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The study of outcrop modeling is located at the interface between two fields of expertise, Sedimentology and Computing Geoscience, which respectively investigates and simulates geological heterogeneity observed in the sedimentary record. During the last past years, modeling tools and techniques were constantly improved. In parallel, the study of Phanerozoic carbonate deposits emphasized the common occurrence of a random facies distribution along single depositional domain. Although both fields of expertise are intrinsically linked during outcrop simulation, their respective advances have not been combined in literature to enhance carbonate modeling studies. The present study re-examines the modeling strategy adapted to the simulation of shallow-water carbonate systems, based on a close relationship between field sedimentology and modeling capabilities. In the present study, the evaluation of three commonly used algorithms Truncated Gaussian Simulation (TGSim), Sequential Indicator Simulation (SISim), and Indicator Kriging (IK), were performed for the first time using visual and quantitative comparisons on an ideally suited carbonate outcrop. The results show that the heterogeneity of carbonate rocks cannot be fully simulated using one single algorithm. The operating mode of each algorithm involves capabilities as well as drawbacks that are not capable to match all field observations carried out across the modeling area. Two end members in the spectrum of carbonate depositional settings, a low-angle Jurassic ramp (High Atlas, Morocco) and a Triassic isolated platform (Dolomites, Italy), were investigated to obtain a complete overview of the geological heterogeneity in shallow-water carbonate systems. Field sedimentology and statistical analysis performed on the type, morphology, distribution, and association of carbonate bodies and combined with palaeodepositional reconstructions, emphasize similar results. At the basin scale (x 1 km), facies association, composed of facies recording similar depositional conditions, displays linear and ordered transitions between depositional domains. Contrarily, at the bedding scale (x 0.1 km), individual lithofacies type shows a mosaic-like distribution consisting of an arrangement of spatially independent lithofacies bodies along the depositional profile. The increase of spatial disorder from the basin to bedding scale results from the influence of autocyclic factors on the transport and deposition of carbonate sediments. Scale-dependent types of carbonate heterogeneity are linked with the evaluation of algorithms in order to establish a modeling strategy that considers both the sedimentary characteristics of the outcrop and the modeling capabilities. A surface-based modeling approach was used to model depositional sequences. Facies associations were populated using TGSim to preserve ordered trends between depositional domains. At the lithofacies scale, a fully stochastic approach with SISim was applied to simulate a mosaic-like lithofacies distribution. This new workflow is designed to improve the simulation of carbonate rocks, based on the modeling of each scale of heterogeneity individually. Contrarily to simulation methods applied in literature, the present study considers that the use of one single simulation technique is unlikely to correctly model the natural patterns and variability of carbonate rocks. The implementation of different techniques customized for each level of the stratigraphic hierarchy provides the essential computing flexibility to model carbonate systems. Closer feedback between advances carried out in the field of Sedimentology and Computing Geoscience should be promoted during future outcrop simulations for the enhancement of 3-D geological models.
The evolution of most orogens typically records cogenetic shortening and extension. Pervasive normal faulting in an orogen, however, has been related to late syn- and post-collisional stages of mountain building with shortening focused along the peripheral sectors of the orogen. While extensional processes constitute an integral part of orogenic evolution, the spatiotemporal characteristics and the kinematic linkage of structures related to shortening and extension in the core regions of the orogen are often not well known. Related to the India-Eurasia collision, the Himalaya forms the southern margin of the Tibetan Plateau and constitutes the most prominent Cenozoic type example of a collisional orogen. While thrusting is presently observed along the foothills of the orogen, several generations of extensional structures have been detected in the internal, high-elevation regions, both oriented either parallel or perpendicular to the strike of the orogen. In the NW Indian Himalaya, earthquake focal mechanisms, seismites and ubiquitous normal faulting in Quaternary deposits, and regional GPS measurements reveal ongoing E-W extension. In contrast to other extensional structures observed in the Himalaya, this extension direction is neither parallel nor perpendicular to the NE-SW regional shortening direction. In this study, I took advantage of this obliquity between the trend of the orogen and structures related to E-W oriented extension in order to address the question of the driving forces of different extension directions. Thus, extension might be triggered triggered by processes within the Tibetan Plateau or originates from the curvature of the Himalayan orogen. In order to elaborate on this topic, I present new fault-kinematic data based on systematic measurements of approximately 2000 outcrop-scale brittle fault planes with displacements of up to several centimeters that cover a large area of the NW Indian Himalaya. This new data set together with field observations relevant for relative chronology allows me to distinguish six different deformation styles. One of the main results are that the overall strain pattern derived from this data reflects the regionally important contractional deformation pattern very well, but also reveals significant extensional deformation. In total, I was able to identify six deformation styles, most of which are temporally and spatially linked and represent protracted shortening, but also significant extensional directions. For example, this is the first data set where a succession of both, arc-normal and E-W extension have been documented in the Himalaya. My observations also furnish the basis for a detailed overview of the younger extensional deformation history in the NW Indian Himalaya. Field and remote-sensing based geomorphic analyses, and geochronologic 40Ar/39Ar data on synkinematic muscovites along normal faults help elucidate widespread E-W extension in the NW Indian Himalaya which must have started at approximately 14-16 Ma, if not earlier. In addition, I documented and mapped fault scarps in Quaternary sedimentary deposits using satellite imagery and field inspection. Furthermore, I made field observations of regional normal faults, compiled structures from geological maps and put them in a regional context. Finally, I documented seismites in lake sediments close to the currently most active normal fault in the study area in order to extend the (paleo) seismic record of this particular fault. Taken together, this data sets document that E-W extension is the dominant active deformation style in the internal parts of the orogen. In addition, the combined field, geomorphic and remote-sensing data sets prove that E-W extension occurs in a much more larger region toward the south and west than the seismicity data have suggested. In conclusion, the data presented here reveal the importance of extension in a region, which is still dominated by ongoing collision and shortening. The regional fault distribution and cross-cutting relationships suggest that extension parallel and perpendicular to the strike of the orogen are an integral part of the southward propagation of the active thrust front and the associated lateral growth of the Himalayan arc. In the light of a wide range of models proposed for extension in the Himalaya and the Tibetan plateau, I propose that E-W extension in the NW Indian Himalaya is transferred from the Tibetan Plateau due the inability of the Karakorum fault (KF) to adequately accommodate ongoing E-W extension on the Tibetan Plateau. Furthermore, in line with other observations from Tibet, the onset of E-W normal faulting in the NW Himalaya may also reflect the attainment of high topography in this region, which generated crustal stresses conducive to spatially extensive extension.
Within a research project about future sustainable water management options in the Elbe River basin, quasi-natural discharge scenarios had to be provided. The semi-distributed eco-hydrological model SWIM was utilised for this task. According to scenario simulations driven by the stochastical climate model STAR, the region would get distinctly drier. However, this thesis focuses on the challenge of meeting the requirement of high model fidelity even for smaller sub-basins. Usually, the quality of the simulations is lower at inner points than at the outlet. Four research paper chapters and the discussion chapter deal with the reasons for local model deviations and the problem of optimal spatial calibration. Besides other assessments, the Markov Chain Monte Carlo method is applied to show whether evapotranspiration or precipitation should be corrected to minimise runoff deviations, principal component analysis is used in an unusual way to evaluate local precipitation alterations by land cover changes, and remotely sensed surface temperatures allow for an independent view on the evapotranspiration landscape. The overall insight is that spatially explicit hydrological modelling of such a large river basin requires a lot of local knowledge. It probably needs more time to obtain such knowledge as is usually provided for hydrological modelling studies.
Climatic variations and human activity now and increasingly in the future cause land cover changes and introduce perturbations in the terrestrial carbon reservoirs in vegetation, soil and detritus. Optical remote sensing and in particular Imaging Spectroscopy has shown the potential to quantify land surface parameters over large areas, which is accomplished by taking advantage of the characteristic interactions of incident radiation and the physico-chemical properties of a material. The objective of this thesis is to quantify key soil parameters, including soil organic carbon, using field and Imaging Spectroscopy. Organic carbon, iron oxides and clay content are selected to be analyzed to provide indicators for ecosystem function in relation to land degradation, and additionally to facilitate a quantification of carbon inventories in semiarid soils. The semiarid Albany Thicket Biome in the Eastern Cape Province of South Africa is chosen as study site. It provides a regional example for a semiarid ecosystem that currently undergoes land changes due to unadapted management practices and furthermore has to face climate change induced land changes in the future. The thesis is divided in three methodical steps. Based on reflectance spectra measured in the field and chemically determined constituents of the upper topsoil, physically based models are developed to quantify soil organic carbon, iron oxides and clay content. Taking account of the benefits limitations of existing methods, the approach is based on the direct application of known diagnostic spectral features and their combination with multivariate statistical approaches. It benefits from the collinearity of several diagnostic features and a number of their properties to reduce signal disturbances by influences of other spectral features. In a following step, the acquired hyperspectral image data are prepared for an analysis of soil constituents. The data show a large spatial heterogeneity that is caused by the patchiness of the natural vegetation in the study area that is inherent to most semiarid landscapes. Spectral mixture analysis is performed and used to deconvolve non-homogenous pixels into their constituent components. For soil dominated pixels, the subpixel information is used to remove the spectral influence of vegetation and to approximate the pure spectral signature coming from the soil. This step is an integral part when working in natural non-agricultural areas where pure bare soil pixels are rare. It is identified as the largest benefit within the multi-stage methodology, providing the basis for a successful and unbiased prediction of soil constituents from hyperspectral imagery. With the proposed approach it is possible (1) to significantly increase the spatial extent of derived information of soil constituents to areas with about 40 % vegetation coverage and (2) to reduce the influence of materials such as vegetation on the quantification of soil constituents to a minimum. Subsequently, soil parameter quantities are predicted by the application of the feature-based soil prediction models to the maps of locally approximated soil signatures. Thematic maps showing the spatial distribution of the three considered soil parameters in October 2009 are produced for the Albany Thicket Biome of South Africa. The maps are evaluated for their potential to detect erosion affected areas as effects of land changes and to identify degradation hot spots in regard to support local restoration efforts. A regional validation, carried out using available ground truth sites, suggests remaining factors disturbing the correlation of spectral characteristics and chemical soil constituents. The approach is developed for semiarid areas in general and not adapted to specific conditions in the study area. All processing steps of the developed methodology are implemented in software modules, where crucial steps of the workflow are fully automated. The transferability of the methodology is shown for simulated data of the future EnMAP hyperspectral satellite. Soil parameters are successfully predicted from these data despite intense spectral mixing within the lower spatial resolution EnMAP pixels. This study shows an innovative approach to use Imaging Spectroscopy for mapping of key soil constituents, including soil organic carbon, for large areas in a non-agricultural ecosystem and under consideration of a partially vegetation coverage. It can contribute to a better assessment of soil constituents that describe ecosystem processes relevant to detect and monitor land changes. The maps further provide an assessment of the current carbon inventory in soils, valuable for carbon balances and carbon mitigation products.
Agriculture is one of the most important human activities providing food and more agricultural goods for seven billion people around the world and is of special importance in sub-Saharan Africa. The majority of people depends on the agricultural sector for their livelihoods and will suffer from negative climate change impacts on agriculture until the middle and end of the 21st century, even more if weak governments, economic crises or violent conflicts endanger the countries’ food security. The impact of temperature increases and changing precipitation patterns on agricultural vegetation motivated this thesis in the first place. Analyzing the potentials of reducing negative climate change impacts by adapting crop management to changing climate is a second objective of the thesis. As a precondition for simulating climate change impacts on agricultural crops with a global crop model first the timing of sowing in the tropics was improved and validated as this is an important factor determining the length and timing of the crops´ development phases, the occurrence of water stress and final crop yield. Crop yields are projected to decline in most regions which is evident from the results of this thesis, but the uncertainties that exist in climate projections and in the efficiency of adaptation options because of political, economical or institutional obstacles have to be considered. The effect of temperature increases and changing precipitation patterns on crop yields can be analyzed separately and varies in space across the continent. Southern Africa is clearly the region most susceptible to climate change, especially to precipitation changes. The Sahel north of 13° N and parts of Eastern Africa with short growing seasons below 120 days and limited wet season precipitation of less than 500 mm are also vulnerable to precipitation changes while in most other part of East and Central Africa, in contrast, the effect of temperature increase on crops overbalances the precipitation effect and is most pronounced in a band stretching from Angola to Ethiopia in the 2060s. The results of this thesis confirm the findings from previous studies on the magnitude of climate change impact on crops in sub-Saharan Africa but beyond that helps to understand the drivers of these changes and the potential of certain management strategies for adaptation in more detail. Crop yield changes depend on the initial growing conditions, on the magnitude of climate change, and on the crop, cropping system and adaptive capacity of African farmers which is only now evident from this comprehensive study for sub-Saharan Africa. Furthermore this study improves the representation of tropical cropping systems in a global crop model and considers the major food crops cultivated in sub-Saharan Africa and climate change impacts throughout the continent.
Assuming that liquid iron alloy from the outer core interacts with the solid silicate-rich lower mantle the influence on the core-mantle reflected phase PcP is studied. If the core-mantle boundary is not a sharp discontinuity, this becomes apparent in the waveform and amplitude of PcP. Iron-silicate mixing would lead to regions of partial melting with higher density which in turn reduces the velocity of seismic waves. On the basis of the calculation and interpretation of short-period synthetic seismograms, using the reflectivity and Gauss Beam method, a model space is evaluated for these ultra-low velocity zones (ULVZs). The aim of this thesis is to analyse the behaviour of PcP between 10° and 40° source distance for such models using different velocity and density configurations. Furthermore, the resolution limits of seismic data are discussed. The influence of the assumed layer thickness, dominant source frequency and ULVZ topography are analysed. The Gräfenberg and NORSAR arrays are then used to investigate PcP from deep earthquakes and nuclear explosions. The seismic resolution of an ULVZ is limited both for velocity and density contrasts and layer thicknesses. Even a very thin global core-mantle transition zone (CMTZ), rather than a discrete boundary and also with strong impedance contrasts, seems possible: If no precursor is observable but the PcP_model /PcP_smooth amplitude reduction amounts to more than 10%, a very thin ULVZ of 5 km with a first-order discontinuity may exist. Otherwise, if amplitude reductions of less than 10% are obtained, this could indicate either a moderate, thin ULVZ or a gradient mantle-side CMTZ. Synthetic computations reveal notable amplitude variations as function of the distance and the impedance contrasts. Thereby a primary density effect in the very steep-angle range and a pronounced velocity dependency in the wide-angle region can be predicted. In view of the modelled findings, there is evidence for a 10 to 13.5 km thick ULVZ 600 km south-eastern of Moscow with a NW-SE extension of about 450 km. Here a single specific assumption about the velocity and density anomaly is not possible. This is in agreement with the synthetic results in which several models create similar amplitude-waveform characteristics. For example, a ULVZ model with contrasts of -5% VP , -15% VS and +5% density explain the measured PcP amplitudes. Moreover, below SW Finland and NNW of the Caspian Sea a CMB topography can be assumed. The amplitude measurements indicate a wavelength of 200 km and a height of 1 km topography, previously also shown in the study by Kampfmann and Müller (1989). Better constraints might be provided by a joined analysis of seismological data, mineralogical experiments and geodynamic modelling.
Growing populations, continued economic development, and limited natural resources are critical factors affecting sustainable development. These factors are particularly pertinent in developing countries in which large parts of the population live at a subsistence level and options for sustainable development are limited. Therefore, addressing sustainable land use strategies in such contexts requires that decision makers have access to evidence-based impact assessment tools that can help in policy design and implementation. Ex-ante impact assessment is an emerging field poised at the science-policy interface and is used to assess the potential impacts of policy while also exploring trade-offs between economic, social and environmental sustainability targets. The objective of this study was to operationalise the impact assessment of land use scenarios in the context of developing countries that are characterised by limited data availability and quality. The Framework for Participatory Impact Assessment (FoPIA) was selected for this study because it allows for the integration of various sustainability dimensions, the handling of complexity, and the incorporation of local stakeholder perceptions. FoPIA, which was originally developed for the European context, was adapted to the conditions of developing countries, and its implementation was demonstrated in five selected case studies. In each case study, different land use options were assessed, including (i) alternative spatial planning policies aimed at the controlled expansion of rural-urban development in the Yogyakarta region (Indonesia), (ii) the expansion of soil and water conservation measures in the Oum Zessar watershed (Tunisia), (iii) the use of land conversion and the afforestation of agricultural areas to reduce soil erosion in Guyuan district (China), (iv) agricultural intensification and the potential for organic agriculture in Bijapur district (India), and (v) land division and privatisation in Narok district (Kenya). The FoPIA method was effectively adapted by dividing the assessment into three conceptual steps: (i) scenario development; (ii) specification of the sustainability context; and (iii) scenario impact assessment. A new methodological approach was developed for communicating alternative land use scenarios to local stakeholders and experts and for identifying recommendations for future land use strategies. Stakeholder and expert knowledge was used as the main sources of information for the impact assessment and was complemented by available quantitative data. Based on the findings from the five case studies, FoPIA was found to be suitable for implementing the impact assessment at case study level while ensuring a high level of transparency. FoPIA supports the identification of causal relationships underlying regional land use problems, facilitates communication among stakeholders and illustrates the effects of alternative decision options with respect to all three dimensions of sustainable development. Overall, FoPIA is an appropriate tool for performing preliminary assessments but cannot replace a comprehensive quantitative impact assessment, and FoPIA should, whenever possible, be accompanied by evidence from monitoring data or analytical tools. When using FoPIA for a policy oriented impact assessment, it is recommended that the process should follow an integrated, complementary approach that combines quantitative models, scenario techniques, and participatory methods.
The past climate in central Asia, and especially on the Tibetan Plateau (TP), is of great importance for an understanding of global climate processes and for predicting the future climate. As a major influence on the climate in this region, the Asian Summer Monsoon (ASM) and its evolutionary history are of vital importance for accurate predictions. However, neither the evolutionary pattern of the summer monsoon nor the driving mechanisms behind it are yet clearly understood. For this research, I first synthesized previously published Late Glacial to Holocene climatic records from monsoonal central Asia in order to extract the general climate signals and the associated summer monsoon intensities. New climate and vegetation sequences were then established using improved quantitative methods, focusing on fossil pollen records recovered from Tibetan lakes and also incorporating new modern datasets. The pollen-vegetation and vegetation-climate relationships on the TP were also evaluated in order to achieve a better understanding of fossil pollen records. The synthesis of previously published moisture-related palaeoclimate records in monsoonal central Asia revealed generally different temporal patterns for the two monsoonal subsystems, i.e. the Indian Summer Monsoon (ISM) and East Asian Summer Monsoon (EASM). The ISM appears to have experienced maximum wet conditions during the early Holocene, while many records from the area affected by the EASM indicate relatively dry conditions at that time, particularly in north-central China where the maximum moisture levels occurred during the middle Holocene. A detailed consideration of possible driving factors affecting the summer monsoon, including summer solar insolation and sea surface temperatures, revealed that the ISM was primarily driven by variations in northern hemisphere solar insolation, and that the EASM may have been constrained by the ISM resulting in asynchronous patterns of evolution for these two subsystems. This hypothesis is further supported by modern monsoon indices estimated using the NCEP/NCAR Reanalysis data from the last 50 years, which indicate a significant negative correlation between the two summer monsoon subsystems. By analogy with the early Holocene, intensification of the ISM during coming decades could lead to increased aridification elsewhere as a result of the asynchronous nature of the monsoon subsystems, as can already be observed in the meteorological data from the last 15 years. A quantitative climate reconstruction using fossil pollen records was achieved through analysis of sediment core recovered from Lake Donggi Cona (in the north-eastern part of the TP) which has been dated back to the Last Glacial Maximum (LGM). A new data-set of modern pollen collected from large lakes in arid to semi-arid regions of central Asia is also presented herein. The concept of "pollen source area" was introduced to modern climate calibration based on pollen from large lakes, and was applied to the fossil pollen sequence from Lake Donggi Cona. Extremely dry conditions were found to have dominated the LGM, and a subsequent gradually increasing trend in moisture during the Late Glacial period was terminated by an abrupt reversion to a dry phase that lasted for about 1000 years and coincided with the first Heinrich Event of the northern Atlantic region. Subsequent periods corresponding to the warm Bølling-Allerød period and the Younger Dryas cold event were followed by moist conditions during the early Holocene, with annual precipitation of up to about 400 mm. A slightly drier trend after 9 cal ka BP was then followed by a second wet phase during the middle Holocene that lasted until 4.5 cal ka BP. Relatively steady conditions with only slight fluctuations then dominated the late Holocene, resulting in the present climatic conditions. In order to investigate the relationship between vegetation and climate, temporal variations in the possible driving factors for vegetation change on the northern TP were examined using a high resolution late Holocene pollen record from Lake Kusai. Moving-window Redundancy Analyses (RDAs) were used to evaluate the correlations between pollen assemblages and individual sedimentary proxies. These analyses have revealed frequent fluctuations in the relative abundances of alpine steppe and alpine desert components, and in particular a decrease in the total vegetation cover at around 1500 cal a BP. The climate was found to have had an important influence on vegetation changes when conditions were relatively wet and stable. However, after the 1500 cal a BP threshold in vegetation cover was crossed the vegetation appears to have been affected more by extreme events such as dust storms or fluvial erosion than by the general climatic trends. In addition, pollen spectra over the last 600 years have been revealed by Procrustes analysis to be significantly different from those recovered from older samples, which is attributed to an increased human impact that resulted in unprecedented changes to the composition of the vegetation. Theoretical models that have been developed and widely applied to the European area (i.e. the Extended R-Value (ERV) model and the Regional Estimates of Vegetation Abundance from Large Sites (REVEALS) model) have been applied to the high alpine TP ecosystems in order to investigate the pollen-vegetation relationships, as well as for quantitative reconstructions of vegetation abundance. The modern pollen–vegetation relationships for four common pollen species on the TP have been investigated using Poaceae as the reference taxa. The ERV Submodel 2 yielded relatively high PPEs for the steppe and desert taxa (Artemisia Chenopodiaceae), and low PPEs for the Cyperaceae that are characteristic of the alpine Kobresia meadows. The plant abundances on the central and north-eastern TP were quantified by applying these PPEs to four post-Late Glacial fossil pollen sequences. The reconstructed vegetation assemblages for the four pollen sequences always yielded smaller compositional species turnovers than suggested by the pollen spectra, indicating that the strength of the previously-reported vegetation changes may therefore have been overestimated. In summary, the key findings of this thesis are that (a) the two ASM subsystems show asynchronous patterns during both the Holocene and modern time periods, (b) fossil pollen records from large lakes reflect regional signals for which the pollen source areas need to be taken into account, (c) climate is not always the main driver for vegetation change, and (d) previously reported vegetation changes on the TP may have been overestimated because they ignored inter-species variations in pollen productivity.
Tectonic and geological processes on Earth often result in structural anisotropy of the subsurface, which can be imaged by various geophysical methods. In order to achieve appropriate and realistic Earth models for interpretation, inversion algorithms have to allow for an anisotropic subsurface. Within the framework of this thesis, I analyzed a magnetotelluric (MT) data set taken from the Cape Fold Belt in South Africa. This data set exhibited strong indications for crustal anisotropy, e.g. MT phases out of the expected quadrant, which are beyond of fitting and interpreting with standard isotropic inversion algorithms. To overcome this obstacle, I have developed a two-dimensional inversion method for reconstructing anisotropic electrical conductivity distributions. The MT inverse problem represents in general a non-linear and ill-posed minimization problem with many degrees of freedom: In isotropic case, we have to assign an electrical conductivity value to each cell of a large grid to assimilate the Earth's subsurface, e.g. a grid with 100 x 50 cells results in 5000 unknown model parameters in an isotropic case; in contrast, we have the sixfold in an anisotropic scenario where the single value of electrical conductivity becomes a symmetric, real-valued tensor while the number of the data remains unchanged. In order to successfully invert for anisotropic conductivities and to overcome the non-uniqueness of the solution of the inverse problem it is necessary to use appropriate constraints on the class of allowed models. This becomes even more important as MT data is not equally sensitive to all anisotropic parameters. In this thesis, I have developed an algorithm through which the solution of the anisotropic inversion problem is calculated by minimization of a global penalty functional consisting of three entries: the data misfit, the model roughness constraint and the anisotropy constraint. For comparison, in an isotropic approach only the first two entries are minimized. The newly defined anisotropy term is measured by the sum of the square difference of the principal conductivity values of the model. The basic idea of this constraint is straightforward. If an isotropic model is already adequate to explain the data, there is no need to introduce electrical anisotropy at all. In order to ensure successful inversion, appropriate trade-off parameters, also known as regularization parameters, have to be chosen for the different model constraints. Synthetic tests show that using fixed trade-off parameters usually causes the inversion to end up by either a smooth model with large RMS error or a rough model with small RMS error. Using of a relaxation approach on the regularization parameters after each successful inversion iteration will result in smoother inversion model and a better convergence. This approach seems to be a sophisticated way for the selection of trade-off parameters. In general, the proposed inversion method is adequate for resolving the principal conductivities defined in horizontal plane. Once none of the principal directions of the anisotropic structure is coincided with the predefined strike direction, only the corresponding effective conductivities, which is the projection of the principal conductivities onto the model coordinate axes direction, can be resolved and the information about the rotation angles is lost. In the end the MT data from the Cape Fold Belt in South Africa has been analyzed. The MT data exhibits an area (> 10 km) where MT phases over 90 degrees occur. This part of data cannot be modeled by standard isotropic modeling procedures and hence can not be properly interpreted. The proposed inversion method, however, could not reproduce the anomalous large phases as desired because of losing the information about rotation angles. MT phases outside the first quadrant are usually obtained by different anisotropic anomalies with oblique anisotropy strike. In order to achieve this challenge, the algorithm needs further developments. However, forward modeling studies with the MT data have shown that surface highly conductive heterogeneity in combination with a mid-crustal electrically anisotropic zone are required to fit the data. According to known geological and tectonic information the mid-crustal zone is interpreted as a deep aquifer related to the fractured Table Mountain Group rocks in the Cape Fold Belt.
Soil conditions under vegetation cover and their spatial and temporal variations from point to catchment scale are crucial for understanding hydrological processes within the vadose zone, for managing irrigation and consequently maximizing yield by precision farming. Soil moisture and soil roughness are the key parameters that characterize the soil status. In order to monitor their spatial and temporal variability on large scales, remote sensing techniques are required. Therefore the determination of soil parameters under vegetation cover was approached in this thesis by means of (multi-angular) polarimetric SAR acquisitions at a longer wavelength (L-band, lambda=23cm). In this thesis, the penetration capabilities of L-band are combined with newly developed (multi-angular) polarimetric decomposition techniques to separate the different scattering contributions, which are occurring in vegetation and on ground. Subsequently the ground components are inverted to estimate the soil characteristics. The novel (multi-angular) polarimetric decomposition techniques for soil parameter retrieval are physically-based, computationally inexpensive and can be solved analytically without any a priori knowledge. Therefore they can be applied without test site calibration directly to agricultural areas. The developed algorithms are validated with fully polarimetric SAR data acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR) for three different study areas in Germany. The achieved results reveal inversion rates up to 99% for the soil moisture and soil roughness retrieval in agricultural areas. However, in forested areas the inversion rate drops significantly for most of the algorithms, because the inversion in forests is invalid for the applied scattering models at L-band. The validation against simultaneously acquired field measurements indicates an estimation accuracy (root mean square error) of 5-10vol.% for the soil moisture (range of in situ values: 1-46vol.%) and of 0.37-0.45cm for the soil roughness (range of in situ values: 0.5-4.0cm) within the catchment. Hence, a continuous monitoring of soil parameters with the obtained precision, excluding frozen and snow covered conditions, is possible. Especially future, fully polarimetric, space-borne, long wavelength SAR missions can profit distinctively from the developed polarimetric decomposition techniques for separation of ground and volume contributions as well as for soil parameter retrieval on large spatial scales.