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The Central Andean region is characterized by diverse climate zones with sharp transitions between them. In this work, the area of interest is the South-Central Andes in northwestern Argentina that borders with Bolivia and Chile. The focus is the observation of soil moisture and water vapour with Global Navigation Satellite System (GNSS) remote-sensing methodologies. Because of the rapid temporal and spatial variations of water vapour and moisture circulations, monitoring this part of the hydrological cycle is crucial for understanding the mechanisms that control the local climate. Moreover, GNSS-based techniques have previously shown high potential and are appropriate for further investigation. This study includes both logistic-organization effort and data analysis. As for the prior, three GNSS ground stations were installed in remote locations in northwestern Argentina to acquire observations, where there was no availability of third-party data.
The methodological development for the observation of the climate variables of soil moisture and water vapour is independent and relies on different approaches. The soil-moisture estimation with GNSS reflectometry is an approximation that has demonstrated promising results, but it has yet to be operationally employed. Thus, a more advanced algorithm that exploits more observations from multiple satellite constellations was developed using data from two pilot stations in Germany. Additionally, this algorithm was slightly modified and used in a sea-level measurement campaign. Although the objective of this application is not related to monitoring hydrological parameters, its methodology is based on the same principles and helps to evaluate the core algorithm. On the other hand, water-vapour monitoring with GNSS observations is a well-established technique that is utilized operationally. Hence, the scope of this study is conducting a meteorological analysis by examining the along-the-zenith air-moisture levels and introducing indices related to the azimuthal gradient.
The results of the experiments indicate higher-quality soil moisture observations with the new algorithm. Furthermore, the analysis using the stations in northwestern Argentina illustrates the limits of this technology because of varying soil conditions and shows future research directions. The water-vapour analysis points out the strong influence of the topography on atmospheric moisture circulation and rainfall generation. Moreover, the GNSS time series allows for the identification of seasonal signatures, and the azimuthal-gradient indices permit the detection of main circulation pathways.
Indonesia is one of the countries most prone to natural hazards. Complex interaction of several tectonic plates with high relative velocities leads to approximately two earthquakes with magnitude Mw>7 every year, being more than 15% of the events worldwide. Earthquakes with magnitude above 9 happen far more infrequently, but with catastrophic effects. The most severe consequences thereby arise from tsunamis triggered by these subduction-related earthquakes, as the Sumatra-Andaman event in 2004 showed. In order to enable efficient tsunami early warning, which includes the estimation of wave heights and arrival times, it is necessary to combine different types of real-time sensor data with numerical models of earthquake sources and tsunami propagation. This thesis was created as a result of the GITEWS project (German Indonesian Tsunami Early Warning System). It is based on five research papers and manuscripts. Main project-related task was the development of a database containing realistic earthquake scenarios for the Sunda Arc. This database provides initial conditions for tsunami propagation modeling used by the simulation system at the early warning center. An accurate discretization of the subduction geometry, consisting of 25x150 subfaults was constructed based on seismic data. Green’s functions, representing the deformational response to unit dip- and strike slip at the subfaults, were computed using a layered half-space approach. Different scaling relations for earthquake dimensions and slip distribution were implemented. Another project-related task was the further development of the ‘GPS-shield’ concept. It consists of a constellation of near field GPS-receivers, which are shown to be very valuable for tsunami early warning. The major part of this thesis is related to the geophysical interpretation of GPS data. Coseismic surface displacements caused by the 2004 Sumatra earthquake are inverted for slip at the fault. The effect of different Earth layer models is tested, favoring continental structure. The possibility of splay faulting is considered and shown to be a secondary order effect in respect to tsunamigenity for this event. Tsunami models based on source inversions are compared to satellite radar altimetry observations. Postseismic GPS time series are used to test a wide parameter range of uni- and biviscous rheological models of the asthenosphere. Steady-state Maxwell rheology is shown to be incompatible with near-field GPS data, unless large afterslip, amounting to more than 10% of the coseismic moment is assumed. In contrast, transient Burgers rheology is in agreement with data without the need for large aseismic afterslip. Comparison to postseismic geoid observation by the GRACE satellites reveals that even with afterslip, the model implementing Maxwell rheology results in amplitudes being too small, and thus supports a biviscous asthenosphere. A simple approach based on the assumption of quasi-static deformation propagation is introduced and proposed for inversion of coseismic near-field GPS time series. Application of this approach to observations from the 2004 Sumatra event fails to quantitatively reconstruct the rupture propagation, since a priori conditions are not fulfilled in this case. However, synthetic tests reveal the feasibility of such an approach for fast estimation of rupturing properties.