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White mica and tourmaline are the dominant hydrothermal alteration minerals at the world-class Panasqueira W-Sn-Cu deposit in Portugal. Thus, understanding the controls on their chemical composition helps to constrain ore formation processes at this deposit and determine their usefulness as pathfinder minerals for mineralization in general. We combine whole-rock geochemistry of altered and unaltered metasedimentary host rocks with in situ LA-ICP-MS measurements of tourmaline and white mica from the alteration halo. Principal component analysis (PCA) is used to better identify geochemical patterns and trends of hydrothermal alteration in the datasets. The hydrothermally altered metasediments are enriched in As, Sn, Cs, Li, W, F, Cu, Rb, Zn, Tl, and Pb relative to unaltered samples. In situ mineral analyses show that most of these elements preferentially partition into white mica over tourmaline (Li, Rb, Cs, Tl, W, and Sn), whereas Zn is enriched in tourmaline. White mica has distinct compositions in different settings within the deposit (greisen, vein selvages, wall rock alteration zone, late fault zone), indicating a compositional evolution with time. In contrast, tourmaline from different settings overlaps in composition, which is ascribed to a stronger dependence on host rock composition and also to the effects of chemical zoning and microinclusions affecting the LA-ICP-MS analyses. Hence, in this deposit, white mica is the better recorder of the fluid composition. The calculated trace-element contents of the Panasqueira mineralizing fluid based on the mica data and estimates of mica-fluid partition coefficients are in good agreement with previous fluid-inclusion analyses. A compilation of mica and tourmaline trace-element compositions from Panasqueira and other W-Sn deposits shows that white mica has good potential as a pathfinder mineral, with characteristically high Li, Cs, Rb, Sn, and W contents. The trace-element contents of hydrothermal tourmaline are more variable. Nevertheless, the compiled data suggest that high Sn and Li contents are distinctive for tourmaline from W-Sn deposits.
The European Alps are amongst the regions with highest glacier mass loss rates over the last decades. Under the threat of ongoing climate change, the ability to predict glacier mass balance changes for water and risk management purposes has become imperative. This raises an urgent need for reliable glacier models. The European Alps do not only host glaciers, but also numerous caves containing carbonate formations, called speleothems. Previous studies have shown that those speleothems also grew during times when the cave was covered by a warm-based glacier. In this thesis, I utilise speleothems from the European Alps as archives of local, environmental conditions related to mountain glacier evolution.
Previous studies have shown that speleothem isotope data from the Alps can be strongly affected by in-cave processes. Therefore, part of this thesis focusses on developing an isotope evolution model, which successfully reproduces differences between contemporaneous growing speleothems. The model is used to propose correction approaches for prior calcite precipitation effects on speleothem oxygen isotopes (δ18O). Applications on speleothem records from caves outside of the Alps demonstrate that corrected δ18O agrees better with other records and climate model simulations.
Existing speleothem growth histories and carbon isotope (δ13C) records from Alpine caves located at different elevations are used to infer soil vs. glacier cover and the thermal regime of the glacier over the last glacial cycle. The compatibility with glacier evolution models is statistically assessed. A general agreement between speleothem δ13C-derived information on soil vs. glacier presence and modelled glacier coverage is found. However, glacier retreat during Marine Isotope Stage (MIS) 3 seems to be underestimated by the model. Furthermore, speleothem data provides evidence of surface temperature above the freezing point which is, however, not fully reproduced by the simulations.
History of glacier cover and their thermal regime is explored for the high-elevation cave system Melchsee-Frutt in the Swiss Alps. Based on new (MIS 9b – MIS 7b, MIS 2) and available speleothem δ13C (MIS 7a – 5d) data, warm-based glacier cover is inferred for MIS 8, 7d, 6, and 2. Also a short period of cold-based ice coverage is found for early MIS 6. In a detailed multi-proxy analysis (δ18O, δ13C, Mg/Ca and Sr/Ca), millennial-scale changes in the glacier-related source of the water infiltrating in the karst during MIS 8 and 7d are found and linked to Northern Hemisphere climate variability.
While speleothem records from high-elevation cave sites in the Alps exhibit huge potential for glacier reconstruction, several limitations remain, which are discussed throughout this thesis. Ultimately, recommendations are given to further leverage subglacial speleothems as an archive of glacier dynamics.
Plate tectonic boundaries constitute the suture zones between tectonic plates. They are shaped by a variety of distinct and interrelated processes and play a key role in geohazards and georesource formation. Many of these processes have been previously studied, while many others remain unaddressed or undiscovered. In this work, the geodynamic numerical modeling software ASPECT is applied to shed light on further process interactions at continental plate boundaries. In contrast to natural data, geodynamic modeling has the advantage that processes can be directly quantified and that all parameters can be analyzed over the entire evolution of a structure. Furthermore, processes and interactions can be singled out from complex settings because the modeler has full control over all of the parameters involved. To account for the simplifying character of models in general, I have chosen to study generic geological settings with a focus on the processes and interactions rather than precisely reconstructing a specific region of the Earth.
In Chapter 2, 2D models of continental rifts with different crustal thicknesses between 20 and 50 km and extension velocities in the range of 0.5-10 mm/yr are used to obtain a speed limit for the thermal steady-state assumption, commonly employed to address the temperature fields of continental rifts worldwide. Because the tectonic deformation from ongoing rifting outpaces heat conduction, the temperature field is not in equilibrium, but is characterized by a transient, tectonically-induced heat flow signal. As a result, I find that isotherm depths of the geodynamic evolution models are shallower than a temperature distribution in equilibrium would suggest. This is particularly important for deep isotherms and narrow rifts. In narrow rifts, the magnitude of the transient temperature signal limits a well-founded applicability of the thermal steady-state assumption to extension velocities of 0.5-2 mm/yr. Estimation of the crustal temperature field affects conclusions on all temperature-dependent processes ranging from mineral assemblages to the feasible exploitation of a geothermal reservoir.
In Chapter 3, I model the interactions of different rheologies with the kinematics of folding and faulting using the example of fault-propagation folds in the Andean fold-and-thrust belt. The evolution of the velocity fields from geodynamic models are compared with those from trishear models of the same structure. While the latter use only geometric and kinematic constraints of the main fault, the geodynamic models capture viscous, plastic, and elastic deformation in the entire model domain. I find that both models work equally well for early, and thus relatively simple stages of folding and faulting, while results differ for more complex situations where off-fault deformation and secondary faulting are present. As fault-propagation folds can play an important role in the formation of reservoirs, knowledge of fluid pathways, for example via fractures and faults, is crucial for their characterization.
Chapter 4 deals with a bending transform fault and the interconnections between tectonics and surface processes. In particular, the tectonic evolution of the Dead Sea Fault is addressed where a releasing bend forms the Dead Sea pull-apart basin, while a restraining bend further to the North resulted in the formation of the Lebanese mountains. I ran 3D coupled geodynamic and surface evolution models that included both types of bends in a single setup. I tested various randomized initial strain distributions, showing that basin asymmetry is a consequence of strain localization. Furthermore, by varying the surface process efficiency, I find that the deposition of sediment in the pull-apart basin not only controls basin depth, but also results in a crustal flow component that increases uplift at the restraining bend.
Finally, in Chapter 5, I present the computational basis for adding further complexity to plate boundary models in ASPECT with the implementation of earthquake-like behavior using the rate-and-state friction framework. Despite earthquakes happening on a relatively small time scale, there are many interactions between the seismic cycle and the long time spans of other geodynamic processes. Amongst others, the crustal state of stress as well as the presence of fluids or changes in temperature may alter the frictional behavior of a fault segment. My work provides the basis for a realistic setup of involved structures and processes, which is therefore important to obtain a meaningful estimate for earthquake hazards.
While these findings improve our understanding of continental plate boundaries, further development of geodynamic software may help to reveal even more processes and interactions in the future.
Ecosystems play a pivotal role in addressing climate change but are also highly susceptible to drastic environmental changes. Investigating their historical dynamics can enhance our understanding of how they might respond to unprecedented future environmental shifts. With Arctic lakes currently under substantial pressure from climate change, lessons from the past can guide our understanding of potential disruptions to these lakes. However, individual lake systems are multifaceted and complex. Traditional isolated lake studies often fail to provide a global perspective because localized nuances—like individual lake parameters, catchment areas, and lake histories—can overshadow broader conclusions. In light of these complexities, a more nuanced approach is essential to analyze lake systems in a global context.
A key to addressing this challenge lies in the data-driven analysis of sedimentological records from various northern lake systems. This dissertation emphasizes lake systems in the northern Eurasian region, particularly in Russia (n=59). For this doctoral thesis, we collected sedimentological data from various sources, which required a standardized framework for further analysis. Therefore, we designed a conceptual model for integrating and standardizing heterogeneous multi-proxy data into a relational database management system (PostgreSQL). Creating a database from the collected data enabled comparative numerical analyses between spatially separated lakes as well as between different proxies.
When analyzing numerous lakes, establishing a common frame of reference was crucial. We achieved this by converting proxy values from depth dependency to age dependency. This required consistent age calculations across all lakes and proxies using one age-depth modeling software. Recognizing the broader implications and potential pitfalls of this, we developed the LANDO approach ("Linked Age and Depth Modelling"). LANDO is an innovative integration of multiple age-depth modeling software into a singular, cohesive platform (Jupyter Notebook). Beyond its ability to aggregate data from five renowned age-depth modeling software, LANDO uniquely empowers users to filter out implausible model outcomes using robust geoscientific data. Our method is not only novel but also significantly enhances the accuracy and reliability of lake analyses.
Considering the preceding steps, this doctoral thesis further examines the relationship between carbon in sediments and temperature over the last 21,000 years. Initially, we hypothesized a positive correlation between carbon accumulation in lakes and modelled paleotemperature. Our homogenized dataset from heterogeneous lakes confirmed this association, even if the highest temperatures throughout our observation period do not correlate with the highest carbon values. We assume that rapid warming events contribute more to high accumulation, while sustained warming leads to carbon outgassing. Considering the current high concentration of carbon in the atmosphere and rising temperatures, ongoing climate change could cause northern lake systems to contribute to a further increase in atmospheric carbon (positive feedback loop). While our findings underscore the reliability of both our standardized data and the LANDO method, expanding our dataset might offer even greater assurance in our conclusions.
Today, near-surface investigations are frequently conducted using non-destructive or minimally invasive methods of applied geophysics, particularly in the fields of civil engineering, archaeology, geology, and hydrology. One field that plays an increasingly central role in research and engineering is the examination of sedimentary environments, for example, for characterizing near-surface groundwater systems. A commonly employed method in this context is ground-penetrating radar (GPR). In this technique, short electromagnetic pulses are emitted into the subsurface by an antenna, which are then reflected, refracted, or scattered at contrasts in electromagnetic properties (such as the water table). A receiving antenna records these signals in terms of their amplitudes and travel times. Analysis of the recorded signals allows for inferences about the subsurface, such as the depth of the groundwater table or the composition and characteristics of near-surface sediment layers. Due to the high resolution of the GPR method and continuous technological advancements, GPR data acquisition is increasingly performed in three-dimensional (3D) fashion today.
Despite the considerable temporal and technical efforts involved in data acquisition and processing, the resulting 3D data sets (providing high-resolution images of the subsurface) are typically interpreted manually. This is generally an extremely time-consuming analysis step. Therefore, representative 2D sections highlighting distinctive reflection structures are often selected from the 3D data set. Regions showing similar structures are then grouped into so-called radar facies. The results obtained from 2D sections are considered representative of the entire investigated area. Interpretations conducted in this manner are often incomplete and highly dependent on the expertise of the interpreters, making them generally non-reproducible.
A promising alternative or complement to manual interpretation is the use of GPR attributes. Instead of using the recorded data directly, derived quantities characterizing distinctive reflection structures in 3D are applied for interpretation. Using various field and synthetic data sets, this thesis investigates which attributes are particularly suitable for this purpose. Additionally, the study demonstrates how selected attributes can be utilized through specific processing and classification methods to create 3D facies models. The ability to generate attribute-based 3D GPR facies models allows for partially automated and more efficient interpretations in the future. Furthermore, the results obtained in this manner describe the subsurface in a reproducible and more comprehensive manner than what has typically been achievable through manual interpretation methods.
A comprehensive study on seismic hazard and earthquake triggering is crucial for effective mitigation of earthquake risks. The destructive nature of earthquakes motivates researchers to work on forecasting despite the apparent randomness of the earthquake occurrences. Understanding their underlying mechanisms and patterns is vital, given their potential for widespread devastation and loss of life. This thesis combines methodologies, including Coulomb stress calculations and aftershock analysis, to shed light on earthquake complexities, ultimately enhancing seismic hazard assessment.
The Coulomb failure stress (CFS) criterion is widely used to predict the spatial distributions of aftershocks following large earthquakes. However, uncertainties associated with CFS calculations arise from non-unique slip inversions and unknown fault networks, particularly due to the choice of the assumed aftershocks (receiver) mechanisms. Recent studies have proposed alternative stress quantities and deep neural network approaches as superior to CFS with predefined receiver mechanisms. To challenge these propositions, I utilized 289 slip inversions from the SRCMOD database to calculate more realistic CFS values for a layered-half space and variable receiver mechanisms. The analysis also investigates the impact of magnitude cutoff, grid size variation, and aftershock duration on the ranking of stress metrics using receiver operating characteristic (ROC) analysis. Results reveal the performance of stress metrics significantly improves after accounting for receiver variability and for larger aftershocks and shorter time periods, without altering the relative ranking of the different stress metrics.
To corroborate Coulomb stress calculations with the findings of earthquake source studies in more detail, I studied the source properties of the 2005 Kashmir earthquake and its aftershocks, aiming to unravel the seismotectonics of the NW Himalayan syntaxis. I simultaneously relocated the mainshock and its largest aftershocks using phase data, followed by a comprehensive analysis of Coulomb stress changes on the aftershock planes. By computing the Coulomb failure stress changes on the aftershock faults, I found that all large aftershocks lie in regions of positive stress change, indicating triggering by either co-seismic or post-seismic slip on the mainshock fault.
Finally, I investigated the relationship between mainshock-induced stress changes and associated seismicity parameters, in particular those of the frequency-magnitude (Gutenberg-Richter) distribution and the temporal aftershock decay (Omori-Utsu law). For that purpose, I used my global data set of 127 mainshock-aftershock sequences with the calculated Coulomb Stress (ΔCFS) and the alternative receiver-independent stress metrics in the vicinity of the mainshocks and analyzed the aftershocks properties depend on the stress values. Surprisingly, the results show a clear positive correlation between the Gutenberg-Richter b-value and induced stress, contrary to expectations from laboratory experiments. This observation highlights the significance of structural heterogeneity and strength variations in seismicity patterns. Furthermore, the study demonstrates that aftershock productivity increases nonlinearly with stress, while the Omori-Utsu parameters c and p systematically decrease with increasing stress changes. These partly unexpected findings have significant implications for future estimations of aftershock hazard.
The findings in this thesis provides valuable insights into earthquake triggering mechanisms by examining the relationship between stress changes and aftershock occurrence. The results contribute to improved understanding of earthquake behavior and can aid in the development of more accurate probabilistic-seismic hazard forecasts and risk reduction strategies.
Strong hydroclimatic controls on vulnerability to subsurface nitrate contamination across Europe
(2020)
Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that similar to 75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least onethird of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes.
Rapidly growing seismic and macroseismic databases and simplified access to advanced machine learning methods have in recent years opened up vast opportunities to address challenges in engineering and strong motion seismology from novel, datacentric perspectives. In this thesis, I explore the opportunities of such perspectives for the tasks of ground motion modeling and rapid earthquake impact assessment, tasks with major implications for long-term earthquake disaster mitigation.
In my first study, I utilize the rich strong motion database from the Kanto basin, Japan, and apply the U-Net artificial neural network architecture to develop a deep learning based ground motion model. The operational prototype provides statistical estimates of expected ground shaking, given descriptions of a specific earthquake source, wave propagation paths, and geophysical site conditions. The U-Net interprets ground motion data in its spatial context, potentially taking into account, for example, the geological properties in the vicinity of observation sites. Predictions of ground motion intensity are thereby calibrated to individual observation sites and earthquake locations.
The second study addresses the explicit incorporation of rupture forward directivity into ground motion modeling. Incorporation of this phenomenon, causing strong, pulse like ground shaking in the vicinity of earthquake sources, is usually associated with an intolerable increase in computational demand during probabilistic seismic hazard analysis (PSHA) calculations. I suggest an approach in which I utilize an artificial neural network to efficiently approximate the average, directivity-related adjustment to ground motion predictions for earthquake ruptures from the 2022 New Zealand National Seismic Hazard Model. The practical implementation in an actual PSHA calculation demonstrates the efficiency and operational readiness of my model. In a follow-up study, I present a proof of concept for an alternative strategy in which I target the generalizing applicability to ruptures other than those from the New Zealand National Seismic Hazard Model.
In the third study, I address the usability of pseudo-intensity reports obtained from macroseismic observations by non-expert citizens for rapid impact assessment. I demonstrate that the statistical properties of pseudo-intensity collections describing the intensity of shaking are correlated with the societal impact of earthquakes. In a second step, I develop a probabilistic model that, within minutes of an event, quantifies the probability of an earthquake to cause considerable societal impact. Under certain conditions, such a quick and preliminary method might be useful to support decision makers in their efforts to organize auxiliary measures for earthquake disaster response while results from more elaborate impact assessment frameworks are not yet available.
The application of machine learning methods to datasets that only partially reveal characteristics of Big Data, qualify the majority of results obtained in this thesis as explorative insights rather than ready-to-use solutions to real world problems. The practical usefulness of this work will be better assessed in the future by applying the approaches developed to growing and increasingly complex data sets.
We present a new set of global and local sea‐level projections at example tide gauge locations under the RCP2.6, RCP4.5, and RCP8.5 emissions scenarios. Compared to the CMIP5‐based sea‐level projections presented in IPCC AR5, we introduce a number of methodological innovations, including (i) more comprehensive treatment of uncertainties, (ii) direct traceability between global and local projections, and (iii) exploratory extended projections to 2300 based on emulation of individual CMIP5 models. Combining the projections with observed tide gauge records, we explore the contribution to total variance that arises from sea‐level variability, different emissions scenarios, and model uncertainty. For the period out to 2300 we further breakdown the model uncertainty by sea‐level component and consider the dependence on geographic location, time horizon, and emissions scenario. Our analysis highlights the importance of local variability for sea‐level change in the coming decades and the potential value of annual‐to‐decadal predictions of local sea‐level change. Projections to 2300 show a substantial degree of committed sea‐level rise under all emissions scenarios considered and highlight the reduced future risk associated with RCP2.6 and RCP4.5 compared to RCP8.5. Tide gauge locations can show large ( > 50%) departures from the global average, in some cases even reversing the sign of the change. While uncertainty in projections of the future Antarctic ice dynamic response tends to dominate post‐2100, we see substantial differences in the breakdown of model variance as a function of location, time scale, and emissions scenario.
Lake sediments are increasingly explored as reliable paleoflood archives. In addition to established flood proxies including detrital layer thickness, chemical composition, and grain size, we explore stable oxygen and carbon isotope data as paleoflood proxies for lakes in catchments with carbonate bedrock geology. In a case study from Lake Mondsee (Austria), we integrate high-resolution sediment trapping at a proximal and a distal location and stable isotope analyses of varved lake sediments to investigate flood-triggered detrital sediment flux. First, we demonstrate a relation between runoff, detrital sediment flux, and isotope values in the sediment trap record covering the period 2011-2013 CE including 22 events with daily (hourly) peak runoff ranging from 10 (24) m(3) s(-1) to 79 (110) m(3) s(-1). The three- to ten-fold lower flood-triggered detrital sediment deposition in the distal trap is well reflected by attenuated peaks in the stable isotope values of trapped sediments. Next, we show that all nine flood-triggered detrital layers deposited in a sediment record from 1988 to 2013 have elevated isotope values compared with endogenic calcite. In addition, even two runoff events that did not cause the deposition of visible detrital layers are distinguished by higher isotope values. Empirical thresholds in the isotope data allow estimation of magnitudes of the majority of floods, although in some cases flood magnitudes are overestimated because local effects can result in too-high isotope values. Hence we present a proof of concept for stable isotopes as reliable tool for reconstructing flood frequency and, although with some limitations, even for flood magnitudes.