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Fan Yang

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#data science Open access Oct 2026

Insights from the DANSk-LSM Project to Advance GRACE(-FO) and Multi-Sensor Data Assimilation for Hydrological Monitoring and Early Warning Systems

The DANSk-LSM (Developing Efficient Multi-Sensor Data Assimilation Frameworks for Integrating Earth Observation Satellite Data into Land Surface Models) project, funded by Independent Research Fund Denmark (DFF), developed and demonstrated physically consistent and computationally efficient data assimilation frameworks...

Ehsan Forootan, Fan Yang, Leire Retegui Schiettekatte et al. · 0 citations
Open access Oct 2026

Assimilation of GRACE/-FO data into global hydrological models for water use scenarios

Global Hydrological Models (GHMs) are an invaluable tool for simulating the dynamics of our freshwater cycle and estimating its contribution to sea level rise. However, uncertainties of input data (e.g., meteorological forcing, water demand estimates) and empirical parameters, as well as errors in the model structure (...

M. Schumacher, Çağatay Çakan, Supriya Tiwari et al. · 0 citations

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