Surface and subsurface water from space: On the integration of microwave remote sensing observations with flood prediction systems

The technique of active microwave remote sensing has made much progress toward its high potential to monitor water storage changes in terrestrial surface and subsurface water bodies at various spatial and temporal scales. The number of studies demonstrating the support these data can offer in hydrological and hydraulic model building, model calibration and model updating is growing rapidly. While there is no doubt that this technological progress has already brought new insights into hydrology and hydraulics, there are still several issues that require attention. The questions to answer are: (1) How to add value to ‘raw’ remote sensing data for hydrological applications, (2) how to combine remote sensing techniques with hydrologic-hydraulic models for improved predictions, and (3) how to evolve irregular and intermittent remote sensing-based applications into systematic services? The first question deals with the adequate data processing to retrieve meaningful information about hydrological/hydraulic variables. Further, remote sensing-derived data are characterized by considerable uncertainty, which needs to be evaluated and clearly communicated to the users of such data. The second question deals with the effective integration of remote sensing-derived information and in situ data with adequate models, either offline for model building and calibration or online via assimilation for model updating. The third question focuses on an efficient production, processing and distribution of satellite data and the development of new services that may help to advance operational water resources management. This thesis deals with all three questions, with a clear focus on active microwave remote sensing and hydrological/hydraulic modeling.Water ResourcesCivil Engineering and Geoscience