Articles | Volume 22, issue 4
https://doi.org/10.5194/hess-22-2135-2018
© Author(s) 2018. 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-22-2135-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Large-scale hydrological model river storage and discharge correction using a satellite altimetry-based discharge product
Charlotte Marie Emery
CORRESPONDING AUTHOR
LEGOS, Université de Toulouse, CNES, CNRS, IRD, UPS, Toulouse, France
now at: JPL, Pasadena, CA, USA
Adrien Paris
LEGOS, Université de Toulouse, CNES, CNRS, IRD, UPS, Toulouse, France
GET, Université de Toulouse, UPS, CNRS, IRD, Toulouse, France
LMI OCE IRD/UNB, Campus Darcy Ribeiro, Brasilia, Brazil
now at: CLS, Ramonville-Saint-Agne, France
Sylvain Biancamaria
LEGOS, Université de Toulouse, CNES, CNRS, IRD, UPS, Toulouse, France
Aaron Boone
Meteo France CNRS, CNRM UMR 3589, Toulouse, France
Stéphane Calmant
LEGOS, Université de Toulouse, CNES, CNRS, IRD, UPS, Toulouse, France
Pierre-André Garambois
ICUBE – UMR 7357, Fluid Mechanics Team, INSA, Strasbourg, France
Joecila Santos da Silva
CESTU, Universidade do Estado do Amazonas, Manaus, Brazil
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- Improved modeling of Congo's hydrology for floods and droughts analysis and ENSO teleconnections S. Wongchuig et al. 10.1016/j.ejrh.2023.101563
- Long-term total water storage change from a Satellite Water Cycle reconstruction over large southern Asian basins V. Pellet et al. 10.5194/hess-24-3033-2020
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- Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces A. Lausch et al. 10.3390/rs12223690
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- Global patterns in river water storage dependent on residence time E. Collins et al. 10.1038/s41561-024-01421-5
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- Performance of Greywater Treatment Using Iron Removal Media (IRM) and Cattail Typha Angustifolia H. Hasan et al. 10.47836/pjst.30.2.32
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- Channel Water Storage Anomaly: A New Remotely Sensed Quantity for Global River Analysis S. Coss et al. 10.1029/2022GL100185
- A review of globally available data sources for modelling the Water-Energy-Food Nexus J. Lodge et al. 10.1016/j.earscirev.2023.104485
- Assimilation of future SWOT-based river elevations, surface extent observations and discharge estimations into uncertain global hydrological models S. Wongchuig-Correa et al. 10.1016/j.jhydrol.2020.125473
- A Framework for Estimating Global River Discharge From the Surface Water and Ocean Topography Satellite Mission M. Durand et al. 10.1029/2021WR031614
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- Generation and analysis of stage-fall-discharge laws from coupled hydrological-hydraulic river network model integrating sparse multi-satellite data T. Malou et al. 10.1016/j.jhydrol.2021.126993
- Streamflow simulation in poorly gauged basins with regionalised assimilation using Kalman filter I. Georgievová et al. 10.1016/j.jhydrol.2023.129373
- Combining Landsat observations with hydrological modelling for improved surface water monitoring of small lakes A. Ogilvie et al. 10.1016/j.jhydrol.2018.08.076
34 citations as recorded by crossref.
- Remote Sensing of River Discharge: A Review and a Framing for the Discipline C. Gleason & M. Durand 10.3390/rs12071107
- River discharge estimation from radar altimetry: Assessment of satellite performance, river scales and methods E. Zakharova et al. 10.1016/j.jhydrol.2020.124561
- Improved modeling of Congo's hydrology for floods and droughts analysis and ENSO teleconnections S. Wongchuig et al. 10.1016/j.ejrh.2023.101563
- Long-term total water storage change from a Satellite Water Cycle reconstruction over large southern Asian basins V. Pellet et al. 10.5194/hess-24-3033-2020
- Monitoring Water Diversity and Water Quality with Remote Sensing and Traits A. Lausch et al. 10.3390/rs16132425
- Underlying Fundamentals of Kalman Filtering for River Network Modeling C. Emery et al. 10.1175/JHM-D-19-0084.1
- Assimilation of transformed water surface elevation to improve river discharge estimation in a continental-scale river M. Revel et al. 10.5194/hess-27-647-2023
- Amazon Hydrology From Space: Scientific Advances and Future Challenges A. Fassoni‐Andrade et al. 10.1029/2020RG000728
- The Copernicus Sentinel-6 mission: Enhanced continuity of satellite sea level measurements from space C. Donlon et al. 10.1016/j.rse.2021.112395
- Potentials and limitations of Sentinel-3 for river discharge assessment A. Tarpanelli et al. 10.1016/j.asr.2019.08.005
- Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces A. Lausch et al. 10.3390/rs12223690
- Remote Sensing of Geomorphodiversity Linked to Biodiversity—Part III: Traits, Processes and Remote Sensing Characteristics A. Lausch et al. 10.3390/rs14092279
- Discharge Estimation via Assimilation of Multisatellite-Based Discharge Products: Case Study Over the Amazon Basin C. Emery et al. 10.1109/LGRS.2020.3020285
- Estimation of the Madeira floodplain dynamics from 2008 to 2018 J. Guilhen et al. 10.3389/frwa.2022.952810
- Sentinel-2 high-resolution data for river discharge monitoring P. Filippucci et al. 10.1016/j.rse.2022.113255
- Assessing the Potential of Upcoming Satellite Altimeter Missions in Operational Flood Forecasting Systems A. Falck et al. 10.3390/rs13214459
- On the Use of Satellite Remote Sensing to Detect Floods and Droughts at Large Scales T. Lopez et al. 10.1007/s10712-020-09618-0
- Constraining Remote River Discharge Estimation Using Reach‐Scale Geomorphology C. Brinkerhoff et al. 10.1029/2020WR027949
- Combining Optical Remote Sensing, McFLI Discharge Estimation, Global Hydrologic Modeling, and Data Assimilation to Improve Daily Discharge Estimates Across an Entire Large Watershed Y. Ishitsuka et al. 10.1029/2020WR027794
- Global patterns in river water storage dependent on residence time E. Collins et al. 10.1038/s41561-024-01421-5
- Assimilation of wide-swath altimetry water elevation anomalies to correct large-scale river routing model parameters C. Emery et al. 10.5194/hess-24-2207-2020
- Performance of Greywater Treatment Using Iron Removal Media (IRM) and Cattail Typha Angustifolia H. Hasan et al. 10.47836/pjst.30.2.32
- Estimating River Discharge With Swath Altimetry: A Proof of Concept Using AirSWOT Observations S. Tuozzolo et al. 10.1029/2018GL080771
- Extending the historical in situ gauge network over Indian river reaches utilizing the Surface Water and Ocean Topography (SWOT) mission M. Soman & J. Indu 10.1080/02626667.2024.2368755
- A review of remote sensing applications for water security: Quantity, quality, and extremes I. Chawla et al. 10.1016/j.jhydrol.2020.124826
- Exploring the Factors Controlling the Error Characteristics of the Surface Water and Ocean Topography Mission Discharge Estimates R. Frasson et al. 10.1029/2020WR028519
- Inland Surface Waters Quantity Monitored from Remote Sensing J. Cretaux et al. 10.1007/s10712-023-09803-x
- Channel Water Storage Anomaly: A New Remotely Sensed Quantity for Global River Analysis S. Coss et al. 10.1029/2022GL100185
- A review of globally available data sources for modelling the Water-Energy-Food Nexus J. Lodge et al. 10.1016/j.earscirev.2023.104485
- Assimilation of future SWOT-based river elevations, surface extent observations and discharge estimations into uncertain global hydrological models S. Wongchuig-Correa et al. 10.1016/j.jhydrol.2020.125473
- A Framework for Estimating Global River Discharge From the Surface Water and Ocean Topography Satellite Mission M. Durand et al. 10.1029/2021WR031614
- Global River Radar Altimetry Time Series (GRRATS): new river elevation earth science data records for the hydrologic community S. Coss et al. 10.5194/essd-12-137-2020
- Generation and analysis of stage-fall-discharge laws from coupled hydrological-hydraulic river network model integrating sparse multi-satellite data T. Malou et al. 10.1016/j.jhydrol.2021.126993
- Streamflow simulation in poorly gauged basins with regionalised assimilation using Kalman filter I. Georgievová et al. 10.1016/j.jhydrol.2023.129373
Latest update: 23 Nov 2024
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.
This study uses remotely sensed river discharge data to correct river storage and discharge in a...