EGU24-10856, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-10856
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Toward a global scale runoff estimation through satellite observations: the STREAM model

Francesco Leopardi1,2, Luca Brocca2, Carla Saltalippi1, Jacopo Dari1,2, Karina Nielsen3, Nico Sneeuw4, Mohammad J. Tourian4, Marco Restano5, Jérôme Benveniste6, and Stefania Camici2
Francesco Leopardi et al.
  • 1Dept. of Civil and Environmental Engineering, University of Perugia, via G. Duranti 93, 06125 Perugia, Italy (francesco.leopardi@studenti.unipg.it)
  • 2National Research Council, Research Institute for Geohydrological Protection, Perugia, Italy
  • 3Division of Geodesy, National Space Institute, Technical University of Denmark
  • 4Institute of Geodesy, University of Stuttgart, Geschwister-Scholl-Straße 24D, 70174 Stuttgart, Germany
  • 5SERCO, ESA-ESRIN, Largo Galileo Galilei, Frascati, 00044, Italy
  • 6European Space Agency, ESA-ESRIN, Largo Galileo Galilei, Frascati, 00044, Italy

River discharge monitoring is critical for many activities ranging from water resource management to flood risk reduction. Due to limitations of in situ stations (e.g. low station density, incomplete temporal coverage and delays in data access), river discharge is not always continuously monitored in time and space. This has led researchers and space agencies, among others, to develop new methods based on satellite observations for estimating river discharge.

In recent years, ESA has funded the SaTellite-based Runoff Evaluation And Mapping (STREAM) and STREAM-NEXT projects, which propose to use satellite observations of precipitation, soil moisture and terrestrial water storage within a simple and conceptually parsimonious model, STREAM, to estimate runoff.

The model, applied to five large basins in the world (Mississippi-Missouri basin, Amazon basin, Danube basin, Murray-Darling basin and Niger basin)  has demonstrated a high ability to estimate runoff and river discharge in both natural and non-natural basins with a high anthropogenic impact (i.e. in basins where flow is regulated by the presence of dams, reservoirs or floodplains along the river; or in heavily irrigated areas). In particular, the good results obtained paved the way for the application of the STREAM approach on a global scale. For this purpose, the STREAM-NEXT project will generalise the STREAM model to make it applicable to more than forty basins worldwide. Depending on the availability of in situ discharge data, the selected basins shall be grouped into calibration and validation clusters. The purpose is to use the basins into the calibration cluster to tune the parameters of the regionalized STREAM model and apply the regionalised model parameters to the validation cluster basins to estimate the accuracy of the STREAM model.  Additional satellite observations, such as altimetric water levels, will be used to estimate the water stored in the reservoirs; gravimetric data with different spatial/temporal resolutions will be explored to investigate the impact of these data on the model results.

Finally, a calibration procedure and a regionalisation approach will be developed to make the STREAM model applicable to non-calibrated basins.

Here we present the STREAM-NEXT project and some preliminary results related to the generalization of the STREAM model framework. Different basins with different climate, topography and level of anthropisation will be selected to demonstrate the suitability of the approach for a global scale application. 

How to cite: Leopardi, F., Brocca, L., Saltalippi, C., Dari, J., Nielsen, K., Sneeuw, N., Tourian, M. J., Restano, M., Benveniste, J., and Camici, S.: Toward a global scale runoff estimation through satellite observations: the STREAM model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10856, https://doi.org/10.5194/egusphere-egu24-10856, 2024.