Refine
Has Fulltext
- yes (36) (remove)
Year of publication
- 2019 (36) (remove)
Document Type
- Doctoral Thesis (18)
- Postprint (15)
- Conference Proceeding (1)
- Habilitation Thesis (1)
- Master's Thesis (1)
Is part of the Bibliography
- yes (36)
Keywords
- Anden (2)
- Andes (2)
- numerische Modellierung (2)
- Abschiebungshorizonte (1)
- Accuracy Asseessment (1)
- Alterationsgeochemie (1)
- Angewandte Geophysik (1)
- Applied Geophysics (1)
- Arctic tundra (1)
- Argentina (1)
Institute
- Institut für Geowissenschaften (36) (remove)
Interactions and feedbacks between tectonics, climate, and upper plate architecture control basin geometry, relief, and depositional systems. The Andes is part of a longlived continental margin characterized by multiple tectonic cycles which have strongly modified the Andean upper plate architecture. In the Andean retroarc, spatiotemporal variations in the structure of the upper plate and tectonic regimes have resulted in marked along-strike variations in basin geometry, stratigraphy, deformational style, and mountain belt morphology. These along-strike variations include high-elevation plateaus (Altiplano and Puna) associated with a thin-skin fold-and-thrust-belt and thick-skin deformation in broken foreland basins such as the Santa Barbara system and the Sierras Pampeanas. At the confluence of the Puna Plateau, the Santa Barbara system and the Sierras Pampeanas, major along-strike changes in upper plate architecture, mountain belt morphology, basement exhumation, and deformation style can be recognized. I have used a source to sink approach to unravel the spatiotemporal tectonic evolution of the Andean retroarc between 26 and 28°S. I obtained a large low-temperature thermochronology data set from basement units which includes apatite fission track, apatite U-Th-Sm/He, and zircon U-Th/He (ZHe) cooling ages. Stratigraphic descriptions of Miocene units were temporally constrained by U-Pb LA-ICP-MS zircon ages from interbedded pyroclastic material.
Modeled ZHe ages suggest that the basement of the study area was exhumed during the Famatinian orogeny (550-450 Ma), followed by a period of relative tectonic quiescence during the Paleozoic and the Triassic. The basement experienced horst exhumation during the Cretaceous development of the Salta rift. After initial exhumation, deposition of thick Cretaceous syn-rift strata caused reheating of several basement blocks within the Santa Barbara system. During the Eocene-Oligocene, the Andean compressional setting was responsible for the exhumation of several disconnected basement blocks. These exhumed blocks were separated by areas of low relief, in which humid climate and low erosion rates facilitated the development of etchplains on the crystalline basement. The exhumed basement blocks formed an Eocene to Oligocene broken foreland basin in the back-bulge depozone of the Andean foreland. During the Early Miocene, foreland basin strata filled up the preexisting Paleogene topography. The basement blocks in lower relief positions were reheated; associated geothermal gradients were higher than 25°C/km. Miocene volcanism was responsible for lateral variations on the amount of reheating along the Campo-Arenal basin. Around 12 Ma, a new deformational phase modified the drainage network and fragmented the lacustrine system. As deformation and rock uplift continued, the easily eroded sedimentary cover was efficiently removed and reworked by an ephemeral fluvial system, preventing the development of significant relief. After ~6 Ma, the low erodibility of the basement blocks which began to be exposed caused relief increase, leading to the development of stable fluvial systems. Progressive relief development modified atmospheric circulation, creating a rainfall gradient. After 3 Ma, orographic rainfall and high relief lead to the development of proximal fluvial-gravitational depositional systems in the surrounding basins.
Partial melting is a first order process for the chemical differentiation of the crust (Vielzeuf et al., 1990). Redistribution of chemical elements during melt generation crucially influences the composition of the lower and upper crust and provides a mechanism to concentrate and transport chemical elements that may also be of economic interest. Understanding of the diverse processes and their controlling factors is therefore not only of scientific interest but also of high economic importance to cover the demand for rare metals.
The redistribution of major and trace elements during partial melting represents a central step for the understanding how granite-bound mineralization develops (Hedenquist and Lowenstern, 1994). The partial melt generation and mobilization of ore elements (e.g. Sn, W, Nb, Ta) into the melt depends on the composition of the sedimentary source and melting conditions. Distinct source rocks have different compositions reflecting their deposition and alteration histories. This specific chemical “memory” results in different mineral assemblages and melting reactions for different protolith compositions during prograde metamorphism (Brown and Fyfe, 1970; Thompson, 1982; Vielzeuf and Holloway, 1988). These factors do not only exert an important influence on the distribution of chemical elements during melt generation, they also influence the volume of melt that is produced, extraction of the melt from its source, and its ascent through the crust (Le Breton and Thompson, 1988). On a larger scale, protolith distribution and chemical alteration (weathering), prograde metamorphism with partial melting, melt extraction, and granite emplacement are ultimately depending on a (plate-)tectonic control (Romer and Kroner, 2016). Comprehension of the individual stages and their interaction is crucial in understanding how granite-related mineralization forms, thereby allowing estimation of the mineralization potential of certain areas. Partial melting also influences the isotope systematics of melt and restite. Radiogenic and stable isotopes of magmatic rocks are commonly used to trace back the source of intrusions or to quantify mixing of magmas from different sources with distinct isotopic signatures (DePaolo and Wasserburg, 1979; Lesher, 1990; Chappell, 1996). These applications are based on the fundamental requirement that the isotopic signature in the melt reflects that of the bulk source from which it is derived. Different minerals in a protolith may have isotopic compositions of radiogenic isotopes that deviate from their whole rock signature (Ayres and Harris, 1997; Knesel and Davidson, 2002). In particular, old minerals with a distinct parent-to-daughter (P/D) ratio are expected to have a specific radiogenic isotope signature. As the partial melting reaction only involves selective phases in a protolith, the isotopic signature of the melt reflects that of the minerals involved in the melting reaction and, therefore, should be different from the bulk source signature. Similar considerations hold true for stable isotopes.
We measure valence-to-core x-ray emission spectra of compressed crystalline GeO₂ up to 56 GPa and of amorphous GeO₂ up to 100 GPa. In a novel approach, we extract the Ge coordination number and mean Ge-O distances from the emission energy and the intensity of the Kβ'' emission line. The spectra of high-pressure polymorphs are calculated using the Bethe-Salpeter equation. Trends observed in the experimental and calculated spectra are found to match only when utilizing an octahedral model. The results reveal persistent octahedral Ge coordination with increasing distortion, similar to the compaction mechanism in the sequence of octahedrally coordinated crystalline GeO₂ high-pressure polymorphs.
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.
Hydrometeorological hazards caused losses of approximately 110 billion U.S. Dollars in 2016 worldwide. Current damage estimations do not consider the uncertainties in a comprehensive way, and they are not consistent between spatial scales. Aggregated land use data are used at larger spatial scales, although detailed exposure data at the object level, such as openstreetmap.org, is becoming increasingly available across the globe.We present a probabilistic approach for object-based damage estimation which represents uncertainties and is fully scalable in space. The approach is applied and validated to company damage from the flood of 2013 in Germany. Damage estimates are more accurate compared to damage models using land use data, and the estimation works reliably at all spatial scales. Therefore, it can as well be used for pre-event analysis and risk assessments. This method takes hydrometeorological damage estimation and risk assessments to the next level, making damage estimates and their uncertainties fully scalable in space, from object to country level, and enabling the exploitation of new exposure data.
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.
The interactions between atmosphere and steep topography in the eastern south–central Andes result in complex relations with inhomogenous rainfall distributions. The atmospheric conditions leading to deep convection and extreme rainfall and their spatial patterns—both at the valley and mountain-belt scales—are not well understood. In this study, we aim to identify the dominant atmospheric conditions and their spatial variability by analyzing the convective available potential energy (CAPE) and dew-point temperature (Td). We explain the crucial effect of temperature on extreme rainfall generation along the steep climatic and topographic gradients in the NW Argentine Andes stretching from the low-elevation eastern foreland to the high-elevation central Andean Plateau in the west. Our analysis relies on version 2.0 of the ECMWF’s (European Centre for Medium-RangeWeather Forecasts) Re-Analysis (ERA-interim) data and TRMM (Tropical Rainfall Measuring Mission) data. We make the following key observations: First, we observe distinctive gradients along and across strike of the Andes in dew-point temperature and CAPE that both control rainfall distributions. Second, we identify a nonlinear correlation between rainfall and a combination of dew-point temperature and CAPE through a multivariable regression analysis. The correlation changes in space along the climatic and topographic gradients and helps to explain controlling factors for extreme-rainfall generation. Third, we observe more contribution (or higher importance) of Td in the tropical low-elevation foreland and intermediate-elevation areas as compared to the high-elevation central Andean Plateau for 90th percentile rainfall. In contrast, we observe a higher contribution of CAPE in the intermediate-elevation area between low and high elevation, especially in the transition zone between the tropical and subtropical areas for the 90th percentile rainfall. Fourth, we find that the parameters of the multivariable regression using CAPE and Td can explain rainfall with higher statistical significance for the 90th percentile compared to lower rainfall percentiles. Based on our results, the spatial pattern of rainfall-extreme events during the past ∼16 years can be described by a combination of dew-point temperature and CAPE in the south–central Andes.
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.
Carbonate-rich silicate and carbonate melts play a crucial role in deep Earth magmatic processes and their melt structure is a key parameter, as it controls physical and chemical properties. Carbonate-rich melts can be strongly enriched in geochemically important trace elements. The structural incorporation mechanisms of these elements are difficult to study because such melts generally cannot be quenched to glasses, which are usually employed for structural investigations. This thesis investigates the influence of CO2 on the local environments of trace elements contained in silicate glasses with variable CO2 concentrations as well as in silicate and carbonate melts. The compositions studied include sodium-rich peralkaline silicate melts and glasses and carbonate melts similar to those occurring naturally at Oldoinyo Lengai volcano, Tanzania.
The local environments of the three elements yttrium (Y), lanthanum (La) and strontium (Sr) were investigated in synthesized glasses and melts using X-ray absorption fine structure (XAFS) spectroscopy. Especially extended X-ray absorption fine structure spectroscopy (EXAFS) provides element specific information on local structure, such as bond lengths, coordination numbers and the degree of disorder. To cope with the enhanced structural disorder present in glasses and melts, EXAFS analysis was based on fitting approaches using an asymmetric distribution function as well as a correlation model according to bond valence theory. Firstly, silicate glasses quenched from high pressure/temperature melts with up to 7.6 wt % CO2 were investigated. In strongly and extremely peralkaline glasses the local structure of Y is unaffected by the CO2 content (with oxygen bond lengths of ~ 2.29 Å). Contrary, the bond lengths for Sr-O and La-O increase with increasing CO2 content in the strongly peralkaline glasses from ~ 2.53 to ~ 2.57 Å and from ~ 2.52 to ~ 2.54 Å, respectively, while they remain constant in extremely peralkaline glasses (at ~ 2.55 Å and 2.54 Å, respectively). Furthermore, silicate and unquenchable carbonate melts were investigated in-situ at high pressure/temperature conditions (2.2 to 2.6 GPa, 1200 to 1500 °C) using a Paris-Edinburgh press. A novel design of the pressure medium assembly for this press was developed, which features increased mechanical stability as well as enhanced transmittance at relevant energies to allow for low content element EXAFS in transmission. Compared to glasses the bond lengths of Y-O, La-O and Sr-O are elongated by up to + 3 % in the melt and exhibit higher asymmetric pair distributions. For all investigated silicate melt compositions Y-O bond lengths were found constant at ~ 2.37 Å, while in the carbonate melt the Y-O length increases slightly to 2.41 Å. The La-O bond lengths in turn, increase systematically over the whole silicate – carbonate melt joint from 2.55 to 2.60 Å. Sr-O bond lengths in melts increase from ~ 2.60 to 2.64 Å from pure silicate to silicate-bearing carbonate composition with constant elevated bond length within the carbonate region.
For comparison and deeper insight, glass and melt structures of Y and Sr bearing sodium-rich silicate to carbonate compositions were simulated in an explorative ab initio molecular dynamics (MD) study. The simulations confirm observed patterns of CO2-dependent local changes around Y and Sr and additionally provide further insights into detailed incorporation mechanisms of the trace elements and CO2. Principle findings include that in sodium-rich silicate compositions carbon either is mainly incorporated as a free carbonate-group or shares one oxygen with a network former (Si or [4]Al) to form a non-bridging carbonate. Of minor importance are bridging carbonates between two network formers. Here, a clear preference for two [4]Al as adjacent network formers occurs, compared to what a statistical distribution would suggest. In C-bearing silicate melts minor amounts of molecular CO2 are present, which is almost totally dissolved as carbonate in the quenched glasses.
The combination of experiment and simulation provides extraordinary insights into glass and melt structures. The new data is interpreted on the basis of bond valence theory and is used to deduce potential mechanisms for structural incorporation of investigated elements, which allow for prediction on their partitioning behavior in natural melts. Furthermore, it provides unique insights into the dissolution mechanisms of CO2 in silicate melts and into the carbonate melt structure. For the latter, a structural model is suggested, which is based on planar CO3-groups linking 7- to 9-fold cation polyhedra, in accordance to structural units as found in the Na-Ca carbonate nyerereite. Ultimately, the outcome of this study contributes to rationalize the unique physical properties and geological phenomena related to carbonated silicate-carbonate melts.
The semiarid northeast of Brazil is one of the most densely populated dryland regions in the world and recurrently affected by severe droughts. Thus, reliable seasonal forecasts of streamflow and reservoir storage are of high value for water managers. Such forecasts can be generated by applying either hydrological models representing underlying processes or statistical relationships exploiting correlations among meteorological and hydrological variables. This work evaluates and compares the performances of seasonal reservoir storage forecasts derived by a process-based hydrological model and a statistical approach.
Driven by observations, both models achieve similar simulation accuracies. In a hindcast experiment, however, the accuracy of estimating regional reservoir storages was considerably lower using the process-based hydrological model, whereas the resolution and reliability of drought event predictions were similar by both approaches. Further investigations regarding the deficiencies of the process-based model revealed a significant influence of antecedent wetness conditions and a higher sensitivity of model prediction performance to rainfall forecast quality.
Within the scope of this study, the statistical model proved to be the more straightforward approach for predictions of reservoir level and drought events at regionally and monthly aggregated scales. However, for forecasts at finer scales of space and time or for the investigation of underlying processes, the costly initialisation and application of a process-based model can be worthwhile. Furthermore, the application of innovative data products, such as remote sensing data, and operational model correction methods, like data assimilation, may allow for an enhanced exploitation of the advanced capabilities of process-based hydrological models.