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Abstract. The Sea of Marmara, in northwestern Turkey, is a transition zone where the dextral North Anatolian Fault zone (NAFZ) propagates westward from the Anatolian Plate to the Aegean Sea Plate. The area is of interest in the context of seismic hazard of Istanbul, a metropolitan area with about 15 million inhabitants. Geophysical observations indicate that the crust is heterogeneous beneath the Marmara basin, but a detailed characterization of the crustal heterogeneities is still missing. To assess if and how crustal heterogeneities are related to the NAFZ segmentation below the Sea of Marmara, we develop new crustal-scale 3-D density models which integrate geological and seismological data and that are additionally constrained by 3-D gravity modeling. For the latter, we use two different gravity datasets including global satellite data and local marine gravity observation. Considering the two different datasets and the general non-uniqueness in potential field modeling, we suggest three possible “end-member” solutions that are all consistent with the observed gravity field and illustrate the spectrum of possible solutions. These models indicate that the observed gravitational anomalies originate from significant density heterogeneities within the crust. Two layers of sediments, one syn-kinematic and one pre-kinematic with respect to the Sea of Marmara formation are underlain by a heterogeneous crystalline crust. A felsic upper crystalline crust (average density of 2720 kgm⁻³) and an intermediate to mafic lower crystalline crust (average density of 2890 kgm⁻³) appear to be cross-cut by two large, dome-shaped mafic highdensity bodies (density of 2890 to 3150 kgm⁻³) of considerable thickness above a rather uniform lithospheric mantle (3300 kgm⁻³). The spatial correlation between two major bends of the main Marmara fault and the location of the highdensity bodies suggests that the distribution of lithological heterogeneities within the crust controls the rheological behavior along the NAFZ and, consequently, maybe influences fault segmentation and thus the seismic hazard assessment in the region.
Dynamic earthquake rupture modeling provides information on the rupture physics as the rupture velocity, frictions or tractions acting during the rupture process. Nevertheless, as often based on spatial gridded preset geometries, dynamic modeling is depending on many free parameters leading to both a high non-uniqueness of the results and large computation times. That decreases the possibilities of full Bayesian error analysis.
To assess the named problems we developed the quasi-dynamic rupture model which is presented in this work. It combines the kinematic Eikonal rupture model with a boundary element method for quasi-static slip calculation.
The orientation of the modeled rupture plane is defined by a previously performed moment tensor inversion. The simultanously inverted scalar seismic moment allows an estimation of the extension of the rupture. The modeled rupture plane is discretized by a set of rectangular boundary elements. For each boundary element an applied traction vector is defined as the boundary value.
For insights in the dynamic rupture behaviour the rupture front propagation is calculated for incremental time steps based on the 2D Eikonal equation. The needed location-dependent rupture velocity field is assumed to scale linearly with a layered shear wave velocity field.
At each time all boundary elements enclosed within the rupture front are used to calculate the quasi-static slip distribution. Neither friction nor stress propagation are considered. Therefore the algorithm is assumed to be “quasi-static”. A series of the resulting quasi-static slip snapshots can be used as a quasi-dynamic model of the rupture process.
As many a priori information is used from the earth model (shear wave velocity and elastic parameters) and the moment tensor inversion (rupture extension and orientation) our model is depending on few free parameters as the traction field, the linear factor between rupture and shear wave velocity and the nucleation point and time. Hence stable and fast modeling results are obtained as proven from the comparison to different infinite and finite static crack solutions.
First dynamic applications show promissing results. The location-dependent rise time is automatically derived by the model. Different simple kinematic models as the slip-pulse or the penny-shaped crack model can be reproduced as well as their corresponding slip rate functions. A source time function (STF) approximation calculated from the cumulative sum of moment rates of each boundary element gives results similar to theoretical and empirical known STFs.
The model was also applied to the 2015 Illapel earthquake. Using a simple rectangular rupture geometry and a 2-layered traction regime yields good estimates of both the rupture front propagation and the slip patterns which are comparable to literature results. The STF approximation shows a good fit with previously published STFs.
The quasi-dynamic rupture model is hence able to fastly calculate reproducable slip results. That allows to test full Bayesian error analysis in the future. Further work on a full seismic source inversion or even a traction field inversion can also extend the scope of our model.
Solar wind observations show that geomagnetic storms are mainly driven by interplanetary coronal mass ejections (ICMEs) and corotating or stream interaction regions (C/SIRs). We present a binary classifier that assigns one of these drivers to 7,546 storms between 1930 and 2015 using ground‐based geomagnetic field observations only. The input data consists of the long‐term stable Hourly Magnetospheric Currents index alongside the corresponding midlatitude geomagnetic observatory time series. This data set provides comprehensive information on the global storm time magnetic disturbance field, particularly its spatial variability, over eight solar cycles. For the first time, we use this information statistically with regard to an automated storm driver identification. Our supervised classification model significantly outperforms unskilled baseline models (78% accuracy with 26[19]% misidentified interplanetary coronal mass ejections [corotating or stream interaction regions]) and delivers plausible driver occurrences with regard to storm intensity and solar cycle phase. Our results can readily be used to advance related studies fundamental to space weather research, for example, studies connecting galactic cosmic ray modulation and geomagnetic disturbances. They are fully reproducible by means of the underlying open‐source software (Pick, 2019, http://doi.org/10.5880/GFZ.2.3.2019.003)
Forest structure is a crucial component in the assessment of whether a forest is likely to act as a carbon sink under changing climate. Detailed 3D structural information about the tundra–taiga ecotone of Siberia is mostly missing and still underrepresented in current research due to the remoteness and restricted accessibility. Field based, high-resolution remote sensing can provide important knowledge for the understanding of vegetation properties and dynamics. In this study, we test the applicability of consumer-grade Unmanned Aerial Vehicles (UAVs) for rapid calculation of stand metrics in treeline forests. We reconstructed high-resolution photogrammetric point clouds and derived canopy height models for 10 study sites from NE Chukotka and SW Yakutia. Subsequently, we detected individual tree tops using a variable-window size local maximum filter and applied a marker-controlled watershed segmentation for the delineation of tree crowns. With this, we successfully detected 67.1% of the validation individuals. Simple linear regressions of observed and detected metrics show a better correlation (R2) and lower relative root mean square percentage error (RMSE%) for tree heights (mean R2 = 0.77, mean RMSE% = 18.46%) than for crown diameters (mean R2 = 0.46, mean RMSE% = 24.9%). The comparison between detected and observed tree height distributions revealed that our tree detection method was unable to representatively identify trees <2 m. Our results show that plot sizes for vegetation surveys in the tundra–taiga ecotone should be adapted to the forest structure and have a radius of >15–20 m to capture homogeneous and representative forest stands. Additionally, we identify sources of omission and commission errors and give recommendations for their mitigation. In summary, the efficiency of the used method depends on the complexity of the forest’s stand structure.
The advances in modern geodetic techniques such as the global navigation satellite system (GNSS) and synthetic aperture radar (SAR) provide surface deformation measurements with an unprecedented accuracy and temporal and spatial resolutions even at most remote volcanoes on Earth. Modelling of the high-quality geodetic data is crucial for understanding the underlying physics of volcano deformation processes. Among various approaches, mathematical models are the most effective for establishing a quantitative link between the surface displacements and the shape and strength of deformation sources. Advancing the geodetic data analyses and hence, the knowledge on the Earth’s interior processes, demands sophisticated and efficient deformation modelling approaches. Yet the majority of these models rely on simplistic assumptions for deformation source geometries and ignore complexities such as the Earth’s surface topography and interactions between multiple sources.
This thesis addresses this problem in the context of analytical and numerical volcano deformation modelling. In the first part, new analytical solutions for triangular dislocations (TDs) in uniform infinite and semi-infinite elastic media have been developed. Through a comprehensive investigation, the locations and causes of artefact singularities and numerical instabilities associated with TDs have been determined and these long-standing drawbacks have been addressed thoroughly. This approach has then been extended to rectangular dislocations (RDs) with full rotational degrees of freedom. Using this solution in a configuration of three orthogonal RDs a compound dislocation model (CDM) has been developed. The CDM can represent generalized volumetric and planar deformation sources efficiently. Thus, the CDM is relevant for rapid inversions in early warning systems and can also be used for detailed deformation analyses. In order to account for complex source geometries and realistic topography in the deformation models, in this thesis the boundary element method (BEM) has been applied to the new solutions for TDs. In this scheme, complex surfaces are simulated as a continuous mesh of TDs that may possess any displacement or stress boundary conditions in the BEM calculations. In the second part of this thesis, the developed modelling techniques have been applied to five different real-world deformation scenarios. As the first and second case studies the deformation sources associated with the 2015 Calbuco eruption and 2013–2016 Copahue inflation period have been constrained by using the CDM. The highly anisotropic source geometries in these two cases highlight the importance of using generalized deformation models such as the CDM, for geodetic data inversions. The other three case studies in this thesis involve high-resolution dislocation models and BEM calculations. As the third case, the 2013 pre-explosive inflation of Volcán de Colima has been simulated by using two ellipsoidal cavities, which locate zones of pressurization in the volcano’s lava dome. The fourth case study, which serves as an example for volcanotectonics interactions, the 3-D kinematics of an active ring-fault at Tendürek volcano has been investigated through modelling displacement time series over the 2003–2010 time period. As the fifth example, the deformation sources associated with North Korea’s underground nuclear test in September 2017 have been constrained. These examples demonstrate the advancement and increasing level of complexity and the general applicability of the developed dislocation modelling techniques.
This thesis establishes a unified framework for rapid and high-resolution dislocation modelling, which in addition to volcano deformations can also be applied to tectonic and humanmade deformations.
Der Porenraum eines Karbonatgesteins ist zumeist aus einer spezifischen Vergesellschaftung verschiedenster Porentypen aufgebaut, die eine unterschiedliche Herkunft aufweisen und zusätzlich in ihrer Form und Größe stark variieren können (e.g., Melim et al., 2001; Lee et al., 2009; He et al., 2014; Dernaika & Sinclair, 2017; Zhang et al., 2017). Diese für Karbonate typischen multimodalen Porensysteme entstehen sowohl durch primäre Ablagerungsprozesse, als auch durch mehrmalige Modifikation des Porenraumes nach Ablagerung des Sediments. Dies führt zu einer ungleichen Verteilung der Porenraumeigenschaften auf engstem Raum und das zeitgleiche Auftreten von effektiven und ineffektiven Poren. Diese immanenten Unterschiede in der Effektivität einzelner Porentypen sind der Hauptgrund für die häufig sehr niedrige Korellation zwischen Porosität und Permeabilität in Karbonaten (e.g., Mazzullo 2004; Ehrenberg & Nadeau, 2005; Hollis et al., 2010; He et al., 2014; Rashid et al., 2015; Dernaika & Sinclair, 2017). Durch die Extraktion von miteinander verbundenen und somit effektiven Porentypen jedoch kann das Verständnis und die Vorhersage der Permeabilität für einen gegeben Porositätswert stark verbessert werden (e.g., Melim et al., 2001; Zhang et al., 2017). Dazu wird in dieser Arbeit eine auf der digitalen Bildanalyse (DIA) beruhende Methode vorgestellt, mit der schrittweise die Effektivität von Poren aus den analysierten mittelmiozänen lakustrinen Karbonaten des Nördlinger Ries Kratersees (Süddeutschland) berechnet werden kann. Mithilfe des Porenformfaktors (sensu Anselmetti et al., 1998), der als Parameter zur Quantifizierung der Interkonnektivität zwischen Poren dient, wird der potentiellen Beitrag an Permeabilität jedes Porentyps zur Gesamtpermeabilität bestimmt. Somit können die effektivsten Porentypen innerhalb der analysierten Karbonate identifiziert werden. Desweiteren wird die digitale Bildanalyse dazu benutzt, zementierte Porenräume zu extrahieren, um den Einfluss der Zementation auf die Porenraumeigenschaften zu quantifizieren. Durch eine unabhängige Methode (Fluid-Flow-Simulation), deren Ergebnisse wiederum mit der digitalen Bildanalyse ausgewertet werden, können die vorherigen Erkentnisse bestätigt werden: Interpeloidale Poren und Lösungsporen sind die beiden effektivsten Porentypen im Porenraum der Riesseekarbonate. Die Extraktion des miteinander verbundenen (d.h. effektiven) Porennetzwerkes führt schließlich zu einer erheblich verbesserten Korrelation zwischen Porosität und Permeabilität in den analysierten Karbonaten. Die in dieser Arbeit beschriebene Methode bietet ein quantitatives petrographisches Werkzeug, mit dessen Hilfe die effektive Porosität eines Porenraumes extrahiert werden kann. Dies führt zu einem besseren Verständnis darüber, wie Porensysteme von Karbonaten Permeabilität erzeugen. Diese Dissertation zeigt auch, dass die Formkomplexität von Poren einer der wichtigsten Parameter ist, der die Interkonnektivität zwischen einzelnen Poren und somit die Entstehung von effektiver Porosität steuert. Außerdem erweist sich die digitale Bildanalyse als ausgezeichnetes Werkzeug um die Porosität und Permeabilität direkt an ihren gemeinsamen Ursprung zu knüpfen: die Gesteinstextur und die damit assoziierte Porenstruktur.
Floods are among the most costly natural hazards that affect Europe and Germany, demanding a continuous adaptation of flood risk management. While social and economic development in recent years altered the flood risk patterns mainly with regard to an increase in flood exposure, different flood events are further expected to increase in frequency and severity in certain European regions due to climate change. As a result of recent major flood events in Germany, the German flood risk management shifted to more integrated approaches that include private precaution and preparation to reduce the damage on exposed assets. Yet, detailed insights into the preparedness decisions of flood-prone households remain scarce, especially in connection to mental impacts and individual coping strategies after being affected by different flood types.
This thesis aims to gain insights into flash floods as a costly hazard in certain German regions and compares the damage driving factors to the damage driving factors of river floods. Furthermore, psychological impacts as well as the effects on coping and mitigation behaviour of flood-affected households are assessed. In this context, psychological models such as the Protection Motivation Theory (PMT) and methods such as regressions and Bayesian statistics are used to evaluate influencing factors on the mental coping after an event and to identify psychological variables that are connected to intended private flood mitigation. The database consists of surveys that were conducted among affected households after major river floods in 2013 and flash floods in 2016.
The main conclusions that can be drawn from this thesis reveal that the damage patterns and damage driving factors of strong flash floods differ significantly from those of river floods due to a rapid flow origination process, higher flow velocities and flow forces. However, the effects on mental coping of people that have been affected by flood events appear to be weakly influenced by different flood types, but yet show a coherence to the event severity, where often thinking of the respective event is pronounced and also connected to a higher mitigation motivation. The mental coping and preparation after floods is further influenced by a good information provision and a social environment, which encourages a positive attitude towards private mitigation.
As an overall recommendation, approaches for an integrated flood risk management in Germany should be followed that also take flash floods into account and consider psychological characteristics of affected households to support and promote private flood mitigation. Targeted information campaigns that concern coping options and discuss current flood risks are important to better prepare for future flood hazards in Germany.
The Arctic-Boreal regions experience strong changes of air temperature and precipitation regimes, which affect the thermal state of the permafrost. This results in widespread permafrost-thaw disturbances, some unfolding slowly and over long periods, others occurring rapidly and abruptly. Despite optical remote sensing offering a variety of techniques to assess and monitor landscape changes, a persistent cloud cover decreases the amount of usable images considerably. However, combining data from multiple platforms promises to increase the number of images drastically. We therefore assess the comparability of Landsat-8 and Sentinel-2 imagery and the possibility to use both Landsat and Sentinel-2 images together in time series analyses, achieving a temporally-dense data coverage in Arctic-Boreal regions. We determined overlapping same-day acquisitions of Landsat-8 and Sentinel-2 images for three representative study sites in Eastern Siberia. We then compared the Landsat-8 and Sentinel-2 pixel-pairs, downscaled to 60 m, of corresponding bands and derived the ordinary least squares regression for every band combination. The acquired coefficients were used for spectral bandpass adjustment between the two sensors. The spectral band comparisons showed an overall good fit between Landsat-8 and Sentinel-2 images already. The ordinary least squares regression analyses underline the generally good spectral fit with intercept values between 0.0031 and 0.056 and slope values between 0.531 and 0.877. A spectral comparison after spectral bandpass adjustment of Sentinel-2 values to Landsat-8 shows a nearly perfect alignment between the same-day images. The spectral band adjustment succeeds in adjusting Sentinel-2 spectral values to Landsat-8 very well in Eastern Siberian Arctic-Boreal landscapes. After spectral adjustment, Landsat and Sentinel-2 data can be used to create temporally-dense time series and be applied to assess permafrost landscape changes in Eastern Siberia. Remaining differences between the sensors can be attributed to several factors including heterogeneous terrain, poor cloud and cloud shadow masking, and mixed pixels.
This dissertation combines field and geochemical observations and analyses with numerical modeling to understand the formation of vein-hosted Sn-W ore in the Panasqueira deposit of Portugal, which is among the ten largest worldwide. The deposit is located above a granite body that is altered by magmatic-hydrothermal fluids in its upper part (greisen). These fluids are thought to be the source of metals, but that was still under debate. The goal of this study is to determine the composition and temperature of hydrothermal fluids at Panasqueira, and with that information to construct a numerical model of the hydrothermal system. The focus is on analysis of the minerals tourmaline and white mica, which formed during mineralization and are widespread throughout the deposit. Tourmaline occurs mainly in alteration zones around mineralized veins and is less abundant in the vein margins. White mica is more widespread. It is abundant in vein margins as well as alteration zones, and also occurs in the granite greisen. The laboratory work involved in-situ microanalysis of major- and trace elements in tourmaline and white mica, and boron-isotope analysis in both minerals by secondary ion mass spectrometry (SIMS).
The boron-isotope composition of tourmaline and white mica suggests a magmatic source. Comparison of hydrothermally-altered and unaltered rocks from drill cores shows that the ore metals (W, Sn, Cu, and Zn) and As, F, Li, Rb, and Cs were introduced during the alteration. Most of these elements are also enriched in tourmaline and mica, which confirms their potential value as exploration guides to Sn-W ores elsewhere.
The thermal evolution of the hydrothermal system was estimated by B-isotope exchange thermometry and the Ti-in-quartz method. Both methods yielded similar temperatures for the early hydrothermal phase: 430° to 460°C for B-isotopes and 503° ± 24°C for Ti-in-quartz. Mineral pairs from a late fault zone yield significantly lower median temperatures of 250°C. The combined results of thermometry with variations in chemical and B-isotope composition of tourmaline and mica suggest that a similar magmatic-hydrothermal fluid was active at all stages of mineralization. Mineralization in the late stage shows the same B-isotope composition as in the main stage despite a ca. 250°C cooling, which supports a multiple injection model of magmatic-hydrothermal fluids.
Two-dimensional numerical simulations of convection in a multiphase NaCl hydrothermal system were conducted: (a) in order to test a new approach (lower dimensional elements) for flow through fractures and faults and (b) in order to identify conditions for horizontal fluid flow as observed in the flat-lying veins at Panasqueira. The results show that fluid flow over an intrusion (heat and fluid source) develops a horizontal component if there is sufficient fracture connectivity. Late, steep fault zones have been identified in the deposit area, which locally contain low-temperature Zn-Pb mineralization. The model results confirm that the presence of subvertical faults with enhanced permeability play a crucial role in the ascent of magmatic fluids to the surface and the recharge of meteoric waters. Finally, our model results suggest that recharge of meteoric fluids and mixing processes may be important at later stages, while flow of magmatic fluids dominate the early stages of the hydrothermal fluid circulation.
Magmatic-hydrothermal fluids are responsible for numerous mineralization types, including porphyry copper and granite related tin-tungsten (Sn-W) deposits. Ore formation is dependent on various factors, including, the pressure and temperature regime of the intrusions, the chemical composition of the magma and hydrothermal fluids, and fluid rock interaction during the ascent. Fluid inclusions have potential to provide direct information on the temperature, salinity, pressure and chemical composition of fluids responsible for ore formation. Numerical modeling allows the parametrization of pluton features that cannot be analyzed directly via geological observations.
Microthermometry of fluid inclusions from the Zinnwald Sn-W deposit, Erzgebirge, Germany / Czech Republic, provide evidence that the greisen mineralization is associated with a low salinity (2-10 wt.% NaCl eq.) fluid with homogenization temperatures between 350°C and 400°C. Quartzes from numerous veins are host to inclusions with the same temperatures and salinities, whereas cassiterite- and wolframite-hosted assemblages with slightly lower temperatures (around 350°C) and higher salinities (ca. 15 wt. NaCl eq.). Further, rare quartz samples contained boiling assemblages consisting of coexisting brine and vapor phases. The formation of ore minerals within the greisen is driven by invasive fluid-rock interaction, resulting in the loss of complexing agents (Cl-) leading to precipitation of cassiterite. The fluid inclusion record in the veins suggests boiling as the main reason for cassiterite and wolframite mineralization. Ore and coexisting gangue minerals hosted different types of fluid inclusions where the beginning boiling processes are solely preserved by the ore minerals emphasizing the importance of microthermometry in ore minerals. Further, the study indicates that boiling as a precipitation mechanism can only occur in mineralization related to shallow intrusions whereas deeper plutons prevent the fluid from boiling and can therefore form tungsten mineralization in the distal regions.
The tin mineralization in the Hämmerlein deposit, Erzgebirge, Germany, occurs within a skarn horizon and the underlying schist. Cassiterite within the skarn contains highly saline (30-50 wt% NaCl eq.) fluid inclusions, with homogenization temperatures up to 500°C, whereas cassiterites from the schist and additional greisen samples contain inclusions of lower salinity (~5 wt% NaCl eq.) and temperature (between 350 and 400°C). Inclusions in the gangue minerals (quartz, fluorite) preserve homogenization temperatures below 350°C and sphalerite showed the lowest homogenization temperatures (ca. 200°C) whereby all minerals (cassiterite from schist and greisen, gangue minerals and sphalerite) show similar salinity ranges (2-5 wt% NaCl eq.). Similar trace element contents and linear trends in the chemistry of the inclusions suggest a common source fluid. The inclusion record in the Hämmerlein deposit documents an early exsolution of hot brines from the underlying granite which is responsible for the mineralization hosted by the skarn. Cassiterites in schist and greisen are mainly forming due to fluid-rock interaction at lower temperatures. The low temperature inclusions documented in the sphalerite mineralization as well as their generally low trace element composition in comparison to the other minerals suggests that their formation was induced by mixing with meteoric fluids.
Numerical simulations of magma chambers and overlying copper distribution document the importance of incremental growth by sills. We analyzed the cooling behavior at variable injection intervals as well as sill thicknesses. The models suggest that magma accumulation requires volumetric injection rates of at least 4 x 10-4 km³/y. These injection rates are further needed to form a stable magmatic-hydrothermal fluid plume above the magma chamber to ensure a constant copper precipitation and enrichment within a confined location in order to form high-grade ore shells within a narrow geological timeframe between 50 and 100 kyrs as suggested for porphyry copper deposits. The highest copper enrichment can be found in regions with steep temperature gradients, typical of regions where the magmatic-hydrothermal fluid meets the cooler ambient fluids.
Garnet of eclogite (formerly termed garnet clinopyroxenite) hosted in lenses of orogenic garnet peridotite from the Granulitgebirge, NW Bohemian Massif, contains unique inclusions of granitic melt, now either glassy or crystallized. Analysed glasses and re‐homogenized inclusions are hydrous, peraluminous, and enriched in highly incompatible elements characteristic of the continental crust such as Cs, Li, B, Pb, Rb, Th, and U. The original melt thus represents a pristine, chemically evolved metasomatic agent, which infiltrated the mantle via deep continental subduction during the Variscan orogeny. The bulk chemical composition of the studied eclogites is similar to that of Fe‐rich basalt and the enrichment in LILE and U suggest a subduction‐related component. All these geochemical features confirm metasomatism. In comparison with many other garnet+clinopyroxene‐bearing lenses in peridotites of the Bohemian Massif, the studied samples from Rubinberg and Klatschmühle are more akin to eclogite than pyroxenites, as reflected in high jadeite content in clinopyroxene, relatively low Mg, Cr, and Ni but relatively high Ti. However, trace elements of both bulk rock and individual mineral phases show also important differences making these samples rather unique. Metasomatism involving a melt requiring a trace element pattern very similar to the composition reported here has been suggested for the source region of rocks of the so‐called durbachite suite, that is, ultrapotassic melanosyenites, which are found throughout the high‐grade Variscan basement. Moreover, the Th, U, Pb, Nb, Ta, and Ti patterns of these newly studied melt inclusions (MI) strongly resemble those observed for peridotite and its enclosed pyroxenite from the T‐7 borehole (Staré, České Středhoři Mountains) in N Bohemia. This suggests that a similar kind of crustal‐derived melt also occurred here. This study of granitic MI in eclogites from peridotites has provided the first direct characterization of a preserved metasomatic melt, possibly responsible for the metasomatism of several parts of the mantle in the Variscides.
Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset
(2019)
Digital elevation models (DEMs) are a gridded representation of the surface of the Earth and typically contain uncertainties due to data collection and processing. Slope and aspect estimates on a DEM contain errors and uncertainties inherited from the representation of a continuous surface as a grid (referred to as truncation error; TE) and from any DEM uncertainty. We analyze in detail the impacts of TE and propagated elevation uncertainty (PEU) on slope and aspect.
Using synthetic data as a control, we define functions to quantify both TE and PEU for arbitrary grids. We then develop a quality metric which captures the combined impact of both TE and PEU on the calculation of topographic metrics. Our quality metric allows us to examine the spatial patterns of error and uncertainty in topographic metrics and to compare calculations on DEMs of different sizes and accuracies.
Using lidar data with point density of ∼10 pts m−2 covering Santa Cruz Island in southern California, we are able to generate DEMs and uncertainty estimates at several grid resolutions. Slope (aspect) errors on the 1 m dataset are on average 0.3∘ (0.9∘) from TE and 5.5∘ (14.5∘) from PEU. We calculate an optimal DEM resolution for our SCI lidar dataset of 4 m that minimizes the error bounds on topographic metric calculations due to the combined influence of TE and PEU for both slope and aspect calculations over the entire SCI. Average slope (aspect) errors from the 4 m DEM are 0.25∘ (0.75∘) from TE and 5∘ (12.5∘) from PEU. While the smallest grid resolution possible from the high-density SCI lidar is not necessarily optimal for calculating topographic metrics, high point-density data are essential for measuring DEM uncertainty across a range of resolutions.
Earthquake swarms are characterized by large numbers of events occurring in a short period of time within a confined source volume and without significant mainshock aftershock pattern as opposed to tectonic sequences. Intraplate swarms in the absence of active volcanism usually occur in continental rifts as for example in the Eger Rift zone in North West Bohemia, Czech Republic. A common hypothesis links event triggering to pressurized fluids. However, the exact causal chain is often poorly understood since the underlying geotectonic processes are slow compared to tectonic sequences. The high event rate during active periods challenges standard seismological routines as these are often designed for single events and therefore costly in terms of human resources when working with phase picks or computationally costly when exploiting full waveforms.
This methodological thesis develops new approaches to analyze earthquake swarm seismicity as well as the underlying seismogenic volume. It focuses on the region of North West (NW) Bohemia, a well studied, well monitored earthquake swarm region.
In this work I develop and test an innovative approach to detect and locate earthquakes using deep convolutional neural networks. This technology offers great potential as it allows to efficiently process large amounts of data which becomes increasingly important given that seismological data storage grows at increasing pace. The proposed deep neural network trained on NW Bohemian earthquake swarm records is able to locate 1000 events in less than 1 second using full waveforms while approaching precision of double difference relocated catalogs. A further technological novelty is that the trained filters of the deep neural network’s first layer can be repurposed to function as a pattern matching event detector without additional training on noise datasets. For further methodological development and benchmarking, I present a new toolbox to generate realistic earthquake cluster catalogs as well as synthetic full waveforms of those clusters in an automated fashion. The input is parameterized using constraints on source volume geometry, nucleation and frequency-magnitude relations. It harnesses recorded noise to produce highly realistic synthetic data for benchmarking and development. This tool is used to study and assess detection performance in terms of magnitude of completeness Mc of a full waveform detector applied to synthetic data of a hydrofracturing experiment at the Wysin site, Poland.
Finally, I present and demonstrate a novel approach to overcome the masking effects of wave propagation between earthquake and stations and to determine source volume attenuation directly in the source volume where clustered earthquakes occur. The new event couple spectral ratio approach exploits high frequency spectral slopes of two events sharing the greater part of their rays. Synthetic tests based on the toolbox mentioned before show that this method is able to infer seismic wave attenuation within the source volume at high spatial resolution. Furthermore, it is independent from the distance towards a station as well as the complexity of the attenuation and velocity structure outside of the source volume of swarms. The application to recordings of the NW Bohemian earthquake swarm shows increased P phase attenuation within the source volume (Qp < 100) based on results at a station located close to the village Luby (LBC). The recordings of a station located in epicentral proximity, close to Nový Kostel (NKC), show a relatively high complexity indicating that waves arriving at that station experience more scattering than signals recorded at other stations. The high level of complexity destabilizes the inversion. Therefore, the Q estimate at NKC is not reliable and an independent proof of the high attenuation finding given the geometrical and frequency constraints is still to be done. However, a high attenuation in the source volume of NW Bohemian swarms has been postulated before in relation to an expected, highly damaged zone bearing CO 2 at high pressure.
The methods developed in the course of this thesis yield the potential to improve our understanding regarding the role of fluids and gases in intraplate event clustering.
Geomagnetic paleosecular variations (PSVs) are an expression of geodynamo processes inside the Earth’s liquid outer core. These paleomagnetic time series provide insights into the properties of the Earth’s magnetic field, from normal behavior with a dominating dipolar geometry, over field crises, such as pronounced intensity lows and geomagnetic excursions with a distorted field geometry, to the complete reversal of the dominating dipole contribution. Particularly, long-term high-resolution and high-quality PSV time series are needed for properly reconstructing the higher frequency components in the spectrum of geomagnetic field variations and for a better understanding of the effects of smoothing during the recording of such paleomagnetic records by sedimentary archives.
In this doctorate study, full vector paleomagnetic records were derived from 16 sediment cores recovered from the southeastern Black Sea. Age models are based on radiocarbon dating and correlations of warming/cooling cycles monitored by high-resolution X-ray fluorescence (XRF) elementary ratios as well as ice-rafted debris (IRD) in Black Sea sediments to the sequence of ‘Dansgaard-Oeschger’ (DO) events defined from Greenland ice core oxygen isotope stratigraphy.
In order to identify the carriers of magnetization in Black Sea sediments, core MSM33-55-1 recovered from the southeast Black Sea was subjected to detailed rock magnetic and electron microscopy investigations. The younger part of core MSM33-55-1 was continuously deposited since 41 ka. Before 17.5 ka, the magnetic minerals were dominated by a mixture of greigite (Fe3S4) and titanomagnetite (Fe3-xTixO4) in samples with SIRM/κLF >10 kAm-1, or exclusively by titanomagnetite in samples with SIRM/κLF ≤10 kAm-1. It was found that greigite is generally present as crustal aggregates in locally reducing micro-environments. From 17.5 ka to 8.3 ka, the dominant magnetic mineral in this transition phase was changing from greigite (17.5 – ~10.0 ka) to probably silicate-hosted titanomagnetite (~10.0 – 8.3 ka). After 8.3 ka, the anoxic Black Sea was a favorable environment for the formation of non-magnetic pyrite (FeS2) framboids.
Aiming to avoid compromising of paleomagnetic data by erroneous directions carried by greigite, paleomagnetic data from samples with SIRM/κLF >10 kAm-1, shown to contain greigite by various methods, were removed from obtained records. Consequently, full vector paleomagnetic records, comprising directional data and relative paleointensity (rPI), were derived only from samples with SIRM/κLF ≤10 kAm-1 from 16 Black Sea sediment cores. The obtained data sets were used to create a stack covering the time window between 68.9 and 14.5 ka with temporal resolution between 40 and 100 years, depending on sedimentation rates.
At 64.5 ka, according to obtained results from Black Sea sediments, the second deepest minimum in relative paleointensity during the past 69 ka occurred. The field minimum during MIS 4 is associated with large declination swings beginning about 3 ka before the minimum. While a swing to 50°E is associated with steep inclinations (50-60°) according to the coring site at 42°N, the subsequent declination swing to 30°W is associated with shallow inclinations of down to 40°. Nevertheless, these large deviations from the direction of a geocentric axial dipole field (I=61°, D=0°) still can not yet be termed as 'excursional', since latitudes of corresponding VGPs only reach down to 51.5°N (120°E) and 61.5°N (75°W), respectively. However, these VGP positions at opposite sides of the globe are linked with VGP drift rates of up to 0.2° per year in between. These extreme secular variations might be the mid-latitude expression of the Norwegian–Greenland Sea excursion found at several sites much further North in Arctic marine sediments between 69°N and 81°N.
At about 34.5 ka, the Mono Lake excursion is evidenced in the stacked Black Sea PSV record by both a rPI minimum and directional shifts. Associated VGPs from stacked Black Sea data migrated from Alaska, via central Asia and the Tibetan Plateau, to Greenland, performing a clockwise loop. This agrees with data recorded in the Wilson Creek Formation, USA., and Arctic sediment core PS2644-5 from the Iceland Sea, suggesting a dominant dipole field. On the other hand, the Auckland lava flows, New Zealand, the Summer Lake, USA., and Arctic sediment core from ODP Site-919 yield distinct VGPs located in the central Pacific Ocean due to a presumably non-dipole (multi-pole) field configuration.
A directional anomaly at 18.5 ka, associated with pronounced swings in inclination and declination, as well as a low in rPI, is probably contemporaneous with the Hilina Pali excursion, originally reported from Hawaiian lava flows. However, virtual geomagnetic poles (VGPs) calculated from Black Sea sediments are not located at latitudes lower than 60° N, which denotes normal, though pronounced secular variations. During the postulated Hilina Pali excursion, the VGPs calculated from Black Sea data migrated clockwise only along the coasts of the Arctic Ocean from NE Canada (20.0 ka), via Alaska (18.6 ka) and NE Siberia (18.0 ka) to Svalbard (17.0 ka), then looping clockwise through the Eastern Arctic Ocean.
In addition to the Mono Lake and the Norwegian–Greenland Sea excursions, the Laschamp excursion was evidenced in the Black Sea PSV record with the lowest paleointensities at about 41.6 ka and a short-term (~500 years) full reversal centered at 41 ka. These excursions are further evidenced by an abnormal PSV index, though only the Laschamp and the Mono Lake excursions exhibit excursional VGP positions. The stacked Black Sea paleomagnetic record was also converted into one component parallel to the direction expected from a geocentric axial dipole (GAD) and two components perpendicular to it, representing only non-GAD components of the geomagnetic field. The Laschamp and the Norwegian–Greenland Sea excursions are characterized by extremely low GAD components, while the Mono Lake excursion is marked by large non-GAD contributions. Notably, negative values of the GAD component, indicating a fully reversed geomagnetic field, are observed only during the Laschamp excursion.
In summary, this doctoral thesis reconstructed high-resolution and high-fidelity PSV records from SE Black Sea sediments. The obtained record comprises three geomagnetic excursions, the Norwegian–Greenland Sea excursion, the Laschamp excursion, and the Mono Lake excursion. They are characterized by abnormal secular variations of different amplitudes centered at about 64.5 ka, 41.0 ka and 34.5 ka, respectively. In addition, the obtained PSV record from the Black Sea do not provide evidence for the postulated 'Hilina Pali excursion' at about 18.5 ka. Anyway, the obtained Black Sea paleomagnetic record, covering field fluctuations from normal secular variations, over excursions, to a short but full reversal, points to a geomagnetic field characterized by a large dynamic range in intensity and a highly variable superposition of dipole and non-dipole contributions from the geodynamo during the past 68.9 to 14.5 ka.
Hyperspectral remote sensing of the spatial and temporal heterogeneity of low Arctic vegetation
(2019)
Arctic tundra ecosystems are experiencing warming twice the global average and Arctic vegetation is responding in complex and heterogeneous ways. Shifting productivity, growth, species composition, and phenology at local and regional scales have implications for ecosystem functioning as well as the global carbon and energy balance. Optical remote sensing is an effective tool for monitoring ecosystem functioning in this remote biome. However, limited field-based spectral characterization of the spatial and temporal heterogeneity limits the accuracy of quantitative optical remote sensing at landscape scales. To address this research gap and support current and future satellite missions, three central research questions were posed:
• Does canopy-level spectral variability differ between dominant low Arctic vegetation communities and does this variability change between major phenological phases?
• How does canopy-level vegetation colour images recorded with high and low spectral resolution devices relate to phenological changes in leaf-level photosynthetic pigment concentrations?
• How does spatial aggregation of high spectral resolution data from the ground to satellite scale influence low Arctic tundra vegetation signatures and thereby what is the potential of upcoming hyperspectral spaceborne systems for low Arctic vegetation characterization?
To answer these questions a unique and detailed database was assembled. Field-based canopy-level spectral reflectance measurements, nadir digital photographs, and photosynthetic pigment concentrations of dominant low Arctic vegetation communities were acquired at three major phenological phases representing early, peak and late season. Data were collected in 2015 and 2016 in the Toolik Lake Research Natural Area located in north central Alaska on the North Slope of the Brooks Range. In addition to field data an aerial AISA hyperspectral image was acquired in the late season of 2016. Simulations of broadband Sentinel-2 and hyperspectral Environmental and Mapping Analysis Program (EnMAP) satellite reflectance spectra from ground-based reflectance spectra as well as simulations of EnMAP imagery from aerial hyperspectral imagery were also obtained.
Results showed that canopy-level spectral variability within and between vegetation communities differed by phenological phase. The late season was identified as the most discriminative for identifying many dominant vegetation communities using both ground-based and simulated hyperspectral reflectance spectra. This was due to an overall reduction in spectral variability and comparable or greater differences in spectral reflectance between vegetation communities in the visible near infrared spectrum.
Red, green, and blue (RGB) indices extracted from nadir digital photographs and pigment-driven vegetation indices extracted from ground-based spectral measurements showed strong significant relationships. RGB indices also showed moderate relationships with chlorophyll and carotenoid pigment concentrations. The observed relationships with the broadband RGB channels of the digital camera indicate that vegetation colour strongly influences the response of pigment-driven spectral indices and digital cameras can track the seasonal development and degradation of photosynthetic pigments.
Spatial aggregation of hyperspectral data from the ground to airborne, to simulated satel-lite scale was influenced by non-photosynthetic components as demonstrated by the distinct shift of the red edge to shorter wavelengths. Correspondence between spectral reflectance at the three scales was highest in the red spectrum and lowest in the near infra-red. By artificially mixing litter spectra at different proportions to ground-based spectra, correspondence with aerial and satellite spectra increased. Greater proportions of litter were required to achieve correspondence at the satellite scale.
Overall this thesis found that integrating multiple temporal, spectral, and spatial data is necessary to monitor the complexity and heterogeneity of Arctic tundra ecosystems. The identification of spectrally similar vegetation communities can be optimized using non-peak season hyperspectral data leading to more detailed identification of vegetation communities. The results also highlight the power of vegetation colour to link ground-based and satellite data. Finally, a detailed characterization non-photosynthetic ecosystem components is crucial for accurate interpretation of vegetation signals at landscape scales.
The trace gases CO2 and CH4 pertain to the most relevant greenhouse gases and are important exchange fluxes of the global carbon (C) cycle. Their atmospheric quantity increased significantly as a result of the intensification of anthropogenic activities, such as especially land-use and land-use change, since the mid of the 18th century. To mitigate global climate change and ensure food security, land-use systems need to be developed, which favor reduced trace gas emissions and a sustainable soil carbon management. This requires the accurate and precise quantification of the influence of land-use and land-use change on CO2 and CH4 emissions. A common method to determine the trace gas dynamics and C sink or source function of a particular ecosystem is the closed chamber method. This method is often used assuming that accuracy and precision are high enough to determine differences in C gas emissions for e.g., treatment comparisons or different ecosystem components.
However, the broad range of different chamber designs, related operational procedures and data-processing strategies which are described in the scientific literature contribute to the overall uncertainty of closed chamber-based emission estimates. Hence, the outcomes of meta-analyses are limited, since these methodical differences hamper the comparability between studies. Thus, a standardization of closed chamber data acquisition and processing is much-needed.
Within this thesis, a set of case studies were performed to: (I) develop standardized routines for an unbiased data acquisition and processing, with the aim of providing traceable, reproducible and comparable closed chamber based C emission estimates; (II) validate those routines by comparing C emissions derived using closed chambers with independent C emission estimates; and (III) reveal processes driving the spatio-temporal dynamics of C emissions by developing (data processing based) flux separation approaches.
The case studies showed: (I) the importance to test chamber designs under field conditions for an appropriate sealing integrity and to ensure an unbiased flux measurement. Compared to the sealing integrity, the use of a pressure vent and fan was of minor importance, affecting mainly measurement precision; (II) that the developed standardized data processing routines proved to be a powerful and flexible tool to estimate C gas emissions and that this tool can be successfully applied on a broad range of flux data sets from very different ecosystem; (III) that automatic chamber measurements display temporal dynamics of CO2 and CH4 fluxes very well and most importantly, that they accurately detect small-scale spatial differences in the development of soil C when validated against repeated soil inventories; and (IV) that a simple algorithm to separate CH4 fluxes into ebullition and diffusion improves the identification of environmental drivers, which allows for an accurate gap-filling of measured CH4 fluxes.
Overall, the proposed standardized data acquisition and processing routines strongly improved the detection accuracy and precision of source/sink patterns of gaseous C emissions. Hence, future studies, which consider the recommended improvements, will deliver valuable new data and insights to broaden our understanding of spatio-temporal C gas dynamics, their particular environmental drivers and underlying processes.
Introducing PebbleCounts
(2019)
Grain-size distributions are a key geomorphic metric of gravel-bed rivers. Traditional measurement methods include manual counting or photo sieving, but these are achievable only at the 1–10 ㎡ scale. With the advent of drones and increasingly high-resolution cameras, we can now generate orthoimagery over hectares at millimeter to centimeter resolution. These scales, along with the complexity of high-mountain rivers, necessitate different approaches for photo sieving. As opposed to other image segmentation methods that use a watershed approach, our open-source algorithm, PebbleCounts, relies on k-means clustering in the spatial and spectral domain and rapid manual selection of well-delineated grains. This improves grain-size estimates for complex riverbed imagery, without post-processing. We also develop a fully automated method, PebbleCountsAuto, that relies on edge detection and filtering suspect grains, without the k-means clustering or manual selection steps. The algorithms are tested in controlled indoor conditions on three arrays of pebbles and then applied to 12 × 1 ㎡ orthomosaic clips of high-energy mountain rivers collected with a camera-on-mast setup (akin to a low-flying drone). A 20-pixel b-axis length lower truncation is necessary for attaining accurate grain-size distributions. For the k-means PebbleCounts approach, average percentile bias and precision are 0.03 and 0.09 ψ, respectively, for ∼1.16 mm pixel⁻¹ images, and 0.07 and 0.05 ψ for one 0.32 mm pixel⁻¹ image. The automatic approach has higher bias and precision of 0.13 and 0.15 ψ, respectively, for ∼1.16 mm pixel⁻¹ images, but similar values of −0.06 and 0.05 ψ for one 0.32 mm pixel⁻¹ image. For the automatic approach, only at best 70 % of the grains are correct identifications, and typically around 50 %. PebbleCounts operates most effectively at the 1 ㎡ patch scale, where it can be applied in ∼5–10 min on many patches to acquire accurate grain-size data over 10–100 ㎡ areas. These data can be used to validate PebbleCountsAuto, which may be applied at the scale of entire survey sites (102–104 ㎡ ). We synthesize results and recommend best practices for image collection, orthomosaic generation, and grain-size measurement using both algorithms.
Sea surface temperature (SST) patterns can – as surface climate forcing – affect weather and climate at large distances. One example is El Niño-Southern Oscillation (ENSO) that causes climate anomalies around the globe via teleconnections. Although several studies identified and characterized these teleconnections, our understanding of climate processes remains incomplete, since interactions and feedbacks are typically exhibited at unique or multiple temporal and spatial scales. This study characterizes the interactions between the cells of a global SST data set at different temporal and spatial scales using climate networks. These networks are constructed using wavelet multi-scale correlation that investigate the correlation between the SST time series at a range of scales allowing instantaneously deeper insights into the correlation patterns compared to traditional methods like empirical orthogonal functions or classical correlation analysis. This allows us to identify and visualise regions of – at a certain timescale – similarly evolving SSTs and distinguish them from those with long-range teleconnections to other ocean regions. Our findings re-confirm accepted knowledge about known highly linked SST patterns like ENSO and the Pacific Decadal Oscillation, but also suggest new insights into the characteristics and origins of long-range teleconnections like the connection between ENSO and Indian Ocean Dipole.
The Central Andes host large reserves of base and precious metals. The region represented, in 2017, an important part of the worldwide mining activity. Three principal types of deposits have been identified and studied: 1) porphyry type deposits extending from central Chile and Argentina to Bolivia, and Northern Peru, 2) iron oxide-copper-gold (IOCG) deposits, extending from central Peru to central Chile, and 3) epithermal tin polymetallic deposits extending from Southern Peru to Northern Argentina, which compose a large part of the deposits of the Bolivian Tin Belt (BTB). Deposits in the BTB can be divided into two major types: (1) tin-tungsten-zinc pluton-related polymetallic deposits, and (2) tin-silver-lead-zinc epithermal polymetallic vein deposits.
Mina Pirquitas is a tin-silver-lead-zinc epithermal polymetallic vein deposit, located in north-west Argentina, that used to be one of the most important tin-silver producing mine of the country. It was interpreted to be part of the BTB and it shares similar mineral associations with southern pluton related BTB epithermal deposits. Two major mineralization events related to three pulses of magmatic fluids mixed with meteoric water have been identified. The first event can be divided in two stages: 1) stage I-1 with quartz, pyrite, and cassiterite precipitating from fluids between 233 and 370 °C and salinity between 0 and 7.5 wt%, corresponding to a first pulse of fluids, and 2) stage I-2 with sphalerite and tin-silver-lead-antimony sulfosalts precipitating from fluids between 213 and 274 °C with salinity up to 10.6 wt%, corresponding to a new pulse of magmatic fluids in the hydrothermal system. The mineralization event II deposited the richest silver ores at Pirquitas. Event II fluids temperatures and salinities range between 190 and 252 °C and between 0.9 and 4.3 wt% respectively. This corresponds to the waning supply of magmatic fluids. Noble gas isotopic compositions and concentrations in ore-hosted fluid inclusions demonstrate a significant contribution of magmatic fluids to the Pirquitas mineralization although no intrusive rocks are exposed in the mine area.
Lead and sulfur isotopic measurements on ore minerals show that Pirquitas shares a similar signature with southern pluton related polymetallic deposits in the BTB. Furthermore, the major part of the sulfur isotopic values of sulfide and sulfosalt minerals from Pirquitas ranges in the field for sulfur derived from igneous rocks. This suggests that the main contribution of sulfur to the hydrothermal system at Pirquitas is likely to be magma-derived. The precise age of the deposit is still unknown but the results of wolframite dating of 2.9 ± 9.1 Ma and local structural observations suggest that the late mineralization event is younger than 12 Ma.
OpenForecast
(2019)
The development and deployment of new operational runoff forecasting systems are a strong focus of the scientific community due to the crucial importance of reliable and timely runoff predictions for early warnings of floods and flashfloods for local businesses and communities. OpenForecast, the first operational runoff forecasting system in Russia, open for public use, is presented in this study. We developed OpenForecast based only on open-source software and data-GR4J hydrological model, ERA-Interim meteorological reanalysis, and ICON deterministic short-range meteorological forecasts. Daily forecasts were generated for two basins in the European part of Russia. Simulation results showed a limited efficiency in reproducing the spring flood of 2019. Although the simulations managed to capture the timing of flood peaks, they failed in estimating flood volume. However, further implementation of the parsimonious data assimilation technique significantly alleviates simulation errors. The revealed limitations of the proposed operational runoff forecasting system provided a foundation to outline its further development and improvement.