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We investigate the applicability of the well-known multilevel Monte Carlo (MLMC) method to the class of density-driven flow problems, in particular the problem of salinisation of coastal aquifers. As a test case, we solve the uncertain Henry saltwater intrusion problem. Unknown porosity, permeability and recharge parameters are modelled by using random fields. The classical deterministic Henry problem is non-linear and time-dependent, and can easily take several hours of computing time. Uncertain settings require the solution of multiple realisations of the deterministic problem, and the total computational cost increases drastically. Instead of computing of hundreds random realisations, typically the mean value and the variance are computed. The standard methods such as the Monte Carlo or surrogate-based methods are a good choice, but they compute all stochastic realisations on the same, often, very fine mesh. They also do not balance the stochastic and discretisation errors. These facts motivated us to apply the MLMC method. We demonstrate that by solving the Henry problem on multi-level spatial and temporal meshes, the MLMC method reduces the overall computational and storage costs. To reduce the computing cost further, parallelization is performed in both physical and stochastic spaces. To solve each deterministic scenario, we run the parallel multigrid solver ug4 in a black-box fashion.
Highlights
• We present the first results of a deep learning model based on a convolutional neural network for earthquake magnitude estimation, using HR-GNSS displacement time series.
• The influence of different dataset configurations, such as station numbers, epicentral distances, signal duration, and earthquake size, were analyzed to figure out how the model can be adapted to various scenarios.
• The model was tested using real data from different regions and magnitudes, resulting in the best cases with 0.09 ≤ RMS ≤ 0.33.
Abstract
High-rate Global Navigation Satellite System (HR-GNSS) data can be highly useful for earthquake analysis as it provides continuous high-frequency measurements of ground motion. This data can be used to analyze diverse parameters related to the seismic source and to assess the potential of an earthquake to prompt strong motions at certain distances and even generate tsunamis. In this work, we present the first results of a deep learning model based on a convolutional neural network for earthquake magnitude estimation, using HR-GNSS displacement time series. The influence of different dataset configurations, such as station numbers, epicentral distances, signal duration, and earthquake size, were analyzed to figure out how the model can be adapted to various scenarios. We explored the potential of the model for global application and compared its performance using both synthetic and real data from different seismogenic regions. The performance of our model at this stage was satisfactory in estimating earthquake magnitude from synthetic data with 0.07 ≤ RMS ≤ 0.11. Comparable results were observed in tests using synthetic data from a different region than the training data, with RMS ≤ 0.15. Furthermore, the model was tested using real data from different regions and magnitudes, resulting in the best cases with 0.09 ≤ RMS ≤ 0.33, provided that the data from a particular group of stations had similar epicentral distance constraints to those used during the model training. The robustness of the DL model can be improved to work independently from the window size of the time series and the number of stations, enabling faster estimation by the model using only near-field data. Overall, this study provides insights for the development of future DL approaches for earthquake magnitude estimation with HR-GNSS data, emphasizing the importance of proper handling and careful data selection for further model improvements.
Die Welt im Wasserstress
(2024)
Wie haben sich die Wasserresourcen in den letzten 120 Jahren verändert? Und was passiert, wenn es bis Ende des 21. Jahrhunderts noch einmal zwei Grad wärmer wird als heute? Fragen wie diese beantwortet das globale Wasser-Modell WaterGAP, das maßgeblich vom Institut für Physische Geographie der Goethe-Universität und von der Ruhr-Universität Bochum entwickelt wird. Bislang ließen sich die damit erzeugten Daten nur von Expertinnen und Experten nutzen. Eine neue Web-App ändert das nun. Entwickelt wurde sie von dem französischen Geodaten-Unternehmen Ageoce, das dafür mit der Goethe-Universität kooperierte.
While high-quality climate reconstructions of some past warm periods in the Cenozoic era now exist, the geological processes responsible for driving the observed longterm changes in atmospheric CO2 are not sufficiently well understood. The long-term change in atmospheric CO2 across the Cenozoic has been proposed to be driven by processes such as terrestrial weathering, organic carbon production and burial, reverse weathering, and volcanic degassing. One way of constraining the relative importance of the various driving forces proposed so far is to better understand the degree to which ocean chemistry has changed because the chemistry of seawater responds to geologic processes that drive atmospheric CO2. In addition, knowledge of the concentration of the major elements in seawater is crucial for accurately applying proxies such as those based on the boron isotopic composition and Mg/Ca of marine carbonates (a proxy for palaeo pH/CO2 and palaeotemperature, respectively). Previously reported records of seawater composition are primarily derived from fluid inclusions in marine evaporites; however, the results are sparse due to the limited availability of such deposits. In this thesis, changes in the Eocene seawater chemistry were reconstructed using trace element (elements/Ca) and isotopic (δ26Mg) proxies in a Larger Benthic Foraminifera (LBFs), i.e., Nummulites sp., to constrain the driving processes of long-term changes in seawater chemistry.
To achieve the objective of this thesis, first, a measurement protocol was established using LA-ICPMS to measure the K/Ca ratio simultaneously with other element/calcium ratios, which is challenging due to the interference of ArH+ on K+. Utilising this newly established measurement protocol, laboratory-cultured Operculina ammonoides grown at different seawater calcium concentrations ([Ca2+]), repeated at different temperatures, as well as modern O. ammonoides collected from different regions exhibiting a range of seawater parameters, were investigated. A significant correlation was observed between K/Casw and K/CaLBF, allowing K/CaLBF to potentially be used as a proxy for seawater major ion reconstructions. In addition, modern O. ammonoides demonstrated no significant influence of most seawater parameters (temperature, salinity, pH, or [CO32-]) on K/CaLBF. Modern O.
ammonoides were also assessed for their Mg isotopic composition (δ26Mg), revealing no significant effect of temperature or salinity on δ26MgLBF. Furthermore, the Mg isotopic fractionation in O. ammonoides was found to be close to that of inorganic calcite, indicating minimal vital effects in these large benthic foraminifera.
Operculina ammonoides is the nearest living relative of the abundant Eocene genus Nummulites, enabling the reconstruction of seawater chemistry using the calibration based on O. ammonoides. The trace elemental/calcium proxies, including Na/Ca, K/Ca, and Mg/Ca, as well as the δ26Mg proxy, were investigated in Eocene Nummulites. The result showed that during the Eocene, [Ca2+]sw was 1.6-2 times higher, while [K+]sw was ~2 times lower than the modern seawater composition. Furthermore, [Mg2+]sw decreased from the early Eocene (54.3− +9 7..69 mmol kg-1 at ~55 Ma) to Late Eocene (37.8− +4 4..3 4 mmol kg-1 at ~31 Ma), followed by
an increase toward modern seawater [Mg]. In contrast, the variability in δ26Mgsw values remained within a narrow range of ~0.3 ‰ throughout the Cenozoic. The reconstructed [Ca2+]sw agrees with the suggestion that Cenozoic seawater chemistry changes can be explained via a change in the seafloor spreading rate. When combined with existing records, the observed minimal change in δ26Mgsw with an increase in [Mg2+]sw suggests an additional possible role of a decrease in the formation of authigenic clay minerals coincident with the Cenozoic decline in deep ocean temperature, which is also supported by the increase in the [K+]sw reconstructed here for the first time. This finding highlights that the reduction in seafloor-spreading rate and decline in reverse weathering during the Cenozoic era has played a significant role in the evolution of seawater chemistry, emphasizing the importance of these processes in driving long-term changes in the carbon cycle.
Highlights
• Germany plans more long-distances water transfers to secure drinking water supply.
• Long-distance water transfers can unfold lock-ins that limit adaptive water governance.
• Our interdisciplinary case study shows how lock-ins emerge over different spaces and times.
• Commercialisation of water but also local protests contributed to various lock-ins.
• We therefore call for context-specific assessments of potentials and risks of LDWT.
Abstract
Germany plans to expand water transfers over long distances in the light of numerous and pressing challenges for drinking water supply. Research on inter- and intrabasin water transfers warns, however, that major investments in large-scale infrastructure systems accompanied by institutional logics and political interests often lead to a so-called lock-in. As a consequence, long-distance water transfers can limit the potential for adaptive water governance in the involved supply areas over decades with negative impacts for people and the environment. By using a case study in Germany as an example, we researched when, where and how such lock-ins around long-distance water transfers emerge. In the infrastructural development of the Elbaue-Ostharz transfer system we found various lock-ins that overlap in space and time. Some are located at the centre others at the margins of the infrastructure and commercialization of the water sector as well as hydraulic and hygienic concerns interlock with local protests in a way that the expansion of the long-distance water transfer infrastructure is presented continuously as imperative. Our findings contribute to a relational understanding of lock-ins of long-distance water transfers as contingent and diverse processes. Given the widespread occurrence of lock-ins, we argue for a context-specific assessment of potentials and risks of long-distance water transfers in times of multiple crises.
We present a new experimental dataset on the impact of the heavy halogens chlorine, bromine and iodine on the Raman water bands concerning pressure and their concentration at room temperature. These experiments were conducted at ambient temperature, with variations in halogen concentration and pressure ranging from 0 to 1.4 GPa.
The strength of the Raman water band shift change increases with the ionic size from chlorine, over bromine, to iodine. Our experiments further demonstrate that increased pressure diminishes the impact of the halogen shift change to a varying extent for each of the three halogens. This finding can have significant implications for the salinity calculation of fluid inclusions in minerals such as quartz or olivine. Particularly in the low salinity range, the concentration can be markedly underestimated if the pressure effect is neglected. For experiments in diamond anvil cells involving halogens dissolved in water, the change in Raman water band shifts can serve either as a new tool to monitor pressure, or to monitor the salinity.
Vladimir Vernadsky's concept of living matter is central to his biogeochemistry, the science he founded. For several reasons, his original understanding of living matter is one of the most complex notions in the history of the life sciences. First, biogeochemistry is by definition an interdisciplinary enterprise that embraces biology, including evolutionary theory, geology, and chemistry, and combines them into a unique research program. Second, if understood in the original sense as used by Vernadsky, living matter is a concept built into idiosyncratic metaphysics constructed around the so-called principle of life's eternity. Third, the concept of living matter reflects the specificity of Vernadsky's sophisticated philosophy of science as he insisted that 'scientific thought' is a planetary phenomenon as well as a geological force. In our contribution, we will introduce Vernadsky's concept of living matter in its historical context. Accordingly, we will also give some chronology of Vernadsky's work related to the growth of his biosphere concept highlighting the 'Ukrainian' period as it is in this period that he intensively elaborated on the notion of living matter. This will be followed by his theory of living matter as it was formulated in his major works of the later period. We are going to locate the notion of living matter within Vernadsky's theoretical system and demonstrate that he regarded his theory of the living as an evolutionary theory complementary to that of Charles Darwin from the very beginning. Additionally, we will briefly present Vladimir Beklemishev's concept of 'geomerida' which he developed at approximately the same time as Vernadsky was elaborating on his 'living matter' to highlight the specificity of the latter's methodology.