hydroweb.next, an open-data WebGIS platform to bring state-of-the-art products derived from satellite remote sensing to hydrology users

The hydroweb.next platform is an open-data thematic hub for hydrology. It aims to foster new uses of remote sensing data for water applications by removing the main barriers: data formatting issues, dispersal of access points, and data processing costs,…

Hydroweb.next has been funded by the French government in the frame of Theia (Data and Services center for continental surfaces) and SWOT downstream (Surface Water and Ocean Topography satellite) programs. The hub brings together products from various providers such as Copernicus Land Services along with products from its own production centers. The production centers operate state-of-the-art algorithms that have been developed with scientists from Theia’s Scientific Expertise Centers: SurfWater for Surface Water Extent (SWE) from Sentinel-1 and Sentinel-2 images, Let It Snow for fractional snow cover and OBS2CO for water quality from Sentinel-2 images. As of June 2023, these 3 products will be made available with a 5 million square kilometer coverage. Products from SWOT and Trishna missions will also be distributed by hydroweb.next as they become available. 
In late 2023, SWOT data will include high-level user-oriented products such as river discharges and lake storage changes with global coverage. In 2025, Trishna products will include water quality, water skin temperature, and evapotranspiration. In situ data are also available to allow comparison with satellite data.

The products are distributed using STAC (Spatio-Temporal Asset Catalog) and WMS/WMTS (Web Mapping Services) protocols that follow the FAIR principles. This enables the direct reuse of the data by other services (e.g. UNESCO’s water quality portals).

The WebGIS interface is designed following a User-Centered Development approach. By involving users from various backgrounds such as Water Agencies, NGOs, industry, or academic research in stages of the project: surveys of user needs during interviews, features design involving users, ergonomics improvement through alpha testing, and quick consideration of user feedbacks through continuous integration and deployment. The interface allows searching relevant data using keywords, geophysical variables, and space-time restrictions. It also allows visualizing the products, their temporal evolution, and multitemporal synthesis. Finally, it allows downloading, harvesting, or streaming data, either through the interface or python APIs.