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Entrapped air in porous media can significantly affect water flow but simulations of air entrapment are still challenging. We developed a pore-network model using quasi-static algorithms to simulate air entrapment during spontaneous wetting and subsequent drainage processes. The model, implemented in OpenPNM, was tailored to replicate an experiment conducted on a medium-sized unconsolidated sand sample. We started building the model with three types of relatively small networks formed by 54,000 pore bodies which we used to calibrate basic network topological parameters by fitting the model to the water retention curve and the saturated hydraulic conductivity of the sand sample. Using these parameters, along with X-ray image data (µCT), a larger network formed by over 250,000 pore bodies was introduced in the form of stacked sub-networks where topological parameters were scaled along the z-axis. We investigated the impact of two different contact angles on air entrapment. For a contact angle of 0, the model showed good agreement with the experimental data, accurately predicting the amount of entrapped air and the saturated hydraulic conductivity. On the contrary, for a contact angle of π/4, the model provided reasonable accuracy for saturated hydraulic conductivity but overestimated the amount of entrapped air. Overall, this approach demonstrated that a reasonable match between simulated and experimental data can be achieved with minimal computational costs. [ABSTRACT FROM AUTHOR]

Hydro-pedotransfer functions (PTFs) relate easy-to-measure and readily available soil information to soil hydraulic properties (SHPs) for applications in a wide range of process-based and empirical models, thereby enabling the assessment of soil hydraulic effects on hydrological, biogeochemical, and ecological processes. At least more than 4 decades of research have been invested to derive such relationships. However, while models, methods, data storage capacity, and computational efficiency have advanced, there are fundamental concerns related to the scope and adequacy of current PTFs, particularly when applied to parameterise models used at the field scale and beyond. Most of the PTF development process has focused on refining and advancing the regression methods, while fundamental aspects have remained largely unconsidered. Most soil systems are not represented in PTFs, which have been built mostly for agricultural soils in temperate climates. Thus, existing PTFs largely ignore how parent material, vegetation, land use, and climate affect processes that shape SHPs. The PTFs used to parameterise the Richards–Richardson equation are mostly limited to predicting parameters of the van Genuchten–Mualem soil hydraulic functions, despite sufficient evidence demonstrating their shortcomings. Another fundamental issue relates to the diverging scales of derivation and application, whereby PTFs are derived based on laboratory measurements while often being applied at the field to regional scales. Scaling, modulation, and constraining strategies exist to alleviate some of these shortcomings in the mismatch between scales. These aspects are addressed here in a joint effort by the members of the International Soil Modelling Consortium (ISMC) Pedotransfer Functions Working Group with the aim of systematising PTF research and providing a roadmap guiding both PTF development and use. We close with a 10-point catalogue for funders and researchers to guide review processes and research. [ABSTRACT FROM AUTHOR]

Soil aggregation is an important process in nearly all soils across the globe. Aggregates develop over time through a series of abiotic and biotic processes and interactions, including plant growth and decay, microbial activity, plant and microbial exudation, bioturbation, and physicochemical stabilization processes, and are greatly influenced by soil management practices. Together, and through feedback with organic matter and primary soil particles, these processes form dynamic soil aggregates and pore spaces, which jointly constitute a soil's structure and contribute to overall soil functioning. Nevertheless, the concept of soil aggregates is hotly debated, leading to confusion about their function or relevancy to soil processes. We argue here that the opposition to the concept of soil aggregation likely stems from the fact that the methods for the characterization of soil aggregates have largely been developed in the context of arable soils, where tillage promotes the formation of distinct soil aggregates that are easily visible in the topsoil. We propose that the widespread use of conceptual figures showing detached and isolated aggregates can be misleading and has contributed to the skepticism towards soil aggregates. However, the fact that we do not always see discrete aggregates within soils in situ does not mean that aggregates do not exist or are not relevant to the study of soil processes. Given that, by definition, soil aggregates consist of any group of soil particles that cohere more strongly to each other than neighboring particles, aggregates may, but do not necessarily need to be, bordered by pore space. Here, we illustrate how aggregates can form and dissipate within the context of undisturbed, intact soils, highlighting the point that aggregates do not necessarily need to have a discrete physical boundary and can exist seamlessly embedded in the soil. We hope that our contribution helps the debate on soil aggregates and supports the foundation of a shared understanding on the characterization and function of soil structure. [ABSTRACT FROM AUTHOR]

Hydro-pedotransfer functions (PTFs) relate easy-to-measure and readily available soil information to soil hydraulic properties for applications in a wide range of process-based and empirical models, thereby enabling the assessment of soil hydraulic effects on hydrological, biogeochemical, and ecological processes. At least more than four decades of research have been invested to derive such relationships. However, while models, methods, data storage capacity, and computational efficiency have advanced, there are fundamental concerns related to the scope and adequacy of current PTFs, particularly when applied to parameterize models used at the field scale and beyond. Most of the PTF development process has focused on refining and advancing the regression methods, while fundamental aspects have remained largely unconsidered. Most system settings are not captured by existing PTFs, which have been built mostly for agricultural soils in temperate climates. Thus. existing PTFs largely ignorie how parent material, vegetation, land use, and climate affect processes that shape soil hydraulic properties. The PTFs used to parameterise the Richards-Richardson equation are mostly limited to predicting parameters of the van Genuchten-Mualem soil hydraulic functions, despite sufficient evidence demonstrating their shortcomings. Another fundamental issue relates to the diverging scales of derivation and application, whereby PTFs are derived based on laboratory measurements while being often applied at field to regional scales. Scaling, modulation, and constraining strategies exist to alleviate some of these shortcomings in the mismatch between scales. These aspects are addressed here in a joint effort by the members of the International Soil Modelling Consortium (ISMC) Pedotransfer Functions Working Group with the aim to systematise PTF research and provide a roadmap guiding both PTF development and use. [ABSTRACT FROM AUTHOR]

Hydro-pedotransfer functions (PTFs) relate easy-to-measure and readily available soil information to soil hydraulic properties for applications in a wide range of process-based and empirical models, thereby enabling the assessment of soil hydraulic effects on hydrological, biogeochemical, and ecological processes. At least more than four decades of research have been invested to derive such relationships. However, while models, methods, data storage capacity, and computational efficiency have advanced, there are fundamental concerns related to the scope and adequacy of current PTFs, particularly when applied to parameterize models used at the field scale and beyond. Most of the PTF development process has focused on refining and advancing the regression methods, while fundamental aspects have remained largely unconsidered. Most system settings are not captured by existing PTFs, which have been built mostly for agricultural soils in temperate climates. Thus. existing PTFs largely ignorie how parent material, vegetation, land use, and climate affect processes that shape soil hydraulic properties. The PTFs used to parameterise the Richards-Richardson equation are mostly limited to predicting parameters of the van Genuchten-Mualem soil hydraulic functions, despite sufficient evidence demonstrating their shortcomings. Another fundamental issue relates to the diverging scales of derivation and applicatio n, whereby PTFs are derived based on laboratory measurements while being often applied at field to regional scales. Scaling, modulation, and constraining strategies exist to alleviate some of these shortcomings in the mismatch between scales. These aspects are addressed here in a joint effort by the members of the International Soil Modelling Consortium (ISMC) Pedotransfer Functions Working Group with the aim to systematise PTF research and provide a roadmap guiding both PTF development and use. [ABSTRACT FROM AUTHOR]

Saturated and near-saturated soil hydraulic conductivities Kh (mmh-1) determine the partitioning of precipitation into surface runoff and infiltration and are fundamental to soils' susceptibility to preferential flow. Recent studies found indications that climate factors influence Kh , which is highly relevant in the face of climate change. In this study, we investigated relationships between pedoclimatic factors and Kh and also evaluated effects of land use and soil management. To this end, we collated the Open Tension-disk Infiltrometer Meta-database (OTIM), which contains 1297 individual data entries from 172 different publication sources. We analysed a spectrum of saturated and near-saturated hydraulic conductivities at matric potentials between 0 and 100 mm. We found that methodological details like the direction of the wetting sequence or the choice of method for calculating infiltration rates to hydraulic conductivities had a large impact on the results. We therefore restricted ourselves to a subset of 466 of the 1297 data entries with similar methodological approaches. Correlations between Ks and Kh at higher supply tensions decreased especially close to saturation, indicating a different flow mechanism at and very close to saturation than towards the dry end of the investigated tension range. Climate factors were better correlated with topsoil near-saturated hydraulic conductivities at supply tensions ≥ 30 mm than soil texture, bulk density and organic carbon content. We find it most likely that the climate variables are proxies for soil macropore networks created by the respective biological activity, pedogenesis and climate-specific land use and management choices. Due to incomplete documentation in the source publications of OTIM, we were able to investigate only a few land use types and agricultural management practices. Land use, tillage system and soil compaction significantly influenced Kh , with effect sizes appearing comparable to the ones of soil texture and soil organic carbon. The data in OTIM show that experimental bias is present, introduced by the choice of measurement time relative to soil tillage, experimental design or data evaluation procedures. The establishment of best-practice rules for tension-disk infiltrometer measurements would therefore be helpful. Future studies are needed to investigate how climate shapes soil macropore networks and how land use and management can be adapted to improve soil hydraulic properties. Both tasks require large numbers of new measurement data with improved documentation on soil biology and land use and management history. [ABSTRACT FROM AUTHOR]

Summarizing information from large bodies of scientific literature is an essential but work-intensive task. This is especially true in environmental studies where multiple factors (e.g., soil, climate, vegetation) can contribute to the effects observed. Meta-analyses, studies that quantitatively summarize findings of a large body of literature, rely on manually curated databases built upon primary publications. However, given the increasing amount of literature, this manual work is likely to require more and more effort in the future. Natural language processing (NLP) facilitates this task, but it is not clear yet to which extent the extraction process is reliable or complete. In this work, we explore three NLP techniques that can help support this task: topic modeling, tailored regular expressions and the shortest dependency path method. We apply these techniques in a practical and reproducible workflow on two corpora of documents: the Open Tension-disk Infiltrometer Meta-database (OTIM) and the Meta corpus. The OTIM corpus contains the source publications of the entries of the OTIM database of near-saturated hydraulic conductivity from tension-disk infiltrometer measurements (https://github.com/climasoma/otim-db , last access: 1 March 2023). The Meta corpus is constituted of all primary studies from 36 selected meta-analyses on the impact of agricultural practices on sustainable water management in Europe. As a first step of our practical workflow, we identified different topics from the individual source publications of the Meta corpus using topic modeling. This enabled us to distinguish well-researched topics (e.g., conventional tillage, cover crops), where meta-analysis would be useful, from neglected topics (e.g., effect of irrigation on soil properties), showing potential knowledge gaps. Then, we used tailored regular expressions to extract coordinates, soil texture, soil type, rainfall, disk diameter and tensions from the OTIM corpus to build a quantitative database. We were able to retrieve the respective information with 56 % up to 100 % of all relevant information (recall) and with a precision between 83 % and 100 %. Finally, we extracted relationships between a set of drivers corresponding to different soil management practices or amendments (e.g., "biochar", "zero tillage") and target variables (e.g., "soil aggregate", "hydraulic conductivity", "crop yield") from the source publications' abstracts of the Meta corpus using the shortest dependency path between them. These relationships were further classified according to positive, negative or absent correlations between the driver and the target variable. This quickly provided an overview of the different driver–variable relationships and their abundance for an entire body of literature. Overall, we found that all three tested NLP techniques were able to support evidence synthesis tasks. While human supervision remains essential, NLP methods have the potential to support automated evidence synthesis which can be continuously updated as new publications become available. [ABSTRACT FROM AUTHOR]

Climate change will most likely lead to an increase of extreme weather events, including heavy rainfall with soil surface runoff and erosion. Adapting agricultural management practices that lead to increased infiltration capacities of soil has potential to mitigate these risks. However, effects of agricultural management practices (tillage, cover crops, amendment, …) on soil variables (hydraulic conductivity, aggregate stability, …) often depend on the pedo-climatic context. Hence, the only possibility to gather information needed to advise stakeholders on suitable management practices is to quantify such dependencies using meta-analyses of studies investigating this topic. As a first step, structured information from scientific publications needs to be extracted to build a meta-database, which then can be analyzed and recommendations can be given in dependence to the pedo-climatic context. Manually building such a database by going through all publications is very time-consuming. Given the increasing amount of literature, this task is likely to require more and more effort in the future. Natural language processing (NLP) facilitates this task, but it is not clear yet to which extent the extraction process is reliable or complete. In this work, two corpora of documents were used, which we refer to as the OTIM and the Meta corpus in the following. The OTIM corpus contains the source publications of the entries of the OTIM database of near-saturated hydraulic conductivity from tension-disk infiltrometer measurements (https://github.com/climasoma/otim-db). The Meta corpus is constituted of all primary studies from 36 selected meta-analyses on the impact of agricultural practices on sustainable water management in Europe. We focused on three NLP techniques: topic modeling, tailored regular expressions and dictionaries and the shortest dependency path. We used topic modeling to sort the individual source-publications of the Meta corpus into 6 topics (e.g. related to cover crops, biochar, …) with a coherence metric Cv ranging from 0.7 to 0.9; Then, we used tailored regular expressions and dictionaries to extract coordinates, soil texture, soil type, rainfall, disk diameter and tensions on the OTIM corpus. We found that the respective information could be retrieved with 56 % up to 100 % of all relevant information (recall) and with a precision between 83 % and 100 %. Finally, we extracted relationships between a set of practices keywords (e.g. 'biochar', 'zero tillage', …) and soil variables (e.g. 'soil aggregate', 'hydraulic conductivity', 'crop yield',…) from the source-publications' abstracts of the Meta corpus using the shortest dependency path between them. These relationships were further classified according to positive, negative or absent correlations between the driver and soil property. This quickly provided an overview of the different driver-variable relationships and their abundance for an entire body of literature. Overall, we found that all three tested NLP techniques were able to support evidence synthesis tasks such as selecting relevant publications on a topic, extracting specific information to build databases for meta-analysis and providing an overview of relationships found in the corpus. While human supervision remains essential, NLP methods have the potential to support fully automated evidence synthesis that can be continuously updated as new publications become available. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) in arable topsoil is known to have beneficial effects on soil physical properties that are important for soil fertility. The effects of SOC content on soil aggregate stability have been well documented; however, few studies have investigated its relationship with the soil pore structure, which has a strong influence on water dynamics and biogeochemical cycling. In the present study, we examined the relationships between SOC and clay contents and pore size distributions (PSDs) across an arable field with large spatial variations in topsoil SOC and clay contents by combining X‐ray tomography and measurements of soil water retention. Additionally, we investigated the relationships between fractionated SOC, reactive Fe and Al oxide contents and soil pore structure. We found that porosities in the 0.2–720 μm diameter class were positively correlated with SOC content. A unit increase of SOC content was associated with a relatively large increase in porosity in the 0.2–5 and 480–720 μm diameter classes, which indicates that enhanced SOC content would increase plant available water content and unsaturated hydraulic conductivity. On the other hand, macroporosities (1200–3120 μm diameter classes) and bioporosity were positively correlated with clay content but not with SOC content. Due to strong correlations between soil texture, carbon‐to‐nitrogen ratios and reactive iron contents, we could not separate the relative importance of these soil properties for PSDs. Reactive aluminium and particulate organic carbon contents were poorer predictors for PSDs compared with clay and SOC contents. This study provides new insights on the relations between SOC and soil pore structure in an arable soil and may lead to improved estimations of the effects of enhanced SOC sequestration on soil water dynamics and soil water supply to crops. Highlights: Relations between soil organic carbon (SOC) and pore size distribution (PSD) in an arable soil were explored.We used X‐ray tomography and soil water retention to quantify a wide range of PSD.There were positive correlations between SOC and porosities in 0.2–720 μm diameter classes.Porosities in 0.2–5 and 480–720 μm diameter classes were more strongly correlated with SOC than clay.Our results have implications for improved estimates of effects of SOC sequestration on soil water dynamics. [ABSTRACT FROM AUTHOR]

Soil compaction by farm machinery may persist for decades, hampering soil productivity and functioning. Assessing compaction costs and guiding recovery strategies are hindered by paucity of data on soil structure recovery rates. A long‐term Soil Structure Observatory was established on a loamy soil in Switzerland to monitor soil structure recovery after prescribed compaction, and to better assess the roles of natural processes (vegetation, macrofauna, and shrink–swell cycles) on recovery patterns. The aim of this study was to quantify short‐term soil structure recovery under natural conditions in the presence and absence of plant cover (ley and bare soil). We measured soil porosity and gas and water transport capabilities at 0.1 and 0.3 m depth. Two years after the compaction event, soil physical properties have not recovered to precompaction levels, even within the topsoil. Surprisingly, no differences were observed in the recovery patterns of ley and bare soil treatments. Measurements show that recovery rates differ among soil properties with the most severely affected properties by compaction (permeability) exhibiting highest recovery rates. Total soil porosity shows no recovery trend, suggesting lack of soil decompaction. Improved soil functions and decompaction are distinct aspects of soil structure recovery, with the latter requiring net upward transport of soil mass. We suggest that soil structure recovery proceeds at two fronts: from the soil surface downward, and expanding around local biologically‐active pockets (marked by biopores) into the compacted soil volumes. This concept could be tested with additional data of longer time series at our site as well as in other soils and climates. Core Ideas: Soil physical properties have not recovered to precompaction values within 2 yr.Recovery rates vary among soil physical properties.Decompaction (increase in total porosity) requires upward transport of soil mass.Functional recovery such as improved permeability does not require decompaction.A concept for soil structure recovery patterns is proposed. [ABSTRACT FROM AUTHOR]

The distribution of organic substrates and microorganisms in soils is spatially heterogeneous at the microscale. Most soil carbon cycling models do not account for this microscale heterogeneity, which may affect predictions of carbon (C) fluxes and stocks. In this study, we hypothesize that the mean respiration rate R‾ at the soil core scale (i) is affected by the microscale spatial heterogeneity of substrate and microorganisms and (ii) depends upon the degree of this heterogeneity. To theoretically assess the effect of spatial heterogeneities on R‾ , we contrast heterogeneous conditions with isolated patches of substrate and microorganisms versus spatially homogeneous conditions equivalent to those assumed in most soil C models. Moreover, we distinguish between biophysical heterogeneity, defined as the nonuniform spatial distribution of substrate and microorganisms, and full heterogeneity, defined as the nonuniform spatial distribution of substrate quality (or accessibility) in addition to biophysical heterogeneity. Four common formulations for decomposition kinetics (linear, multiplicative, Michaelis–Menten, and inverse Michaelis–Menten) are considered in a coupled substrate–microbial biomass model valid at the microscale. We start with a 2-D domain characterized by a heterogeneous substrate distribution and numerically simulate organic matter dynamics in each cell in the domain. To interpret the mean behavior of this spatially explicit system, we propose an analytical scale transition approach in which microscale heterogeneities affect R‾ through the second-order spatial moments (spatial variances and covariances). The model assuming homogeneous conditions was not able to capture the mean behavior of the heterogeneous system because the second-order moments cause R‾ to be higher or lower than in the homogeneous system, depending on the sign of these moments. This effect of spatial heterogeneities appears in the upscaled nonlinear decomposition formulations, whereas the upscaled linear decomposition model deviates from homogeneous conditions only when substrate quality is heterogeneous. Thus, this study highlights the inadequacy of applying at the macroscale the same decomposition formulations valid at the microscale and proposes a scale transition approach as a way forward to capture microscale dynamics in core-scale models. [ABSTRACT FROM AUTHOR]

While renewable biofuels can reduce negative effects of fossil fuel energy consumption, the magnitude of their benefits depends on the magnitude of N2O emissions. High variability of N2O emissions overpowers efforts to curb uncertainties in estimating N2O fluxes from biofuel systems. In this study, we explored (a) N2O production via bacterial denitrification and (b) N2O emissions from soils under several contrasting bioenergy cropping systems, with specific focus on explaining N2O variations by accounting for soil pore characteristics. Intact soil samples were collected after 9 years of implementing five biofuel systems: continuous corn with and without winter cover crop, monoculture switchgrass, poplars, and early‐successional vegetation. After incubation, N2O emissions were measured and bacterial denitrification was determined based on the site‐preference method. Soil pore characteristics were quantified using X‐ray computed microtomography. Three bioenergy systems with low plant diversity, that is, corn and switchgrass systems, had low porosities, low organic carbon contents, and large volumes of poorly aerated soil. In these systems, greater volumes of poorly aerated soil were associated with greater bacterial denitrification, which in turn was associated with greater N2O emissions (R2 = 0.52, p < 0.05). However, the two systems with high plant diversity, that is, poplars and early‐successional vegetation, over the 9 years of implementation had developed higher porosities and organic carbon contents. In these systems, volumes of poorly aerated soil were positively associated with N2O emissions without a concomitant increase in bacterial denitrification. Our results suggest that changes in soil pore architecture generated by long‐term implementation of contrasting bioenergy systems may affect the pathways of N2O production, thus, change associations between N2O emissions and other soil properties. Plant diversity appears as one of the factors determining which microscale soil characteristics will influence the amounts of N2O emitted into the atmosphere and, thus, which can be used as effective empirical predictors. Long‐term implementation of bioenergy systems with contrasting plant diversity influences microscale pore architecture, which then affects predictors of N2O production and emission. [ABSTRACT FROM AUTHOR]

Due to the great year-round demand for forest products, off-road forestry traffic occurs even when the ground is susceptible to soil compaction and rutting. We investigated the impacts of repeated passes with a laden forwarder (34 Mg) on the soil physical properties of two clear-cuts on stony till soils in northern Sweden. Core samples (n = 71) were collected from the top 5 cm of mineral soil in and beside wheel tracks, after six passes with the forwarder. Soil physical properties were quantified using classical soil physical analyses and X-ray tomography. The hydraulic conductivity was 70% lower in the wheel tracks than in the soil beside. The X-ray image analysis indicated that this was due to the smaller total volume and lower connectivity of structural pores (φ > 60 µm). Total porosity was 24% and 12% lower in the tracks at the two sites respectively, and mean bulk density was 1.39 g cm−3in the tracks, compared to 1.13 g cm−3beside them. To conclude, traffic changed the soil physical properties in a way that may lead to longer periods of high water content in the wheel tracks, increased risk of surface runoff and insufficient aeration for optimal seedling growth. [ABSTRACT FROM AUTHOR]

Core Ideas: Three‐dimensional X‐ray imaging is a valuable tool for vadose zone research.Quantitative 3‐D X‐ray image analyses require a large amount of time and expertise.SoilJ is an X‐ray image processing tool for the automatized analyses of X‐ray images.SoilJ lowers the amount of time and expertise needed to evaluate 3‐D X‐ray images. Noninvasive three‐ and four‐dimensional X‐ray imaging approaches have proved to be valuable analysis tools for vadose zone research. One of the main bottlenecks for applying X‐ray imaging to data sets with a large number of soil samples is the relatively large amount of time and expertise needed to extract quantitative data from the respective images. SoilJ is a plugin for the free and open imaging software ImageJ that aims at automating the corresponding processing steps for cylindrical soil columns. It includes modules for automatic column outline recognition, correction of image intensity bias, image segmentation, extraction of particulate organic matter and roots, soil surface topography detection, as well as morphology and percolation analyses. In this study, the functionality and precision of some key SoilJ features were demonstrated on five different image data sets of soils. SoilJ has proved to be useful for strongly decreasing the amount of time required for image processing of large image data sets. At the same time, it allows researchers with little experience in image processing to make use of X‐ray imaging methods. The SoilJ source code is freely available and may be modified and extended at will by its users. It is intended to stimulate further community‐driven development of this software. [ABSTRACT FROM AUTHOR]

Several studies have shown that the distribution of cation adsorption sites (CASs) is patchy at a millimetre to centimetre scale. Often, larger concentrations of CASs in biopores or aggregate coatings have been reported in the literature. This heterogeneity has implications on the accessibility of CASs and may influence the performance of soil system models that assume a spatially homogeneous distribution of CASs. In this study, we present a new method to quantify the abundance and 3-D distribution of CASs in undisturbed soil that allows for investigating CAS densities with distance to the soil macropores.We used X-ray imaging with Ba2+ as a contrast agent. Ba2+ has a high adsorption affinity to CASs and is widely used as an index cation to measure the cation exchange capacity (CEC). Eight soil cores (approx. 10 cm3) were sampled from three locations with contrasting texture and organic matter contents. The CASs of our samples were saturated with Ba2+ in the laboratory using BaCl2 (0.3 mol L-1). Afterwards, KCl (0.1 mol L-1) was used to rinse out Ba2+ ions that were not bound to CASs. Before and after this process the samples were scanned using an industrial X-ray scanner. Ba2+ bound to CASs was then visualized in 3-D by the difference image technique. The resulting difference images were interpreted as depicting the Ba2+ bound to CASs only. The X-ray image-derived CEC correlated significantly with results of the commonly used ammonium acetate method to determine CEC in well-mixed samples. The CEC of organic-matter-rich samples seemed to be systematically overestimated and in the case of the clay-rich samples with less organic matter the CEC seemed to be systematically underestimated. The results showed that the distribution of the CASs varied spatially within most of our samples down to a millimetre scale. There was no systematic relation between the location of CASs and the soil macropore structure.We are convinced that the approach proposed here will strongly aid the development of more realistic soil system models. [ABSTRACT FROM AUTHOR]

Despite significant advances during the last decades, there are still many processes related to nonequilibrium flow and transport in macroporous soil that are far from completely understood. The use of X-rays for imaging time-lapse 3-D solute transport has a large potential to help advance the knowledge in this field. We visualized the transport of potassium iodide (20 g iodide l−1 H2O) through a small undisturbed soil column (height 3.8 cm, diameter 6.8 cm) under steady state hydraulic conditions using an industrial X-ray scanner. In addition, the electrical conductivity was measured in the effluent solution during the experiment. We attained a series of seventeen 3-D difference images which we related to iodide concentrations using a linear calibration relationship. The solute transport through the soil mainly took place in two cylindrical macropores, by-passing more than 90% of the bulk soil volume during the entire experiment. From these macropores the solute diffused into the surrounding soil matrix. We illustrated the properties of the investigated solute transport by comparing it to a 1-D convective-dispersive transport and by calculating the temporal evolution of the dilution index. We furthermore showed that the tracer diffusion from one of the macropores into the surrounding soil matrix could not be exactly fitted with the cylindrical diffusion equation. We believe that similar studies will help establish links between soil structure and solute transport processes and lead to improvements in models for solute transport through undisturbed soil. [ABSTRACT FROM AUTHOR]

Soil structure influences water infiltration, aeration and root growth and, thereby, also the conditions for sustainable crop production. Our objective was to quantify the effects of different soil management methods, with a focus on liming, on the topsoil structure of clay soils in Sweden. We sampled 32 intact soil columns (18 cm high, 12.7 cm diameter) from an experimental field with four treatments: conventional tillage (CT), conventional tillage followed by liming (CTL), reduced tillage (RT) and unfertilized fallow (UF). The samples were taken in autumn after harvest, seven years after CaO was applied to the CTL plots. We also sampled in total 72 smaller columns (6 cm high, 6 cm diameter) from the same experiment and from two additional liming experiments where a mixture of Ca(OH)2 and CaCO3 had been applied three years prior to sampling. All columns were analysed using X-ray tomography. One soil aggregate (diameter approximately 5 mm) were isolated from each small column and analysed with the same method. Despite a relatively large number of replicates per treatment for the large columns, there were no significant differences between any of the investigated macropore network properties related to tilled treatments. It is possible that the effects of liming on soil structure was limited to a few years, which means that any effect would have diminished by the time of sampling. The UF treatment, in contrast, exhibited more vertically oriented macropores, which were also better connected compared to the other treatments. This confirms previous findings that tillage may disrupt the vertical continuity of macropore clusters. Liming had generally reduced total imaged porosity for pores >100 μm) for the smaller columns resulting in less connected pore networks. Liming had no significant effects on the pore networks (pores>11 μm) of the aggregates. [ABSTRACT FROM AUTHOR]

The freezing of water porous media is a complex process dependent, among other effects, on pore size distribution and shape of particles. Magnetic resonance imaging (MRI) of freezing and thawing process was performed on two samples of different porous materials, each one in two replicates. The soil freeze sample assembly consisted of two Plexiglas cylinders, the outer dimensions of the set-up was 6 cm in diameter and 12.5 cm high. The inner cylindrical container (3 cm in diameter, 6 cm high) was filled with the sample material. The inner cylinder was insulated by vacuum. On the top of the porous media, a glass disk (2.8 cm in diameter, 1 cm thickness) was placed to define the upper boundary of a material during freezing and thawing. One inflow tube and two outflow tubes at the top of the inner cylinder were used for circulation of cold nitrogen gas as a freezing medium to the top of the sample. The temperatures of the freezing medium were continuously recorded by the temperature sensors located outside of the MR coil. The first sample packing consisted of 72 glass beads, 0.8 cm in diameter immersed in the 1 mM/L GdDTPa2-∙2Na+. In the second sample, the coarse sand was packed in 0.5 cm thick layers in the same sample solute. Total eight freezing-thawing cycles were performed and recorded on the samples. As a result, time-lapse series of 3D MR images were obtained. The geometric distortion of these 4D MR images due to magnetic field inhomogeneity had to be elaborated prior to the process analysis. The analyses of the freezing-thawing process on glass beads revealed interesting effects while thawing, where the thin layers on the glass beads surface exhibited faster melting in otherwise homogeneous ice. The impact of MRI heat transfers has to be evaluated. The freezing-thawing fronts recorded of sand samples were relatively uniform. Small changes in sand structure as a consequence of volumetric ice-water changes are studied. The spatiotemporal analysis of the frozen water volume is done. The data are available for a two-phase ice-water simulation models evaluation. [ABSTRACT FROM AUTHOR]

Soil samples with a volume of approximately 100 mL are commonly used for measuring soil properties needed to parameterize continuum models of transport processes in soils. The necessary assumption that the sampled soil volume corresponds to a representative elementary volume (REV) has only been occasionally tested. Furthermore, the few studies so far have focused on bulk properties such as porosity and bulk density and have not investigated the scale-dependence of pore-space connectivity, which is fundamental for transport properties such as the permeability of soil. In this study, we investigated the scale-dependence of morphologic properties of the soil pore-space in 25 undisturbed soil columns sampled from five different depths (8, 23, 33, 53 and 73 cm) from a field site in southern Norway (Skuterud). The analyses of scale-dependence were conducted on regions of interests of dimensions 4 x 4 x 4 cm3 from binarized X-ray images with a resolution of 40 microns. We focused our evaluation on imaged porosity and five measures of pore-space connectivity, i.e. percolation probability, percolating porosity, critical pore diameter, connection probability and the Euler-Poincaré number. As pore network connectivity is scale-dependent and because the connectivity of large pores has a very strong impact on the soil permeability, we conducted our analyses considering three contrasting minimum pore diameters, namely 80, 250 and 500 microns. Our results show individual scaling-characteristics of all investigated measures for all 25 soil samples. Plateau-regions in the scale-relationships, which occurred at scales between 2 and 4 cm, were only observed for the imaged porosity for the samples taken from depths of 8 and 33 cm. This indicates that the soil volume of 64 cm3 did not constitute a REV for the connectivity measures. The scaling-characteristics for the analyses with different minimum pore diameters were similar for the porosity, but diverged significantly for the connectivity measures, with the larger pores showing poorer connectivity. These results call into question the suitability of 100 mL samples for measuring properties that strongly depend on the connectivity of larger soil pores, (e.g. permeability) and also suggest that scale-effects deserve more attention in the modelling of soil systems. [ABSTRACT FROM AUTHOR]