Developing an Ensemble Kalman Filter calibration and data assimilation (EnC/DA) approach for integrating geodetic and remote sensing data into a global hydrological model

• Applicant: Professor Dr.-Ing. Jürgen Kusche
• Subject Area: Geodesy, Photogrammetry, Remote Sensing, Geoinformatics, Cartography ; Hydrogeology, Hydrology, Limnology, Urban Water Management, Water Chemistry, Integrated Water Resources Management
• Term: from 2018 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 324641997

Main objective of project P1 is the development and implementation of an effective Ensemble Kalman Filter for the integration of data assimilation and parameter calibration with hydrological modelling. Foci within the first phase were simultaneously integrating multiple data sets and creating observation operators; and developing and investigating the ensemble-based model parameter calibration. After setting up a working environment, work in the 2nd phase will turn towards refining our method, comparing approaches across the RU, developing a global assimila-tion system including parameter calibration, and creating new quantitative descriptions of global-scale water fluxes and storages, including a characterization of the uncertainty.

• DFG Programme: Research Units
• Subproject of: FOR 2630: Understanding the global freshwater system by combining geodetic and remote sensing information with modelling using a calibration/data assimilation approach (GlobalCDA)