2019 – 2022
The GEMS/Water Data Centre served as strategic partner in the GlobeWQ project, funded by the German Federal Ministry of Education and Research. The project was led by the Helmholtz Centre for Environmental Research (UFZ) in Magdeburg, Germany and developed a prototype for a water quality analysis and service platforms that integrates data from in situ monitoring, modelling and remote sensing to assess the water quality status, following the triangulation approach concept (see figure). Five pilot platforms were developed as part of the project:
• A platform for global rivers, providing information on fecal coliform bacteria, biological oxygen demand and total dissolved solids,
• A platform for European rivers, providing information on the nitrogen surplus in soil (total nitrogen inputs minus total nitrogen outputs),
• A platform for the Elbe river in Germany, providing information on oxygen concentration, temperature, chlorophyll a, algae blooms, turbidity, trophic state and absorption,
• A platform for Lake Sevan in Armenia, providing information on discharge, fecal coliform bacteria, biological oxygen demand, chlorophyll, turbidity and absorption,
• A platform for Lake Victoria, shared by Uganda, Kenya and the United Republic of Tanzania, providing information on total phosphorus, chlorophyll a, harmful algae blooms, turbidity and absorption.
These platforms are currently being migrated to a new server and should be available again by the end of January 2026. More information can be found on the project homepage.
In the final report published in 2023, the project group gives an overview on global trends and water quality hotspots with regard to fecal coliform bacteria, organic pollution, salinity and nitrate. Further chapters of the report are dedicated to trends in nitrogen surplus in Europe and a detailed discussion of the three case studies Elbe river, Lake Sevan and Lake Victoria.
Screenshot of the GlobeWQ online platform linking to the five pilots.
Triangular approach of the WWQA for the World Water Quality Assessment, combining in-situ-, modelling-, and remote sensing data.

