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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 first step towards assessing hazards in seismically active regions involves mapping capable faults and estimating their recurrence times. While the mapping of active faults is commonly based on distinct geologic and geomorphic features evident at the surface, mapping blind seismogenic faults is complicated by the absence of on-fault diagnostic features. Here we investigated the Pichilemu Fault in coastal Chile, unknown until it generated a Mw 7.0 earthquake in 2010. The lack of evident surface faulting suggests activity along a partly-hidden blind fault. We used off-fault deformed marine terraces to estimate a fault-slip rate of 0.52 ± 0.04 m/ka, which, when integrated with satellite geodesy suggests a 2.12 ± 0.2 ka recurrence time for Mw~7.0 normal-faulting earthquakes. We propose that extension in the Pichilemu region is associated with stress changes during megathrust earthquakes and accommodated by sporadic slip during upper-plate earthquakes, which has implications for assessing the seismic potential of cryptic faults along convergent margins and elsewhere.
Among the multitude of geomorphological processes, aeolian shaping processes are of special character, Pedogenic dust is one of the most important sources of atmospheric aerosols and therefore regarded as a key player for atmospheric processes. Soil dust emissions, being complex in composition and properties, influence atmospheric processes and air quality and has impacts on other ecosystems. In this because even though their immediate impact can be considered low (exceptions exist), their constant and large-scale force makes them a powerful player in the earth system. dissertation, we unravel a novel scientific understanding of this complex system based on a holistic dataset acquired during a series of field experiments on arable land in La Pampa, Argentina. The field experiments as well as the generated data provide information about topography, various soil parameters, the atmospheric dynamics in the very lower atmosphere (4m height) as well as measurements regarding aeolian particle movement across a wide range of particle size classes between 0.2μm up to the coarse sand.
The investigations focus on three topics: (a) the effects of low-scale landscape structures on aeolian transport processes of the coarse particle fraction, (b) the horizontal and vertical fluxes of the very fine particles and (c) the impact of wind gusts on particle emissions.
Among other considerations presented in this thesis, it could in particular be shown, that even though the small-scale topology does have a clear impact on erosion and deposition patterns, also physical soil parameters need to be taken into account for a robust statistical modelling of the latter. Furthermore, specifically the vertical fluxes of particulate matter have different characteristics for the particle size classes. Finally, a novel statistical measure was introduced to quantify the impact of wind gusts on the particle uptake and its application on the provided data set. The aforementioned measure shows significantly increased particle concentrations during points in time defined as gust event.
With its holistic approach, this thesis further contributes to the fundamental understanding of how atmosphere and pedosphere are intertwined and affect each other.
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.
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.
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.
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.
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.
Der zentralasiatische Naturraum, wie er sich uns heute präsentiert, ist das Ergebnis eines Zusammenwirkens vieler verschiedener Faktoren über Jahrmillionen hinweg. Im aktuellen Kontext des Klimawandels zeigt sich jedoch, wie stark sich Stoffflüsse auch kurzfristig ändern und dabei das Gesicht der Landschaft verwandeln können. Die Gobi-Wüste in der Inneren Mongolei (China), als Teil der gleichnamigen Trockenregionen Nordwestchinas, ist aufgrund der Ausgestaltung ihrer landschaftsprägenden Elemente sowie ihrer Landschaftsdynamik, im Zusammenhang mit der Lage zum Tibet-Plateau, in den Fokus der klimageschichtlichen Grundlagenforschung gerückt. Als großes Langzeitarchiv unterschiedlichster fluvialer, lakustriner und äolischer Sedimente stellt sie eine bedeutende Lokalität zur Rekonstruktion von lokalen und regionalen Stoffflüssen dar.. Andererseits ist die Gobi-Wüste zugleich auch eine bedeutende Quelle für den überregionalen Staubtransport, da sie aufgrund der klimatischen Bedingungen insbesondere der Erosion durch Ausblasung preisgegeben wird. Vor diesem Hintergrund erfolgten zwischen 2011 und 2014, im Rahmen des BMBF-Verbundprogramms WTZ Zentralasien – Monsundynamik & Geoökosysteme (Förderkennzeichen 03G0814), mehrere deutsch-chinesische Expeditionen in das Ejina-Becken (Innere Mongolei) und das Qilian Shan-Vorland. Im Zuge dieser Expeditionen wurden für eine Bestimmung potenzieller Sedimentquellen erstmals zahlreiche Oberflächenproben aus dem gesamten Einzugsgebiet des Heihe (schwarzer Fluss) gesammelt. Zudem wurden mit zwei Bohrungen im inneren des Ejina-Beckens, ergänzende Sedimentbohrkerne zum bestehenden Bohrkern D100 (siehe Wünnemann (2005)) abgeteuft, um weit reichende, ergänzende Informationen zur Landschaftsgeschichte und zum überregionalen Sedimenttransfer zu erhalten. Gegenstand und Ziel der vorliegenden Doktorarbeit ist die sedimentologisch-mineralogische Charakterisierung des Untersuchungsgebietes in Bezug auf potenzielle Sedimentquellen und Stoffflüsse des Ejina-Beckens sowie die Rekonstruktion der Ablagerungsgeschichte eines dort erbohrten, 19m langen Sedimentbohrkerns (GN100). Schwerpunkt ist hierbei die Klärung der Sedimentherkunft innerhalb des Bohrkerns sowie die Ausweisung von Herkunftssignalen und möglichen Sedimentquellen bzw. Sedimenttransportpfaden. Die methodische Herangehensweise basiert auf einem Multi-Proxy-Ansatz zur Charakterisierung der klastischen Sedimentfazies anhand von Geländebeobachtungen, lithologisch-granulometrischen und mineralogisch-geochemischen Analysen sowie statistischen Verfahren. Für die mineralogischen Untersuchungen der Sedimente wurde eine neue, rasterelektronenmikroskopische Methode zur automatisierten Partikelanalyse genutzt und den traditionellen Methoden gegenübergestellt. Die synoptische Betrachtung der granulometrischen, geochemischen und mineralogischen Befunde der Oberflächensedimente ergibt für das Untersuchungsgebiet ein logisches Kaskadenmodell mit immer wiederkehrenden Prozessbereichen und ähnlichen Prozesssignalen. Die umfangreichen granulometrischen Analysen deuten dabei auf abnehmende Korngrößen mit zunehmender Entfernung vom Qilian Shan hin und ermöglichen die Identifizierung von vier texturellen Signalen: den fluvialen Sanden, den Dünensanden, den Stillwassersedimenten und Stäuben. Diese Ergebnisse können als Interpretationsgrundlage für die Korngrößenanalysen des Bohrkerns genutzt werden. Somit ist es möglich, die Ablagerungsgeschichte der Bohrkernsedimente zu rekonstruieren und in Verbindung mit eigenen und literaturbasierten Datierungen in einen Gesamtkontext einzuhängen. Für das Untersuchungsgebiet werden somit vier Ablagerungsphasen ausgewiesen, die bis in die Zeit des letzten glazialen Maximums (LGM) zurückreichen. Während dieser Ablagerungsphasen kam es im Zuge unterschiedlicher Aktivitäts- und Stabilitätsphasen zu einer kontinuierlichen Progradation und Überprägung des Schwemmfächers. Eine besonders aktive Phase kann zwischen 8 ka und 4 ka BP festgestellt werden, während der es aufgrund zunehmender fluvialer Aktivitäten zu einer deutlich verstärkten Schwemmfächerdynamik gekommen zu sein scheint. In den Abschnitten davor und danach waren es vor allem äolische Prozesse, die zu einer Überprägung des Schwemmfächers geführt haben. Hinsichtlich der mineralogischen Herkunftssignale gibt es eine große Variabilität. Dies spiegelt die enorme Heterogenität der Geologie des Untersuchungsgebietes wider, wodurch die räumlichen Signale nicht sehr stark ausgeprägt sind. Dennoch, können für das Einzugsgebiet drei größere Bereiche deklariert werden, die als Herkunftsgebiet in Frage kommen. Das östliche Qilian Shan Vorland zeichnet sich dabei durch deutlich höhere Chloritgehalte als primäre Quelle für die Sedimente im Ejina-Becken aus. Sie unterscheiden sich insbesondere durch stark divergierende Chloritgehalte in der Tonmineral- und Gesamtmineralfraktion, was das östliche Qilian Shan Vorland als primäre Quelle für die Sedimente im Ejina-Becken auszeichnet. Dies steht in Zusammenhang mit den Grünschiefern, Ophioliten und Serpentiniten in diesem Bereich. Geochemisch deutet vor allem das Cr/Rb-Verhältnis eine große Variabilität innerhalb des Einzugsgebietes an. Auch hier ist es das östliche Vorland, welches aufgrund seines hohen Anteils an mafischen Gesteinen reich an Chromiten und Spinellen ist und sich somit vom restlichen Untersuchungsgebiet abhebt. Die zeitliche aber auch die generelle Variabilität der Sedimentherkunft lässt sich in den Bohrkernsedimenten nicht so deutlich nachzeichnen. Die mineralogisch-sedimentologischen Eigenschaften der erbohrten klastischen Sedimente zeugen zwar von zwischenzeitlichen Änderungen bei der Sedimentherkunft, diese sind jedoch nicht so deutlich ausgeprägt, wie es die Quellsignale in den Oberflächensedimenten vermuten lassen. Ein Grund dafür scheint die starke Vermischung unterschiedlichster Sedimente während des Transportes zu sein. Die Kombination der Korngrößenergebnisse mit den Befunden der Gesamt- und Schwermineralogie deuten darauf hin, dass es zwischenzeitlich eine Phase mit überwiegend äolischen Prozessen gegeben hat, die mit einem Sedimenteintrag aus dem westlichen Bei Shan in Verbindung stehen. Neben der Zunahme ultrastabiler Schwerminerale wie Zirkon und Granat und der Abnahme opaker Schwerminerale, weisen vor allem die heutigen Verhältnisse darauf hin. Der Vergleich der traditionellen Schwermineralanalyse mit der Computer-Controlled-Scanning-Electron-Microscopy (kurz: CCSEM), die eine automatisierte Partikelauswertung der Proben ermöglicht, zeigt den deutlichen Vorteil der modernen Analysemethode. Neben einem zeitlichen Vorteil, den man durch die automatisierte Abarbeitung der vorbereiteten Proben erlangen kann, steht vor allem die deutlich größere statistische Signifikanz des Ergebnisses im Vordergrund. Zudem können mit dieser Methode auch chemische Varietäten einiger Schwerminerale bestimmt werden, die eine noch feinere Klassifizierung und sicherere Aussagen zu einer möglichen Sedimentherkunft ermöglichen. Damit ergeben sich außerdem verbesserte Aussagen zu Zusammensetzungen und Entstehungsprozessen der abgelagerten Sedimente. Die Studie verdeutlicht, dass die Sedimentherkunft innerhalb des Untersuchungsgebietes sowie die ablaufenden Prozesse zum Teil stark von lokalen Gegebenheiten abhängen. Die Heterogenität der Geologie und die Größe des Einzugsgebietes sowie die daraus resultierende Komplexität der Sedimentgenese, machen exakte Zuordnungen zu klar definierten Sedimentquellen sehr schwer. Dennoch zeigen die Ergebnisse, dass die Sedimentzufuhr in das Ejina-Becken in erster Linie durch fluviale klastische Sedimente des Heihe aus dem Qilian Shan erfolgt sein muss. Die Untersuchungsergebnisse zeigen jedoch ebenso die Notwendigkeit einer ergänzenden Bearbeitung angrenzender Untersuchungsgebiete, wie beispielsweise den Gobi-Altai im Norden oder den Beishan im Westen, sowie die Verdichtung der Oberflächenbeprobung zur feineren Auflösung von lokalen Sedimentquellen.