Project Details
Description
This project is funded by the European Space Agency (ESA) to prototype a full advanced end-to-end demonstrator of DTE over Europe and targeted regions in Africa and central America at high resolution in space and time (targeting 1 km and 1 hour).
The contribution of the Geodesy Group is this DTE Hydrology Next project is around addressing 1) Developing Machine Learning-based algorithms for downscaling satellite gravity and satellite soil moisture data based on the available 1 km resolution water storage and water flux products of this project; (2) A scientific development for formulating statistical inversion and Bayesian Fusion approaches for estimating groundwater storage from various input data with different uncertainty levels; (3) Addressing differences between the temporal resolution of satellite data with the target temporal resolution of this study (hourly and daily time scales), and (4) validations against the in-situ groundwater network of Europe.
The contribution of the Geodesy Group is this DTE Hydrology Next project is around addressing 1) Developing Machine Learning-based algorithms for downscaling satellite gravity and satellite soil moisture data based on the available 1 km resolution water storage and water flux products of this project; (2) A scientific development for formulating statistical inversion and Bayesian Fusion approaches for estimating groundwater storage from various input data with different uncertainty levels; (3) Addressing differences between the temporal resolution of satellite data with the target temporal resolution of this study (hourly and daily time scales), and (4) validations against the in-situ groundwater network of Europe.
| Acronym | DTE Hydrology Next |
|---|---|
| Status | Active |
| Effective start/end date | 01/10/2024 → 30/09/2026 |
Collaborative partners
- National Research Council of Italy
- TU Wien
- Ghent University
- International Centre for Environmental Monitoring
- Ebro Observatory University Institute
- Università degli Studi di Perugia
- Deltares
- RHEA
- Meteorological Environmental Earth Observation
- Helmholtz Centre for Environmental Research
- eGEOS
Keywords
- Groundwater
- Terrestrial Water Storage
- satellite
- GRACE
- GRACE-FO
- Data Assimilation
- Bayesian Probabilistic Modeling
- Bayesian
- Fusion
- Digital Twin
- Earth Observation
- Hydrology
- Inversion
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
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SFAS: Space-based Free Flood Awareness System for Africa
Forootan, E. (PI), Schumacher, M. (CoI), Kittel, C. (CoI), Murray, A. (CoI) & Madsen, H. (CoI)
01/03/2025 → 31/07/2027
Project: Research
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DANSk-LSM: Developing efficient multi-sensor Data Assimilation frameworks for integrating Earth ObservatioN Satellite data into Land Surface Models (DANSk-LSM)
Forootan, E. (PI), Schumacher, M. (CoI), Yang, F. (Project Participant) & Retegui Schiettekatte, L. A. (Project Participant)
Uddannelses- og forskningsministeriet
01/09/2022 → 31/08/2026
Project: Research
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MuSe-BDA: Multi-Sensor Bayesian Data Assimilation for Large-Scale Drought Monitoring System (MuSe-BDA)
Forootan, E. (PI) & Mehrnegar, N. (PI)
08/09/2022 → 15/07/2025
Project: Research
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Exploring GRACE and GRACE-FO data to estimate the groundwater component of a digital twin of the terrestrial water cycle
Forootan, E., Mehrnegar, N., Yang, F., Retegui Schiettekatte, L. A., Schumacher, M. & Brocca, L., May 2025.Research output: Contribution to conference without publisher/journal › Poster › Research
Open AccessFile42 Downloads (Pure) -
How can a hierarchical Bayesian approach bridge the gap between multi-source remote sensing data and hydrological models?
Mehrnegar, N. & Forootan, E., May 2025.Research output: Contribution to conference without publisher/journal › Conference abstract for conference › Research
Open Access