Articles | Volume 22, issue 2
https://doi.org/10.5194/hess-22-1453-2018
© 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-22-1453-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Informing a hydrological model of the Ogooué with multi-mission remote sensing data
Department of Environmental Engineering, Technical University of
Denmark, Technical University of Denmark, 2800 Kgs. Lyngby,
Denmark
Karina Nielsen
National Space Institute, Technical University of Denmark,
2800 Kgs. Lyngby, Denmark
Christian Tøttrup
DHI-GRAS, 2970 Hørsholm, Denmark
Peter Bauer-Gottwein
Department of Environmental Engineering, Technical University of
Denmark, Technical University of Denmark, 2800 Kgs. Lyngby,
Denmark
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33 citations as recorded by crossref.
- A systematic review of Muskingum flood routing techniques A. Salvati et al. 10.1080/02626667.2024.2324132
- Comparing single and multi-objective hydrologic model calibration considering reservoir inflow and streamflow observations J. Bomhof et al. 10.1080/07011784.2019.1623077
- Hydro-climatology study of the Ogooué River basin using hydrological modeling and satellite altimetry S. Bogning et al. 10.1016/j.asr.2020.03.045
- Learning from satellite observations: increased understanding of catchment processes through stepwise model improvement P. Hulsman et al. 10.5194/hess-25-957-2021
- Using Remote Sensing Data‐Based Hydrological Model Calibrations for Predicting Runoff in Ungauged or Poorly Gauged Catchments Q. Huang et al. 10.1029/2020WR028205
- Sentinel-3 radar altimetry for river monitoring – a catchment-scale evaluation of satellite water surface elevation from Sentinel-3A and Sentinel-3B C. Kittel et al. 10.5194/hess-25-333-2021
- Developing a Baseline Characterization of River Bathymetry and Time-Varying Height for Chindwin River in Myanmar Using SRTM and Landsat Data I. Bose et al. 10.1061/(ASCE)HE.1943-5584.0002126
- Application of Spatially Distributed Calibrated Hydrological Model in Evapotranspiration Simulation of Three Gorges Reservoir Area of China: A Case Study in the Madu River Basin J. Chen et al. 10.1007/s11769-022-1318-9
- Multisource remote sensing data facilitate ecohydrological simulations without runoff calibration D. Yang et al. 10.1002/hyp.14773
- On the contribution of remote sensing-based calibration to model hydrological and hydraulic processes in tropical regions A. Meyer Oliveira et al. 10.1016/j.jhydrol.2021.126184
- River levels from multi mission altimetry, a statistical approach K. Nielsen et al. 10.1016/j.rse.2021.112876
- Ecohydrologic model with satellite-based data for predicting streamflow in ungauged basins J. Choi et al. 10.1016/j.scitotenv.2023.166617
- Investigating links between rainfall variations in the Ogooué River basin and ENSO in the Pacific Ocean over the period 1940–1999 S. Bogning et al. 10.5194/piahs-384-181-2021
- Inland Surface Waters Quantity Monitored from Remote Sensing J. Cretaux et al. 10.1007/s10712-023-09803-x
- On the capacity of ICESat-2 laser altimetry for river level retrieval: An investigation in the Ohio River basin H. Li et al. 10.1016/j.jhydrol.2023.130277
- Short-term trends in Africa's freshwater resources: Rates and drivers M. Ahmed & D. Wiese 10.1016/j.scitotenv.2019.133843
- Validation of Sentinel-6MF based lake levels – An assessment with in situ data and other satellite altimetry data B. Nilsson & K. Nielsen 10.1016/j.asr.2024.04.006
- Informing hydrological models of poorly gauged river catchments – A parameter regionalization and calibration approach C. Kittel et al. 10.1016/j.jhydrol.2020.124999
- Numerical daemons of hydrological models are summoned by extreme precipitation P. La Follette et al. 10.5194/hess-25-5425-2021
- Statistical evaluation of Jason-2 satellite altimetry products in a trans-boundary river basin; the case study of the White Volta River basin in Ghana S. Darko et al. 10.1007/s40808-022-01655-5
- Contrasting physical erosion rates in cratonic catchments: The Ogooué and Mbei rivers, Western Central Africa V. Regard et al. 10.1016/j.gr.2024.10.013
- Estimating Reservoir Release Using Multi-Source Satellite Datasets and Hydrological Modeling Techniques Y. Shen et al. 10.3390/rs14040815
- Improving glacio-hydrological model calibration and model performance in cold regions using satellite snow cover data B. Mohammadi et al. 10.1007/s13201-024-02102-9
- Assessing Freshwater Changes over Southern and Central Africa (2002–2017) I. Kalu et al. 10.3390/rs13132543
- Using altimetry observations combined with GRACE to select parameter sets of a hydrological model in a data-scarce region P. Hulsman et al. 10.5194/hess-24-3331-2020
- Hydraulic Model Calibration Using CryoSat‐2 Observations in the Zambezi Catchment C. Kittel et al. 10.1029/2020WR029261
- Development of Rainfall-Runoff Models for Sustainable Stormwater Management in Urbanized Catchments B. Szeląg et al. 10.3390/w14131997
- Evaluation of Sentinel-3 SRAL SAR altimetry over Chinese rivers L. Jiang et al. 10.1016/j.rse.2019.111546
- Design discharge estimation in small and ungauged basins: EBA4SUB framework sensitivity analysis A. Petroselli et al. 10.4081/jae.2020.1040
- Contrasted Chemical Weathering Rates in Cratonic Basins: The Ogooué and Mbei Rivers, Western Central Africa J. Moquet et al. 10.3389/frwa.2020.589070
- On the Performance of Sentinel‐3 Altimetry Over New Reservoirs: Approaches to Determine Onboard A Priori Elevation X. Zhang et al. 10.1029/2020GL088770
- Flow regime changes in the Lancang River, revealed by integrated modeling with multiple Earth observation datasets X. Zhang et al. 10.1016/j.scitotenv.2022.160656
- Improved Lake Level Estimation From Radar Altimeter Using an Automatic Multiscale-Based Peak Detection Retracker J. Chen et al. 10.1109/JSTARS.2020.3035686
Latest update: 06 Dec 2024
Short summary
In this study, we integrate free, global Earth observations in a user-friendly and flexible model to reliably characterize an otherwise unmonitored river basin. The proposed model is the best baseline characterization of the Ogooué basin in light of available observations. Furthermore, the study shows the potential of using new, publicly available Earth observations and a suitable model structure to obtain new information in poorly monitored or remote areas and to support user requirements.
In this study, we integrate free, global Earth observations in a user-friendly and flexible...