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Conference Paper

Estimating Daily Discharge of an Entire River Network Using Space-based SWOT Observations

Authors

Ke,  Siqi
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Tourian,  Mohammad
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Sneeuw,  Nico
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Paiva,  Rodrigo
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Durand,  Michael
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

David,  Cédric
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Citation

Ke, S., Tourian, M., Sneeuw, N., Paiva, R., Durand, M., David, C. (2023): Estimating Daily Discharge of an Entire River Network Using Space-based SWOT Observations, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-3878


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5020668
Abstract
Accurate estimates of river discharge are vital to quantify the amount of water resources. In view of the steadily declining in-situ gauge network hydrological monitoring through spaceborne sensors becomes a necessity. The SWOT mission is the first satellite to conduct a global survey of Earth's surface water. It can provide measurements such as water surface elevations, changes in cross-sectional areas, river widths, and slopes. As the SWOT data is sparse due to the 21 days orbit repeat period, we aim to develop a Kalman filter for continuous discharge estimation of an entire river network. To this end, we obtain the process model based on a physically based spatiotemporal correlation, which represents the correlation between the discharge values of river network in time and space. The observation model is derived from the discretization of the mass conservation equation, where the changes in cross-sectional areas are as the observations. The Kalman filter will be executed simultaneously in time and space domain to obtain daily discharges for river basins.The feasibility of the approach is verified by Pepsi2 data, which is a synthetic river dataset built for testing and development of the SWOT mission discharge algorithms. This method is also very promising for combining multiple data as from SWOT, nadir altimetry, imagery and in situ.