Institut für Erd- und Umweltwissenschaften
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In this study, we analyze interactions in lake and lake catchment systems of a continuous permafrost area. We assessed colored dissolved organic matter (CDOM) absorption at 440 nm (a(440)(CDOM)) and absorption slope (S300-500) in lakes using field sampling and optical remote sensing data for an area of 350 km(2) in Central Yamal, Siberia. Applying a CDOM algorithm (ratio of green and red band reflectance) for two high spatial resolution multispectral GeoEye-1 and Worldview-2 satellite images, we were able to extrapolate the a()(CDOM) data from 18 lakes sampled in the field to 356 lakes in the study area (model R-2 = 0.79). Values of a(440)(CDOM) in 356 lakes varied from 0.48 to 8.35 m(-1) with a median of 1.43 m(-1). This a()(CDOM) dataset was used to relate lake CDOM to 17 lake and lake catchment parameters derived from optical and radar remote sensing data and from digital elevation model analysis in order to establish the parameters controlling CDOM in lakes on the Yamal Peninsula. Regression tree model and boosted regression tree analysis showed that the activity of cryogenic processes (thermocirques) in the lake shores and lake water level were the two most important controls, explaining 48.4% and 28.4% of lake CDOM, respectively (R-2 = 0.61). Activation of thermocirques led to a large input of terrestrial organic matter and sediments from catchments and thawed permafrost to lakes (n = 15, mean a(440)(CDOM) = 5.3 m(-1)). Large lakes on the floodplain with a connection to Mordy-Yakha River received more CDOM (n = 7, mean a(440)(CDOM) = 3.8 m(-1)) compared to lakes located on higher terraces.
Changes in species' distributions are classically projected based on their climate envelopes. For Siberian forests, which have a tremendous significance for vegetation-climate feedbacks, this implies future shifts of each of the forest-forming larch (Larix) species to the north-east. However, in addition to abiotic factors, reliable projections must assess the role of historical biogeography and biotic interactions. Here, we use sedimentary ancient DNA and individual-based modelling to investigate the distribution of larch species and mitochondrial haplotypes through space and time across the treeline ecotone on the southern Taymyr peninsula, which at the same time presents a boundary area of two larch species. We find spatial and temporal patterns, which suggest that forest density is the most influential driver determining the precise distribution of species and mitochondrial haplotypes. This suggests a strong influence of competition on the species' range shifts. These findings imply possible climate change outcomes that are directly opposed to projections based purely on climate envelopes. Investigations of such fine-scale processes of biodiversity change through time are possible using paleoenvironmental DNA, which is available much more readily than visible fossils and can provide information at a level of resolution that is not reached in classical palaeoecology.
Dating growth strata and basin fill by combining 26Al/10Be burial dating and magnetostratigraphy
(2018)
Cosmogenic burial dating enables dating of coarse-grained, Pliocene-Pleistocene sedimentary units that are typically difficult to date with traditional methods, such as magnetostratigraphy. In the actively deforming western Tarim Basin in NW China, Pliocene-Pleistocene conglomerates were dated at eight sites, integrating Al-26/Be-10 burial dating with previously published magnetostratigraphic sections. These samples were collected from growth strata on the flanks of growing folds and from sedimentary units beneath active faults to place timing constraints on the initiation of deformation of structures within the basin and on shortening rates on active faults. These new basin-fill and growthstrata ages document the late Neogene and Quaternary growth of the Pamir and Tian Shan orogens between >5 and 1 Ma and delineate the eastward propagation of deformation at rates up to 115 km/m.y. and basinward growth of both mountain belts at rates up to 12 km/m.y.
Ferruginous conditions were a prominent feature of the oceans throughout the Precambrian Eons and thus throughout much of Earth’s history. Organic matter mineralization and diagenesis within the ferruginous sediments that deposited from Earth’s early oceans likely played a key role in global biogeochemical cycling. Knowledge of organic matter mineralization in ferruginous sediments, however, remains almost entirely conceptual, as modern analogue environments are extremely rare and largely unstudied, to date. Lake Towuti on the island of Sulawesi, Indonesia is such an analogue environment and the purpose of this PhD project was to investigate the rates and pathways of organic matter mineralization in its ferruginous sediments.
Lake Towuti is the largest tectonic lake in Southeast Asia and is hosted in the mafic and ultramafic rocks of the East Sulawesi Ophiolite. It has a maximum water depth of 203 m and is weakly thermally stratified. A well-oygenated surface layer extends to 70 m depth, while waters below 130 m are persistently anoxic. Intensive weathering of the ultramafic catchment feeds the lake with large amounts of iron(oxy)hydroxides while the runoff contains only little sulfate, leading to sulfate-poor (< 20 µM) lake water and anoxic ferruginous conditions below 130 m. Such conditions are analogous to the ferruginous water columns that persisted throughout much of the Archean and Proterozoic eons. Short (< 35 cm) sediment cores were collected from different water depths corresponding to different bottom water redox conditions. Also, a drilling campaign of the International Continental Scientific Drilling Program (ICDP) retrieved a 114 m long sediment core dedicated for geomicrobiological investigations from a water depth of 153 m, well below the depth of oxygen penetration at the time of sampling. Samples collected from these sediment cores form the fundament of this thesis and were used to perform a suite of biogeochemical and microbiological analyses.
Geomirobiological investigations depend on uncontaminated samples. However, exploration of subsurface environments relies on drilling, which requires the use of a drilling fluid. Drilling fluid infiltration during drilling can not be avoided. Thus, in order to trace contamination of the sediment core and to identify uncontaminated samples for further analyses a simple and inexpensive technique for assessing contamination during drilling operations was developed and applied during the ICDP drilling campaign. This approach uses an aqeous fluorescent pigment dispersion commonly used in the paint industry as a particulate tracer. It has the same physical properties as conventionally used particulate tracers. However, the price is nearly four orders of magnitude lower solving the main problem of particulate tracer approaches. The approach requires only a minimum of equipment and allows for a rapid contamination assessment potentially even directly on site, while the senstitivity is in the range of already established approaches. Contaminated samples in the drill core were identified and not included for further geomicrobiological investigations.
Biogeochemical analyses of short sediment cores showed that Lake Towutis sediments are strongly depleted in electron acceptors commonly used in microbial organic matter mineralization (i.e. oxygen, nitrate, sulfate). Still, the sediments harbor high microbial cell densities, which are a function of redox conditions of Lake Towuti’s bottom water. In shallow water depths bottom water oxygenation leads to a higher input of labile organic matter and electron acceptors like sulfate and iron, which promotes a higher microbial abundance. Microbial analyses showed that a versatile microbial community with a potential to perform metabolisms related to iron and sulfate reduction, fermentation as well as methanogenesis inhabits Lake Towuti’s surface sediments.
Biogeochemical investigations of the upper 12 m of the 114 m sediment core showed that Lake Towuti’s sediment is extremely rich in iron with total concentrations up to 2500 µmol cm-3 (20 wt. %), which makes it the natural sedimentary environment with the highest total iron concentrations studied to date. In the complete or near absence of oxygen, nitrate and sulfate, organic matter mineralization in ferruginous sediments would be expected to proceed anaerobically via the energetically most favorable terminal electron acceptors available - in this case ferric iron. Astonishingly, however, methanogenesis is the dominant (>85 %) organic matter mineralization process in Lake Towuti’s sediment. Reactive ferric iron known to be available for microbial iron reduction is highly abundant throughout the upper 12 m and thus remained stable for at least 60.000 years. The produced methane is not oxidized anaerobically and diffuses out of the sediment into the water column. The proclivity towards methanogenesis, in these very iron-rich modern sediments, implies that methanogenesis may have played a more important role in organic matter mineralization thoughout the Precambrian than previously thought and thus could have been a key contributor to Earth’s early climate dynamics.
Over the whole sequence of the 114 m long sediment core siderites were identified and characterized using high-resolution microscopic and spectroscopic imaging together with microchemical and geochemical analyses. The data show early diagenetic growth of siderite crystals as a response to sedimentary organic matter mineralization. Microchemical zoning was identified in all siderite crystals. Siderite thus likely forms during diagenesis through growth on primary existing phases and the mineralogical and chemical features of these siderites are a function of changes in redox conditions of the pore water and sediment over time. Identification of microchemical zoning in ancient siderites deposited in the Precambrian may thus also be used to infer siderite growth histories in ancient sedimentary rocks including sedimentary iron formations.
RainNet v1.0
(2020)
In this study, we present RainNet, a deep convolutional neural network for radar-based precipitation nowcasting. Its design was inspired by the U-Net and SegNet families of deep learning models, which were originally designed for binary segmentation tasks. RainNet was trained to predict continuous precipitation intensities at a lead time of 5min, using several years of quality-controlled weather radar composites provided by the German Weather Service (DWD). That data set covers Germany with a spatial domain of 900km × 900km and has a resolution of 1km in space and 5min in time. Independent verification experiments were carried out on 11 summer precipitation events from 2016 to 2017. In order to achieve a lead time of 1h, a recursive approach was implemented by using RainNet predictions at 5min lead times as model inputs for longer lead times. In the verification experiments, trivial Eulerian persistence and a conventional model based on optical flow served as benchmarks. The latter is available in the rainymotion library and had previously been shown to outperform DWD's operational nowcasting model for the same set of verification events.
RainNet significantly outperforms the benchmark models at all lead times up to 60min for the routine verification metrics mean absolute error (MAE) and the critical success index (CSI) at intensity thresholds of 0.125, 1, and 5mm h⁻¹. However, rainymotion turned out to be superior in predicting the exceedance of higher intensity thresholds (here 10 and 15mm h⁻¹). The limited ability of RainNet to predict heavy rainfall intensities is an undesirable property which we attribute to a high level of spatial smoothing introduced by the model. At a lead time of 5min, an analysis of power spectral density confirmed a significant loss of spectral power at length scales of 16km and below. Obviously, RainNet had learned an optimal level of smoothing to produce a nowcast at 5min lead time. In that sense, the loss of spectral power at small scales is informative, too, as it reflects the limits of predictability as a function of spatial scale. Beyond the lead time of 5min, however, the increasing level of smoothing is a mere artifact – an analogue to numerical diffusion – that is not a property of RainNet itself but of its recursive application. In the context of early warning, the smoothing is particularly unfavorable since pronounced features of intense precipitation tend to get lost over longer lead times. Hence, we propose several options to address this issue in prospective research, including an adjustment of the loss function for model training, model training for longer lead times, and the prediction of threshold exceedance in terms of a binary segmentation task. Furthermore, we suggest additional input data that could help to better identify situations with imminent precipitation dynamics. The model code, pretrained weights, and training data are provided in open repositories as an input for such future studies.
Hydrometric networks play a vital role in providing information for decision-making in water resource management. They should be set up optimally to provide as much information as possible that is as accurate as possible and, at the same time, be cost-effective. Although the design of hydrometric networks is a well-identified problem in hydrometeorology and has received considerable attention, there is still scope for further advancement. In this study, we use complex network analysis, defined as a collection of nodes interconnected by links, to propose a new measure that identifies critical nodes of station networks. The approach can support the design and redesign of hydrometric station networks. The science of complex networks is a relatively young field and has gained significant momentum over the last few years in different areas such as brain networks, social networks, technological networks, or climate networks. The identification of influential nodes in complex networks is an important field of research. We propose a new node-ranking measure – the weighted degree–betweenness (WDB) measure – to evaluate the importance of nodes in a network. It is compared to previously proposed measures used on synthetic sample networks and then applied to a real-world rain gauge network comprising 1229 stations across Germany to demonstrate its applicability. The proposed measure is evaluated using the decline rate of the network efficiency and the kriging error. The results suggest that WDB effectively quantifies the importance of rain gauges, although the benefits of the method need to be investigated in more detail.
Many institutions struggle to tap into the potential of their large archives of radar reflectivity: these data are often affected by miscalibration, yet the bias is typically unknown and temporally volatile. Still, relative calibration techniques can be used to correct the measurements a posteriori. For that purpose, the usage of spaceborne reflectivity observations from the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) platforms has become increasingly popular: the calibration bias of a ground radar (GR) is estimated from its average reflectivity difference to the spaceborne radar (SR). Recently, Crisologo et al. (2018) introduced a formal procedure to enhance the reliability of such estimates: each match between SR and GR observations is assigned a quality index, and the calibration bias is inferred as a quality-weighted average of the differences between SR and GR. The relevance of quality was exemplified for the Subic S-band radar in the Philippines, which is greatly affected by partial beam blockage.
The present study extends the concept of quality-weighted averaging by accounting for path-integrated attenuation (PIA) in addition to beam blockage. This extension becomes vital for radars that operate at the C or X band. Correspondingly, the study setup includes a C-band radar that substantially overlaps with the S-band radar. Based on the extended quality-weighting approach, we retrieve, for each of the two ground radars, a time series of calibration bias estimates from suitable SR overpasses. As a result of applying these estimates to correct the ground radar observations, the consistency between the ground radars in the region of overlap increased substantially. Furthermore, we investigated if the bias estimates can be interpolated in time, so that ground radar observations can be corrected even in the absence of prompt SR overpasses. We found that a moving average approach was most suitable for that purpose, although limited by the absence of explicit records of radar maintenance operations.
Unterschiedliche Verfahren zur Ermittlung von Georadar-Wellengeschwindigkeiten wurden entwickelt und erfolgreich angewendet. Für die Verfahren wurden statistische Methoden und Schwarmintelligenz-Algorithmen benutzt. Es wurde gezeigt, dass die neuen Verfahren schneller, präziser und besser reproduzierbare Ergebnisse für Georadar-Wellengeschwindigkeit erzielen als herkömmliche Verfahren.
Mit verbesserten Werten der Georadar-Wellengeschwindigkeit lassen sich die verzerrten dreidimensionalen Abbilder der obersten zehn Meter des Untergrundes, welche sich mit Georadar-Daten erzeugen lassen, korrigieren. In diesen korrigierten Abbildern sind dann realistische Tiefen von Schichten oder Objekten im Untergrund besser messbar. Außerdem verbessern präzisere Wellengeschwindigkeiten die Bestimmung von Bodenparametern, wie Wassergehalt oder Tonanteil. Die präsentierten Verfahren erlauben eine quantitative Angabe von Fehlern der bestimmten Wellengeschwindigkeit und der daraus folgenden Tiefen und Bodenparametern im Untergrund. Die Vorteile dieser neu entwickelten Verfahren zur Charakterisierung des Untergrundes der oberen Meter wurde an Feldbeispielen demonstriert.
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.
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.