Inhalt des Dokuments
GNSS-based remote sensing: Innovative observation of key hydrological parameters in the central Andes
- Basic principle of GPS reflectometry for soil moisture estimation. When the soil moisture is high (red line), the signal does not penetrate the ground. On the other hand, when it is low, there is some penetration, which is causing a delay (phase shift) in its SNR interferometric pattern.
- © Antonoglou (GFZ)
Fakultät VI - Planen Bauen Umwelt, Technischen Universität Berlin
Institut für Erd- und Umweltwissenschaften, Universität Potsdam
The central Andes are characterized by a steep climatic gradient where key hydrologic variables change across short distances. One of the largest unknown component in this environment is the storage of water in the atmosphere, soil (soil moisture) and the snow height (or snow water equivalent). Both are parameters that can be quantified with modern remote sensing technology and we seek to enhance our understanding of the complete water fluxes in this environment – especially the highly dynamic fluxes that are often associated with hydrometerological extreme events.
In the past two decades, innovative GNSS (Global Navigational Satellite Systems) based remote sensing techniques were successfully tested and established and the resulting observations evolved into an important data source for numerous meteorological applications. The most prominent example for this development is the operational use of GNSS-based temperature and water vapor data to improve day-by-day regional and global weather forecasts since 2006. The exploitation of Earth reflected signals (GNSS Reflectometry, GNSS-R), however is not yet operationally applied and still focus of international research to reach operational application level as well. GNSS data provide an excellent opportunity to study the dynamics of hydrometeorological extreme events, because of the very high sampling interval.
This project relies on close collaboration with Argentinean researchers that maintain a regional GNSS ground network. In the framework of this project, new stations at specific, key locations will be installed and the data used to decipher hydrologic process. This project requires strong quantitative skills and thorough environmental knowledge.