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Cosmic-ray neutron sensing (CRNS) has become an effective method to measure soil moisture at a horizontal scale of hundreds of metres and a depth of decimetres. Recent studies proposed operating CRNS in a network with overlapping footprints in order to cover root-zone water dynamics at the small catchment scale and, at the same time, to represent spatial heterogeneity. In a joint field campaign from September to November 2020 (JFC-2020), five German research institutions deployed 15 CRNS sensors in the 0.4 km2 Wüstebach catchment (Eifel mountains, Germany). The catchment is dominantly forested (but includes a substantial fraction of open vegetation) and features a topographically distinct catchment boundary. In addition to the dense CRNS coverage, the campaign featured a unique combination of additional instruments and techniques: hydro-gravimetry (to detect water storage dynamics also below the root zone); ground-based and, for the first time, airborne CRNS roving; an extensive wireless soil sensor network, supplemented by manual measurements; and six weighable lysimeters. Together with comprehensive data from the long-term local research infrastructure, the published data set (available at https://doi.org/10.23728/b2share.756ca0485800474e9dc7f5949c63b872; Heistermann et al., 2022) will be a valuable asset in various research contexts: to advance the retrieval of landscape water storage from CRNS, wireless soil sensor networks, or hydrogravimetry; to identify scale-specific combinations of sensors and methods to represent soil moisture variability; to improve the understanding and simulation of land–atmosphere exchange as well as hydrological and hydrogeological processes at the hillslope and the catchment scale; and to support the retrieval of soil water content from airborne and spaceborne remote sensing platforms.
The Arctic is changing rapidly and permafrost is thawing. Especially ice-rich permafrost, such as the late Pleistocene Yedoma, is vulnerable to rapid and deep thaw processes such as surface subsidence after the melting of ground ice. Due to permafrost thaw, the permafrost carbon pool is becoming increasingly accessible to microbes, leading to increased greenhouse gas emissions, which enhances the climate warming.
The assessment of the molecular structure and biodegradability of permafrost organic matter (OM) is highly needed. My research revolves around the question “how does permafrost thaw affect its OM storage?” More specifically, I assessed (1) how molecular biomarkers can be applied to characterize permafrost OM, (2) greenhouse gas production rates from thawing permafrost, and (3) the quality of OM of frozen and (previously) thawed sediments.
I studied deep (max. 55 m) Yedoma and thawed Yedoma permafrost sediments from Yakutia (Sakha Republic). I analyzed sediment cores taken below thermokarst lakes on the Bykovsky Peninsula (southeast of the Lena Delta) and in the Yukechi Alas (Central Yakutia), and headwall samples from the permafrost cliff Sobo-Sise (Lena Delta) and the retrogressive thaw slump Batagay (Yana Uplands). I measured biomarker concentrations of all sediment samples. Furthermore, I carried out incubation experiments to quantify greenhouse gas production in thawing permafrost.
I showed that the biomarker proxies are useful to assess the source of the OM and to distinguish between OM derived from terrestrial higher plants, aquatic plants and microbial activity. In addition, I showed that some proxies help to assess the degree of degradation of permafrost OM, especially when combined with sedimentological data in a multi-proxy approach. The OM of Yedoma is generally better preserved than that of thawed Yedoma sediments. The greenhouse gas production was highest in the permafrost sediments that thawed for the first time, meaning that the frozen Yedoma sediments contained most labile OM. Furthermore, I showed that the methanogenic communities had established in the recently thawed sediments, but not yet in the still-frozen sediments.
My research provided the first molecular biomarker distributions and organic carbon turnover data as well as insights in the state and processes in deep frozen and thawed Yedoma sediments. These findings show the relevance of studying OM in deep permafrost sediments.
Technological progress allows for producing ever more complex predictive models on the basis of increasingly big datasets. For risk management of natural hazards, a multitude of models is needed as basis for decision-making, e.g. in the evaluation of observational data, for the prediction of hazard scenarios, or for statistical estimates of expected damage. The question arises, how modern modelling approaches like machine learning or data-mining can be meaningfully deployed in this thematic field. In addition, with respect to data availability and accessibility, the trend is towards open data. Topic of this thesis is therefore to investigate the possibilities and limitations of machine learning and open geospatial data in the field of flood risk modelling in the broad sense. As this overarching topic is broad in scope, individual relevant aspects are identified and inspected in detail.
A prominent data source in the flood context is satellite-based mapping of inundated areas, for example made openly available by the Copernicus service of the European Union. Great expectations are directed towards these products in scientific literature, both for acute support of relief forces during emergency response action, and for modelling via hydrodynamic models or for damage estimation. Therefore, a focus of this work was set on evaluating these flood masks. From the observation that the quality of these products is insufficient in forested and built-up areas, a procedure for subsequent improvement via machine learning was developed. This procedure is based on a classification algorithm that only requires training data from a particular class to be predicted, in this specific case data of flooded areas, but not of the negative class (dry areas). The application for hurricane Harvey in Houston shows the high potential of this method, which depends on the quality of the initial flood mask.
Next, it is investigated how much the predicted statistical risk from a process-based model chain is dependent on implemented physical process details. Thereby it is demonstrated what a risk study based on established models can deliver. Even for fluvial flooding, such model chains are already quite complex, though, and are hardly available for compound or cascading events comprising torrential rainfall, flash floods, and other processes. In the fourth chapter of this thesis it is therefore tested whether machine learning based on comprehensive damage data can offer a more direct path towards damage modelling, that avoids explicit conception of such a model chain. For that purpose, a state-collected dataset of damaged buildings from the severe El Niño event 2017 in Peru is used. In this context, the possibilities of data-mining for extracting process knowledge are explored as well. It can be shown that various openly available geodata sources contain useful information for flood hazard and damage modelling for complex events, e.g. satellite-based rainfall measurements, topographic and hydrographic information, mapped settlement areas, as well as indicators from spectral data. Further, insights on damaging processes are discovered, which mainly are in line with prior expectations. The maximum intensity of rainfall, for example, acts stronger in cities and steep canyons, while the sum of rain was found more informative in low-lying river catchments and forested areas. Rural areas of Peru exhibited higher vulnerability in the presented study compared to urban areas. However, the general limitations of the methods and the dependence on specific datasets and algorithms also become obvious.
In the overarching discussion, the different methods – process-based modelling, predictive machine learning, and data-mining – are evaluated with respect to the overall research questions. In the case of hazard observation it seems that a focus on novel algorithms makes sense for future research. In the subtopic of hazard modelling, especially for river floods, the improvement of physical models and the integration of process-based and statistical procedures is suggested. For damage modelling the large and representative datasets necessary for the broad application of machine learning are still lacking. Therefore, the improvement of the data basis in the field of damage is currently regarded as more important than the selection of algorithms.
Localisation of deformation is a ubiquitous feature in continental rift dynamics and observed across drastically different time and length scales. This thesis comprises one experimental and two numerical modelling studies investigating strain localisation in (1) a ductile shear zone induced by a material heterogeneity and (2) in an active continental rift setting. The studies are related by the fact that the weakening mechanisms on the crystallographic and grain size scale enable bulk rock weakening, which fundamentally enables the formation of shear zones, continental rifts and hence plate tectonics. Aiming to investigate the controlling mechanisms on initiation and evolution of a shear zone, the torsion experiments of the experimental study were conducted in a Patterson type apparatus with strong Carrara marble cylinders with a weak, planar Solnhofen limestone inclusion. Using state-of-the-art numerical modelling software, the torsion experiments were simulated to answer questions regarding localisation procedure like stress distribution or the impact of rheological weakening. 2D numerical models were also employed to integrate geophysical and geological data to explain characteristic tectonic evolution of the Southern and Central Kenya Rift. Key elements of the numerical tools are a randomized initial strain distribution and the usage of strain softening. During the torsion experiments, deformation begins to localise at the limestone inclusion tips in a process zone, which propagates into the marble matrix with increasing deformation until a ductile shear zone is established. Minor indicators for coexisting brittle deformation are found close to the inclusion tip and presumed to slightly facilitate strain localisation besides the dominant ductile deformation processes. The 2D numerical model of the torsion experiment successfully predicts local stress concentration and strain rate amplification ahead of the inclusion in first order agreement with the experimental results. A simple linear parametrization of strain weaking enables high accuracy reproduction of phenomenological aspects of the observed weakening. The torsion experiments suggest that loading conditions do not affect strain localisation during high temperature deformation of multiphase material with high viscosity contrasts. A numerical simulation can provide a way of analysing the process zone evolution virtually and extend the examinable frame. Furthermore, the nested structure and anastomosing shape of an ultramylonite band was mimicked with an additional second softening step. Rheological weakening is necessary to establish a shear zone in a strong matrix around a weak inclusion and for ultramylonite formation.
Such strain weakening laws are also incorporated into the numerical models of the
Southern and Central Kenya Rift that capture the characteristic tectonic evolution. A three-stage early rift evolution is suggested that starts with (1) the accommodation of strain by a single border fault and flexure of the hanging-wall crust, after which (2) faulting in the hanging-wall and the basin centre increases before (3) the early-stage asymmetry is lost and basinward localisation of deformation occurs. Along-strike variability of rifts can be produced by modifying the initial random noise distribution. In summary, the three studies address selected aspects of the broad range of mechanisms and processes that fundamentally enable the deformation of rock and govern the localisation patterns across the scales. In addition to the aforementioned results, the first and second manuscripts combined, demonstrate a procedure to find new or improve on existing numerical formulations for specific rheologies and their dynamic weakening. These formulations are essential in addressing rock deformation from the grain to the global scale. As within the third study of this thesis, where geodynamic controls on the evolution of a rift were examined and acquired by the integration of geological and geophysical data into a numerical model.
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.
Plate tectonics describes the movement of rigid plates at the surface of the Earth as well as their complex deformation at three types of plate boundaries: 1) divergent boundaries such as rift zones and mid-ocean ridges, 2) strike-slip boundaries where plates grind past each other, such as the San Andreas Fault, and 3) convergent boundaries that form large mountain ranges like the Andes. The generally narrow deformation zones that bound the plates exhibit complex strain patterns that evolve through time. During this evolution, plate boundary deformation is driven by tectonic forces arising from Earth’s deep interior and from within the lithosphere, but also by surface processes, which erode topographic highs and deposit the resulting sediment into regions of low elevation. Through the combination of these factors, the surface of the Earth evolves in a highly dynamic way with several feedback mechanisms. At divergent boundaries, for example, tensional stresses thin the lithosphere, forcing uplift and subsequent erosion of rift flanks, which creates a sediment source. Meanwhile, the rift center subsides and becomes a topographic low where sediments accumulate. This mass transfer from foot- to hanging wall plays an important role during rifting, as it prolongs the activity of individual normal faults. When rifting continues, continents are eventually split apart, exhuming Earth’s mantle and creating new oceanic crust. Because of the complex interplay between deep tectonic forces that shape plate boundaries and mass redistribution at the Earth’s surface, it is vital to understand feedbacks between the two domains and how they shape our planet.
In this study I aim to provide insight on two primary questions: 1) How do divergent and strike-slip plate boundaries evolve? 2) How is this evolution, on a large temporal scale and a smaller structural scale, affected by the alteration of the surface through erosion and deposition? This is done in three chapters that examine the evolution of divergent and strike-slip plate boundaries using numerical models. Chapter 2 takes a detailed look at the evolution of rift systems using two-dimensional models. Specifically, I extract faults from a range of rift models and correlate them through time to examine how fault networks evolve in space and time. By implementing a two-way coupling between the geodynamic code ASPECT and landscape evolution code FastScape, I investigate how the fault network and rift evolution are influenced by the system’s erosional efficiency, which represents many factors like lithology or climate. In Chapter 3, I examine rift evolution from a three-dimensional perspective. In this chapter I study linkage modes for offset rifts to determine when fast-rotating plate-boundary structures known as continental microplates form. Chapter 4 uses the two-way numerical coupling between tectonics and landscape evolution to investigate how a strike-slip boundary responds to large sediment loads, and whether this is sufficient to form an entirely new type of flexural strike-slip basin.
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.
Salt deposits offer a variety of usage types. These include the mining of rock salt and potash salt as important raw materials, the storage of energy in man-made underground caverns, and the disposal of hazardous substances in former mines. The most serious risk with any of these usage types comes from the contact with groundwater or surface water. It causes an uncontrolled dissolution of salt rock, which in the worst case can result in the flooding or collapse of underground facilities. Especially along potash seams, cavernous structures can spread quickly, because potash salts show a much higher solubility than rock salt. However, as their chemical behavior is quite complex, previous models do not account for these highly soluble interlayers. Therefore, the objective of the present thesis is to describe the evolution of cavernous structures along potash seams in space and time in order to improve hazard mitigation during the utilization of salt deposits.
The formation of cavernous structures represents an interplay of chemical and hydraulic processes. Hence, the first step is to systematically investigate the dissolution and precipitation reactions that occur when water and potash salt come into contact. For this purpose, a geochemical reaction model is used. The results show that the minerals are only partially dissolved, resulting in a porous sponge like structure. With the saturation of the solution increasing, various secondary minerals are formed, whose number and type depend on the original rock composition. Field data confirm a correlation between the degree of saturation and the distance from the center of the cavern, where solution is entering. Subsequently, the reaction model is coupled with a flow and transport code and supplemented by a novel approach called ‘interchange’. The latter enables the exchange of solution and rock between areas of different porosity and mineralogy, and thus ultimately the growth of the cavernous structure. By means of several scenario analyses, cavern shape, growth rate and mineralogy are systematically investigated, taking also heterogeneous potash seams into account. The results show that basically four different cases can be distinguished, with mixed forms being a frequent occurrence in nature. The classification scheme is based on the dimensionless numbers Péclet and Damköhler, and allows for a first assessment of the hazard potential. In future, the model can be applied to any field case, using measurement data for calibration.
The presented research work provides a reactive transport model that is able to spatially and temporally characterize the propagation of cavernous structures along potash seams for the first time. Furthermore, it allows to determine thickness and composition of transition zones between cavern center and unaffected salt rock. The latter is particularly important in potash mining, so that natural cavernous structures can be located at an early stage and the risk of mine flooding can thus be reduced. The models may also contribute to an improved hazard prevention in the construction of storage caverns and the disposal of hazardous waste in salt deposits. Predictions regarding the characteristics and evolution of cavernous structures enable a better assessment of potential hazards, such as integrity or stability loss, as well as of suitable mitigation measures.
The intensification of Northern Hemisphere glaciations at the end of the Pliocene epoch marks one of the most substantial climatic shifts of the Cenozoic. Despite global cooling, sea surface temperatures in the high latitude North Atlantic Ocean rose between 2.9–2.7 million years ago. Here we present sedimentary geochemical proxy data from the Gulf of Cadiz to reconstruct the variability of Mediterranean Outflow Water, an important heat source to the North Atlantic. We find evidence for enhanced production of Mediterranean Outflow from the mid-Pliocene to the late Pliocene which we infer could have driven a sub-surface heat channel into the high-latitude North Atlantic. We then use Earth System Models to constrain the impact of enhanced Mediterranean Outflow production on the northward heat transport in the North Atlantic. In accord with the proxy data, the numerical model results support the formation of a sub-surface channel that pumped heat from the subtropics into the high latitude North Atlantic. We further suggest that this mechanism could have delayed ice sheet growth at the end of the Pliocene.
Major challenges during geothermal exploration and exploitation include the structural-geological characterization of the geothermal system and the application of sustainable monitoring concepts to explain changes in a geothermal reservoir during production and/or reinjection of fluids. In the absence of sufficiently permeable reservoir rocks, faults and fracture networks are preferred drilling targets because they can facilitate the migration of hot and/or cold fluids. In volcanic-geothermal systems considerable amounts of gas emissions can be released at the earth surface, often related to these fluid-releasing structures.
In this thesis, I developed and evaluated different methodological approaches and measurement concepts to determine the spatial and temporal variation of several soil gas parameters to understand the structural control on fluid flow. In order to validate their potential as innovative geothermal exploration and monitoring tools, these methodological approaches were applied to three different volcanic-geothermal systems. At each site an individual survey design was developed regarding the site-specific questions.
The first study presents results of the combined measurement of CO2 flux, ground temperatures, and the analysis of isotope ratios (δ13CCO2, 3He/4He) across the main production area of the Los Humeros geothermal field, to identify locations with a connection to its supercritical (T > 374◦C and P > 221 bar) geothermal reservoir. The results of the systematic and large-scale (25 x 200 m) CO2 flux scouting survey proved to be a fast and flexible way to identify areas of anomalous degassing. Subsequent sampling with high resolution surveys revealed the actual extent and heterogenous pattern of anomalous degassing areas. They have been related to the internal fault hydraulic architecture and allowed to assess favourable structural settings for fluid flow such as fault intersections. Finally, areas of unknown structurally controlled permeability with a connection to the superhot geothermal reservoir have been determined, which represent promising targets for future geothermal exploration and development.
In the second study, I introduce a novel monitoring approach by examining the variation of CO2 flux to monitor changes in the reservoir induced by fluid reinjection. For that reason, an automated, multi-chamber CO2 flux system was deployed across the damage zone of a major normal fault crossing the Los Humeros geothermal field. Based on the results of the CO2 flux scouting survey, a suitable site was selected that had a connection to the geothermal reservoir, as identified by hydrothermal CO2 degassing and hot ground temperatures (> 50 °C). The results revealed a response of gas emissions to changes in reinjection rates within 24 h, proving an active hydraulic communication between the geothermal reservoir and the earth surface. This is a promising monitoring strategy that provides nearly real-time and in-situ data about changes in the reservoir and allows to timely react to unwanted changes (e.g., pressure decline, seismicity).
The third study presents results from the Aluto geothermal field in Ethiopia where an area-wide and multi-parameter analysis, consisting of measurements of CO2 flux, 222Rn, and 220Rn activity concentrations and ground temperatures was conducted to detect hidden permeable structures. 222Rn and 220Rn activity concentrations are evaluated as a complementary soil gas parameter to CO2 flux, to investigate their potential to understand tectono-volcanic degassing. The combined measurement of all parameters enabled to develop soil gas fingerprints, a novel visualization approach. Depending on the magnitude of gas emissions and their migration velocities the study area was divided in volcanic (heat), tectonic (structures), and volcano-tectonic dominated areas. Based on these concepts, volcano-tectonic dominated areas, where hot hydrothermal fluids migrate along permeable faults, present the most promising targets for future geothermal exploration and development in this geothermal field. Two of these areas have been identified in the south and south-east which have not yet been targeted for geothermal exploitation. Furthermore, two unknown areas of structural related permeability could be identified by 222Rn and 220Rn activity concentrations.
Eventually, the fourth study presents a novel measurement approach to detect structural controlled CO2 degassing, in Ngapouri geothermal area, New Zealand. For the first time, the tunable diode laser (TDL) method was applied in a low-degassing geothermal area, to evaluate its potential as a geothermal exploration method. Although the sampling approach is based on profile measurements, which leads to low spatial resolution, the results showed a link between known/inferred faults and increased CO2 concentrations. Thus, the TDL method proved to be a successful in the determination of structural related permeability, also in areas where no obvious geothermal activity is present. Once an area of anomalous CO2 concentrations has been identified, it can be easily complemented by CO2 flux grid measurements to determine the extent and orientation of the degassing segment.
With the results of this work, I was able to demonstrate the applicability of systematic and area-wide soil gas measurements for geothermal exploration and monitoring purposes. In particular, the combination of different soil gases using different measurement networks enables the identification and characterization of fluid-bearing structures and has not yet been used and/or tested as standard practice. The different studies present efficient and cost-effective workflows and demonstrate a hands-on approach to a successful and sustainable exploration and monitoring of geothermal resources. This minimizes the resource risk during geothermal project development. Finally, to advance the understanding of the complex structure and dynamics of geothermal systems, a combination of comprehensive and cutting-edge geological, geochemical, and geophysical exploration methods is essential.