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Atmospheric water vapour content is a key variable that controls the development of deep convective storms and rainfall extremes over the central Andes. Direct measurements of water vapour are challenging; however, recent developments in microwave processing allow the use of phase delays from L-band radar to measure the water vapour content throughout the atmosphere: Global Navigation Satellite System (GNSS)-based integrated water vapour (IWV) monitoring shows promising results to measure vertically integrated water vapour at high temporal resolutions. Previous works also identified convective available potential energy (CAPE) as a key climatic variable for the formation of deep convective storms and rainfall in the central Andes. Our analysis relies on GNSS data from the Argentine Continuous Satellite Monitoring Network, Red Argentina de Monitoreo Satelital Continuo (RAMSAC) network from 1999 to 2013. CAPE is derived from version 2.0 of the ECMWF’s (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-interim) and rainfall from the TRMM (Tropical Rainfall Measuring Mission) product. In this study, we first analyse the rainfall characteristics of two GNSS-IWV stations by comparing their complementary cumulative distribution function (CCDF). Second, we separately derive the relation between rainfall vs. CAPE and GNSS-IWV. Based on our distribution fitting analysis, we observe an exponential relation of rainfall to GNSS-IWV. In contrast, we report a power-law relationship between the daily mean value of rainfall and CAPE at the GNSS-IWV station locations in the eastern central Andes that is close to the theoretical relationship based on parcel theory. Third, we generate a joint regression model through a multivariable regression analysis using CAPE and GNSS-IWV to explain the contribution of both variables in the presence of each other to extreme rainfall during the austral summer season. We found that rainfall can be characterised with a higher statistical significance for higher rainfall quantiles, e.g., the 0.9 quantile based on goodness-of-fit criterion for quantile regression. We observed different contributions of CAPE and GNSS-IWV to rainfall for each station for the 0.9 quantile. Fourth, we identify the temporal relation between extreme rainfall (the 90th, 95th, and 99th percentiles) and both GNSS-IWV and CAPE at 6 h time steps. We observed an increase before the rainfall event and at the time of peak rainfall—both for GNSS-integrated water vapour and CAPE. We show higher values of CAPE and GNSS-IWV for higher rainfall percentiles (99th and 95th percentiles) compared to the 90th percentile at a 6-h temporal scale. Based on our correlation analyses and the dynamics of the time series, we show that both GNSS-IWV and CAPE had comparable magnitudes, and we argue to consider both climatic variables when investigating their effect on rainfall extremes.
The spread of shrubs in Namibian savannas raises questions about the resilience of these ecosystems to global change. This makes it necessary to understand the past dynamics of the vegetation, since there is no consensus on whether shrub encroachment is a new phenomenon, nor on its main drivers. However, a lack of long-term vegetation datasets for the region and the scarcity of suitable palaeoecological archives, makes reconstructing past vegetation and land cover of the savannas a challenge.
To help meet this challenge, this study addresses three main research questions: 1) is pollen analysis a suitable tool to reflect the vegetation change associated with shrub encroachment in savanna environments? 2) Does the current encroached landscape correspond to an alternative stable state of savanna vegetation? 3) To what extent do pollen-based quantitative vegetation reconstructions reflect changes in past land cover?
The research focuses on north-central Namibia, where despite being the region most affected by shrub invasion, particularly since the 21st century, little is known about the dynamics of this phenomenon.
Field-based vegetation data were compared with modern pollen data to assess their correspondence in terms of composition and diversity along precipitation and grazing intensity gradients. In addition, two sediment cores from Lake Otjikoto were analysed to reveal changes in vegetation composition that have occurred in the region over the past 170 years and their possible drivers. For this, a multiproxy approach (fossil pollen, sedimentary ancient DNA (sedaDNA), biomarkers, compound specific carbon (δ13C) and deuterium (δD) isotopes, bulk carbon isotopes (δ13Corg), grain size, geochemical properties) was applied at high taxonomic and temporal resolution. REVEALS modelling of the fossil pollen record from Lake Otjikoto was run to quantitatively reconstruct past vegetation cover. For this, we first made pollen productivity estimates (PPE) of the most relevant savanna taxa in the region using the extended R-value model and two pollen dispersal options (Gaussian plume model and Lagrangian stochastic model). The REVEALS-based vegetation reconstruction was then validated using remote sensing-based regional vegetation data.
The results show that modern pollen reflects the composition of the vegetation well, but diversity less well. Interestingly, precipitation and grazing explain a significant amount of the compositional change in the pollen and vegetation spectra. The multiproxy record shows that a state change from open Combretum woodland to encroached Terminalia shrubland can occur over a century, and that the transition between states spans around 80 years and is characterized by a unique vegetation composition. This transition is supported by gradual environmental changes induced by management (i.e. broad-scale logging for the mining industry, selective grazing and reduced fire activity associated with intensified farming) and related land-use change. Derived environmental changes (i.e. reduced soil moisture, reduced grass cover, changes in species composition and competitiveness, reduced fire intensity) may have affected the resilience of Combretum open woodlands, making them more susceptible to change to an encroached state by stochastic events such as consecutive years of precipitation and drought, and by high concentrations of pCO2. We assume that the resulting encroached state was further stabilized by feedback mechanisms that favour the establishment and competitiveness of woody vegetation.
The REVEALS-based quantitative estimates of plant taxa indicate the predominance of a semi-open landscape throughout the 20th century and a reduction in grass cover below 50% since the 21st century associated with the spread of encroacher woody taxa. Cover estimates show a close match with regional vegetation data, providing support for the vegetation dynamics inferred from multiproxy analyses. Reasonable PPEs were made for all woody taxa, but not for Poaceae.
In conclusion, pollen analysis is a suitable tool to reconstruct past vegetation dynamics in savannas. However, because pollen cannot identify grasses beyond family level, a multiproxy approach, particularly the use of sedaDNA, is required. I was able to separate stable encroached states from mere woodland phases, and could identify drivers and speculate about related feedbacks. In addition, the REVEALS-based quantitative vegetation reconstruction clearly reflects the magnitude of the changes in the vegetation cover that occurred during the last 130 years, despite the limitations of some PPEs.
This research provides new insights into pollen-vegetation relationships in savannas and highlights the importance of multiproxy approaches when reconstructing past vegetation dynamics in semi-arid environments. It also provides the first time series with sufficient taxonomic resolution to show changes in vegetation composition during shrub encroachment, as well as the first quantitative reconstruction of past land cover in the region. These results help to identify the different stages in savanna dynamics and can be used to calibrate predictive models of vegetation change, which are highly relevant to land management.
A tale of shifting relations
(2021)
Understanding the dynamics between the East Asian summer (EASM) and winter monsoon (EAWM) is needed to predict their variability under future global warming scenarios. Here, we investigate the relationship between EASM and EAWM as well as the mechanisms driving their variability during the last 10,000 years by stacking marine and terrestrial (non-speleothem) proxy records from the East Asian realm. This provides a regional and proxy independent signal for both monsoonal systems. The respective signal was subsequently analysed using a linear regression model. We find that the phase relationship between EASM and EAWM is not time-constant and significantly depends on orbital configuration changes. In addition, changes in the Atlantic Meridional Overturning circulation, Arctic sea-ice coverage, El Niño-Southern Oscillation and Sun Spot numbers contributed to millennial scale changes in the EASM and EAWM during the Holocene. We also argue that the bulk signal of monsoonal activity captured by the stacked non-speleothem proxy records supports the previously argued bias of speleothem climatic archives to moisture source changes and/or seasonality.
Magmatic continental rifts often constitute the earliest stage of nascent plate boundaries. These extensional tectonic provinces are characterized by ubiquitous normal faulting and volcanic activity; the spatial pattern, the geometry, and the age of these normal faults can help to unravel the spatiotemporal relationships between extensional deformation, magmatism, and long-wavelength crustal deformation of continental rift provinces. This study focuses on the active faulting in the Kenya Rift of the Cenozoic East African Rift System (EARS) with a focus on the mid-Pleistocene to the present-day.
To examine the early stages of continental break-up in the EARS, this thesis presents a time-averaged minimum extension rate for the inner graben of the Northern Kenya Rift (NKR) for the last 0.5 m.y. Using the TanDEM-X digital elevation model, fault-scarp geometries and associated throws are determined across the volcano-tectonic axis of the inner graben of the NKR. By integrating existing geochronology of faulted units with new ⁴⁰Ar/³⁹Ar radioisotopic dates, time-averaged extension rates are calculated. This study reveals that in the inner graben of the NKR, the long-term extension rate based on mid-Pleistocene to recent brittle deformation has minimum values of 1.0 to 1.6 mm yr⁻¹, locally with values up to 2.0 mm yr⁻¹. In light of virtually inactive border faults of the NKR, we show that extension is focused in the region of the active volcano-tectonic axis in the inner graben, thus highlighting the maturing of continental rifting in the NKR.
The phenomenon of focused extension is further investigated with a structural analysis of the youngest volcanic manifestations of the Kenya Rift, their relationship with extensional structures, and their overprint by Holocene faulting. In this context I analyzed the fault characteristics at the ~36 ka old Menengai Caldera and adjacent areas in the Central Kenya Rift using detailed field mapping and a structure-from-motion-based DEM generated from UAV data. In general, the Holocene intra-rift normal faults are dip-slip faults which strike NNE and thus reflect the present-day tectonic stress field; however, inside Menengai caldera persistent magmatic activity and magmatic resurgence overprints these young structures significantly. The caldera is located at the center of an actively extending rift segment and this and the other volcanic edifices of the Kenya Rift may constitute nucleation points of faulting an magmatic extensional processes that ultimately lead into a future stage of magma-assisted rifting.
When viewed at the scale of the entire Kenya Rift the protracted normal faulting in this region compartmentalizes the larger rift depressions, and influences the sedimentology and the hydrology of the intra-rift basins at a scale of less than 100 km. In the present day, most of the fault-bounded sub-basins of the Kenya Rift are hydrologically isolated due to this combination of faulting and magmatic activity that has generated efficient hydrological barriers that maintain these basins as semi-independent geomorphic entities. This isolation, however, was overcome during wetter climatic conditions during the past when the basins were transiently connected. I therefore also investigated the hydrological connectivity of the rift basins during the African Humid Period of the early Holocene, when climate was wetter. With the help of DEM analysis, lake-highstand indicators, radiocarbon dating, and a review of the fossil record, two lake-river-cascades could be identified: one directed southward, and one directed northward. Both cascades connected presently isolated rift basins during the early Holocene via spillovers of lakes and incised river gorges. This hydrological connection fostered the dispersal of aquatic faunas along the rift, and in addition, the water divide between the two river systems represented the only terrestrial dispersal corridor across the Kenya Rift. The reconstruction explains isolated distributions of Nilotic fish species in Kenya Rift lakes and of Guineo-Congolian mammal species in forests east of the Kenya Rift. On longer timescales, repeated episodes of connectivity and isolation must have occurred. To address this problem I participated in research to analyze a sediment drill core from the Koora basin of the Southern Kenya Rift, which provides a paleo-environmental record of the last 1 Ma. Based on this record it can be concluded that at ~400 ka relatively stable environmental conditions were disrupted by tectonic, hydrological, and ecological changes, resulting in increasingly large and frequent fluctuations in water availability, grassland communities, and woody plant cover. The major environmental shifts reflected in the drill core data coincide with phases where volcano-tectonic activity affected the basin. This thesis therefore shows how protracted extensional tectonic processes and the resulting geomorphologic conditions can affect the hydrology, the paleo-environment and the biodiversity of extensional zones in Kenya and elsewhere.
Fluids in the Earth's crust can move by creating and flowing through fractures, in a process called `hydraulic fracturing’. The tip-line of such fluid-filled fractures grows at locations where stress is larger than the strength of the rock. Where the tip stress vanishes, the fracture closes and the fluid-front retreats. If stress gradients exist on the fracture's walls, induced by fluid/rock density contrasts or topographic stresses, this results in an asymmetric shape and growth of the fracture, allowing for the contained batch of fluid to propagate through the crust.
The state-of-the-art analytical and numerical methods to simulate fluid-filled fracture propagation are two-dimensional (2D). In this work I extend these to three dimensions (3D). In my analytical method, I approximate the propagating 3D fracture as a penny-shaped crack that is influenced by both an internal pressure and stress gradients. In addition, I develop a numerical method to model propagation where curved fractures can be simulated as a mesh of triangular dislocations, with the displacement of faces computed using the displacement discontinuity method. I devise a rapid technique to approximate stress intensity and use this to calculate the advance of the tip-line. My 3D models can be applied to arbitrary stresses, topographic and crack shapes, whilst retaining short computation times.
I cross-validate my analytical and numerical methods and apply them to various natural and man-made settings, to gain additional insights into the movements of hydraulic fractures such as magmatic dikes and fluid injections in rock. In particular, I calculate the `volumetric tipping point’, which once exceeded allows a fluid-filled fracture to propagate in a `self-sustaining’ manner. I discuss implications this has for hydro-fracturing in industrial operations. I also present two studies combining physical models that define fluid-filled fracture trajectories and Bayesian statistical techniques. In these studies I show that the stress history of the volcanic edifice defines the location of eruptive vents at volcanoes. Retrieval of the ratio between topographic to remote stresses allows for forecasting of probable future vent locations. Finally, I address the mechanics of 3D propagating dykes and sills in volcanic regions. I focus on Sierra Negra volcano in the Gal\'apagos islands, where in 2018, a large sill propagated with an extremely curved trajectory. Using a 3D analysis, I find that shallow horizontal intrusions are highly sensitive to topographic and buoyancy stress gradients, as well as the effects of the free surface.
Quantitative geomorphic research depends on accurate topographic data often collected via remote sensing. Lidar, and photogrammetric methods like structure-from-motion, provide the highest quality data for generating digital elevation models (DEMs). Unfortunately, these data are restricted to relatively small areas, and may be expensive or time-consuming to collect. Global and near-global DEMs with 1 arcsec (∼30 m) ground sampling from spaceborne radar and optical sensors offer an alternative gridded, continuous surface at the cost of resolution and accuracy. Accuracy is typically defined with respect to external datasets, often, but not always, in the form of point or profile measurements from sources like differential Global Navigation Satellite System (GNSS), spaceborne lidar (e.g., ICESat), and other geodetic measurements. Vertical point or profile accuracy metrics can miss the pixel-to-pixel variability (sometimes called DEM noise) that is unrelated to true topographic signal, but rather sensor-, orbital-, and/or processing-related artifacts. This is most concerning in selecting a DEM for geomorphic analysis, as this variability can affect derivatives of elevation (e.g., slope and curvature) and impact flow routing. We use (near) global DEMs at 1 arcsec resolution (SRTM, ASTER, ALOS, TanDEM-X, and the recently released Copernicus) and develop new internal accuracy metrics to assess inter-pixel variability without reference data. Our study area is in the arid, steep Central Andes, and is nearly vegetation-free, creating ideal conditions for remote sensing of the bare-earth surface. We use a novel hillshade-filtering approach to detrend long-wavelength topographic signals and accentuate short-wavelength variability. Fourier transformations of the spatial signal to the frequency domain allows us to quantify: 1) artifacts in the un-projected 1 arcsec DEMs at wavelengths greater than the Nyquist (twice the nominal resolution, so > 2 arcsec); and 2) the relative variance of adjacent pixels in DEMs resampled to 30-m resolution (UTM projected). We translate results into their impact on hillslope and channel slope calculations, and we highlight the quality of the five DEMs. We find that the Copernicus DEM, which is based on a carefully edited commercial version of the TanDEM-X, provides the highest quality landscape representation, and should become the preferred DEM for topographic analysis in areas without sufficient coverage of higher-quality local DEMs.
The Big Naryn Complex (BNC) in the East Djetim-Too Range of the Kyrgyz Middle Tianshan block is a tectonized, at least 2 km thick sequence of predominantly felsic to intermediate volcanic rocks intruded by porphyric rhyolite sills. It overlies a basement of metamorphic rocks and is overlain by late Neoproterozoic Djetim-Too Formation sediments; these also occur as tectonic intercalations in the BNC. The up to ca. 1100 m thick Lower Member is composed of predominantly rhyolites-to-dacites and minor basalts, while the at least 900 m thick pyroclastic Upper Member is dominated by rhyolitic-to-dacitic ignimbrites. Porphyric rhyolite sills are concentrated at the top of the Lower Member. A Lower Member rhyolite and a sill sample have LA-ICP-MS U-Pb zircon crystallization ages of 726.1 +/- 2.2 Ma and 720.3 +/- 6.5 Ma, respectively, showing that most of the magmatism occurred within a short time span in the late Tonian-early Cryogenian. Inherited zircons in the sill sample have Neoarchean (2.63, 2.64 Ga), Paleo- (2.33-1.81 Ga), Meso- (1.55 Ga), and Neoproterozoic (ca. 815 Ma) ages, and were derived from a heterogeneous Kuilyu Complex basement. A 1751 +/- 7 Ma Ar-40/Ar-39 age for amphibole from metagabbro is the age of cooling subsequent to Paleoproterozoic metamorphism of the Kuilyu Complex. The large amount of pyroclastic rocks, and their major and trace element compositions, the presence of Neoarchean to Neoproterozoic inherited zircons and a depositional basement of metamorphic rocks point to formation of the BNC in a continental magmatic arc setting.
One third of the world's population lives in areas where earthquakes causing at least slight damage are frequently expected. Thus, the development and testing of global seismicity models is essential to improving seismic hazard estimates and earthquake-preparedness protocols for effective disaster-risk mitigation. Currently, the availability and quality of geodetic data along plate-boundary regions provides the opportunity to construct global models of plate motion and strain rate, which can be translated into global maps of forecasted seismicity. Moreover, the broad coverage of existing earthquake catalogs facilitates in present-day the calibration and testing of global seismicity models. As a result, modern global seismicity models can integrate two independent factors necessary for physics-based, long-term earthquake forecasting, namely interseismic crustal strain accumulation and sudden lithospheric stress release.
In this dissertation, I present the construction of and testing results for two global ensemble seismicity models, aimed at providing mean rates of shallow (0-70 km) earthquake activity for seismic hazard assessment. These models depend on the Subduction Megathrust Earthquake Rate Forecast (SMERF2), a stationary seismicity approach for subduction zones, based on the conservation of moment principle and the use of regional "geodesy-to-seismicity" parameters, such as corner magnitudes, seismogenic thicknesses and subduction dip angles. Specifically, this interface-earthquake model combines geodetic strain rates with instrumentally-recorded seismicity to compute long-term rates of seismic and geodetic moment. Based on this, I derive analytical solutions for seismic coupling and earthquake activity, which provide this earthquake model with the initial abilities to properly forecast interface seismicity. Then, I integrate SMERF2 interface-seismicity estimates with earthquake computations in non-subduction zones provided by the Seismic Hazard Inferred From Tectonics based on the second iteration of the Global Strain Rate Map seismicity approach to construct the global Tectonic Earthquake Activity Model (TEAM). Thus, TEAM is designed to reduce number, and potentially spatial, earthquake inconsistencies of its predecessor tectonic earthquake model during the 2015-2017 period. Also, I combine this new geodetic-based earthquake approach with a global smoothed-seismicity model to create the World Hybrid Earthquake Estimates based on Likelihood scores (WHEEL) model. This updated hybrid model serves as an alternative earthquake-rate approach to the Global Earthquake Activity Rate model for forecasting long-term rates of shallow seismicity everywhere on Earth.
Global seismicity models provide scientific hypotheses about when and where earthquakes may occur, and how big they might be. Nonetheless, the veracity of these hypotheses can only be either confirmed or rejected after prospective forecast evaluation. Therefore, I finally test the consistency and relative performance of these global seismicity models with independent observations recorded during the 2014-2019 pseudo-prospective evaluation period. As a result, hybrid earthquake models based on both geodesy and seismicity are the most informative seismicity models during the testing time frame, as they obtain higher information scores than their constituent model components. These results support the combination of interseismic strain measurements with earthquake-catalog data for improved seismicity modeling. However, further prospective evaluations are required to more accurately describe the capacities of these global ensemble seismicity models to forecast longer-term earthquake activity.
In my doctoral thesis, I examine continuous gravity measurements for monitoring of the geothermal site at Þeistareykir in North Iceland. With the help of high-precision superconducting gravity meters (iGravs), I investigate underground mass changes that are caused by operation of the geothermal power plant (i.e. by extraction of hot water and reinjection of cold water). The overall goal of this research project is to make a statement about the sustainable use of the geothermal reservoir, from which also the Icelandic energy supplier and power plant operator Landsvirkjun should benefit.
As a first step, for investigating the performance and measurement stability of the gravity meters, in summer 2017, I performed comparative measurements at the gravimetric observatory J9 in Strasbourg. From the three-month gravity time series, I examined calibration, noise and drift behaviour of the iGravs in comparison to stable long-term time series of the observatory superconducting gravity meters. After preparatory work in Iceland (setup of gravity stations, additional measuring equipment and infrastructure, discussions with Landsvirkjun and meetings with the Icelandic partner institute ISOR), gravity monitoring at Þeistareykir was started in December 2017. With the help of the iGrav records of the initial 18 months after start of measurements, I carried out the same investigations (on calibration, noise and drift behaviour) as in J9 to understand how the transport of the superconducting gravity meters to Iceland may influence instrumental parameters.
In the further course of this work, I focus on modelling and reduction of local gravity contributions at Þeistareykir. These comprise additional mass changes due to rain, snowfall and vertical surface displacements that superimpose onto the geothermal signal of the gravity measurements. For this purpose, I used data sets from additional monitoring sensors that are installed at each gravity station and adapted scripts for hydro-gravitational modelling. The third part of my thesis targets geothermal signals in the gravity measurements.
Together with my PhD colleague Nolwenn Portier from France, I carried out additional gravity measurements with a Scintrex CG5 gravity meter at 26 measuring points within the geothermal field in the summers of 2017, 2018 and 2019. These annual time-lapse gravity measurements are intended to increase the spatial coverage of gravity data from the three continuous monitoring stations to the entire geothermal field. The combination of CG5 and iGrav observations, as well as annual reference measurements with an FG5 absolute gravity meter represent the hybrid gravimetric monitoring method for Þeistareykir. Comparison of the gravimetric data to local borehole measurements (of groundwater levels, geothermal extraction and injection rates) is used to relate the observed gravity changes to the actually extracted (and reinjected) geothermal fluids. An approach to explain the observed gravity signals by means of forward modelling of the geothermal production rate is presented at the end of the third (hybrid gravimetric) study. Further modelling with the help of the processed gravity data is planned by Landsvirkjun. In addition, the experience from time-lapse and continuous gravity monitoring will be used for future gravity measurements at the Krafla geothermal field 22 km south-east of Þeistareykir.
Glacial lakes in the Hindu Kush–Karakoram–Himalayas–Nyainqentanglha (HKKHN) region have grown rapidly in number and area in past decades, and some dozens have drained in catastrophic glacial lake outburst floods (GLOFs). Estimating regional susceptibility of glacial lakes has largely relied on qualitative assessments by experts, thus motivating a more systematic and quantitative appraisal. Before the backdrop of current climate-change projections and the potential of elevation-dependent warming, an objective and regionally consistent assessment is urgently needed. We use an inventory of 3390 moraine-dammed lakes and their documented outburst history in the past four decades to test whether elevation, lake area and its rate of change, glacier-mass balance, and monsoonality are useful inputs to a probabilistic classification model. We implement these candidate predictors in four Bayesian multi-level logistic regression models to estimate the posterior susceptibility to GLOFs. We find that mostly larger lakes have been more prone to GLOFs in the past four decades regardless of the elevation band in which they occurred. We also find that including the regional average glacier-mass balance improves the model classification. In contrast, changes in lake area and monsoonality play ambiguous roles. Our study provides first quantitative evidence that GLOF susceptibility in the HKKHN scales with lake area, though less so with its dynamics. Our probabilistic prognoses offer improvement compared to a random classification based on average GLOF frequency. Yet they also reveal some major uncertainties that have remained largely unquantified previously and that challenge the applicability of single models. Ensembles of multiple models could be a viable alternative for more accurately classifying the susceptibility of moraine-dammed lakes to GLOFs.
DeepGeoMap
(2021)
In recent years, deep learning improved the way remote sensing data is processed. The classification of hyperspectral data is no exception. 2D or 3D convolutional neural networks have outperformed classical algorithms on hyperspectral image classification in many cases. However, geological hyperspectral image classification includes several challenges, often including spatially more complex objects than found in other disciplines of hyperspectral imaging that have more spatially similar objects (e.g., as in industrial applications, aerial urban- or farming land cover types). In geological hyperspectral image classification, classical algorithms that focus on the spectral domain still often show higher accuracy, more sensible results, or flexibility due to spatial information independence. In the framework of this thesis, inspired by classical machine learning algorithms that focus on the spectral domain like the binary feature fitting- (BFF) and the EnGeoMap algorithm, the author of this thesis proposes, develops, tests, and discusses a novel, spectrally focused, spatial information independent, deep multi-layer convolutional neural network, named 'DeepGeoMap’, for hyperspectral geological data classification. More specifically, the architecture of DeepGeoMap uses a sequential series of different 1D convolutional neural networks layers and fully connected dense layers and utilizes rectified linear unit and softmax activation, 1D max and 1D global average pooling layers, additional dropout to prevent overfitting, and a categorical cross-entropy loss function with Adam gradient descent optimization. DeepGeoMap was realized using Python 3.7 and the machine and deep learning interface TensorFlow with graphical processing unit (GPU) acceleration. This 1D spectrally focused architecture allows DeepGeoMap models to be trained with hyperspectral laboratory image data of geochemically validated samples (e.g., ground truth samples for aerial or mine face images) and then use this laboratory trained model to classify other or larger scenes, similar to classical algorithms that use a spectral library of validated samples for image classification. The classification capabilities of DeepGeoMap have been tested using two geological hyperspectral image data sets. Both are geochemically validated hyperspectral data sets one based on iron ore and the other based on copper ore samples. The copper ore laboratory data set was used to train a DeepGeoMap model for the classification and analysis of a larger mine face scene within the Republic of Cyprus, where the samples originated from. Additionally, a benchmark satellite-based dataset, the Indian Pines data set, was used for training and testing. The classification accuracy of DeepGeoMap was compared to classical algorithms and other convolutional neural networks. It was shown that DeepGeoMap could achieve higher accuracies and outperform these classical algorithms and other neural networks in the geological hyperspectral image classification test cases. The spectral focus of DeepGeoMap was found to be the most considerable advantage compared to spectral-spatial classifiers like 2D or 3D neural networks. This enables DeepGeoMap models to train data independently of different spatial entities, shapes, and/or resolutions.
Anthropogenic climate change alters the hydrological cycle. While certain areas experience more intense precipitation events, others will experience droughts and increased evaporation, affecting water storage in long-term reservoirs, groundwater, snow, and glaciers. High elevation environments are especially vulnerable to climate change, which will impact the water supply for people living downstream. The Himalaya has been identified as a particularly vulnerable system, with nearly one billion people depending on the runoff in this system as their main water resource. As such, a more refined understanding of spatial and temporal changes in the water cycle in high altitude systems is essential to assess variations in water budgets under different climate change scenarios.
However, not only anthropogenic influences have an impact on the hydrological cycle, but changes to the hydrological cycle can occur over geological timescales, which are connected to the interplay between orogenic uplift and climate change. However, their temporal evolution and causes are often difficult to constrain. Using proxies that reflect hydrological changes with an increase in elevation, we can unravel the history of orogenic uplift in mountain ranges and its effect on the climate.
In this thesis, stable isotope ratios (expressed as δ2H and δ18O values) of meteoric waters and organic material are combined as tracers of atmospheric and hydrologic processes with remote sensing products to better understand water sources in the Himalayas. In addition, the record of modern climatological conditions based on the compound specific stable isotopes of leaf waxes (δ2Hwax) and brGDGTs (branched Glycerol dialkyl glycerol tetraethers) in modern soils in four Himalayan river catchments was assessed as proxies of the paleoclimate and (paleo-) elevation. Ultimately, hydrological variations over geological timescales were examined using δ13C and δ18O values of soil carbonates and bulk organic matter originating from sedimentological sections from the pre-Siwalik and Siwalik groups to track the response of vegetation and monsoon intensity and seasonality on a timescale of 20 Myr.
I find that Rayleigh distillation, with an ISM moisture source, mainly controls the isotopic composition of surface waters in the studied Himalayan catchments. An increase in d-excess in the spring, verified by remote sensing data products, shows the significant impact of runoff from snow-covered and glaciated areas on the surface water isotopic values in the timeseries.
In addition, I show that biomarker records such as brGDGTs and δ2Hwax have the potential to record (paleo-) elevation by yielding a significant correlation with the temperature and surface water δ2H values, respectively, as well as with elevation. Comparing the elevation inferred from both brGDGT and δ2Hwax, large differences were found in arid sections of the elevation transects due to an additional effect of evapotranspiration on δ2Hwax. A combined study of these proxies can improve paleoelevation estimates and provide recommendations based on the results found in this study.
Ultimately, I infer that the expansion of C4 vegetation between 20 and 1 Myr was not solely dependent on atmospheric pCO2, but also on regional changes in aridity and seasonality from to the stable isotopic signature of the two sedimentary sections in the Himalaya (east and west).
This thesis shows that the stable isotope chemistry of surface waters can be applied as a tool to monitor the changing Himalayan water budget under projected increasing temperatures. Minimizing the uncertainties associated with the paleo-elevation reconstructions were assessed by the combination of organic proxies (δ2Hwax and brGDGTs) in Himalayan soil. Stable isotope ratios in bulk soil and soil carbonates showed the evolution of vegetation influenced by the monsoon during the late Miocene, proving that these proxies can be used to record monsoon intensity, seasonality, and the response of vegetation. In conclusion, the use of organic proxies and stable isotope chemistry in the Himalayas has proven to successfully record changes in climate with increasing elevation. The combination of δ2Hwax and brGDGTs as a new proxy provides a more refined understanding of (paleo-)elevation and the influence of climate.
By regulating the concentration of carbon in our atmosphere, the global carbon cycle drives changes in our planet’s climate and habitability. Earth surface processes play a central, yet insufficiently constrained role in regulating fluxes of carbon between terrestrial reservoirs and the atmosphere. River systems drive global biogeochemical cycles by redistributing significant masses of carbon across the landscape. During fluvial transit, the balance between carbon oxidation and preservation determines whether this mass redistribution is a net atmospheric CO2 source or sink. Existing models for fluvial carbon transport fail to integrate the effects of sediment routing processes, resulting in large uncertainties in fluvial carbon fluxes to the oceans.
In this Ph.D. dissertation, I address this knowledge gap through three studies that focus on the timescale and routing pathways of fluvial mass transfer and show their effect on the composition and fluxes of organic carbon exported by rivers. The hypotheses posed in these three studies were tested in an analog lowland alluvial river system – the Rio Bermejo in Argentina. The Rio Bermejo annually exports more than 100 Mt of sediment and organic matter from the central Andes, and transports this material nearly 1300 km downstream across the lowland basin without influence from tributaries, allowing me to isolate the effects of geomorphic processes on fluvial organic carbon cycling. These studies focus primarily on the geochemical composition of suspended sediment collected from river depth profiles along the length of the Rio Bermejo.
In Chapter 3, I aimed to determine the mean fluvial sediment transit time for the Rio Bermejo and evaluate the geomorphic processes that regulate the rate of downstream sediment transfer. I developed a framework to use meteoric cosmogenic 10Be (10Bem) as a chronometer to track the duration of sediment transit from the mountain front downstream along the ~1300 km channel of the Rio Bermejo. I measured 10Bem concentrations in suspended sediment sampled from depth profiles, and found a 230% increase along the fluvial transit pathway. I applied a simple model for the time-dependent accumulation of 10Bem on the floodplain to estimate a mean sediment transit time of 8.5±2.2 kyr. Furthermore, I show that sediment transit velocity is influenced by lateral migration rate and channel morphodynamics. This approach to measuring sediment transit time is much more precise than other methods previously used and shows promise for future applications.
In Chapter 4, I aimed to quantify the effects of hydrodynamic sorting on the composition and quantity of particulate organic carbon (POC) export transported by lowland rivers. I first used scanning electron miscroscopy (SEM) coupled with nanoscale secondary ion mass spectrometry (NanoSIMS) analyses to show that the Bermejo transports two principal types of POC: 1) mineral-bound organic carbon associated with <4 µm, platy grains, and 2) coarse discrete organic particles. Using n-alkane stable isotope data and particle shape analysis, I showed that these two carbon pools are vertically sorted in the water column, due to differences in particle settling velocity. This vertical sorting may drive modern POC to be transported efficiently from source-to-sink, driving efficient CO2 drawdown. Simultaneously, vertical sorting may drive degraded, mineral-bound POC to be deposited overbank and stored on the floodplain for centuries to millennia, resulting in enhanced POC remineralization. In the Rio Bermejo, selective deposition of coarse material causes the proportion of mineral-bound POC to increase with distance downstream, but the majority of exported POC is composed of discrete organic particles, suggesting that the river is a net carbon sink. In summary, this study shows that selective deposition and hydraulic sorting control the composition and fate of fluvial POC during fluvial transit.
In Chapter 5, I characterized and quantified POC transformation and oxidation during fluvial transit. I analyzed the radiocarbon content and stable carbon isotopic composition of Rio Bermejo suspended sediment and found that POC ages during fluvial transit, but is also degraded and oxidized during transient floodplain storage. Using these data, I developed a conceptual model for fluvial POC cycling that allows the estimation of POC oxidation relative to POC export, and ultimately reveals whether a river is a net source or sink of CO2 to the atmosphere. Through this study, I found that the Rio Bermejo annually exports more POC than is oxidized during transit, largely due to high rates of lateral migration that cause erosion of floodplain vegetation and soil into the river. These results imply that human engineering of rivers could alter the fluvial carbon balance, by reducing lateral POC inputs and increasing the mean sediment transit time.
Together, these three studies quantitatively link geomorphic processes to rates of POC transport and degradation across sub-annual to millennial time scales and nanoscale to 103 km spatial scales, laying the groundwork for a global-scale fluvial organic carbon cycling model.
We developed an orbital tuned age model for the composite Chew Bahir sediment core, obtained from the Chew Bahir basin (CHB), southern Ethiopia. To account for the effects of sedimentation rate changes on the spectral expression of the orbital cycles we developed a new method: the Multi-band Wavelet Age modeling technique (MUBAWA). By using a Continuous Wavelet Transformation, we were able to track frequency shifts that resulted from changing sedimentation rates and thus calculated tuned age model encompassing the last 620 kyrs. The results show a good agreement with the directly dated age model that is available from the dating of volcanic ashes. Then we used the XRF data from CHB and developed a new and robust humid-arid index of east African climate during the last 620 kyrs. To disentangle the relationship of the selected elements we performed a principal component analysis (PCA). In a following step we applied a continuous wavelet transformation on the PC1, using the directly dated age model. The resulting wavelet power spectrum, unlike a normal power spectrum, displays the occurrence of cycles/frequencies in time. The results highlight that the precession cycles are most dominantly expressed under the 400 kyrs eccentricity maximum whereas weakly expressed during eccentricity minimum. This suggests that insolation is a key driver of the climatic variability observed at CHB throughout the last 620 kyrs. In addition, the prevalence of half-precession and obliquity signals was documented. The latter is attributed to the inter-tropical insolation gradient and not interpreted as an imprint of high latitudes forcing on climatic changes in the tropics. In addition, a windowed analysis of variability was used to detect changes in variance over time and showed that strong climate variability occurred especially along the transition from a dominant insolation-controlled humid climate background state towards a predominantly dry and less-insolation controlled climate. The last chapter dealt with non-linear aspects of climate changes represented by the sediments of the CHB. We use recurrence quantification analysis to detect non-linear changes within the potassium concentration of Chew Bahir sediment cores during the last 620 kyrs. The concentration of potassium in the sediments of the lake is subject to geochemical processes related to the evaporation rate of the lake water at the time of deposition. Based on recurrence analysis, two types of variabilities could be distinguished. Type 1 represents slow variations within the precession period bandwidth of 20 kyrs and a tendency towards extreme climatic events whereas type 2 represents fast, highly variable climatic transitions between wet and dry climate states. While type 1 variability is linked to eccentricity maxima, type 2 variability occurs during the 400 kyrs eccentricity minimum. The climate history presented here shows that during high eccentricity a strongly insolation-driven climate system prevailed, whereas during low eccentricity the climate was more strongly affected by short-term variability changes. The short-term environmental changes, reflected in the increased variability might have influenced the evolution, technological advances and expansion of early modern humans who lived in this region. In the Olorgesaille Basin the temporal changes in the occurrence of stone tools, which bracket the transition from Acheulean to Middle Stone Age (MSA) technologies at between 499–320 kyrs, could potentially correlate to the marked transition from a rather stable climate with less variability to a climate with increased variability in the CHB. We conclude that populations of early anatomically modern humans are more likely to have experienced climatic stress during episodes of low eccentricity, associated with dry and high variability climate conditions, which may have led to technological innovation, such as the transition from the Acheulean to the Middle Stone Age.
Soziale Medien sind ein wesentlicher Bestandteil des Alltags von Schüler*innen und gleichzeitig zunehmend wichtig in Wirtschaft, Politik und Wissenschaft. Am Beispiel von Twitter zeigt dieser Beitrag, dass soziale Medien im Unterricht auch für die Beantwortung geographischer Fragestellungen verwendet werden können. Hierfür eignen sich Twitter-Daten aufgrund ihrer Georeferenzierung und weiterer interessanter Inhalte besonders. Der Beitrag gibt einen Überblick über die Verwendung von Twitter für sozialwissenschaftliche und humangeographische Fragestellungen und reflektiert die Nutzung von Twitter im Unterricht. Für die Unterrichtspraxis werden Beispiele zu den Themen Braunkohle, Flutereignisse und Raumwahrnehmungen sowie Anleitungen zur Auswertung, Anwendung und Reflexion von Twitter-Analysen vorgestellt.
Forming as a result of the collision between the Adriatic and European plates, the Alpine orogen exhibits significant lithospheric heterogeneity due to the long history of interplay between these plates, other continental and oceanic blocks in the region, and inherited features from preceeding orogenies. This implies that the thermal and rheological configuration of the lithosphere also varies significantly throughout the region. Lithology and temperature/pressure conditions exert a first order control on rock strength, principally via thermally activated creep deformation and on the distribution at depth of the brittle-ductile transition zone, which can be regarded as the lower bound to the seismogenic zone. Therefore, they influence the spatial distribution of seismicity within a lithospheric plate. In light of this, accurately constrained geophysical models of the heterogeneous Alpine lithospheric configuration, are crucial in describing regional deformation patterns. However, despite the amount of research focussing on the area, different hypotheses still exist regarding the present-day lithospheric state and how it might relate to the present-day seismicity distribution.
This dissertaion seeks to constrain the Alpine lithospheric configuration through a fully 3D integrated modelling workflow, that utilises multiple geophysical techniques and integrates from all available data sources. The aim is therefore to shed light on how lithospheric heterogeneity may play a role in influencing the heterogeneous patterns of seismicity distribution observed within the region. This was accomplished through the generation of: (i) 3D seismically constrained, structural and density models of the lithosphere, that were adjusted to match the observed gravity field; (ii) 3D models of the lithospheric steady state thermal field, that were adjusted to match observed wellbore temperatures; and (iii) 3D rheological models of long term lithospheric strength, with the results of each step used as input for the following steps.
Results indicate that the highest strength within the crust (~ 1 GPa) and upper mantle (> 2 GPa), are shown to occur at temperatures characteristic for specific phase transitions (more felsic crust: 200 – 400 °C; more mafic crust and upper lithospheric mantle: ~600 °C) with almost all seismicity occurring in these regions. However, inherited lithospheric heterogeneity was found to significantly influence this, with seismicity in the thinner and more mafic Adriatic crust (~22.5 km, 2800 kg m−3, 1.30E-06 W m-3) occuring to higher temperatures (~600 °C) than in the thicker and more felsic European crust (~27.5 km, 2750 kg m−3, 1.3–2.6E-06 W m-3, ~450 °C). Correlation between seismicity in the orogen forelands and lithospheric strength, also show different trends, reflecting their different tectonic settings. As such, events in the plate boundary setting of the southern foreland correlate with the integrated lithospheric strength, occurring mainly in the weaker lithosphere surrounding the strong Adriatic indenter. Events in the intraplate setting of the northern foreland, instead correlate with crustal strength, mainly occurring in the weaker and warmer crust beneath the Upper Rhine Graben.
Therefore, not only do the findings presented in this work represent a state of the art understanding of the lithospheric configuration beneath the Alps and their forelands, but also a significant improvement on the features known to significantly influence the occurrence of seismicity within the region. This highlights the importance of considering lithospheric state in regards to explaining observed patterns of deformation.
This work develops hybrid methods of imaging spectroscopy for open pit mining and examines their feasibility compared with state-of-the-art. The material distribution within a mine face differs in the small scale and within daily assigned extraction segments. These changes can be relevant to subsequent processing steps but are not always visually identifiable prior to the extraction. Misclassifications that cause false allocations of extracted material need to be minimized in order to reduce energy-intensive material re-handling. The use of imaging spectroscopy aspires to the allocation of relevant deposit-specific materials before extraction, and allows for efficient material handling after extraction. The aim of this work is the parameterization of imaging spectroscopy for pit mining applications and the development and evaluation of a workflow for a mine face, ground- based, spectral characterization. In this work, an application-based sensor adaptation is proposed. The sensor complexity is reduced by down-sampling the spectral resolution of the system based on the samples’ spectral characteristics. This was achieved by the evaluation of existing hyperspectral outcrop analysis approaches based on laboratory sample scans from the iron quadrangle in Minas Gerais, Brazil and by the development of a spectral mine face monitoring workflow which was tested for both an operating and an inactive open pit copper mine in the Republic of Cyprus.
The workflow presented here is applied to three regional data sets: 1) Iron ore samples from Brazil, (laboratory); 2) Samples and hyperspectral mine face imagery from the copper-gold-pyrite mine Apliki, Republic of Cyprus (laboratory and mine face data); and 3) Samples and hyperspectral mine face imagery from the copper-gold-pyrite deposit Three Hills, Republic of Cyprus (laboratory and mine face data). The hyperspectral laboratory dataset of fifteen Brazilian iron ore samples was used to evaluate different analysis methods and different sensor models. Nineteen commonly used methods to analyze and map hyperspectral data were compared regarding the methods’ resulting data products and the accuracy of the mapping and the analysis computation time. Four of the evaluated methods were determined for subsequent analyses to determine the best-performing algorithms: The spectral angle mapper (SAM), a support vector machine algorithm (SVM), the binary feature fitting algorithm (BFF) and the EnMap geological mapper (EnGeoMap). Next, commercially available imaging spectroscopy sensors were evaluated for their usability in open pit mining conditions. Step-wise downsampling of the data - the reduction of the number of bands with an increase of each band’s bandwidth - was performed to investigate the possible simplification and ruggedization of a sensor without a quality fall-off of the mapping results. The impact of the atmosphere visible in the spectrum between 1300–2010nm was reduced by excluding the spectral range from the data for mapping. This tested the feasibility of the method under realistic open pit data conditions. Thirteen datasets based on the different, downsampled sensors were analyzed with the four predetermined methods. The optimum sensor for spectral mine face material distinction was determined as a VNIR-SWIR sensor with 40nm bandwidths in the VNIR and 15nm bandwidths in the SWIR spectral range and excluding the atmospherically impacted bands. The Apliki mine sample dataset was used for the application of the found optimal analyses and sensors. Thirty-six samples were analyzed geochemically and mineralogically. The sample spectra were compiled to two spectral libraries, both distinguishing between seven different geochemical-spectral clusters. The reflectance dataset was downsampled to five different sensors. The five different datasets were mapped with the SAM, BFF and SVM method achieving mapping accuracies of 85-72%, 85-76% and 57-46% respectively. One mine face scan of Apliki was used for the application of the developed workflow. The mapping results were validated against the geochemistry and mineralogy of thirty-six documented field sampling points and a zonation map of the mine face which is based on sixty-six samples and field mapping. The mine face was analyzed with SAM and BFF. The analysis maps were visualized on top of a Structure-from-Motion derived 3D model of the open pit. The mapped geological units and zones correlate well with the expected zonation of the mine face. The third set of hyperspectral imagery from Three Hills was available for applying the fully-developed workflow. Geochemical sample analyses and laboratory spectral data of fifteen different samples from the Three Hills mine, Republic of Cyprus, were used to analyse a downsampled mine face scan of the open pit. Here, areas of low, medium and high ore content were identified.
The developed workflow is successfully applied to the open pit mines Apliki and Three Hills and the spectral maps reflect the prevailing geological conditions. This work leads through the acquisition, preparation and processing of imaging spectroscopy data, the optimum choice of analysis methodology, and the utilization of simplified, robust sensors that meet the requirements of open pit mining conditions. It accentuates the importance of a site-specific and deposit-specific spectral library for the mine face analysis and underlines the need for geological and spectral analysis experts to successfully implement imaging spectroscopy in the field of open pit mining.
Due to the high concentration of people and infrastructures in European cities, the possible impacts of climate change are particularly high (cities' social, economic and technical vulnerabilities). Adaptation measures to reduce the sensitivity of a city to climate risks are therefore of particular importance. Nevertheless, it is also common to develop compact and dense urban areas to reduce urban sprawl. Urban infill development and sustainable spatial climate policies are thus in apparent conflict with each other. This article examines how German cities deal with the tensions between these two policy fields. Using six case studies, a new heuristic analysis method is applied. This study identifies three key governance aspects that are essential for promoting the joint implementation: instruments, organisation and interaction. Based on our case studies, we conclude that successful implementation can only be achieved through integrative governance including all three domains.
Carbonatite magmatism is a highly efficient transport mechanism from Earth’s mantle to the crust, thus providing insights into the chemistry and dynamics of the Earth’s mantle. One evolving and promising tool for tracing magma interaction are stable iron isotopes, particularly because iron isotope fractionation is controlled by oxidation state and bonding environment. Meanwhile, a large data set on iron isotope fractionation in igneous rocks exists comprising bulk rock compositions and fractionation between mineral groups. Iron isotope data from natural carbonatite rocks are extremely light and of remarkably high variability. This resembles iron isotope data from mantle xenoliths, which are characterized by a variability in δ56Fe spanning three times the range found in basalts, and by the extremely light values of some whole rock samples, reaching δ56Fe as low as -0.69 ‰ in a spinel lherzolite. Cause to this large range of variations may be metasomatic processes, involving metasomatic agents like volatile bearing high-alkaline silicate melts or carbonate melts. The expected effects of metasomatism on iron isotope fractionation vary with parameters like melt/rock-ratio, reaction time, and the nature of metasomatic agents and mineral reactions involved. An alternative or additional way to enrich light isotopes in the mantle could be multiple phases of melt extraction. To interpret the existing data sets more knowledge on iron isotope fractionation factors is needed.
To investigate the behavior of iron isotopes in the carbonatite systems, kinetic and equilibration experiments in natro-carbonatite systems between immiscible silicate and carbonate melts were performed in an internally heated gas pressure vessel at intrinsic redox conditions at temperatures between 900 and 1200 °C and pressures of 0.5 and 0.7 GPa. The iron isotope compositions of coexisting silicate melt and carbonate melt were analyzed by solution MC-ICP-MS. The kinetic experiments employing a Fe-58 spiked starting material show that isotopic equilibrium is obtained after 48 hours. The experimental studies of equilibrium iron isotope fractionation between immiscible silicate and carbonate melts have shown that light isotopes are enriched in the carbonatite melt. The highest Δ56Fesil.m.-carb.melt (mean) of 0.13 ‰ was determined in a system with a strongly peralkaline silicate melt composition (ASI ≥ 0.21, Na/Al ≤ 2.7). In three systems with extremely peralkaline silicate melt compositions (ASI between 0.11 and 0.14) iron isotope fractionation could analytically not be resolved. The lowest Δ56Fesil.m.-carb.melt (mean) of 0.02 ‰ was determined in a system with an extremely peralkaline silicate melt composition (ASI ≤ 0.11 , Na/Al ≥ 6.1). The observed iron isotope fractionation is most likely governed by the redox conditions of the system. Yet, in the systems, where no fractionation occurred, structural changes induced by compositional changes possibly overrule the influence of redox conditions. This interpretation implicates, that the iron isotope system holds the potential to be useful not only for exploring redox conditions in magmatic systems, but also for discovering structural changes in a melt.
In situ iron isotope analyses by femtosecond laser ablation coupled to MC-ICP-MS on magnetite and olivine grains were performed to reveal variations in iron isotope composition on the micro scale. The investigated sample is a melilitite bomb from the Salt Lake Crater group at Honolulu (Oahu, Hawaii), showing strong evidence for interaction with a carbonatite melt. While magnetite grains are rather homogeneous in their iron isotope compositions, olivine grains span a far larger range in iron isotope ratios. The variability of δ56Fe in magnetite is limited from - 0.17 ‰ (± 0.11 ‰, 2SE) to +0.08 ‰ (± 0.09 ‰, 2SE). δ56Fe in olivine range from -0.66‰ (± 0.11 ‰, 2SE) to +0.10 ‰ (± 0.13 ‰, 2SE). Olivine and magnetite grains hold different informations regarding kinetic and equilibrium fractionation due to their different Fe diffusion coefficients. The observations made in the experiments and in the in situ iron isotope analyses suggest that the extremely light iron isotope signatures found in carbonatites are generated by several steps of isotope fractionation during carbonatite genesis. These may involve equilibrium and kinetic fractionation. Since iron isotopic signatures in natural systems are generated by a combination of multiple factors (pressure, temperature, redox conditions, phase composition and structure, time scale), multi tracer approaches are needed to explain signatures found in natural rocks.
Silicate melts are major components of the Earth’s interior and as such they make an essential contribution in igneous processes, in the dynamics of the solid Earth and the chemical development of the entire Earth. Macroscopic physical and chemical properties such as density, compressibility, viscosity, degree of polymerization etc. are determined by the atomic structure of the melt. Depending on the pressure, but also on the temperature and the chemical composition, silicate melts show different structural properties. These properties are best described by the local coordination environment, i.e. symmetry and number of neighbors (coordination number) of an atom, as well as the distance between the central atom and its neighbors (inter-atomic distance). With increasing pressure and temperature, i.e. with increasing depth in the Earth, the density of the melt increases, which can lead to changes in coordination number and distances. If the coordination number remains the same, the distance usually decreases. If the coordination number increases, the distance can increase. These general trends can, however, vary greatly, which can be attributed in particular to the chemical composition.
Due to the fact that natural melts of the deep earth are not accessible to direct investigations, in order to understand their properties under the relevant conditions, extensive experimental and theoretical investigations have been carried out so far. This has often been studied using the example of amorphous samples of the end-members SiO2 and GeO2 , with the latter serving as a structural and chemical analog model to SiO2. Commonly, the experiments were carried out at high pressure and at room temperature. Natural melts are chemically much more complex than the simple end-member SiO2 and GeO2, so that observations made on them may lead to incorrect compression models. Furthermore, the investigations on glasses at room temperature can show potentially strong deviations from the properties of melts under natural thermodynamic conditions.
The aim of this thesis was to explain the influence of the composition and the temperature on the structural properties of the melts at high pressures. To understand this, we studied complex alumino-germanate and alumino-silicate glasses. More precisely, we studied synthetic glasses that have a composition like the mineral albite and like a mixture of albite-diopside at the eutectic point. The albite glass is structurally similar to a simplified granitic melt, while the albite-diopside glass simulates a simplified basaltic melt. To study the local coordination environment of the elements, we used X-ray absorption spectroscopy in combination with a diamond anvil cell. Because the diamonds have a high absorbance for X-rays with energies below 10 keV, the direct investigation of the geologically relevant elements such as Si, Al, Ca, Mg etc. with this spectroscopic probe technique in combination with a diamond anvil cell is not possible. Therefore the glasses were doped with Ge and Sr. These elements serve partially or fully as substitutes for important major elements. In this sense, Ge serves as an a substitute for Si and other network formers, while Sr replaces network modifiers such as Ca, Na, Mg etc.,
as well as other cations with a large ionic radius.
In the first step we studied the Ge K-edge in Ge-Albit-glass, NaAlGe3O8, at room temperature up to 131 GPa. This glass has a higher chemical complexity than SiO2 and GeO2, but it is still fully polymerized. The differences in the compression mechanism between this glass and the simple oxides can clearly be attributed to higher chemical complexity. The albite and albite-diopside compositions partially doped with Ge and Sr were probed at room temperature for Ge up to 164 GPa and for Sr up to 42 GPa. While the albite glass is nominally fully polymerized like NaAlGe3O8, the albite-diopside glass is partially depolymerized. The results show that structural changes take place in all three glasses in the first 25 to a maximum of 30 GPa, with both Ge and Sr reaching the maximum coordination number 6 and ∼9, respectively. At higher pressures, only isostructural shrinkage of the coordination polyhedra takes place in the glasses. The most important finding of the high pressure studies on the alumino-silicate and alumino-germanate glasses is that in these complex glasses the polyhedra show a much higher compressibility than what can be observed in the end-members. This is shown in particular by the strong shortening of the Ge-O distances in the amorphous NaAlGe3O8 and albite-diopside glass at pressures above 30 GPa.
In addition to the effects of the composition on the compaction process, we investigated the influence of temperature on the structural changes. To do this, we probed the albite-diopside glass, as it is chemically most similar to the melts in the lower mantle. We studied the Ge K edge of the sample with a resistively heated and a laser-heated diamond anvil cell, for a pressure range of up to 48 GPa and a temperature range of up to 5000 K. High temperatures at which the sample is liquid and that are relevant for the Earth mantle, have a significant impact on the structural transformation, with a shift of approx. 30% to significantly lower pressures, compared to the glasses at room temperature and below 1000 K.
The results of this thesis represent an important contribution to the understanding of the properties of melts at conditions of the lower mantle. In the context of the discussion about the existence and origin of ultra-dense silicate melts at the core-mantle boundary, these investigations show that the higher density compared to the surrounding material cannot be explained by only structural features, but by a distinct chemical composition. The results also suggest that only very low solubilities of noble gases are to be expected for melts in the lower mantle, so that the structural properties clearly influence the overall budget and transport of noble gases in the Earth’s mantle.