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River discharge monitoring is crucial for many activities ranging from the management of water resources to flood risk mitigation. Due to the limitations of the in situ stations (e.g., low station density, incomplete temporal coverage as well as delays in data access), the river discharge is not always continuously monitored in time and in space. This prompted researchers and space agencies, among others, in developing new methods based on satellite observations for the river discharge estimation. In the last year, ESA has funded the SaTellite based Runoff Evaluation And Mapping and River Discharge Estimation (STREAMRIDE) project, which proposes the combination of two innovative and complementary approaches, STREAM and RIDESAT, that use almost exclusively satellite data for estimating river discharge. In particular, precipitation, soil moisture and terrestrial water storage observations are used within a simple and conceptual parsimonious approach (STREAM) to estimate runoff, whereas altimeter and Near InfraRed (NIR) sensors are jointly exploited to derive river discharge within RIDESAT. By modelling different processes that act at the basin or at local scale, the combination of STREAM and RIDESAT is able to provide less than 3-day temporal resolution river discharge estimates in many large rivers of the world (e.g., Mississippi, Amazon, Danube, Po), where the single approaches fail. Indeed, even if both the approaches demonstrated high capability to estimate accurate river discharge at multiple cross sections, they are not optimal under certain conditions such as in presence of densely vegetated and mountainous areas or in non-natural basins with high anthropogenic impact (i.e., in basin where the flow is regulated by the presence of dams, reservoirs or floodplains along the river; or in highly irrigated areas). Here, we present some new advancements of both STREAM and RIDESAT approaches which help to overcome the limitations encountered. In particular, specific modules (e.g., reservoir or irrigation modules for STREAM approach) as well as improvements in the retrieval algorithm (e.g., to take in account the contribution of the river sediment load and vegetation for RIDESAT algorithm) were implemented. Furthermore, in order to exploit the complementarity of the two approaches, the two river discharge estimates were also integrated within a simple data integration framework and evaluated over sites located on the Amazon and Mississippi river basins. Results demonstrated the added-value of a complementary river discharge estimate with respect to a stand-alone estimate.

The Copernicus Sentinel-3 Surface Topography Mission (STM), based on a constellation of two satellites, provides extremely valuable surface elevation information over inland waters, sea ice and land ice, thanks to its SAR altimeter which retrieves high-resolution along-track elevation measurements, and to its orbit that covers high-latitude polar regions. To ensure that these measurements can be used with confidence, and to maximize the return on investment of the Copernicus Sentinel-3 STM, adequate validation of the geophysical retrieval methods, processing algorithms and corrections must be performed, considering independent observations as Reference Measurements. St3TART is an EU and ESA funded project led by NOVELTIS with a consortium of 17 European partners (CNES, DTU, NPI, vorteX.io, LEGOS, Hydro Matters, CLS, LOCEAN, IGE, SERTIT, GIS, CNR-IRPI, NPL, DT/INSU, IRD, M2C, SYRTE). It aims to generalize the concept of Fiducial Reference Measurements (FRM) for the Copernicus Sentinel-3 STM and to collect and distribute FRM data for the validation of the satellite mission over inland waters, sea ice and land ice. The provision of FRM will serve the validation activities of the ESA S3 Land Altimetry products, currently performed by the Sentinel-3 Mission Performance Centre, with the support of the Sentinel-3 Validation Team, for the sake of performance assessment and fitness-for-purpose of the Sentinel-3 STM Land core products. Those products cover inland waters, land-ice and sea-ice areas. The objective of the St3TART project is not only to collect existing data or measure new observations during field campaigns, but to ensure that these observations meet the criteria of FRM standards and can be used in an operational way for the validation of the Sentinel-3 Land topography mission. Within the project, field campaigns are means to provide operational observations for the validation of the Sentinel-3 data. One of the tasks of the project is the development of a Super Cal/Val Site Identifier Tool (SCalSIT). This tool will support the Cal/Val community and scientists in identifying potential in-situ Cal/Val sites over Inland Water Surfaces, by an appropriate cross-processing of the satellite orbits versus water mask ground data. The tool is configurable, to take into account a specific geographic area, a list of satellite orbits (theorical or user orbit products), a land water mask, the percentage of surface water occurrence, a buffer around the satellite tracks, and the minimum number of passes over a crossover. The output vector files can be in KML, CSV or GeoJSON formats. It has been developed for the needs of the Sentinel-3 Surface Topography Mission constellation, but its generic implementation makes it compatible with other missions such as CryoSat-2, Sentinel-6 or SWOT. The SCalSIT software is an open-source software, developed as a QGIS plugin, which makes it very easy to use and platform-independent, and it can also be used via a Command Line Interface. The poster will present the main characteristics of the tool and an example of outputs.

The Copernicus Sentinel-3 Surface Topography Mission (STM) provides extremely valuable surface elevation information over inland waters, sea ice and land ice, thanks to its SAR altimeter which retrieves high-resolution along-track elevation measurements, and to its orbit that covers high-latitude polar regions. To ensure that these measurements can be used with confidence, and to maximize the return on investment of the Copernicus Sentinel-3 STM, adequate validation of the geophysical retrieval methods, processing algorithms and corrections must be performed, considering independent observations as Reference Measurements. St3TART is an EU and ESA funded project led by NOVELTIS with a consortium of 17 European partners (CNES, DTU, NPI, vorteX.io, LEGOS, Hydro Matters, CLS, LOCEAN, IGE, SERTIT, GIS, CNR-IRPI, NPL, DT/INSU, IRD, M2C, SYRTE). It aims to generalize the concept of Fiducial Reference Measurements (FRM) for the Copernicus Sentinel-3 STM and to collect and distribute FRM data for the validation of the satellite mission over inland waters, sea ice and land ice. The provision of FRM will serve the validation activities of the ESA S3 Land Altimetry products, currently performed by the Sentinel-3 Mission Performance Centre, with the support of the Sentinel-3 Validation Team, for the sake of performance assessment and fitness-for-purpose of the Sentinel-3 STM Land core products. Those products cover inland waters, land-ice and sea-ice areas. The objective of the St3TART project is not only to collect existing data or measure new observations during field campaigns, but to ensure that these observations meet the criteria of FRM standards and can be used in an operational way for the validation of the Sentinel-3 Land topography mission. The FRM Data Hub will provide a centralized access to these FRM measurements. It aims to federate the Cal/Val community in sharing these reference observations in a free and accessible manner, with fully characterized and documented FRM processing and measurements. The poster will present the architecture of the tool, its interface, the first available datasets and the format specification.

Determining the spatiotemporal variability in the annual streamflow volume plays a relevant role in hydrology with regard to improving and implementing sustainable and resilient policies and practices of water resource management. This study investigates annual streamflow volume trends in a newly assembled, consolidated, and validated data set of daily mean river flow records from more than 3000 stations which cover near-natural basins in more than 40 countries across Europe. Although the data set contains streamflow time series from 1900 to 2013 in some stations, the statistical analyses were carried out by including observations from 1950 to 2013 in order to have a consistent and reliable data set over the continent. Trends were detected by calculating the slope of the Theil–Sen line over the annual anomalies of streamflow volume. The results show that annual streamflow volume trends have emerged at European scale, with a marked negative tendency in Mediterranean regions, with about -1×103 m3/(km2 yr−2), and a generally positive trend in northern ones, with about 0.5×103 m3/(km−2 yr−2). The annual streamflow volume trend patterns appear to be in agreement with the continental-scale meteorological observations in response to climate change drivers. In the Mediterranean area, the decline of annual streamflow volumes started in 1965, and since the early 1980s, volumes have consistently been lower than the 1950–2013 average. The spatiotemporal annual streamflow volume patterns observed in this work can help to contextualize short-term trends and regional studies already available in the scientific literature, as well as to provide a valid benchmark for further accurate quantitative analysis of annual streamflow volumes.