Hybrid Estimation and Remote sensing Monitoring of Evaporation and Soil moisture (HERMES)

01 December 2022 → 30 June 2025
Federal funding: various
Research disciplines
  • Natural sciences
    • Climate change
    • Natural hazards
    • Remote sensing
    • Surfacewater hydrology
Drought Evaporation Soil moisture Remote sensing
Project description

HERMES will yield a first-of-its-kind, high-resolution, high accuracy, evaporation (E) and root-zone soil moisture (SM) datasets across Europe and Africa. It will benefit from (a) the progress in high-resolution remote sensing heralded by the EU Copernicus program, the Sentinel constellation, and the Meteosat second generation sensors, and (b) novel advances in AI and visualization technologies applied to Earth Observation data. By combining pioneering work from previous BELSPO STEREO III projects on high-resolution E and SM (ET–Sense) and hybrid modelling (ALBERI), HERMES will also bridge towards actual stakeholder requirements in the fields of water and agricultural management. To do so, the influence of irrigation on E and SM will be accounted for by assimilating Sentinel 1 backscatter data into an improved GLEAM-Hybrid, and the potential of new AI technologies for estimating E and SM will be intensively explored. Moreover, the interpretable hybrid framework will enable an unparalleled exploration of the drivers of E and SM in different ecosystems, with specific emphasis on periods of agricultural drought and heatwaves. The final outcomes of HERMES – including the high-resolution E and SM data in Europe and Africa – will be provided through an interactive web mapping tool based on the concept of 'datacubes', which will be regularly updated to provide timely information of interest to a wide range of end-users. The project will feed into the activities under the umbrella of the European Space Agency (ESA) Digital Twin Earth and the Global Climate Observing System (GCOS), thanks to the involvement of the HERMES partners in those initiatives. Overall, HERMES will bring new conceptual understanding on crucial hydro-climatic variables while pushing scientific boundaries at the interface between Earth Observation and AI.