Articles | Volume 24, issue 6
https://doi.org/10.5194/hess-24-3331-2020
https://doi.org/10.5194/hess-24-3331-2020
Research article
 | 
30 Jun 2020
Research article |  | 30 Jun 2020

Using altimetry observations combined with GRACE to select parameter sets of a hydrological model in a data-scarce region

Petra Hulsman, Hessel C. Winsemius, Claire I. Michailovsky, Hubert H. G. Savenije, and Markus Hrachowitz

Related authors

On the importance of plant phenology in the evaporative process of a semi-arid woodland: could it be why satellite-based evaporation estimates in the miombo differ?
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024,https://doi.org/10.5194/hess-28-3633-2024, 2024
Short summary
High-resolution (1 km) all-sky net radiation over Europe enabled by the merging of land surface temperature retrievals from geostationary and polar-orbiting satellites
Dominik Rains, Isabel Trigo, Emanuel Dutra, Sofia Ermida, Darren Ghent, Petra Hulsman, Jose Gómez-Dans, and Diego G. Miralles
Earth Syst. Sci. Data, 16, 567–593, https://doi.org/10.5194/essd-16-567-2024,https://doi.org/10.5194/essd-16-567-2024, 2024
Short summary
On the importance of phenology in the Miombo ecosystem: Evaluation of open-source satellite evaporation models
Henry Zimba, Miriam Coenders-Gerrits, Kawawa Banda, Petra Hulsman, Nick van de Giesen, Imasiku Nyambe, and Hubert Savenije
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-114,https://doi.org/10.5194/hess-2022-114, 2022
Manuscript not accepted for further review
Short summary
Learning from satellite observations: increased understanding of catchment processes through stepwise model improvement
Petra Hulsman, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 25, 957–982, https://doi.org/10.5194/hess-25-957-2021,https://doi.org/10.5194/hess-25-957-2021, 2021
Short summary
Rainfall-runoff modelling using river-stage time series in the absence of reliable discharge information: a case study in the semi-arid Mara River basin
Petra Hulsman, Thom A. Bogaard, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 22, 5081–5095, https://doi.org/10.5194/hess-22-5081-2018,https://doi.org/10.5194/hess-22-5081-2018, 2018
Short summary

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Exploring the potential processes controlling changes in precipitation–runoff relationships in non-stationary environments
Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 29, 903–924, https://doi.org/10.5194/hess-29-903-2025,https://doi.org/10.5194/hess-29-903-2025, 2025
Short summary
A diversity-centric strategy for the selection of spatio-temporal training data for LSTM-based streamflow forecasting
Everett Snieder and Usman T. Khan
Hydrol. Earth Syst. Sci., 29, 785–798, https://doi.org/10.5194/hess-29-785-2025,https://doi.org/10.5194/hess-29-785-2025, 2025
Short summary
Simulating the Tone River eastward diversion project in Japan carried out 4 centuries ago
Joško Trošelj and Naota Hanasaki
Hydrol. Earth Syst. Sci., 29, 753–766, https://doi.org/10.5194/hess-29-753-2025,https://doi.org/10.5194/hess-29-753-2025, 2025
Short summary
Lack of robustness of hydrological models: a large-sample diagnosis and an attempt to identify hydrological and climatic drivers
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 29, 683–700, https://doi.org/10.5194/hess-29-683-2025,https://doi.org/10.5194/hess-29-683-2025, 2025
Short summary
Achieving water budget closure through physical hydrological process modelling: insights from a large-sample study
Xudong Zheng, Dengfeng Liu, Shengzhi Huang, Hao Wang, and Xianmeng Meng
Hydrol. Earth Syst. Sci., 29, 627–653, https://doi.org/10.5194/hess-29-627-2025,https://doi.org/10.5194/hess-29-627-2025, 2025
Short summary

Cited articles

Abas, I.: Remote river rating in Zambia: A case study in the Luangwa river basin, Master of Science, Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands, 2018. 
Ajami, N. K., Gupta, H., Wagener, T., and Sorooshian, S.: Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system, J. Hydrol., 298, 112–135, https://doi.org/10.1016/j.jhydrol.2004.03.033, 2004. 
Bai, P., Liu, X., and Liu, C.: Improving hydrological simulations by incorporating GRACE data for model calibration, J. Hydrol., 557, 291–304, https://doi.org/10.1016/j.jhydrol.2017.12.025, 2018. 
Bauer-Gottwein, P., Jensen, I. H., Guzinski, R., Bredtoft, G. K. T., Hansen, S., and Michailovsky, C. I.: Operational river discharge forecasting in poorly gauged basins: the Kavango River basin case study, Hydrol. Earth Syst. Sci., 19, 1469–1485, https://doi.org/10.5194/hess-19-1469-2015, 2015. 
Beilfuss, R. and dos Santos, D.: Patterns of Hydrological Change in the Zambezi Delta, Mozambique, in: Working Paper #2 Program for the Sustainable Management of Cahora Bassa Dam and the Lower Zambezi Valley, International Crane Foundation, Sofala, Mozambique, 2001. 
Download
Short summary
In the absence of discharge data in ungauged basins, remotely sensed river water level data, i.e. altimetry, may provide valuable information to calibrate hydrological models. This study illustrated that for large rivers in data-scarce regions, river altimetry data from multiple locations combined with GRACE data have the potential to fill this gap when combined with estimates of the river geometry, thereby allowing a step towards more reliable hydrological modelling in data-scarce regions.
Share