The latest IPCC assessment report identified once more the land hydrology as the most uncertain component of the global water cycle. Variations of continental water storage occur in several hydrological compartments such as groundwater, soil moisture, surface water and snow. These storage variations and related changes of mass and surface water extensions map into a considerable number of different space based or in-situ observation systems such as the GRACE gravity field mission, radar and laser altimeter systems, radiometers, optical sensors, synthetic aperture radar, and in-situ river gauges.
The project aims to perform a multi-sensor approach in order to detect, separate and balance individual contributions to continental water storage variations for selected large river basins. A specific focus of the study is on the analysis of climate signals. The project exploits the synergies of various observation systems and combines their output with hydrological simulation models. The project is carried out within a largely interdisciplinary group of networking scientists and PhD students from space engineering, geodesy, hydrology and climate research. It provides new and valuable insights into hydrological processes and the impacts of climate change on the global water cycle.
The roadmap of this project includes (1) the elaboration of the potential und usability of contemporary space-borne and terrestrial sensors, (2) a quantification of water storage variations in different compart-ments from multi-mission analysis, (3) an assessment and analysis of the total water storage change from GRACE gravity field observations, (4) the computation of water balance for different study areas, (5) the analysis of balance inconsistencies with respect to non-hydrological mass changes (e.g. due to forest fires and erosion), (6) the formulation of recommendations for future research and future satellite missions on the basis of deficits in the water balance, and, finally, (7) the interpretation of the results for water storage changes in terms of variability of weather and climate.