Universität Stuttgart
Permanent URI for this communityhttps://elib.uni-stuttgart.de/handle/11682/1
Browse
58 results
Search Results
Item Open Access Confirmation of siderazot, Fe3N1.33, the only terrestrial nitride mineral(2021) Bette, Sebastian; Theye, Thomas; Bernhardt, Heinz-Jürgen; Clark, William P.; Niewa, RainerSiderazot, the only terrestrial nitride mineral, was reported only once in 1876 to occur as coating on volcanic rocks in a fumarolic environment from Mt. Etna and, to date, has been neither confirmed nor structurally characterized. We have studied the holotype sample from the Natural History Museum, London, UK, originally collected by O. Silvestri in 1874, and present siderazot with epsilon-Fe3N-type crystal structure and composition of Fe3N1.33(7) according to crystal structure Rietveld refinements, in good agreement with electron microprobe analyses. Crystal structure data, chemical composition, and Raman and reflectance measurements are reported. Possible formation conditions are derived from composition and phase stability data according to synthetic samples.Item Open Access Using GRACE data to study the impact of snow and rainfall on terrestrial water storage in Northeast China(2020) Qian, An; Yi, Shuang; Chang, Le; Sun, Guangtong; Liu, XiaoyangWater resources are important for agricultural, industrial, and urban development. In this paper, we analyzed the influence of rainfall and snowfall on variations in terrestrial water storage (TWS) in Northeast China from Gravity Recovery and Climate Experiment (GRACE) gravity satellite data, GlobSnow snow water equivalent product, and ERA5-land monthly total precipitation, snowfall, and snow depth data. This study revealed the main composition and variation characteristics of TWS in Northeast China. We found that GRACE provided an effective method for monitoring large areas of stable seasonal snow cover and variations in TWS in Northeast China at both seasonal and interannual scales. On the seasonal scale, although summer rainfall was 10 times greater than winter snowfall, the terrestrial water storage in Northeast China peaked in winter, and summer rainfall brought about only a sub-peak, 1 month later than the maximum rainfall. On the interannual scale, TWS in Northeast China was controlled by rainfall. The correlation analysis results revealed that the annual fluctuations of TWS and rainfall in Northeast China appear to be influenced by ENSO (EI Niño-Southern Oscillation) events with a lag of 2-3 years. In addition, this study proposed a reconstruction model for the interannual variation in TWS in Northeast China from 2003 to 2016 on the basis of the contemporary terrestrial water storage and rainfall data.Item Open Access Editorial for PFG issue 5/2023(2023) Gerke, Markus; Cramer, MichaelItem Open Access Forearc tectonics and volcanism during the Devonian-Carboniferous evolution of the North Patagonian segment, southern Chile (41,3°S)(2022) Palape, Camilo; Quezada, Paulo; Bastías, Joaquin; Hervé, Francisco; Reyes, Tommy; Veas, Marta; Vildoso, Francisca; Calderón, Mauricio; Theye, Thomas; Fuentes, Francisco; Chiaradia, MassimoLate Paleozoic to early Mesozoic subduction complexes formed during the evolution of southwestern Gondwana and extensively crop out along the Chilean continental margin. Recent findings in northern Patagonia (40°-43°S) revealed that accretionary processes were active since the Devonian when enhanced lithosphere stretching in the forearc led to the formation of Chaitenia island arc. The extension in the crust consecutively developed a backarc basin, which culminated during a compressive episode that re-amalgamated the Chaitenia island arc with the margin. This episode produced intermediate grade metamorphism in the sedimentary rocks that were formed throughout the extension. To constrain the tectonic evolution of these processes, we combined petrology, structural analysis, whole-rock geochemical, and whole-rock isotopic tracing (Sr-Nd-Pb) data along with thermodynamic modelling. Two petro-tectonic domains are here defined. The Western Coastal Range Domain is composed of Carboniferous to Permian metapsammopelitic rocks, which are mainly schists with a metasedimentary Carboniferous protolith exhibiting a penetrative northeast to southwest dipping main foliation associated with basal accretion. The Eastern Coastal Range Domain is comprised by garnet micaschists, metabasalts, metarhyolites, and metasandstones. This unit is folded by three ductile structures: The first is related to rootless isoclinal folds, the second is associated with kilometric scale west-verging tight folds, and the third is associated with west-verging cylindrical folds. The volcanic rocks of this domain are comprised by middle Devonian alkaline metarhyolites and metabasalts with enriched-MORB and normal-MORB affinities. Trace element composition suggests that the metabasalts formed through shallow melting in an extensional setting over a supra-subduction zone. Nd and Pb isotope data point to a mantle source change for the basaltic melts from an EM1-like to a DM-like and are interpreted to reflect the embryonic to mature evolution of the early Devonian to Carboniferous backarc system. The calculated P-T evolution of the garnet micaschists follows: 1) a clockwise IP-IT prograde Barrovian path, 2) an isobaric thermal increase at ∼7 kbar and 540°C, and 3) an adiabatic decompression. Finally, after the metamorphism, these rocks were uplifted by thrusting processes that probably occurred during the late Permian.Item Open Access Modeling of evaporation-driven multiple salt precipitation in porous media with a real field application(2020) Mejri, Emna; Helmig, Rainer; Bouhlila, RachidaSoil and groundwater salinization are very important environmental issues of global concern. They threaten mainly the arid and semiarid regions characterized by dry climate conditions and an increase of irrigation practices. Among these regions, the south of Tunisia is considered, on the one hand, to be a salt-affected zone facing a twofold problem: The scarcity of water resources and the degradation of their quality due to the overexploitation of the aquifers for irrigation needs. On the other hand, this Tunisian landform is the only adequate area for planting date palm trees which provide the country with the first and most important exportation product. In order to maintain the existence of these oases and develop the date production, a good understanding of the salinization problem threatening this region, and the ability to predict its distribution and evolution, should not be underestimated. The work presented in this paper deals with the Oasis of Segdoud in southern Tunisia, with the objective of modeling the evaporation-driven salt precipitation processes at the soil profile scale and under real climatic conditions. The model used is based on the one developed and presented in a previous work. In order to fulfil the real field conditions, a further extension of the geochemical system of the existing model was required. The precipitated salts considered in this work were halite (NaCl), gypsum (CaSO4) and thenardite (Na2SO4). The extended model reproduces very well the same tendencies of the physico-chemical processes of the natural system in terms of the spatio-temporal distribution and evolution of the evaporation and multiple-salt precipitation. It sheds new lights on the simulation of sequences of salt precipitation in arid regions. The simulation results provide an analysis of the influence of salt precipitation on hydrodynamic properties of the porous medium (porosity and permeability). Moreover, the sensitivity analysis done here reveals the influence of the water table level on the evaporation rate.Item Open Access Seasonal dynamics of gaseous CO2 concentrations in a karst cave correspond with aqueous concentrations in a stagnant water column(2023) Class, Holger; Keim, Leon; Schirmer, Larissa; Strauch, Bettina; Wendel, Kai; Zimmer, MartinDissolved CO2 in karst water is the key driving force of karstification. Replenishment of CO2 concentrations in karst water occurs by meteoric water that percolates through the vadose zone, where CO2 produced from microbial activity is dissolved. CO2 can thus be transported with the percolating water or in the gas phase due to ventilation in karst systems. We measured seasonally fluctuating CO2 concentrations in the air of a karst cave and their influence on aqueous CO2 concentrations in different depths of a stagnant water column. The observed data were compared to numerical simulations. The data give evidence that density-driven enhanced dissolution of gaseous CO2 at the karst water table is the driving force for a fast increase of aqueous CO2 during periods of high gaseous concentrations in the cave, whereas during periods of lower gaseous concentrations, the decline of aqueous CO2 is limited to shallow water depths in the order of 1 m. This is significant because density-driven CO2 dissolution has not been previously considered relevant for karst hydrology in the literature. Attempts at reproducing the measured aqueous CO2 concentrations with numerical modeling revealed challenges related to computational demands, discretization, and the high sensitivity of the processes to tiny density gradients.Item Open Access Editorial - rapid, reproducible, and robust environmental modeling for decision support : worked examples and open-source software tools(2023) White, Jeremy T.; Fienen, Michael N.; Moore, Catherine R.; Guthke, AnneliItem Open Access Assessment of uncertainties in a complex modeling chain for predicting reservoir sedimentation under changing climate(2023) Pesci, María Herminia; Mouris, Kilian; Haun, Stefan; Förster, KristianLong-term predictions of reservoir sedimentation require an objective consideration of the preceding catchment processes. In this study, we apply a complex modeling chain to predict sedimentation processes in the Banja reservoir (Albania). The modeling chain consists of the water balance model WaSiM, the soil erosion and sediment transport model combination RUSLE-SEDD, and the 3d hydro-morphodynamic reservoir model SSIIM2 to accurately represent all relevant physical processes. Furthermore, an ensemble of climate models is used to analyze future scenarios. Although the capabilities of each model enable us to obtain satisfying results, the propagation of uncertainties in the modeling chain cannot be neglected. Hence, approximate model parameter uncertainties are quantified with the First-Order Second-Moment (FOSM) method. Another source of uncertainty for long-term predictions is the spread of climate projections. Thus, we compared both sources of uncertainties and found that the uncertainties generated by climate projections are 408% (for runoff), 539% (for sediment yield), and 272% (for bed elevation in the reservoir) larger than the model parameter uncertainties. We conclude that (i) FOSM is a suitable method for quantifying approximate parameter uncertainties in a complex modeling chain, (ii) the model parameter uncertainties are smaller than the spread of climate projections, and (iii) these uncertainties are of the same order of magnitude as the change signal for the investigated low-emission scenario. Thus, the proposed method might support modelers to communicate different sources of uncertainty in complex modeling chains, including climate impact models.Item Open Access Pressure management via brine extraction in geological CO2 storage : adaptive optimization strategies under poorly characterized reservoir conditions(2019) González-Nicolás, Ana; Cihan, Abdullah; Petrusak, Robin; Zhou, Quanlin; Trautz, Robert; Godec, Michael; Birkholzer, Jens T.Industrial-scale injection of CO2 into the subsurface increases the fluid pressure in the reservoir, which if not properly controlled can potentially lead to geomechanical damage (i.e., fracturing of the caprock or reactivation of faults) and subsequent CO2 leakage. Brine extraction is one approach for managing formation pressure, effective stress, and plume movement in response to CO2 injection. The management of the extracted brine can be expensive (i.e., due to transportation, treatment, disposal, or re-injection), with added cost to the carbon capture and sequestration (CCS); thus, minimizing the volume of extraction brine is of great importance to ensure that the economics of CCS are favorable. The main objective of this study is to demonstrate the use of adaptive optimization methods in the planning of brine extraction and to investigate how the quality of initial site characterization data and the use of newly acquired monitoring data (e.g. pressure at observation wells) impact the optimization performance. We apply an adaptive management approach that integrates monitoring, calibration, and optimization of brine extraction rates to achieve pre-defined pressure constraints. Our results show that reservoir pressure management can be extremely benefited by early and high frequency pressure monitoring during early injection times, especially for poor initial reservoir characterization. Low frequencies of model calibration and optimization with monitoring data may lead to optimization problems, because either pressure buildup constraints are violated or excessively high extraction rates are proposed. The adaptive pressure management approach may constitute an effective tool to manage pressure buildup under uncertain reservoir conditions by minimizing the volumes of extracted brine while controlling pressure buildup.Item Open Access Multivariate motion patterns and applications to rainfall radar data(2023) Fischer, Svenja; Oesting, Marco; Schnurr, AlexanderThe classification of movement in space is one of the key tasks in environmental science. Various geospatial data such as rainfall or other weather data, data on animal movement or landslide data require a quantitative analysis of the probable movement in space to obtain information on potential risks, ecological developments or changes in future. Usually, machine-learning tools are applied for this task, as these approaches are able to classify large amounts of data. Yet, machine-learning approaches also have some drawbacks, e.g. the often required large training sets and the fact that the algorithms are often hard to interpret. We propose a classification approach for spatial data based on ordinal patterns. Ordinal patterns have the advantage that they are easily applicable, even to small data sets, are robust in the presence of certain changes in the time series and deliver interpretative results. They therefore do not only offer an alternative to machine-learning in the case of small data sets but might also be used in pre-processing for a meaningful feature selection. In this work, we introduce the basic concept of multivariate ordinal patterns and the corresponding limit theorem. A simulation study based on bootstrap demonstrates the validity of the results. The approach is then applied to two real-life data sets, namely rainfall radar data and the movement of a leopard. Both applications emphasize the meaningfulness of the approach. Clearly, certain patterns related to the atmosphere and environment occur significantly often, indicating a strong dependence of the movement on the environment.