Discrete-Continuum Multiphase Model for Structure Formation in Soils Including Electrostatic Effects

Structure formation and self organization in soils determine soil functions and regulate soil processes. Mathematically based modeling can facilitate the understanding of organizing mechanisms at different scales, provided that the major driving forces are taken into account. In this research we present an extension of the mechanistic model for transport, biomass development and solid restructuring that was proposed in a former publication of the authors. Three main extensions are implemented. First, arbitrary shapes for the building units (e.g., spherical, needle-like, or platy particles), and also their compositions are incorporated into the model. Second, a gas phase is included in addition to solid, biofilm, and fluid phases. Interaction rules within and between the phases are prescribed using a cellular automaton method (CAM) and a system of partial differential equations (PDEs). These result in a structural self organization of the respective phases which define the time-dependent composition of the computational domain. Within the non-solid phases, chemical species may diffuse and react. In particular a kinetic Langmuir isotherm for heterogeneous surface reactions and a Henry condition for the transfer from/into the gas phase are applied. As third important model extension charges and charge conservation laws are included into the model for both the solid phase and ions in solution, as electrostatic attraction is a major driving force for aggregation. The ions move obeying the Nernst-Planck equations. A fully implicit local discontinuous Galerkin (LDG) method is applied to solve the resulting equation systems. The operational, comprehensive model allows to study structure formation as a function of the size and shape of the solid particles. Moreover, the effect of attraction and repulsion by charges is thoroughly discussed. The presented model is a first step to capture various aspects of structure formation and self organization in soils, it is a process-based tool to study the interplay of relevant mechanisms in silico

Application of a Cellular Automaton Method to Model the Structure Formation in Soils Under Saturated Conditions: A Mechanistic Approach

Soil functions are closely related to the structure of soil microaggregates. Yet, the mechanisms controlling the establishment of soil structure are diverse and partly unknown. Hence, the understanding of soil processes and functions requires the connection of the concepts on the formation and consolidation of soil structural elements across scales that are hard to observe experimentally. At the bottom level, the dynamics of microaggregate development and restructuring build the basis for transport phenomena at the continuum scale. By modeling the interactions of specific minerals and/or organic matter, we aim to identify the mechanisms that control the evolution of structure and establishment of stationary aggregate properties. We present a mechanistic framework based on a cellular automaton model to simulate the interplay between the prototypic building units of soil microaggregates quartz, goethite, and illite subject to attractive and repulsive electrostatic interaction forces. The resulting structures are quantified by morphological measures. We investigated shielding effects due to charge neutralization and the aggregate growth rate in response to the net system charge. We found that the fraction as well as the size of the interacting oppositely charged constituents control the size, shape, and amount of occurring aggregates. Furthermore, the concentration in terms of the liquid solid ratio has been shown to increase the aggregation rate. We further adopt the model for an assessment of the temporal evolution of aggregate formation due to successive formation of particle dimers at early stages in comparison to higher order aggregates at later stages. With that we show the effect of composition, charge, size ratio, time, and concentration on microaggregate formation by the application of a mechanistic model which also provides predictions for soil aggregation behavior in case an observation is inhibited by experimental limitations

Archaeal Diversity and CO 2

Groundwater environments provide habitats for diverse microbial communities, and although Archaea usually represent a minor fraction of communities, they are involved in key biogeochemical cycles. We analysed the archaeal diversity within a mixed carbonate-rock/siliciclastic-rock aquifer system, vertically from surface soils to subsurface groundwater including aquifer and aquitard rocks. Archaeal diversity was also characterized along a monitoring well transect that spanned surface land uses from forest/woodland to grassland and cropland. Sequencing of 16S rRNA genes showed that only a few surface soil-inhabiting Archaea were present in the groundwater suggesting a restricted input from the surface. Dominant groups in the groundwater belonged to the marine group I (MG-I) Thaumarchaeota and the Woesearchaeota. Most of the groups detected in the aquitard and aquifer rock samples belonged to either cultured or predicted lithoautotrophs (e.g., Thaumarchaeota or Hadesarchaea). Furthermore, to target autotrophs, a series of 13CO2 stable isotope-probing experiments were conducted using filter pieces obtained after filtration of 10,000 L of groundwater to concentrate cells. These incubations identified the SAGMCG Thaumarchaeota and Bathyarchaeota as groundwater autotrophs. Overall, the results suggest that the majority of Archaea on rocks are fixing CO2, while archaeal autotrophy seems to be limited in the groundwater

Nitrogen Loss from Pristine Carbonate-Rock Aquifers of the Hainich Critical Zone Exploratory (Germany) Is Primarily Driven by Chemolithoautotrophic Anammox Processes

Despite the high relevance of anaerobic ammonium oxidation (anammox) for nitrogen loss from marine systems, its relative importance compared to denitrification has less been studied in freshwater ecosystems, and our knowledge is especially scarce for groundwater. Surprisingly, phospholipid fatty acids (PLFA)-based studies identified zones with potentially active anammox bacteria within two superimposed pristine limestone aquifer assemblages of the Hainich Critical Zone Exploratory (CZE; Germany). We found anammox to contribute an estimated 83% to total nitrogen loss in suboxic groundwaters of these aquifer assemblages at rates of 3.5–4.7 nmol L−1 d−1, presumably favored over denitrification by low organic carbon availability. Transcript abundances of hzsA genes encoding hydrazine synthase exceeded nirS and nirK transcript abundances encoding denitrifier nitrite reductase by up to two orders of magnitude, providing further support of a predominance of anammox. Anammox bacteria, dominated by groups closely related to Cand. Brocadia fulgida, constituted up to 10.6% of the groundwater microbial community and were ubiquitously present across the two aquifer assemblages with indication of active anammox bacteria even in the presence of 103 μmol L−1 oxygen. Co-occurrence of hzsA and amoA gene transcripts encoding ammonia mono-oxygenase suggested coupling between aerobic and anaerobic ammonium oxidation under suboxic conditions. These results clearly demonstrate the relevance of anammox as a key process driving nitrogen loss from oligotrophic groundwater environments, which might further be enhanced through coupling with incomplete nitrification

Results of Closed-Flow Column Experiments (zip-archive 2.3 MB)

The identification of transport parameters by inverse modeling often suffers from equifinality or parameter correlation when models are fitted to observations of the solute breakthrough in column outflow experiments. This parameters uncertainty can be approached by the application of multiple experimental designs such as column experiments in open-flow mode and the recently proposed closed-flow mode. Latter are characterized by the recirculation of the column effluent into the solution supply vessel that feeds the inflow. Depending on the experimental conditions, the solute concentration in the solution supply vessel and the effluent follows a damped sinusoidal oscillation. As a result, the closed-flow experiment provides additional observables in the breakthrough curve. The evaluation of these emergent features allows intrinsic control over boundary conditions and impacts the uncertainty of parameters in inverse modeling. We present a comprehensive sensitivity analysis to illustrate the potential application of closed-flow experiments. We show that the sensitivity with respect to the apparent dispersion can be controlled by the experimenter leading to a decrease in parameter uncertainty as compared to classical experiments by an order of magnitude for optimal settings. With these finding we are also able to reduce the equifinality found for situations, where rate-limited interactions impede a proper determination of the apparent dispersion and rate coefficients. Furthermore, we show the expected breakthrough curve for equilibrium and kinetic sorption, the latter showing strong similarities to the behavior found for completely mixed batch reactor experiments. This renders the closed-flow mode a useful complementary approach to classical column experiments

Closed-flow column experiment results (zip-archive 67 kB)

Transport studies that employ column experiments in closed-flow mode complement classical approaches by providing new characteristic features observed in the breakthrough behavior and an equilibrium between liquid and solid phase. Specific to the closed-flow mode is the recirculation of the column effluent to the inflow via a mixing vessel. Depending on the ratio of volume of the water-filled pore space to the volume of the mixing vessel, a damped oscillating solute concentration emerges in effluent and mixing vessel. Oscillation frequency, extent of damping and amplitude are thereby governed by the transport properties of the porous medium. These characteristics allow for the analysis of transport processes in soils in a similar fashion as known for classical open-flow column experiments. However, the experimental design considers feedbacks of liquid solid interactions by connecting the effluent solution with the inflow. In this way, solute and porous medium can equilibrate with respect to all physicochemical parameters, thereby permitting a convenient consideration of mass balances. With this paper, the features emerging in the breakthrough of column experiments run in closed-flow mode and methods of evaluation are illustrated under experimental boundary conditions forcing the appearance of these oscillations. Additionally, the effect of flow velocity and mixing vessel volume on the breakthrough is investigated. We demonstrate that the water content of the porous medium and the pumping rate can be determined from a conservative tracer breakthrough curve. In this way, external preconditioning of the soil material, e.g., drying, can be avoided. This renders the closed-flow column approach especially interesting for the study of porous media with diverse mineral content and bacterial community that react strongly on changes in the water content. Furthermore, the basis for the modeling of closed-flow experiments is given by the derivation of constitutive equations and numerical implementation, validated by the presented experiments

Groundwater metabolome responds to recharge in fractured sedimentary strata

Understanding the sources, structure and fate of dissolved organic matter (DOM) in groundwater is paramount for the protection and sustainable use of this vital resource. On its passage through the Critical Zone, DOM is subject to biogeochemical conversions. Therefore, it carries valuable cross-habitat information for monitoring and predicting the stability of groundwater ecosystem services and assessing these ecosystems' response to fluctuations caused by external impacts such as climatic extremes. Challenges arise from insufficient knowledge on groundwater metabolite composition and dynamics due to a lack of consistent analytical approaches for long-term monitoring. Our study establishes groundwater metabolomics to decipher the complex biogeochemical transport and conversion of DOM. We explore fractured sedimentary bedrock along a hillslope recharge area by a 5-year untargeted metabolomics monitoring of oxic perched and anoxic phreatic groundwater. A summer with extremely high temperatures and low precipitation was included in the monitoring. Water was accessed by a monitoring well-transect and regularly collected for liquid chromatography-mass spectrometry (LC-MS) investigation. Dimension reduction of the resulting complex data set by principal component analysis revealed that metabolome dissimilarities between distant wells coincide with transient cross-stratal flow indicated by groundwater levels. Time series of the groundwater metabolome data provides detailed insights into subsurface responses to recharge dynamics. We demonstrate that dissimilarity variability between groundwater bodies with contrasting aquifer properties coincides with recharge dynamics. This includes groundwater high- and lowstands as well as recharge and recession phases. Our monitoring approach allows to survey groundwater ecosystems even under extreme conditions. Notably, the metabolome was highly variable lacking seasonal patterns and did not segregate by geographical location of sampling wells, thus ruling out vegetation or (agricultural) land use as a primary driving factor. Patterns that emerge from metabolomics monitoring give insight into subsurface ecosystem functioning and water quality evolution, essential for sustainable groundwater use and climate change-adapted management