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SaTellite-based Run-off Evaluation And Mapping (STREAM)



Water is at the centre of economic and social development; it is vital to maintain health, grow food, and manage the environment. As over half of the world’s potable water supply is extracted from rivers, either directly or from reservoirs, understanding the variability of the stored water on and below landmasses, i.e. the Total Runoff, is of primary importance.

For this reason, the STREAM Project aims at developing an “observational” physically-based approach for deriving daily runoff estimates from satellite soil moisture (SM), precipitation (P) and terrestrial water storage anomalies (TWSA).

The Project will support multiple operational and scientific applications (from flood warning systems to the understanding of water cycle). On the one hand, it will allow fine-tuning a simple modelling framework that adequately forced with satellite observations is potentially suitable for global runoff monitoring at daily time scale. On the other hand, it will allow increasing knowledge on the natural processes, human activities and on their interactions on the land.

STREAM is also a feasibility study intended to answer the following research questions:

  1. To what extent satellite observations of precipitation, soil moisture and terrestrial water storage anomalies can provide reliable total runoff estimates?
  2. Is it possible to obtain a total runoff product with spatiotemporal resolutions beyond the one of GRACE and GRACE-FO measurements?
  3. Up to which spatiotemporal scales is this feasible and with which accuracy?

The quality assessment of STREAM total runoff estimates will be pursued at multiple pilot basins across the world (5 large basins + multiple sub-basins) characterised by different physiographic/climatic features in order to highlight the role of climatic conditions/basin characteristics on the reliability of STREAM modelling framework and identify the optimal space/time scale that provides the best compromise between total runoff product accuracy and resolution.

With respect to the state-of-the-art, the STREAM project proposes the following four innovative characteristics:

  1. The STREAM project will investigate the possibility to provide “model-independent” runoff estimates not relying on strong modelling assumptions;
  2. The STREAM runoff estimates will be derived solely from satellite observations;
  3. Differently from the available literature, the STREAM project will incorporate the fundamental role of soil moisture conditions in the runoff generation process;
  4. Beyond the use of off-the-shelf GRACE products (baseline), the STREAM project will explore finer spatial resolutions of sub-catchments by implementing tailored filters.

Moreover, the STREAM project will contribute in understanding how limiting factors (e.g. freshwater availability) affect processes on the land surface and how this can adequately be represented in prediction models.

The activity is led by CNR-IRPI with the participation of the Institute of Geodesy (GIS) at University of Stuttgart. The duration is of 12 months, until April 2020.



Prime contractor
  • Technical University of Denmark (DK)