Projekter pr. år
Projektdetaljer
Beskrivelse
Drought monitoring and hydrological early warning system are important tools for
water resources management, and they must be further complemented by forecasting facilities that are well integrated with the EU’s Earth Observation data. In this project, based on Forootan and Mehrnegar's expertise, Bayesian-based Data Assimilation (DA) framework(s) will be developed to merge available satellite data with hydrological models to better understand and forecast the recent and future spatial-temporal changes in continental water storage and water fluxes.
water resources management, and they must be further complemented by forecasting facilities that are well integrated with the EU’s Earth Observation data. In this project, based on Forootan and Mehrnegar's expertise, Bayesian-based Data Assimilation (DA) framework(s) will be developed to merge available satellite data with hydrological models to better understand and forecast the recent and future spatial-temporal changes in continental water storage and water fluxes.
| Akronym | MuSe-BDA |
|---|---|
| Status | Igangværende |
| Effektiv start/slut dato | 08/09/2022 → 07/08/2024 |
FN's verdensmål
I 2015 blev FN-landene enige om 17 verdensmål til at bekæmpe fattigdom, beskytte planeten og sikre velstand for alle. Dette projekt bidrager til følgende verdensmål:
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Udforsk forskningsemnerne, som dette projekt berører. Disse etiketter er oprettet på grundlag af de underliggende bevillinger/legater. Sammen danner de et unikt fingerprint.
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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)
01/09/2022 → 31/08/2026
Projekter: Projekt › Forskning
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Time-Variable Satellite Gravity
Yang, F. & Forootan, E.
01/10/2018 → 01/01/2022
Projekter: Projekt › Forskning
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Bayesian Frameworks for Separating Global Ocean Mass, Hydrology, and Surface Deformation Signals from GRACE Data
Forootan, E., Jones, O. & Mehrnegar, N.
01/10/2017 → 31/12/2020
Projekter: Projekt › Forskning
Publikation
- 2 Tidsskriftartikel
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Global groundwater droughts are more severe than they appear in hydrological models: an investigation through a Bayesian merging of GRACE and GRACE-FO data with a water balance model
Forootan, E., Mehrnegar, N., Schumacher, M., Retegui Schiettekatte, L. A., Jagdhuber, T., Farzaneh, S., van Dijk, A. I. J. M., Shamsudduha, M. & Shum, CK., 20 feb. 2024, I: Science of the Total Environment. 912, 14 s., 169476.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Åben adgangFil19 Downloads (Pure) -
Making the Best Use of GRACE, GRACE-FO and SMAP Data Through a Constrained Bayesian Data-Model Integration
Mehrnegar, N., Schumacher, M., Jagdhuber, T. & Forootan, E., sep. 2023, I: Water Resources Research. 59, 9, 22 s., e2023WR034544.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Åben adgangFil2 Citationer (Scopus)17 Downloads (Pure)