martin, C. H. David, and F. Leseur
Hydrol. Earth Syst. Sci., 18, 4207–4222, https://doi.org/10.5194/hess-18-4207-2014, https://doi.org/10.5194/hess-18-4207-2014, 2014
N. Flipo, A. Mouhri, B. Labarthe, S. Biancamaria, A. Rivière, and P. Weill
Hydrol. Earth Syst. Sci., 18, 3121–3149, https://doi.org/10.5194/hess-18-3121-2014, https://doi.org/10.5194/hess-18-3121-2014, 2014
V. Masson, P. Le Moigne, E. Martin, S. Faroux, A. Alias, R. Alkama, S. Belamari, A. Barbu, A. Boone, F. Bouyssel, P. Brousseau, E. Brun, J.-C. Calvet, D. Carrer, B. Decharme, C. Delire, S. Donier, K. Essaouini, A.-L. Gibelin, H. Giordani, F. Habets, M. Jidane, G. Kerdraon, E. Kourzeneva, M. Lafaysse, S. Lafont, C. Lebeaupin Brossier, A. Lemonsu, J.-F. Mahfouf, P. Marguinaud, M. Mokhtari, S. Morin, G. Pigeon, R. Salgado, Y. Seity, F. Taillefer, G. Tanguy, P. Tulet, B. Vincendon, V. Vionnet, and A. Voldoire
Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, https://doi.org/10.5194/gmd-6-929-2013, 2013
S. Barthélémy, S. Ricci, O. Pannekoucke, O. Thual, and P. O. Malaterre
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-6963-2013, https://doi.org/10.5194/hessd-10-6963-2013, 2013
Preprint withdrawn
M. Coustau, S. Ricci, V. Borrell-Estupina, C. Bouvier, and O. Thual
Nat. Hazards Earth Syst. Sci., 13, 583–596, https://doi.org/10.5194/nhess-13-583-2013, https://doi.org/10.5194/nhess-13-583-2013, 2013
Related subject area
Subject: Rivers and Lakes | Techniques and Approaches: Remote Sensing and GIS
High-resolution automated detection of headwater streambeds for large watersheds
Remote quantification of the trophic status of Chinese lakes
Hydrological regime of Sahelian small waterbodies from combined Sentinel-2 MSI and Sentinel-3 Synthetic Aperture Radar Altimeter data
Deriving transmission losses in ephemeral rivers using satellite imagery and machine learning
Long-term water clarity patterns of lakes across China using Landsat series imagery from 1985 to 2020
Changes in glacial lakes in the Poiqu River basin in the central Himalayas
Assimilation of probabilistic flood maps from SAR data into a coupled hydrologic–hydraulic forecasting model: a proof of concept
A simple cloud-filling approach for remote sensing water cover assessments
Evaluation of historic and operational satellite radar altimetry missions for constructing consistent long-term lake water level records
Sentinel-3 radar altimetry for river monitoring – a catchment-scale evaluation of satellite water surface elevation from Sentinel-3A and Sentinel-3B
Assessing the capabilities of the Surface Water and Ocean Topography (SWOT) mission for large lake water surface elevation monitoring under different wind conditions
Technical Note: Flow velocity and discharge measurement in rivers using terrestrial and unmanned-aerial-vehicle imagery
River-ice and water velocities using the Planet optical cubesat constellation
Exposure of tourism development to salt karst hazards along the Jordanian Dead Sea shore
A global lake and reservoir volume analysis using a surface water dataset and satellite altimetry
Surface water monitoring in small water bodies: potential and limits of multi-sensor Landsat time series
Technical note: Bathymetry observations of inland water bodies using a tethered single-beam sonar controlled by an unmanned aerial vehicle
Satellite-derived light extinction coefficient and its impact on thermal structure simulations in a 1-D lake model
Observing river stages using unmanned aerial vehicles
Quantification of the contribution of the Beauce groundwater aquifer to the discharge of the Loire River using thermal infrared satellite imaging
Swath-altimetry measurements of the main stem Amazon River: measurement errors and hydraulic implications
Satellite radar altimetry for monitoring small rivers and lakes in Indonesia
Quantifying river form variations in the Mississippi Basin using remotely sensed imagery
River ice flux and water velocities along a 600 km-long reach of Lena River, Siberia, from satellite stereo
Geometric dependency of Tibetan lakes on glacial runoff
Assessing the potential hydrological impact of the Gibe III Dam on Lake Turkana water level using multi-source satellite data
River monitoring from satellite radar altimetry in the Zambezi River basin
Flood occurrence mapping of the middle Mahakam lowland area using satellite radar
Satellite remote sensing of water turbidity in Alqueva reservoir and implications on lake modelling
Hydro-physical processes at the plunge point: an analysis using satellite and in situ data
Regional scale analysis of landform configuration with base-level (isobase) maps
Reconstructing the Tropical Storm Ketsana flood event in Marikina River, Philippines
Reading the bed morphology of a mountain stream: a geomorphometric study on high-resolution topographic data
Francis Lessard, Naïm Perreault, and Sylvain Jutras
Hydrol. Earth Syst. Sci., 28, 1027–1040, https://doi.org/10.5194/hess-28-1027-2024, https://doi.org/10.5194/hess-28-1027-2024, 2024
Short summary
Short summary
Headwaters streams, which are small streams at the top of a watershed, represent two-thirds of the total length of streams, yet their exact locations are still unknown. This article compares different techniques in order to remotely detect the position of these streams. Thus, a database of more than 464 km of headwaters was used to explain what drives their presence. A technique developed in this article makes it possible to detect headwater streams with more accuracy, despite the land uses.
Sijia Li, Shiqi Xu, Kaishan Song, Tiit Kutser, Zhidan Wen, Ge Liu, Yingxin Shang, Lili Lyu, Hui Tao, Xiang Wang, Lele Zhang, and Fangfang Chen
Hydrol. Earth Syst. Sci., 27, 3581–3599, https://doi.org/10.5194/hess-27-3581-2023, https://doi.org/10.5194/hess-27-3581-2023, 2023
Short summary
Short summary
1. Blue/red and green/red Rrs(λ) are sensitive to lake TSI. 2. Machine learning algorithms reveal optimum performance of TSI retrieval. 3. An accurate TSI model was achieved by MSI imagery data and XGBoost. 4. Trophic status in five limnetic regions was qualified. 5. The 10m TSI products were first produced in 555 typical lakes in China.
Mathilde de Fleury, Laurent Kergoat, and Manuela Grippa
Hydrol. Earth Syst. Sci., 27, 2189–2204, https://doi.org/10.5194/hess-27-2189-2023, https://doi.org/10.5194/hess-27-2189-2023, 2023
Short summary
Short summary
This study surveys small lakes and reservoirs, which are vital resources in the Sahel, through a multi-sensor satellite approach. Water height changes compared to evaporation losses in dry seasons highlight anthropogenic withdrawals and water supplies due to river and groundwater connections. Some reservoirs display weak withdrawals, suggesting low usage may be due to security issues. The
satellite-derived water balance thus proved effective in estimating water resources in semi-arid areas.
Antoine Di Ciacca, Scott Wilson, Jasmine Kang, and Thomas Wöhling
Hydrol. Earth Syst. Sci., 27, 703–722, https://doi.org/10.5194/hess-27-703-2023, https://doi.org/10.5194/hess-27-703-2023, 2023
Short summary
Short summary
We present a novel framework to estimate how much water is lost by ephemeral rivers using satellite imagery and machine learning. This framework proved to be an efficient approach, requiring less fieldwork and generating more data than traditional methods, at a similar accuracy. Furthermore, applying this framework improved our understanding of the water transfer at our study site. Our framework is easily transferable to other ephemeral rivers and could be applied to long time series.
Xidong Chen, Liangyun Liu, Xiao Zhang, Junsheng Li, Shenglei Wang, Yuan Gao, and Jun Mi
Hydrol. Earth Syst. Sci., 26, 3517–3536, https://doi.org/10.5194/hess-26-3517-2022, https://doi.org/10.5194/hess-26-3517-2022, 2022
Short summary
Short summary
A 30 m LAke Water Secchi Depth (LAWSD30) dataset of China was first developed for 1985–2020, and national-scale water clarity estimations of lakes in China over the past 35 years were analyzed. Lake clarity in China exhibited a significant downward trend before the 21st century, but improved after 2000. The developed LAWSD30 dataset and the evaluation results can provide effective guidance for water preservation and restoration.
Pengcheng Su, Jingjing Liu, Yong Li, Wei Liu, Yang Wang, Chun Ma, and Qimin Li
Hydrol. Earth Syst. Sci., 25, 5879–5903, https://doi.org/10.5194/hess-25-5879-2021, https://doi.org/10.5194/hess-25-5879-2021, 2021
Short summary
Short summary
We identified ± 150 glacial lakes in the Poiqu River basin (central Himalayas), and we explore the changes in five lakes over the last few decades based on remote sensing images, field surveys, and satellite photos. We reconstruct the lake basin topography, calculate the water capacity, and propose a water balance equation (WBE) to explain glacial lake evolution in response to local weather conditions. The WBE also provides a framework for the water balance in rivers from glacierized sources.
Concetta Di Mauro, Renaud Hostache, Patrick Matgen, Ramona Pelich, Marco Chini, Peter Jan van Leeuwen, Nancy K. Nichols, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 4081–4097, https://doi.org/10.5194/hess-25-4081-2021, https://doi.org/10.5194/hess-25-4081-2021, 2021
Short summary
Short summary
This study evaluates how the sequential assimilation of flood extent derived from synthetic aperture radar data can help improve flood forecasting. In particular, we carried out twin experiments based on a synthetically generated dataset with controlled uncertainty. Our empirical results demonstrate the efficiency of the proposed data assimilation framework, as forecasting errors are substantially reduced as a result of the assimilation.
Connor Mullen, Gopal Penny, and Marc F. Müller
Hydrol. Earth Syst. Sci., 25, 2373–2386, https://doi.org/10.5194/hess-25-2373-2021, https://doi.org/10.5194/hess-25-2373-2021, 2021
Short summary
Short summary
The level of lake water is rapidly changing globally, and long-term, consistent observations of lake water extents are essential for ascertaining and attributing these changes. These data are rarely collected and challenging to obtain from satellite imagery. The proposed method addresses these challenges without any local data, and it was successfully validated against lakes with and without ground data. The algorithm is a valuable tool for the reliable historical water extent of changing lakes.
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.
Cecile M. M. Kittel, Liguang Jiang, Christian Tøttrup, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 25, 333–357, https://doi.org/10.5194/hess-25-333-2021, https://doi.org/10.5194/hess-25-333-2021, 2021
Short summary
Short summary
In poorly instrumented catchments, satellite altimetry offers a unique possibility to obtain water level observations. Improvements in instrument design have increased the capabilities of altimeters to observe inland water bodies, including rivers. In this study, we demonstrate how a dense Sentinel-3 water surface elevation monitoring network can be established at catchment scale using publicly accessible processing platforms. The network can serve as a useful supplement to ground observations.
Jean Bergeron, Gabriela Siles, Robert Leconte, Mélanie Trudel, Damien Desroches, and Daniel L. Peters
Hydrol. Earth Syst. Sci., 24, 5985–6000, https://doi.org/10.5194/hess-24-5985-2020, https://doi.org/10.5194/hess-24-5985-2020, 2020
Short summary
Short summary
We want to assess how well the Surface Water and Ocean Topography (SWOT) satellite mission will be able to provide information on lake surface water elevation and how much of an impact wind conditions (speed and direction) can have on these retrievals.
Anette Eltner, Hannes Sardemann, and Jens Grundmann
Hydrol. Earth Syst. Sci., 24, 1429–1445, https://doi.org/10.5194/hess-24-1429-2020, https://doi.org/10.5194/hess-24-1429-2020, 2020
Short summary
Short summary
An automatic workflow is introduced to measure surface flow velocities in rivers. The provided tool enables the measurement of spatially distributed surface flow velocities independently of the image acquisition perspective. Furthermore, the study illustrates how river discharge in previously ungauged and unmeasured regions can be retrieved, considering the image-based flow velocities and digital elevation models of the studied river reach reconstructed with UAV photogrammetry.
Andreas Kääb, Bas Altena, and Joseph Mascaro
Hydrol. Earth Syst. Sci., 23, 4233–4247, https://doi.org/10.5194/hess-23-4233-2019, https://doi.org/10.5194/hess-23-4233-2019, 2019
Short summary
Short summary
Knowledge of water surface velocities in rivers is useful for understanding a wide range of processes and systems, but is difficult to measure over large reaches. Here, we present a novel method to exploit near-simultaneous imagery produced by the Planet cubesat constellation to track river ice floes and estimate water surface velocities. We demonstrate the method for a 60 km long reach of the Amur River and a 200 km long reach of the Yukon River.
Najib Abou Karaki, Simone Fiaschi, Killian Paenen, Mohammad Al-Awabdeh, and Damien Closson
Hydrol. Earth Syst. Sci., 23, 2111–2127, https://doi.org/10.5194/hess-23-2111-2019, https://doi.org/10.5194/hess-23-2111-2019, 2019
Short summary
Short summary
The Dead Sea shore is a unique salt karst system. Development began in the 1960s, when the water resources that used to feed the Dead Sea were diverted. The water level is falling at more than 1 m yr−1, causing a hydrostatic disequilibrium between the underground fresh water and the base level. Despite these conditions, tourism development projects have flourished. Here, we show that a 10 km long strip of coast that encompasses several resorts is exposed to subsidence, sinkholes and landslides.
Tim Busker, Ad de Roo, Emiliano Gelati, Christian Schwatke, Marko Adamovic, Berny Bisselink, Jean-Francois Pekel, and Andrew Cottam
Hydrol. Earth Syst. Sci., 23, 669–690, https://doi.org/10.5194/hess-23-669-2019, https://doi.org/10.5194/hess-23-669-2019, 2019
Short summary
Short summary
This paper estimates lake and reservoir volume variations over all continents from 1984 to 2015 using remote sensing alone. This study improves on previous methodologies by using the Global Surface Water dataset developed by the Joint Research Centre, which allowed for volume calculations on a global scale, a high resolution (30 m) and back to 1984 using very detailed lake area dynamics. Using 18 in situ volume time series as validation, our volume estimates showed a high accuracy.
Andrew Ogilvie, Gilles Belaud, Sylvain Massuel, Mark Mulligan, Patrick Le Goulven, and Roger Calvez
Hydrol. Earth Syst. Sci., 22, 4349–4380, https://doi.org/10.5194/hess-22-4349-2018, https://doi.org/10.5194/hess-22-4349-2018, 2018
Short summary
Short summary
Accurate monitoring of surface water extent is essential for hydrological investigation of small lakes (1–10 ha), which supports millions of smallholder farmers. Landsat monitoring of long-term surface water dynamics is shown to be suited to lakes over 3 ha based on extensive hydrometric data from seven field sites over 15 years. MNDWI water classification optimized here for the specificities of small water bodies reduced mean surface area errors by 57 % compared to published global datasets.
Filippo Bandini, Daniel Olesen, Jakob Jakobsen, Cecile Marie Margaretha Kittel, Sheng Wang, Monica Garcia, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 22, 4165–4181, https://doi.org/10.5194/hess-22-4165-2018, https://doi.org/10.5194/hess-22-4165-2018, 2018
Short summary
Short summary
Water depth observations are essential data to forecast flood hazard, predict sediment transport, or monitor in-stream habitats. We retrieved bathymetry with a sonar wired to a drone. This system can improve the speed and spatial scale at which water depth observations are retrieved. Observations can be retrieved also in unnavigable or inaccessible rivers. Water depth observations showed an accuracy of ca. 2.1 % of actual depth, without being affected by water turbidity or bed material.
Kiana Zolfaghari, Claude R. Duguay, and Homa Kheyrollah Pour
Hydrol. Earth Syst. Sci., 21, 377–391, https://doi.org/10.5194/hess-21-377-2017, https://doi.org/10.5194/hess-21-377-2017, 2017
Short summary
Short summary
A remotely-sensed water clarity value (Kd) was applied to improve FLake model simulations of Lake Erie thermal structure using a time-invariant (constant) annual value as well as monthly values of Kd. The sensitivity of FLake model to Kd values was studied. It was shown that the model is very sensitive to variations in Kd when the value is less than 0.5 m-1.
Tomasz Niedzielski, Matylda Witek, and Waldemar Spallek
Hydrol. Earth Syst. Sci., 20, 3193–3205, https://doi.org/10.5194/hess-20-3193-2016, https://doi.org/10.5194/hess-20-3193-2016, 2016
Short summary
Short summary
We study detectability of changes in water surface areas on orthophotomaps. We use unmanned aerial vehicles to acquire visible light photographs. We offer a new method for detecting changes in water surface areas and river stages. The approach is based on the application of the Student's t test, in asymptotic and bootstrapped versions. We test our approach on aerial photos taken during 3-year observational campaign. We detect transitions between all characteristic river stages using drone data.
E. Lalot, F. Curie, V. Wawrzyniak, F. Baratelli, S. Schomburgk, N. Flipo, H. Piegay, and F. Moatar
Hydrol. Earth Syst. Sci., 19, 4479–4492, https://doi.org/10.5194/hess-19-4479-2015, https://doi.org/10.5194/hess-19-4479-2015, 2015
Short summary
Short summary
This work shows that satellite thermal infrared images (LANDSAT) can be used to locate and quantify groundwater discharge into a large river (Loire River, France - 100 to 300 m wide). Groundwater discharge rate is found to be highly variable with time and space and maximum during flow recession periods and in winter. The main identified groundwater discharge area into the Loire River corresponds to a known discharge area of the Beauce aquifer.
M. D. Wilson, M. Durand, H. C. Jung, and D. Alsdorf
Hydrol. Earth Syst. Sci., 19, 1943–1959, https://doi.org/10.5194/hess-19-1943-2015, https://doi.org/10.5194/hess-19-1943-2015, 2015
Short summary
Short summary
We use a virtual mission analysis on a ca. 260km reach of the central Amazon River to assess the hydraulic implications of potential measurement errors in swath-altimetry imagery from the forthcoming Surface Water and Ocean Topography (SWOT) satellite mission. We estimated water surface slope from imagery of water heights and then derived channel discharge. Errors in estimated discharge were lowest when using longer reach lengths and channel cross-sectional averaging to estimate water slopes.
Y. B. Sulistioadi, K.-H. Tseng, C. K. Shum, H. Hidayat, M. Sumaryono, A. Suhardiman, F. Setiawan, and S. Sunarso
Hydrol. Earth Syst. Sci., 19, 341–359, https://doi.org/10.5194/hess-19-341-2015, https://doi.org/10.5194/hess-19-341-2015, 2015
Short summary
Short summary
This paper investigates the possibility of monitoring small water bodies through Envisat altimetry observation. A novel approach is introduced to identify qualified and non-qualified altimetry measurements by assessing the waveform shapes for each returned radar signal. This research indicates that small lakes (extent < 100 km2) and medium-sized rivers (e.g., 200--800 m in width) can be successfully monitored by satellite altimetry.
Z. F. Miller, T. M. Pavelsky, and G. H. Allen
Hydrol. Earth Syst. Sci., 18, 4883–4895, https://doi.org/10.5194/hess-18-4883-2014, https://doi.org/10.5194/hess-18-4883-2014, 2014
Short summary
Short summary
Many previous studies have used stream gauge data to estimate patterns of river width and depth based on variations in river discharge. However, these relationships may not capture all of the actual variability in width and depth. We have instead mapped the widths of all of the rivers wider than 100 m (and many narrower) in the Mississippi Basin and then used them to also improve estimates of depth as well. Our results show width and depth variations not captured by power-law relationships.
A. Kääb, M. Lamare, and M. Abrams
Hydrol. Earth Syst. Sci., 17, 4671–4683, https://doi.org/10.5194/hess-17-4671-2013, https://doi.org/10.5194/hess-17-4671-2013, 2013
V. H. Phan, R. C. Lindenbergh, and M. Menenti
Hydrol. Earth Syst. Sci., 17, 4061–4077, https://doi.org/10.5194/hess-17-4061-2013, https://doi.org/10.5194/hess-17-4061-2013, 2013
N. M. Velpuri and G. B. Senay
Hydrol. Earth Syst. Sci., 16, 3561–3578, https://doi.org/10.5194/hess-16-3561-2012, https://doi.org/10.5194/hess-16-3561-2012, 2012
C. I. Michailovsky, S. McEnnis, P. A. M. Berry, R. Smith, and P. Bauer-Gottwein
Hydrol. Earth Syst. Sci., 16, 2181–2192, https://doi.org/10.5194/hess-16-2181-2012, https://doi.org/10.5194/hess-16-2181-2012, 2012
H. Hidayat, D. H. Hoekman, M. A. M. Vissers, and A. J. F. Hoitink
Hydrol. Earth Syst. Sci., 16, 1805–1816, https://doi.org/10.5194/hess-16-1805-2012, https://doi.org/10.5194/hess-16-1805-2012, 2012
M. Potes, M. J. Costa, and R. Salgado
Hydrol. Earth Syst. Sci., 16, 1623–1633, https://doi.org/10.5194/hess-16-1623-2012, https://doi.org/10.5194/hess-16-1623-2012, 2012
A. T. Assireu, E. Alcântara, E. M. L. M. Novo, F. Roland, F. S. Pacheco, J. L. Stech, and J. A. Lorenzzetti
Hydrol. Earth Syst. Sci., 15, 3689–3700, https://doi.org/10.5194/hess-15-3689-2011, https://doi.org/10.5194/hess-15-3689-2011, 2011
C. H. Grohmann, C. Riccomini, and M. A. C. Chamani
Hydrol. Earth Syst. Sci., 15, 1493–1504, https://doi.org/10.5194/hess-15-1493-2011, https://doi.org/10.5194/hess-15-1493-2011, 2011
C. C. Abon, C. P. C. David, and N. E. B. Pellejera
Hydrol. Earth Syst. Sci., 15, 1283–1289, https://doi.org/10.5194/hess-15-1283-2011, https://doi.org/10.5194/hess-15-1283-2011, 2011
S. Trevisani, M. Cavalli, and L. Marchi
Hydrol. Earth Syst. Sci., 14, 393–405, https://doi.org/10.5194/hess-14-393-2010, https://doi.org/10.5194/hess-14-393-2010, 2010
Cited articles
Andreadis, K. M. and Schumann, G. J. P.:
Estimating the impact of satellite observations on the predictability of large-scale hydraulic models,
Adv. Water Res.,
73, 44–54, https://doi.org/10.1016/j.advwatres.2014.06.006, 2014. a
Andreadis, K. M., Clark, E. A., Lettenmaier, D. P., and Alsdorf, D. E.:
Prospects for river discharge and depth estimation through assimilation of swath-altimetry into a raster-based hydrodynamics model,
Geophys. Res. Lett.,
34, L10403, https://doi.org/10.1029/2007GL029721, 2007. a
Beighley, R. E., Eggert, K. G., Dunne, T., He, Y., Gummadi, V., and Verdin, K. L.:
Simulating hydrologic and hydraulic processed throughout the Amazon basin,
Hydrol. Process.,
23, 1221–1235, https://doi.org/10.1002/hyp.7252, 2009. a
Beven, K. and Freer, J.:
Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using GLUE methodology,
J. Hydrol.,
249, 11–29, https://doi.org/10.1016/S0022-1694(01)00421-8, 2001. a
Beven, K. J.:
Down to basics: runoff processes and the modelling of processes,
in:
Rainfall-Runoff Modelling,
John Wiley and Sons, West Sussex, UK, chap. 1, 1–22, 2012. a
Biancamaria, S., Bates, P., Boone, A., and Mognard, N.:
Large-scale coupled hydrologic and hydraulic modelling of teh Ob river in Siberia,
J. Hydrol.,
379, 136–150, https://doi.org/10.1016/j.jhydrol.2009.09.054, 2009. a
Biancamaria, S., Durant, M., Andreadis, K. M., Bates, P. D., Boone, A., Mognard, N. M., Rodriguez, E., Alsdorf, D. E., Lettenmaier, D. P., and Clark, E. A.:
Assimilation of virtual wide swath altimetry to improve Arctic river modeling,
Remote Sens. Environ.,
115, 373–381, https://doi.org/10.1016/j.rse.2010.09.008, 2011. a, b
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. a
Bierkens, M. F. P.:
Global hydrology 2015: State, trends, and directions,
Water Resour. Res.,
51, 4923–4947, https://doi.org/10.1002/2015WR017173, 2015. a
Birkett, C. M., Mertes, L. A. K., Dunne, T., Costa, M. H., and Jasinski, M. J.:
Surface water dynamics in the Amazon basin: Application of satellite radar altimetry,
J. Geophys. Res.,
107, L10403, https://doi.org/10.1029/2001JD000609, 2002. a
Bishop, C. H., Etherton, B. J., and Majumbar, S. J.:
Adaptative sampling with the ensemble transform Kalman filter. Part I: Theoretical aspects,
Mon. Weather Rev.,
129, 420–436, https://doi.org/10.1175/1520-0493(2001)129<0420:ASWTET>2.0.CO;2, 2001. a
Boone, A., Calvet, J.-C., and Noilhan, J.:
Inclusion of a Third Soil Layer in a Land Surface Scheme Using the Force-Restore Method,
J. Hydrometeorol.,
38, 1611–1630, https://doi.org/10.1175/1520-0450(1999)038<1611:IOATSL>2.0.CO;2, 1999. a
Brisset, P., Monnier, J., Garambois, P.-A., and Roux, H.:
On the assimilation of altimetry data in 1D Saint-Venant river models,
Adv. Water Res.,
119, 41–59, https://doi.org/10.1016/J.advwatres.2018.06.004, 2018. a
Buis, S., Piacentini, A., and Declat, D.: PALM: a computational framework for assembling high-performance computing applications, Concurrency Computat.: Pract. Exper., 18, 247–262, 2006 (data available at: http://www.cerfacs.fr/globc/PALM_WEB/, last access: 20 April 2020). a
Burgers, G., Leeuwen, P. J. V., and Evensen, G.:
Analysis Scheme in the Ensemble Kalman Filter,
Mon. Weather Rev.,
126, 1719–1724, https://doi.org/10.1175/1520-0493(1998)126<1719:ASITEK>2.0.CO;2, 1998. a
Clark, M. P., Rupp, D. E., Woods, R. A., Zheng, X., Ibbitt, R. P., Slater, A. G., Schmidt, J., and Uddstrom, M. J.:
Hydrological data assimilation with the ensemble Kalman filter: Use of streamflow observations to update states in a distributed hydrological model,
Adv. Water Res.,
31, 1309–1324, https://doi.org/10.1016/j.advwatres.2008.06.005, 2008. a
Cretaux, J.-F., Calmant, S., Romanoski, V., Shabunin, A., Lyard, F., Berge-Nguyen, M., Cazenave, A., Hernandez, F., and Perosanz, F.:
An absolute calibration site for radar altimeters in the continental domain: Lake Issykkul in Central Asia,
J. Geodesy,
83, 723–735, https://doi.org/10.1007/s00190-008-0289-7, 2009. a
Decharme, B., Alkama, R., Douville, H., Becker, M., and Cazenave, A.:
Global Evaluation of the ISBA-TRIP Continental Hydrological System. Part II: Uncertainties in River Routing Simulation Related to Flow Velocity and Groundwater Storage,
J. Hydrometeorol.,
11, 601–617, https://doi.org/10.1175/2010JHM1212.1, 2010. a
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, 2012 (data available at: http://www.cnrm-game-meteo.fr/surfex/, last access: 20 April 2020). a, b, c, d, e, f
Decharme, B., Delire, C., Minvielle, M., Colin, J., Vergnes, J.‐P., Alias, A., Saint‐Martin, D., Séférian, R., Sénési, S., and Voldoire, A.:
Recent changes in the ISBA-CTRIP land surface system for use in CNRM-CM6 climate model and global off-line hydrological applications,
J. Adv. Model. Earth Sy.,
11, 1207–1252, https://doi.org/10.1029/2018MS001545, 2019. a, b, c
Deng, C., Liu, P., Guo, S., Li, Z., and Wang, D.: Identification of hydrological model parameter variation using ensemble Kalman filter, Hydrol. Earth Syst. Sci., 20, 4949–4961, https://doi.org/10.5194/hess-20-4949-2016, 2016. a
Doll, P., Douville, H., Güntner, A., Schmied, H. M., and Wada, Y.:
Modelling Freshwater Resources at the Global Scale: Challenges and Propects,
Surv. Geophys.,
37, 195–221, https://doi.org/10.1007/s10712-015-9343-1, 2015. a
Durand, M., Andreadis, K., Alsdorf, D., Lettenmaier, D., Moller, D., and Wilson, M.:
Estimation of bathymetric depth and slope from data assimilation of swath altimetry into a hydrodynamic model,
Geophys. Res. Lett.,
35, L20401, https://doi.org/10.1029/2008GL034150, 2008. a, b, c
Emery, C. M., Biancamaria, S., Boone, A., Garambois, P.-A., Ricci, S., Rochoux, M. C., and Decharme, B.:
Temporal variance-based sensitivity analysis of the river routing component of the large scale hydrological model ISBA-TRIP: Application on the Amazon Basin,
J. Hydrometeorol.,
17, 3007–3027, https://doi.org/10.1175/JHM-D-16-0050.1, 2016. a, b, c, d, e, f, g, h, i, j, k
Emery, C. M., Paris, A., Biancamaria, S., Boone, A., Calmant, S., Garambois, P.-A., and Santos da Silva, J.: Large-scale hydrological model river storage and discharge correction using a satellite altimetry-based discharge product, Hydrol. Earth Syst. Sci., 22, 2135–2162, https://doi.org/10.5194/hess-22-2135-2018, 2018. a, b, c, d
Esteban Fernandez, D.:
SWOT Project, Mission performance and error budget,
Tech. rep., Jet Propulsion Laboratory, 2017. a
Evensen, G.:
Sequential data assimilation with a nonlinear quasi-geostropic model using Monte Carlo methods to forecast error statistics,
J. Geophys. Res.,
99, 10143–10162, https://doi.org/10.1029/94JC00572, 1994. a
Evensen, G.:
Advanced data assimilation for strongly nonlinear dynamics,
Mon. Weather Rev.,
125, 1342–1354, https://doi.org/10.1175/1520-0493(1997)125<1342:ADAFSN>2.0.CO;2, 1997. a
Evensen, G.:
The Ensemble Kalman Filter: theoretical formulation and practical implementation,
Ocean Dynam.,
53, 343–367, https://doi.org/10.1007/s10236-003-0036-9, 2003. a
Evensen, G.:
Sampling strategies and square root analysis schemes for the EnKF,
Ocean Dynam.,
54, 539–560, https://doi.org/10.1007/s10236-004-0099-2, 2004. a, b
Evensen, G. and Leeuwen, P. V.:
An ensemble kalman smoother for nonlinear dynamics,
Mon. Weather Rev.,
128, 1852–1867, https://doi.org/10.1175/1520-0493(2000)128<1852:AEKSFN>2.0.CO;2, 2000. a, b
Fjørtoft, R., Gaudin, J.-M., Pourthie, N., Lalaurie, J.-C., Mallet, A., Nouvel, J.-F., Martinot-Lagarde, J., Oriot, H., Borderies, P., Ruiz, C., and Daniel, S.:
KaRIn on SWOT: Characteristics of near-nadir Ka-band interferometric SAR imagery,
IEEE T. Geosci. Remote,
52, 2172–2185, https://doi.org/10.1109/TGRS.2013.2258402, 2014. a
Guillet, O., Weaver, A., Vasseur, X., Michel, M., Gratton, S., and Gürol, S.:
Modelling spatially correlated observation errors in variational data assimilation using a diffusion operator on an unstructured mesh,
Q. J. Roy. Meteor. Soc., 145, 1947–1967,
https://doi.org/10.1002/qj.3537, 2018. a
Gupta, H. V., Sorooshian, S., and Yapo, P. O.:
Toward improved calibration of hydrological models: multiple and noncommensurable measures of information,
Water Resour. Res.,
34, 751–763, https://doi.org/10.1029/97WR03495, 1998. a
Hafliger, V., Martin, E., Boone, A., Ricci, S., and Biancamaria, S.:
Assimilation of synthetic SWOT river depths in a regional hydrometeorological model,
Water,
11, 78, https://doi.org/10.3390/w11010078, 2019. a, b
Hunt, B., Kalnay, E., Kostelich, E. J., Ott, E., Patil, D. T., Sauer, T., Szunyogh, I., Yorke, J. A., and Zimin, A. V.:
Four-dimensional ensemble Kalman filtering,
Tellus,
56, 273–277, https://doi.org/10.1111/j.1600-0870.2004.00066.x, 2004. a
Hunt, B. R., Kostelich, E. J., and Szunyogh, I.:
Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter,
Physica D,
230, 112–126, https://doi.org/10.1016/j.physd.2006.11.008, 2007. a
International Association of Hydrological Sciences Ad Hoc Group on Global Water Sets, Vörösmarty, C., Askew, A., Grabs, W., Barry, R. G., Birkett, C., Döll, P., Goodison, B., Hall, A., Jenne, R., Kitaev, L., Landwehr, J., Keeler, M., Leavesley, G., Schaake, J., Strzepek, K., Sundarvel, S. S., Takeuchi, K., and Webster, F.:
Global water data: a newly endangered species,
EOS T. Am. Geophys. Un.,
82, 54–58, https://doi.org/10.1029/01EO00031, 2001. a
Kim, H.: Global Soil Wetness Project Phase 3 Atmospheric Boundary Conditions (Experiment 1), Data set, Data Integration and Analysis System, https://doi.org/10.20783/DIAS.501, 2017. a
Kurtz, W., Hendricks-Frassen, H.-J., and Vereecken, H.:
Identification of time-variant river bed properties with Ensemble Kalman Filter,
Water Resour. Res.,
48, W10534, https://doi.org/10.1029/2011WR011743, 2012. a
Leeuwen, P. V. and Evensen, G.:
Data assimilation and inverse methods in terms of a probabilistic formulation,
Mon. Weather Rev.,
124, 2898–2913, https://doi.org/10.1175/1520-0493(1996)124<2898:DAAIMI>2.0.CO;2, 1996. a
Liu, Y. and Gupta, H. V.:
Uncertainty in hydrological modeling: Towards an integrated data assimilation framework,
Water Resour. Res.,
43, W07401, https://doi.org/10.1029/2006WR005756, 2007. a, b
Liu, Y., Weerts, A. H., Clark, M., Hendricks Franssen, H.-J., Kumar, S., Moradkhani, H., Seo, D.-J., Schwanenberg, D., Smith, P., van Dijk, A. I. J. M., van Velzen, N., He, M., Lee, H., Noh, S. J., Rakovec, O., and Restrepo, P.: Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities, Hydrol. Earth Syst. Sci., 16, 3863–3887, https://doi.org/10.5194/hess-16-3863-2012, 2012. a
Maidment, D. R.:
Handbook of Hydrology,
McGraw Hill Professional, 1993. a
Manning, R.:
On the flow of water in open channels and pipes,
Institution of Civil Engineers of Ireland,
20, 161–207, 1891. a
Meade, R., Rayol, J., Conceicão, S. D., and Natividade, J.:
Backwater Effects in the Amazon River Basin of Brazil,
Environ. Geol. Water S.,
18, 105–114, https://doi.org/10.1007/BF01704664, 1991. a
Melsen, L., Teuling, A., Torfs, P., Zappa, M., Mizukami, N., Clark, M., and Uijlenhoet, R.: Representation of spatial and temporal variability in large-domain hydrological models: case study for a mesoscale pre-Alpine basin, Hydrol. Earth Syst. Sci., 20, 2207–2226, https://doi.org/10.5194/hess-20-2207-2016, 2016. a, b
Mersel, M. K., Smith, L. C., Andreadis, K. M., and Durand, M. T.:
Estimation of river depth from remotely-sensed hydraulic relationship,
Water Resour. Res.,
49, 3165–3179, https://doi.org/10.1002/wrcr.20176, 2013. a
Michailovsky, C. I. and Bauer-Gottwein, P.: Operational reservoir inflow forecasting with radar altimetry: the Zambezi case study, Hydrol. Earth Syst. Sci., 18, 997–1007, https://doi.org/10.5194/hess-18-997-2014, 2014. a
Michailovsky, C. I., Milzow, C., and Bauer-Gottwein, P.:
Assimilation of radar altimetry to a routing model of the Brahmaputra river,
Water Resour. Res.,
49, 4807–4816, https://doi.org/10.1002/wrcr.20345, 2013. a, b
Molinier, M., Guyot, J.-L., Orstom, B., Guimarães, V., de Oliveira, E., and Dnaee, B.: Hydrologie du bassin de l'Amazone,
in: Grands Bassins Fluviaux Périatlantiques,
PEGI-INSA-CNRS-ORSTOM, Paris, available at: http://horizon.documentation.ird.fr/exl-doc/pleins_textes/pleins_textes_7/carton01/40102.pdf
(last access: 4 May 2020), 335–345, 1993. a
Montzka, C., Moradkhani, H., Weihermüller, L., Hendricks-Franssen, H.-J., Canty, M., and Vereecken, H.:
Hydraulic parameter estimation by remotely-sensed top soil moisture observations with the particle filter,
J. Hydrol.,
399, 410–421, https://doi.org/10.1016/j.jhydrol.2011.01.020, 2011. a
Moradkhani, H., Hsu, K.-L., Gupta, H., and Sorooshian, S.:
Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using particle filter,
Water Resour. Res.,
41, W05012, https://doi.org/10.1029/2004WR003604, 2005. a, b, c
Munier, S., Polebistki, A., Brown, C., Belaud, G., and Lettenmaier, D. P.:
SWOT data assimilation for operational reservoir management on the upper Niger river basin,
Water Resour. Res.,
51, 554–575, https://doi.org/10.1002/2014WR016157, 2015. a
Noilhan, J. and Planton, S.:
A simple parameterization of land surface processes for meteorological models,
Mon. Weather Rev.,
117, 536–549, https://doi.org/10.1175/1520-0493(1989)117<0536:ASPOLS>2.0.CO;2, 1989. a, b
Oki, T. and Sud, Y. C.:
Design of Total Integrating Pathways (TRIP)—A Global River Channel Network,
Earth Interact.,
2, 1–36, https://doi.org/10.1175/1087-3562(1998)002<0001:DOTRIP>2.3.CO;2, 1998. a, b, c
Ott, E., Hunt, B. R., Szunyogh, I., Kostelich, A. V. Z. A. J., Corazza, M., Kalnay, E., Patil, D. J., and Yorke, J. A.:
A local ensemble Kalman filter for atmospheric data assimilation,
Tellus A,
56, 415–428, https://doi.org/10.1111/j.1600-0870.2004.00076.x, 2004. a
Oubanas, H., Gejadze, I., Malaterre, P.-O., Durand, M., Wei, R., Frasson, R. P. M., and Domeneghetti, A.:
Discharge estimation in ungauged basins through variational data assimilation: the potential of the SWOT mission,
Water Resour. Res.,
54, 2405–2423, https://doi.org/10.1002/2017WR021735, 2018. a, b, c
Paiva, R. C. D., Buarque, D. C., Collischonn, W., Bonnet, M.-P., Frappart, F., Calmant, S., and Mendes, C. A. B.:
Large scale hydrological and hydrodynamic modeling of the Amazon River basin,
Water Resour. Res.,
49, 1226–1243, https://doi.org/10.1002/wrcr.20067, 2013. a
Panzeri, M., Riva, M., Guadagnini, A., and Neuman, S. P.:
Data assimilation and parameter estimation via ensemble kalman filter coupled with stochastic moment equations of transient groudwater flow,
Water Resour. Res.,
49, 1334–1344, https://doi.org/10.1002/wrcr.20113, 2013. a
Pathiraja, S., Marshall, L., Sharma, A., and Moradkhani, H.:
Detecting non-stationar hydrologic model parameters in a paired catchment system using data assimilation,
Adv. Water Res.,
94, 103–119, https://doi.org/10.1016/j.advwatres.2016.04.021, 2016. a, b
Pedinotti, V., Boone, A., Ricci, S., Biancamaria, S., and Mognard, N.: Assimilation of satellite data to optimize large-scale hydrological model parameters: a case study for the SWOT mission, Hydrol. Earth Syst. Sci., 18, 4485–4507, https://doi.org/10.5194/hess-18-4485-2014, 2014. a, b, c, d, e, f, g, h
Rakovec, O., Weerts, A. H., Sumihar, J., and Uijlenhoet, R.: Operational aspects of asynchronous filtering for flood forecasting, Hydrol. Earth Syst. Sci., 19, 2911–2924, https://doi.org/10.5194/hess-19-2911-2015, 2015. a, b
Renard, B., Kavetski, D., Kuczera, G., Thyer, M., and Franks, S. W.:
Understanding predictive uncertainty in hydrologic modeling: the challenge of identifying input and structural errors,
Water Resour. Res.,
46, W05521, https://doi.org/10.1029/2009WR008328, 2010. a
Rodell, M., Beaudoing, H. K., L'Ecuyer, T. S., Olson, W. S., Famiglietti, J. S., 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. H., Lettenmaier, D. P., Liu, W. T., Roberton, 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. a
Ruiz, J. J., Pulido, M., and Miyoshi, T.:
Estimating model parameters with ensemble-based data assimilation,
J. Meteorol. Soc. Jpn.,
91, 79–99, https://doi.org/10.2151/jmsj.2013-201, 2013. a
Sakov, P., Evensen, G., and Bertino, L.:
Asynchronous data assimilation with the EnKF,
Tellus,
62, 24–29, https://doi.org/10.1111/j.1600-0870.2009.00417.x, 2010. a, b
Sanoo, A. K., Pan, M., Troy, T. J., Vinukollu, R. K., Sheffield, J., and Wood, E. F.:
Reconciling the global terrestrial water budget using satellite remote sensing,
Remote Sens. Environ.,
115, 1850–1865, https://doi.org/10.1016/j.rse.2011.03.009, 2011. a
Shi, Y., Davis, K. J., Zhang, F., Duffy, C. J., and Yu, X.:
Parameter estimation of physically-based land surface model hydrologic model using an ensemble Kalman filter: a multivariate real-data experiment,
Adv. Water Res.,
83, 421–427, https://doi.org/10.1016/j.advwatres.2015.06.009, 2015. a
Silva, J. S. D., Calmant, S., Seyler, F., Filho, O. C. R., Cochonneau, G., and Mansur, W. J.:
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. a
Sood, A. and Smakhtin, V.:
Global hydrological models: a review,
Hydrolog. Sci. J.,
60, 549–565, https://doi.org/10.1080/02626667.2014.950580, 2015.
a
Talagrand, O. and Courtier, P.:
Variational assimilation of meteorological observations with the adjoint vorticity equation, Part 1: Theory,
Q. J. Roy. Meteor. Soc.,
113, 1311–1328, https://doi.org/10.1002/qj.49711347812, 1987. a
Vinukollu, R. K., Meynadier, R., Sheffield, J., and Wood, E. F.:
Multi-model, multi-sensor esti- mates of global evapotranspiration: climatology, uncertainties and trents,
Hydrol. Process.,
25, 3993–4010, https://doi.org/10.1002/hyp.8393, 2011. a
Vrugt, J. A., ter Braak, C. J. F., Diks, C. G. H., and Shoups, G.:
Hydrological data assimilation using particle Markov chain Monte Carlo simulation: Theory, concepts and applications,
Adv. Water Res.,
51, 457–478, https://doi.org/10.1016/j.advwatres.2012.04.002, 2012. a
Wisser, D., Fekete, B. M., Vörösmarty, C. J., and Schumann, A. H.: Reconstructing 20th century global hydrography: a contribution to the Global Terrestrial Network- Hydrology (GTN-H), Hydrol. Earth Syst. Sci., 14, 1–24, https://doi.org/10.5194/hess-14-1-2010, 2010. a
Yoon, Y., Durand, M., Merry, C. J., Clark, E. A., Andreadis, K. M., and Alsdorf, D. E.:
Estimating river bathymetry from data assimilation of synthetic SWOT measurements,
J. Hydrol.,
464-465, 363–375, https://doi.org/10.1016/j.jhydrol.2012.07.028, 2012. a
Short summary
The flow of freshwater in rivers is commonly studied with computer programs known as hydrological models. An important component of those programs lies in the description of the river environment, such as the channel resistance to the flow, that is critical to accurately predict the river flow but is still not well known. Satellite data can be combined with models to enrich our knowledge of these features. Here, we show that the coming SWOT mission can help better know this channel resistance.
The flow of freshwater in rivers is commonly studied with computer programs known as...
