Articles | Volume 20, issue 7
https://doi.org/10.5194/hess-20-2827-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-20-2827-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Assimilation of SMOS soil moisture into a distributed hydrological model and impacts on the water cycle variables over the Ouémé catchment in Benin
Delphine J. Leroux
CORRESPONDING AUTHOR
CNES, LTHE, Laboratoire d'Étude des Transferts en Hydrologie et Environnement, Grenoble, France
CNRS, CESBIO, Centre d'Etudes Spatiales de la Biosphère, Toulouse, France
Thierry Pellarin
University Grenoble Alpes, LTHE, Grenoble, France
CNRS, LTHE, Grenoble, France
Théo Vischel
University Grenoble Alpes, LTHE, Grenoble, France
Jean-Martial Cohard
University Grenoble Alpes, LTHE, Grenoble, France
Tania Gascon
University Grenoble Alpes, LTHE, Grenoble, France
François Gibon
University Grenoble Alpes, LTHE, Grenoble, France
Arnaud Mialon
CNRS, CESBIO, Centre d'Etudes Spatiales de la Biosphère, Toulouse, France
Sylvie Galle
University Grenoble Alpes, LTHE, Grenoble, France
IRD, LTHE, Grenoble, France
Christophe Peugeot
IRD, HydroSciences, Montpellier, France
Luc Seguis
IRD, HydroSciences, Montpellier, France
Viewed
Total article views: 3,090 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 19 Jan 2016)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
1,754 | 1,232 | 104 | 3,090 | 106 | 121 |
- HTML: 1,754
- PDF: 1,232
- XML: 104
- Total: 3,090
- BibTeX: 106
- EndNote: 121
Total article views: 2,393 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 14 Jul 2016)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
1,435 | 860 | 98 | 2,393 | 96 | 109 |
- HTML: 1,435
- PDF: 860
- XML: 98
- Total: 2,393
- BibTeX: 96
- EndNote: 109
Total article views: 697 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 19 Jan 2016)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
319 | 372 | 6 | 697 | 10 | 12 |
- HTML: 319
- PDF: 372
- XML: 6
- Total: 697
- BibTeX: 10
- EndNote: 12
Cited
36 citations as recorded by crossref.
- Observations of an Extreme Atmospheric River Storm With a Diverse Sensor Network B. Hatchett et al. 10.1029/2020EA001129
- The soil moisture data bank: The ground-based, model-based, and satellite-based soil moisture data A. Tavakol et al. 10.1016/j.rsase.2021.100649
- Improving the Predictive Skill of a Distributed Hydrological Model by Calibration on Spatial Patterns With Multiple Satellite Data Sets M. Dembélé et al. 10.1029/2019WR026085
- Unsupervised ensemble Kalman filtering with an uncertain constraint for land hydrological data assimilation M. Khaki et al. 10.1016/j.jhydrol.2018.06.080
- The application of multi-mission satellite data assimilation for studying water storage changes over South America M. Khaki & J. Awange 10.1016/j.scitotenv.2018.08.079
- Estimating the drainage rate from surface soil moisture drydowns: Application of DfD model to in situ soil moisture data E. Jalilvand et al. 10.1016/j.jhydrol.2018.08.035
- SMOS Neural Network Soil Moisture Data Assimilation in a Land Surface Model and Atmospheric Impact N. Rodríguez-Fernández et al. 10.3390/rs11111334
- Comprehensive propagation characteristics between paired meteorological and hydrological drought events: Insights from various underlying surfaces J. Chen et al. 10.1016/j.atmosres.2023.107193
- Toward a Surface Soil Moisture Product at High Spatiotemporal Resolution: Temporally Interpolated, Spatially Disaggregated SMOS Data Y. Malbéteau et al. 10.1175/JHM-D-16-0280.1
- Monitoring water storage decline over the Middle East M. Khaki & I. Hoteit 10.1016/j.jhydrol.2021.127166
- The Impact of Satellite Soil Moisture Data Assimilation on the Hydrological Modeling of SWAT in a Highly Disturbed Catchment Y. Liu et al. 10.3390/rs16020429
- Improved Understanding of the Link Between Catchment‐Scale Vegetation Accessible Storage and Satellite‐Derived Soil Water Index L. Bouaziz et al. 10.1029/2019WR026365
- Integrating satellite soil-moisture estimates and hydrological model products over Australia M. Khaki et al. 10.1080/08120099.2019.1620855
- Assessing data assimilation frameworks for using multi-mission satellite products in a hydrological context M. Khaki et al. 10.1016/j.scitotenv.2018.08.032
- Improving hydrological simulations by incorporating GRACE data for model calibration P. Bai et al. 10.1016/j.jhydrol.2017.12.025
- Remote Sensed and/or Global Datasets for Distributed Hydrological Modelling: A Review M. Ali et al. 10.3390/rs15061642
- Mapping paddy rice agriculture over China using AMSR-E time series data P. Song et al. 10.1016/j.isprsjprs.2018.08.015
- Integrated Multisource Data Assimilation and NSGA-II Multiobjective Optimization Framework for Streamflow Simulations M. Bahrami et al. 10.1061/JHYEFF.HEENG-6263
- Reducing False Flood Warnings of TRMM Rain Rates Thresholds over Riyadh City, Saudi Arabia by Utilizing AMSR-E Soil Moisture Information A. Tekeli & H. Fouli 10.1007/s11269-017-1573-1
- Ecohydrologic model with satellite-based data for predicting streamflow in ungauged basins J. Choi et al. 10.1016/j.scitotenv.2023.166617
- Stronger influences of grassland growth than grassland area on hydrological processes in the source region of the Yellow River H. Zhan et al. 10.1016/j.jhydrol.2024.131886
- On the assimilation set-up of ASCAT soil moisture data for improving streamflow catchment simulation J. Loizu et al. 10.1016/j.advwatres.2017.10.034
- Improved modelling of a Prairie catchment using a progressive two-stage calibration strategy with in situ soil moisture and streamflow data S. Budhathoki et al. 10.2166/nh.2020.109
- Soil moisture assimilation in urban watersheds: A method to identify the limiting imperviousness threshold based on watershed characteristics J. Leach & P. Coulibaly 10.1016/j.jhydrol.2020.124958
- Impacts of Introducing Remote Sensing Soil Moisture in Calibrating a Distributed Hydrological Model for Streamflow Simulation L. Xiong & L. Zeng 10.3390/w11040666
- Akşehir Gölü su seviyesinin çekilmesinin meteorolojik ve uydu verileri ile incelenmesi S. Dönmez 10.17341/gazimmfd.406790
- Impacts of Spatiotemporal Gaps in Satellite Soil Moisture Data on Hydrological Data Assimilation K. Mohammed et al. 10.3390/w15020321
- Soil Moisture Estimation for Winter-Wheat Waterlogging Monitoring by Assimilating Remote Sensing Inversion Data into the Distributed Hydrology Soil Vegetation Model X. Zhang et al. 10.3390/rs14030792
- SMOS brightness temperature assimilation into the Community Land Model D. Rains et al. 10.5194/hess-21-5929-2017
- Calibrating land hydrological models and enhancing their forecasting skills using an ensemble Kalman filter with one-step-ahead smoothing M. Khaki et al. 10.1016/j.jhydrol.2020.124708
- Effect of provenance on population structure and regeneration of six multiple-use tree species along Ouémé catchment in Benin: Implications for conservation B. Lokonon et al. 10.1016/j.tfp.2022.100206
- Data Assimilation of Satellite-Based Soil Moisture into a Distributed Hydrological Model for Streamflow Predictions N. Jadidoleslam et al. 10.3390/hydrology8010052
- Simulation of surface energy fluxes and meteorological variables using the Regional Atmospheric Modeling System (RAMS): Evaluating the impact of land-atmosphere coupling on short-term forecasts I. Gómez et al. 10.1016/j.agrformet.2017.10.027
- A multi-objective calibration approach using in-situ soil moisture data for improved hydrological simulation of the Prairies S. Budhathoki et al. 10.1080/02626667.2020.1715982
- Multi-Temporal Variabilities of Evapotranspiration Rates and Their Associations with Climate Change and Vegetation Greening in the Gan River Basin, China M. Bai et al. 10.3390/w11122568
- Multi-mission satellite remote sensing data for improving land hydrological models via data assimilation M. Khaki et al. 10.1038/s41598-020-75710-5
36 citations as recorded by crossref.
- Observations of an Extreme Atmospheric River Storm With a Diverse Sensor Network B. Hatchett et al. 10.1029/2020EA001129
- The soil moisture data bank: The ground-based, model-based, and satellite-based soil moisture data A. Tavakol et al. 10.1016/j.rsase.2021.100649
- Improving the Predictive Skill of a Distributed Hydrological Model by Calibration on Spatial Patterns With Multiple Satellite Data Sets M. Dembélé et al. 10.1029/2019WR026085
- Unsupervised ensemble Kalman filtering with an uncertain constraint for land hydrological data assimilation M. Khaki et al. 10.1016/j.jhydrol.2018.06.080
- The application of multi-mission satellite data assimilation for studying water storage changes over South America M. Khaki & J. Awange 10.1016/j.scitotenv.2018.08.079
- Estimating the drainage rate from surface soil moisture drydowns: Application of DfD model to in situ soil moisture data E. Jalilvand et al. 10.1016/j.jhydrol.2018.08.035
- SMOS Neural Network Soil Moisture Data Assimilation in a Land Surface Model and Atmospheric Impact N. Rodríguez-Fernández et al. 10.3390/rs11111334
- Comprehensive propagation characteristics between paired meteorological and hydrological drought events: Insights from various underlying surfaces J. Chen et al. 10.1016/j.atmosres.2023.107193
- Toward a Surface Soil Moisture Product at High Spatiotemporal Resolution: Temporally Interpolated, Spatially Disaggregated SMOS Data Y. Malbéteau et al. 10.1175/JHM-D-16-0280.1
- Monitoring water storage decline over the Middle East M. Khaki & I. Hoteit 10.1016/j.jhydrol.2021.127166
- The Impact of Satellite Soil Moisture Data Assimilation on the Hydrological Modeling of SWAT in a Highly Disturbed Catchment Y. Liu et al. 10.3390/rs16020429
- Improved Understanding of the Link Between Catchment‐Scale Vegetation Accessible Storage and Satellite‐Derived Soil Water Index L. Bouaziz et al. 10.1029/2019WR026365
- Integrating satellite soil-moisture estimates and hydrological model products over Australia M. Khaki et al. 10.1080/08120099.2019.1620855
- Assessing data assimilation frameworks for using multi-mission satellite products in a hydrological context M. Khaki et al. 10.1016/j.scitotenv.2018.08.032
- Improving hydrological simulations by incorporating GRACE data for model calibration P. Bai et al. 10.1016/j.jhydrol.2017.12.025
- Remote Sensed and/or Global Datasets for Distributed Hydrological Modelling: A Review M. Ali et al. 10.3390/rs15061642
- Mapping paddy rice agriculture over China using AMSR-E time series data P. Song et al. 10.1016/j.isprsjprs.2018.08.015
- Integrated Multisource Data Assimilation and NSGA-II Multiobjective Optimization Framework for Streamflow Simulations M. Bahrami et al. 10.1061/JHYEFF.HEENG-6263
- Reducing False Flood Warnings of TRMM Rain Rates Thresholds over Riyadh City, Saudi Arabia by Utilizing AMSR-E Soil Moisture Information A. Tekeli & H. Fouli 10.1007/s11269-017-1573-1
- Ecohydrologic model with satellite-based data for predicting streamflow in ungauged basins J. Choi et al. 10.1016/j.scitotenv.2023.166617
- Stronger influences of grassland growth than grassland area on hydrological processes in the source region of the Yellow River H. Zhan et al. 10.1016/j.jhydrol.2024.131886
- On the assimilation set-up of ASCAT soil moisture data for improving streamflow catchment simulation J. Loizu et al. 10.1016/j.advwatres.2017.10.034
- Improved modelling of a Prairie catchment using a progressive two-stage calibration strategy with in situ soil moisture and streamflow data S. Budhathoki et al. 10.2166/nh.2020.109
- Soil moisture assimilation in urban watersheds: A method to identify the limiting imperviousness threshold based on watershed characteristics J. Leach & P. Coulibaly 10.1016/j.jhydrol.2020.124958
- Impacts of Introducing Remote Sensing Soil Moisture in Calibrating a Distributed Hydrological Model for Streamflow Simulation L. Xiong & L. Zeng 10.3390/w11040666
- Akşehir Gölü su seviyesinin çekilmesinin meteorolojik ve uydu verileri ile incelenmesi S. Dönmez 10.17341/gazimmfd.406790
- Impacts of Spatiotemporal Gaps in Satellite Soil Moisture Data on Hydrological Data Assimilation K. Mohammed et al. 10.3390/w15020321
- Soil Moisture Estimation for Winter-Wheat Waterlogging Monitoring by Assimilating Remote Sensing Inversion Data into the Distributed Hydrology Soil Vegetation Model X. Zhang et al. 10.3390/rs14030792
- SMOS brightness temperature assimilation into the Community Land Model D. Rains et al. 10.5194/hess-21-5929-2017
- Calibrating land hydrological models and enhancing their forecasting skills using an ensemble Kalman filter with one-step-ahead smoothing M. Khaki et al. 10.1016/j.jhydrol.2020.124708
- Effect of provenance on population structure and regeneration of six multiple-use tree species along Ouémé catchment in Benin: Implications for conservation B. Lokonon et al. 10.1016/j.tfp.2022.100206
- Data Assimilation of Satellite-Based Soil Moisture into a Distributed Hydrological Model for Streamflow Predictions N. Jadidoleslam et al. 10.3390/hydrology8010052
- Simulation of surface energy fluxes and meteorological variables using the Regional Atmospheric Modeling System (RAMS): Evaluating the impact of land-atmosphere coupling on short-term forecasts I. Gómez et al. 10.1016/j.agrformet.2017.10.027
- A multi-objective calibration approach using in-situ soil moisture data for improved hydrological simulation of the Prairies S. Budhathoki et al. 10.1080/02626667.2020.1715982
- Multi-Temporal Variabilities of Evapotranspiration Rates and Their Associations with Climate Change and Vegetation Greening in the Gan River Basin, China M. Bai et al. 10.3390/w11122568
- Multi-mission satellite remote sensing data for improving land hydrological models via data assimilation M. Khaki et al. 10.1038/s41598-020-75710-5
Saved (preprint)
Latest update: 04 Nov 2024
Short summary
Water is one of the most valuable resources and has an undeniable influence on every aspect of life. Being a very good indicator of the water cycle, the soil water content can be monitored by satellites from space. The region studied here is located in Benin, West Africa, where people have to face major water-related risks every year during the monsoon season. By adjusting the model simulations with satellite observations, river discharge and water table levels have greatly been improved.
Water is one of the most valuable resources and has an undeniable influence on every aspect of...