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White mica and tourmaline are the dominant hydrothermal alteration minerals at the world-class Panasqueira W-Sn-Cu deposit in Portugal. Thus, understanding the controls on their chemical composition helps to constrain ore formation processes at this deposit and determine their usefulness as pathfinder minerals for mineralization in general. We combine whole-rock geochemistry of altered and unaltered metasedimentary host rocks with in situ LA-ICP-MS measurements of tourmaline and white mica from the alteration halo. Principal component analysis (PCA) is used to better identify geochemical patterns and trends of hydrothermal alteration in the datasets. The hydrothermally altered metasediments are enriched in As, Sn, Cs, Li, W, F, Cu, Rb, Zn, Tl, and Pb relative to unaltered samples. In situ mineral analyses show that most of these elements preferentially partition into white mica over tourmaline (Li, Rb, Cs, Tl, W, and Sn), whereas Zn is enriched in tourmaline. White mica has distinct compositions in different settings within the deposit (greisen, vein selvages, wall rock alteration zone, late fault zone), indicating a compositional evolution with time. In contrast, tourmaline from different settings overlaps in composition, which is ascribed to a stronger dependence on host rock composition and also to the effects of chemical zoning and microinclusions affecting the LA-ICP-MS analyses. Hence, in this deposit, white mica is the better recorder of the fluid composition. The calculated trace-element contents of the Panasqueira mineralizing fluid based on the mica data and estimates of mica-fluid partition coefficients are in good agreement with previous fluid-inclusion analyses. A compilation of mica and tourmaline trace-element compositions from Panasqueira and other W-Sn deposits shows that white mica has good potential as a pathfinder mineral, with characteristically high Li, Cs, Rb, Sn, and W contents. The trace-element contents of hydrothermal tourmaline are more variable. Nevertheless, the compiled data suggest that high Sn and Li contents are distinctive for tourmaline from W-Sn deposits.
The Devonian Las Chacras-Potrerillos batholith comprises six nested monzonitic to granitic intrusions with metaluminous to weakly peraluminous composition and a Sr-Nd isotopic signature indicating a dominantly juvenile mantle-derived source. The chemically most evolved units in the southern batholith contain a large number of intra-granitic, pod-shaped tourmaline-bearing pegmatites. This study uses in situ chemical and boron isotopic analyses of tourmaline from nine of these pegmatites to discuss their relationship to the respective host intrusions and the implications of their B-isotope composition for the source and evolution of the magmas. The tourmalines reveal a diversity in element composition (e.g., FeO, MgO, TiO2, CaO, MnO, F) which distinguishes individual pegmatites from one another. However, all have a narrow 5 11 B range of -13.7 to -10.5%0 (n = 100) which indicates a relatively uniform magmatic system and similar temperature conditions during tourmaline crystallization. The average delta(11) B value of -11.7%0 is typical for S-type granites and is within the range reported for peraluminous granites. pegmatites, and metamorphic units of the Ordovician basement into which the Las Chacras-Potrerillos batholith intruded. The B-isotope evidence argues for a crustal boron source like that of the Ordovician basement, in contrast to the metaluminous to weakly peraluminous composition and juvenile initial Sr and Nd isotope ratios of the Las Chacras-Potrerillos batholith magmas. We propose that the boron was not derived from the magma source region but was incorporated from dehydration melting of elastic metasedimentary rocks higher up in the crustal column.
The Altiplano-Puna Plateau holds several shallow lakes, which are very sensitive to climate changes. This work is focused on a high-altitude lake system called Lagunas de Vilama (LVS), located in a complex climatic transition area with scarcity of continuous and homogeneous instrumental records. The objective of this study is to determine the regional spatial-temporal variability of precipitation and evaluate the seasonal and interannual lake responses. We use a lake-surfaces record derived from Landsat images to investigate links with regional precipitations and different climatic forcings. The results reveal that austral summer and autumn precipitations control the variability of the annual lake-surfaces. Also, we found intra-annual and interannual lags in the lake responses to precipitations, and identified several wet and dry stages. Our results show negative trends in precipitations and lake-surfaces, whose were strengthened by a shift to a warm phase of the Atlantic Multidecadal Oscillation in the 1990s. The El Nino Southern Oscillation, Pacific Decadal Oscillation, and Southern Annular Mode also exert a strong influence in the region. This study demonstrates that the variability of LVS lakes is strongly related to the South American Monsoon System dynamics and large-scale climate fordngs from the Pacific and Atlantic Oceans. This work provides novel indices which demonstrated to be good indicators of regional hydroclimatological variability for this region of South America.
Long- and short-term monitoring of a dam in response to seasonal changes and ground motion loading
(2021)
An experimental multi-parameter structural monitoring system has been installed on the Kurpsai dam, western Kyrgyz Republic. This system consists of equipment for seismic and strain measurements for making longer- (days, weeks, months) and shorter- (minutes, hours) term observations, dealing with, for example seasonal (longer) effects or the response of the dam to ground motion from noise or seismic events. Fibre-optic strain sensors allow the seasonal and daily opening and closing of the spaces between the dam's segments to be tracked. For the seismic data, both amplitude (in terms of using differences in amplitudes in the Fourier spectra for mapping the modes of vibration of the dam) and their time-frequency distribution for a set of small to moderate seismic events are investigated and the corresponding phase variabilities (in terms of lagged coherency) are evaluated. Even for moderate levels of seismic-induced ground motion, some influence on the structural response can be detected, which then sees the dam quickly return to its original state. A seasonal component was identified in the strain measurements, while levels of noise arising from the operation of the dam's generators and associated water flow have been provisionally identified.
Centroid moment tensor (CMT) parameters can be estimated from seismic waveforms. Since these data indirectly observe the deformation process, CMTs are inferred as solutions to inverse problems which are generally underdetermined and require significant assumptions, including assumptions about data noise. Broadly speaking, we consider noise to include both theory and measurement errors, where theory errors are due to assumptions in the inverse problem and measurement errors are caused by the measurement process. While data errors are routinely included in parameter estimation for full CMTs, less attention has been paid to theory errors related to velocity-model uncertainties and how these affect the resulting moment-tensor (MT) uncertainties. Therefore, rigorous uncertainty quantification for CMTs may require theory-error estimation which becomes a problem of specifying noise models. Various noise models have been proposed, and these rely on several assumptions. All approaches quantify theory errors by estimating the covariance matrix of data residuals. However, this estimation can be based on explicit modelling, empirical estimation and/or ignore or include covariances. We quantitatively compare several approaches by presenting parameter and uncertainty estimates in nonlinear full CMT estimation for several simulated data sets and regional field data of the M-1 4.4, 2015 June 13 Fox Creek, Canada, event. While our main focus is at regional distances, the tested approaches are general and implemented for arbitrary source model choice. These include known or unknown centroid locations, full MTs, deviatoric MTs and double-couple MTs. We demonstrate that velocity-model uncertainties can profoundly affect parameter estimation and that their inclusion leads to more realistic parameter uncertainty quantification. However, not all approaches perform equally well. Including theory errors by estimating non-stationary (non-Toeplitz) error covariance matrices via iterative schemes during Monte Carlo sampling performs best and is computationally most efficient. In general, including velocity-model uncertainties is most important in cases where velocity structure is poorly known.
Ice-rich permafrost has been subject to abrupt thaw and thermokarst formation in the past and is vulnerable to current global warming. The ice-rich permafrost domain includes Yedoma sediments that have never thawed since deposition during the late Pleistocene and Alas sediments that were formed by previous thermokarst processes during the Lateglacial and Holocene warming. Permafrost thaw unlocks organic carbon (OC) and minerals from these deposits and exposes OC to mineralization. A portion of the OC can be associated with iron (Fe), a redox-sensitive element acting as a trap for OC. Post-depositional thaw processes may have induced changes in redox conditions in these deposits and thereby affected Fe distribution and interactions between OC and Fe, with knock-on effects on the role that Fe plays in mediating present day OC mineralization. To test this hypothesis, we measured Fe concentrations and proportion of Fe oxides and Fe complexed with OC in unthawed Yedoma and previously thawed Alas deposits. Total Fe concentrations were determined on 1,292 sediment samples from the Yedoma domain using portable X-ray fluorescence; these concentrations were corrected for trueness using a calibration based on a subset of 144 samples measured by inductively coupled plasma optical emission spectrometry after alkaline fusion (R (2) = 0.95). The total Fe concentration is stable with depth in Yedoma deposits, but we observe a depletion or accumulation of total Fe in Alas deposits, which experienced previous thaw and/or flooding events. Selective Fe extractions targeting reactive forms of Fe on unthawed and previously thawed deposits highlight that about 25% of the total Fe is present as reactive species, either as crystalline or amorphous oxides, or complexed with OC, with no significant difference in proportions of reactive Fe between Yedoma and Alas deposits. These results suggest that redox driven processes during past thermokarst formation impact the present-day distribution of total Fe, and thereby the total amount of reactive Fe in Alas versus Yedoma deposits. This study highlights that ongoing thermokarst lake formation and drainage dynamics in the Arctic influences reactive Fe distribution and thereby interactions between Fe and OC, OC mineralization rates, and greenhouse gas emissions.
How biased are our models?
(2021)
Geophysical process simulations play a crucial role in the understanding of the subsurface. This understanding is required to provide, for instance, clean energy sources such as geothermal energy. However, the calibration and validation of the physical models heavily rely on state measurements such as temperature. In this work, we demonstrate that focusing analyses purely on measurements introduces a high bias. This is illustrated through global sensitivity studies. The extensive exploration of the parameter space becomes feasible through the construction of suitable surrogate models via the reduced basis method, where the bias is found to result from very unequal data distribution. We propose schemes to compensate for parts of this bias. However, the bias cannot be entirely compensated. Therefore, we demonstrate the consequences of this bias with the example of a model calibration.
This study is trying to understand the pre-eruptive magma storage and crystallization conditions of the Middle Miocene aged, silica-saturated trachytic rocks of the Afyon Volcanic Complex (AVC) in Western Anatolia, Turkey. Those rocks can be divided by their high K2O, K2O/Na2O ratio and Mg# into two groups, namely the intermediate-potassic (IPG) and the ultrapotassic (UPG). Here we are comparing calculated pressure (P) - temperature (T) conditions derived from geothermobarometric calculations of natural samples with results of high-pressure, high-temperature phase equilibria experiments. IPG samples are richer in silica (57-64 wt% SiO2), whereas UPG samples show intermediate SiO2 contents of 56-58 wt%. UPG are having high K2O contents ((>)9 wt %), K2O/Na2O ratios ((>)10 wt%) and Mg# values (75-77). IPG phenocrysts comprise plagioclase + biotite + amphibole + clinopyroxene +/- orthopyroxene +/- sanidine +/- phlogopite and oxides, while UPG mineralogical assemblage consists of amphibole + phlogopite + clinopyroxene + olivine + sanidine and oxides. IPG and UPG are enriched in Large-Ion Lithophile Elements (LILE), and both have negative anomalies in Nb, Sr, Zr and Ti elements. Additionally, IPG shows positive anomalies in Pb. Both IPG and UPG display enrichment in Light Rare Earth Elements (LREE), while IPG shows a more significant negative anomaly in Eu when compared to UPG. Plagioclase fractionation may play a role in magma generation. In IPG samples Ni and Cr values range between (3.3-18.8 ppm) and (2.6-27.8 ppm), respectively; whereas UPG samples have (119.1-120.7 ppm) Ni and (212.1-219.9 ppm) Cr. Dy/Yb ratios of IPG and UPG are higher than 2 and may indicate that garnet was present in the source. Geothermobarometric calculations for natural IPG clinopyroxene-melt pairs imply higher PT conditions (Dogan-Kulahci et al., 2015), while in this study high-pressure/high-temperature (HP/HT) phase equilibria experiments recreated the natural mineral assemblage at 2-4 kbar, 6-9 km and c. 900 degrees C. New plagioclase-melt calculations have confirmed lower mean magma storage temperatures, which are closer to the experimental results but still slightly elevated. Thus, trace element results of the natural rocks and experimental data may imply that a deep garnet-bearing magma source mixed with shallower magmas (IPG) was feeding the volcanic eruption.
Cyanobacteria are important primary producers in temperate freshwater ecosystems. However, studies on the seasonal and spatial distribution of cyanobacteria in deep lakes based on high-throughput DNA sequencing are still rare. In this study, we combined monthly water sampling and monitoring in 2019, amplicon sequence variants analysis (ASVs; a proxy for different species) and quantitative PCR targeting overall cyanobacteria abundance to describe the seasonal and spatial dynamics of cyanobacteria in the deep hard-water oligo-mesotrophic Lake Tiefer See, NE Germany. We observed significant seasonal variation in the cyanobacterial community composition (p < 0.05) in the epi- and metalimnion layers, but not in the hypolimnion. In winter-when the water column is mixed-picocyanobacteria (Synechococcus and Cyanobium) were dominant. With the onset of stratification in late spring, we observed potential niche specialization and coexistence among the cyanobacteria taxa driven mainly by light and nutrient dynamics. Specifically, ASVs assigned to picocyanobacteria and the genus Planktothrix were the main contributors to the formation of deep chlorophyll maxima along a light gradient. While Synechococcus and different Cyanobium ASVs were abundant in the epilimnion up to the base of the euphotic zone from spring to fall, Planktothrix mainly occurred in the metalimnetic layer below the euphotic zone where also overall cyanobacteria abundance was highest in summer. Our data revealed two potentially psychrotolerant (cold-adapted) Cyanobium species that appear to cope well under conditions of lower hypolimnetic water temperature and light as well as increasing sediment-released phosphate in the deeper waters in summer. The potential cold-adapted Cyanobium species were also dominant throughout the water column in fall and winter. Furthermore, Snowella and Microcystis-related ASVs were abundant in the water column during the onset of fall turnover. Altogether, these findings suggest previously unascertained and considerable spatiotemporal changes in the community of cyanobacteria on the species level especially within the genus Cyanobium in deep hard-water temperate lakes.
The Kohat fold and thrust belt in Pakistan shows a significantly different structural style due to the structural evolution on the double décollement compared to the rest of the Subhimalaya. In order to better understand the spatio-temporal structural evolution of the Kohat fold and thrust belt, we combine balanced cross sections with apatite (U?Th-Sm)/He (AHe) and apatite fission track (AFT) dating. The AHe and AFT ages appear to be totally reset, allowing us to date exhumation above structural ramps. The results suggest that deformation began on the frontal Surghar thrust at-15 Ma, predating or coeval with the development of the Main Boundary thrust at-12 Ma. Deformation propagated southward from the Main Boundary thrust on double de?collements between 10 Ma and 2 Ma, resulting in a disharmonic structural style inside the Kohat fold and thrust belt. Thermal modeling of the thermochronologic data suggest that samples inside Kohat fold and thrust belt experienced cooling due to formation of the duplexes; this deformation facilitated tectonic thickening of the wedge and erosion of the Miocene to Pliocene foreland strata. The spatial distribution of AHe and AFT ages in combination with the structural forward model suggest that, in the Kohat fold and thrust belt, the wedge deformed in-sequence as a supercritical wedge (-15-12 Ma), then readjusted by out-sequence deformation (-12-0 Ma) within the Kohat fold and thrust belt into a sub-critical wedge.
Strong hydroclimatic controls on vulnerability to subsurface nitrate contamination across Europe
(2020)
Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that similar to 75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least onethird of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes.
Strong hydroclimatic controls on vulnerability to subsurface nitrate contamination across Europe
(2020)
Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that similar to 75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least onethird of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes.
Rapidly growing seismic and macroseismic databases and simplified access to advanced machine learning methods have in recent years opened up vast opportunities to address challenges in engineering and strong motion seismology from novel, datacentric perspectives. In this thesis, I explore the opportunities of such perspectives for the tasks of ground motion modeling and rapid earthquake impact assessment, tasks with major implications for long-term earthquake disaster mitigation.
In my first study, I utilize the rich strong motion database from the Kanto basin, Japan, and apply the U-Net artificial neural network architecture to develop a deep learning based ground motion model. The operational prototype provides statistical estimates of expected ground shaking, given descriptions of a specific earthquake source, wave propagation paths, and geophysical site conditions. The U-Net interprets ground motion data in its spatial context, potentially taking into account, for example, the geological properties in the vicinity of observation sites. Predictions of ground motion intensity are thereby calibrated to individual observation sites and earthquake locations.
The second study addresses the explicit incorporation of rupture forward directivity into ground motion modeling. Incorporation of this phenomenon, causing strong, pulse like ground shaking in the vicinity of earthquake sources, is usually associated with an intolerable increase in computational demand during probabilistic seismic hazard analysis (PSHA) calculations. I suggest an approach in which I utilize an artificial neural network to efficiently approximate the average, directivity-related adjustment to ground motion predictions for earthquake ruptures from the 2022 New Zealand National Seismic Hazard Model. The practical implementation in an actual PSHA calculation demonstrates the efficiency and operational readiness of my model. In a follow-up study, I present a proof of concept for an alternative strategy in which I target the generalizing applicability to ruptures other than those from the New Zealand National Seismic Hazard Model.
In the third study, I address the usability of pseudo-intensity reports obtained from macroseismic observations by non-expert citizens for rapid impact assessment. I demonstrate that the statistical properties of pseudo-intensity collections describing the intensity of shaking are correlated with the societal impact of earthquakes. In a second step, I develop a probabilistic model that, within minutes of an event, quantifies the probability of an earthquake to cause considerable societal impact. Under certain conditions, such a quick and preliminary method might be useful to support decision makers in their efforts to organize auxiliary measures for earthquake disaster response while results from more elaborate impact assessment frameworks are not yet available.
The application of machine learning methods to datasets that only partially reveal characteristics of Big Data, qualify the majority of results obtained in this thesis as explorative insights rather than ready-to-use solutions to real world problems. The practical usefulness of this work will be better assessed in the future by applying the approaches developed to growing and increasingly complex data sets.
The correct orientation of seismic sensors is critical for studies such as full moment tensor inversion, receiver function analysis, and shear-wave splitting. Therefore, the orientation of horizontal components needs to be checked and verified systematically. This study relies on two different waveform-based approaches, to assess the sensor orientations of the broadband network of the Kandilli Observatory and Earthquake Research Institute (KOERI). The network is an important backbone for seismological research in the Eastern Mediterranean Region and provides a comprehensive seismic data set for the North Anatolian fault. In recent years, this region became a worldwide field laboratory for continental transform faults. A systematic survey of the sensor orientations of the entire network, as presented here, facilitates related seismic studies. We apply two independent orientation tests, based on the polarization of P waves and Rayleigh waves to 123 broadband seismic stations, covering a period of 15 yr (2004-2018). For 114 stations, we obtain stable results with both methods. Approximately, 80% of the results agree with each other within 10 degrees. Both methods indicate that about 40% of the stations are misoriented by more than 10 degrees. Among these, 20 stations are misoriented by more than 20 degrees. We observe temporal changes of sensor orientation that coincide with maintenance work or instrument replacement. We provide time-dependent sensor misorientation correction values for the KOERI network in the supplemental material.
Water bodies are a highly abundant feature of Arctic permafrost ecosystems and strongly influence their hydrology, ecology and biogeochemical cycling. While very high resolution satellite images enable detailed mapping of these water bodies, the increasing availability and abundance of this imagery calls for fast, reliable and automatized monitoring. This technical work presents a largely automated and scalable workflow that removes image noise, detects water bodies, removes potential misclassifications from infrastructural features, derives lake shoreline geometries and retrieves their movement rate and direction on the basis of ortho-ready very high resolution satellite imagery from Arctic permafrost lowlands. We applied this workflow to typical Arctic lake areas on the Alaska North Slope and achieved a successful and fast detection of water bodies. We derived representative values for shoreline movement rates ranging from 0.40-0.56 m yr(-1) for lake sizes of 0.10 ha-23.04 ha. The approach also gives an insight into seasonal water level changes. Based on an extensive quantification of error sources, we discuss how the results of the automated workflow can be further enhanced by incorporating additional information on weather conditions and image metadata and by improving the input database. The workflow is suitable for the seasonal to annual monitoring of lake changes on a sub-meter scale in the study areas in northern Alaska and can readily be scaled for application across larger regions within certain accuracy limitations.
This study deals with the East Beni Suef Basin (Eastern Desert, Egypt) and aims to evaluate the source-generative potential, reconstruct the burial and thermal history, examine the most influential parameters on thermal maturity modeling, and improve on the models already published for the West Beni Suef to ultimately formulate a complete picture of the whole basin evolution.
Source rock evaluation was carried out based on TOC, Rock-Eval pyrolysis, and visual kerogen petrography analyses. Three kerogen types (II, II/III, and III) are distinguished in the East Beni Suef Basin, where the Abu Roash "F" Member acts as the main source rock with good to excellent source potential, oil-prone mainly type II kerogen, and immature to marginal maturity levels.
The burial history shows four depositional and erosional phases linked with the tectonic evolution of the basin. A hiatus (due to erosion or non-deposition) has occurred during the Late Eocene-Oligocene in the East Beni Suef Basin, while the West Beni Suef Basin has continued subsiding.
Sedimentation began later (Middle to Late Albian) with lower rates in the East Beni Suef Basin compared with the West Beni Suef Basin (Early Albian). The Abu Roash "F" source rock exists in the early oil window with a present-day transformation ratio of about 19% and 21% in the East and West Beni Suef Basin, respectively, while the Lower Kharita source rock, which is only recorded in the West Beni Suef Basin, has reached the late oil window with a present-day transformation ratio of about 70%.
The magnitude of erosion and heat flow have proportional and mutual effects on thermal maturity.
We present three possible scenarios of basin modeling in the East Beni Suef Basin concerning the erosion from the Apollonia and Dabaa formations.
Results of this work can serve as a basis for subsequent 2D and/or 3D basin modeling, which are highly recommended to further investigate the petroleum system evolution of the Beni Suef Basin.
The subsurface is a temporally dynamic and spatially heterogeneous compartment of the Earth's critical zone, and biogeochemical transformations taking place in this compartment are crucial for the cycling of nutrients.
The impact of spatial heterogeneity on such microbially mediated nutrient cycling is not well known, which imposes a severe challenge in the prediction of in situ biogeochemical transformation rates and further of nutrient loading contributed by the groundwater to the surface water bodies.
Therefore, we used a numerical modelling approach to evaluate the sensitivity of groundwater microbial biomass distribution and nutrient cycling to spatial heterogeneity in different scenarios accounting for various residence times.
The model results gave us an insight into domain characteristics with respect to the presence of oxic niches in predominantly anoxic zones and vice versa depending on the extent of spatial heterogeneity and the flow regime.
The obtained results show that microbial abundance, distribution, and activity are sensitive to the applied flow regime and that the mobile (i.e. observable by groundwater sampling) fraction of microbial biomass is a varying, yet only a small, fraction of the total biomass in a domain. Furthermore, spatial heterogeneity resulted in anaerobic niches in the domain and shifts in microbial biomass between active and inactive states. The lack of consideration of spatial heterogeneity, thus, can result in inaccurate estimation of microbial activity. In most cases this leads to an overestimation of nutrient removal (up to twice the actual amount) along a flow path.
We conclude that the governing factors for evaluating this are the residence time of solutes and the Damkohler number (Da) of the biogeochemical reactions in the domain. We propose a relationship to scale the impact of spatial heterogeneity on nutrient removal governed by the logioDa.
This relationship may be applied in upscaled descriptions of microbially mediated nutrient cycling dynamics in the subsurface thereby resulting in more accurate predictions of, for example, carbon and nitrogen cycling in groundwater over long periods at the catchment scale.
ABSTRACT: Structural evolution of cesium triiodide at high pressures has been revealed by synchrotron single-crystal X-ray diffraction. Cesium triiodide undergoes a first-order phase transition above 1.24(3) GPa from an orthorhombic to a trigonal system. This transition is coupled with severe reorganization of the polyiodide network from a layered to three-dimensional architecture. Quantum chemical calculations show that even though the two polymorphic phases are nearly isoenergetic under ambient conditions, the PV term is decisive in stabilizing the trigonal polymorph above the transition point. Phonon calculations using a non-local correlation functional that accounts for dispersion interactions confirm that this polymorph is dynamically unstable under ambient conditions. The high-pressure behavior of crystalline CsI3 can be correlated with other alkali metal trihalides, which undergo a similar sequence of structural changes upon load.
Alpine glacial erosion exerts a first-order control on mountain topography and sediment production, but its mechanisms are poorly understood. Observational data capable of testing glacial erosion and transport laws in glacial models are mostly lacking. New insights, however, can be gained from detrital tracer thermochronology. Detrital tracer thermochronology works on the premise that thermochronometer bedrock ages vary systematically with elevation, and that detrital downstream samples can be used to infer the source elevation sectors of sediments. We analyze six new detrital samples of different grain sizes (sand and pebbles) from glacial deposits and the modern river channel integrated with data from 18 previously analyzed bedrock samples from an elevation transect in the Leones Valley, Northern Patagonian Icefield, Chile (46.7 degrees S). We present 622 new detrital zircon (U-Th)/He (ZHe) single-grain analyses and 22 new bedrock ZHe analyses for two of the bedrock samples to determine age reproducibility. Results suggest that glacial erosion was focused at and below the Last Glacial Maximum and neoglacial equilibrium line altitudes, supporting previous modeling studies. Furthermore, grain age distributions from different grain sizes (sand, pebbles) might indicate differences in erosion mechanisms, including mass movements at steep glacial valley walls. Finally, our results highlight complications and opportunities in assessing glacigenic environments, such as dynamics of sediment production, transport, transient storage, and final deposition, that arise from settings with large glacio-fluvial catchments.
Frequency-domain electromagnetic (FDEM) data are commonly inverted to characterize subsurface geoelectrical properties using smoothness constraints in 1D inversion schemes assuming a layered medium.
Smoothness constraints are suitable for imaging gradual transitions of subsurface geoelectrical properties caused, for example, by varying sand, clay, or fluid content. However, such inversion approaches are limited in characterizing sharp interfaces. Alternative regularizations based on the minimum gradient support (MGS) stabilizers can, instead, be used to promote results with different levels of smoothness/sharpness selected by simply acting on the so-called focusing parameter.
The MGS regularization has been implemented for different kinds of geophysical data inversion strategies. However, concerning FDEM data, the MGS regularization has only been implemented for vertically constrained inversion (VCI) approaches but not for laterally constrained inversion (LCI) approaches.
We present a novel LCI approach for FDEM data using the MGS regularization for the vertical and lateral direction. Using synthetic and field data examples, we demonstrate that our approach can efficiently and automatically provide a set of model solutions characterized by different levels of sharpness and variable lateral consistencies.
In terms of data misfit, the obtained set of solutions contains equivalent models allowing us also to investigate the non-uniqueness of FDEM data inversion.