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Sustainable intensification of agriculture requires understanding of the effect of soil characteristics and nutrient supply on crop growth. As farms are increasing in size by acquiring small fields from various farmers, the soil characteristics and nutrient supply might be very different from field to field, while at the same time specific soil properties might limit the nutrient uptake. As a result, there might be a large number of heterogeneous reasons why crop growth varies significantly. New data analysis techniques can help to explain variability in crop growth among fields. This paper introduces Exceptional Growth Mining (EGM) as a first contribution. EGM instantiates the data mining framework Exceptional Model Mining (EMM) such that subgroups of fields can be found that grow exceptionally in terms of three growth parameters (high/low maximum growth, steep/flat linear growth and early/late midpoint of maximum growth). As second contribution, we apply EGM to a case study by analyzing the dataset of a potato farm in the south of the Netherlands. EGM consists of (i) estimating growth curves by applying nonlinear mixed models, (ii) investigating the correlation between the estimated growth parameters, and (iii) applying EMM on these growth curve parameters using a growth curve-specific quality measure. By applying EGM on the data of the potato farm, we obtain the following results: 1) the estimated growth curves represent the variability in potato tuber growth very well (R2 of 0.92), 2) the steepness of the growth curve has a strong correlation with the maximum growth and the midpoint of maximum growth, and the correlation between the midpoint of maximum growth and maximum growth is weak, 3) the subgroup analyses indicate that: high values of K correspond to high maxima; low values of K correspond to low maxima, steep growth curves', and a late midpoint of halfway growth; Mg influences the midpoint of the growth curve; values of B are higher on dry soils with high tuber growth, while low values of B are found on wet soils with high tuber growth; high values of Zn, Mn, and Fe are found in subgroups with low tuber weight, probably related to the soil's low pH. In summary, this paper introduces EGM to obtain understanding in crop response to soil properties and nutrient supply. In addition, EGM provides a way to analyze only small parts of a large dataset, such that the impact of soil factors on growth can be analyzed on a more detailed level than existing methods. [ABSTRACT FROM AUTHOR]

This paper presents an experimental and numerical investigation of RCC (Reinforced Concrete) piles with helical grooves under axial and lateral loads in cohesionless soil. A set of experiments is carried out to assess the performance of RCC piles with helical grooves. To replicate the experimental findings, the Finite Element Method (FEM) is employed using Abaqus software. Three-dimensional (3D) models are created to represent both the pile and the soil using Abaqus. The paper compares settlement characteristics and lateral displacement of plain RCC piles and RCC piles with helical grooves. This study also evaluates the impact of varying the pitch of helical grooves on enhancing pile performance. The results indicate that RCC piles with helical grooves outperform plain RCC piles in terms of both axial and lateral load-carrying capacity, inferred from both experimental and analytical techniques. [ABSTRACT FROM AUTHOR]

The construction of airport runways or other infrastructures on soft soil might risk damage and create potential hazards if inappropriate foundation treatments have been conducted. Preloading on soft soil is a commonly used ground improvement method in airport runway construction, owing to the cost efficiency and simplicity of this method. However, the theoretical basis for the design parameter estimation of this method has not been fully understood, for example, preloading height calculation and preloading time determination. In this paper, calculation models of settlement characteristics for soft soil preloading treatment and influence factors of preloading for soft soil are proposed, in accordance with Terzaghi one-dimensional consolidation theory. Preloading is counted as a dynamic process in this theory, and the settlement calculation model is expressed as an integration formula. In addition, a simplified calculation model is proposed in this paper for a specific condition of preloading treatment. Reliability of the models was verified with in situ data from an airport runway construction site in China. Results from multiple analysis reveal that preloading treatment can significantly increase the total settlement and consolidation, and accelerate the settlement rate of soft soil. Sensitivity analysis of the theoretical model found that preloading height is the key parameter affecting the preloading efficiency when ignoring the material type of soft soil. Moreover, the thickness of soft soil is the critical input parameter, as analyzing the factors affects the preloading height, and preloading treatment is a continues process rather than an instantaneous process, as can be noted from analyzing the settlement characteristics of the two loading conditions. The proposed settlement characteristic model provides valuable information for the design of preloading parameters of similar projects. Preloading is a simple and widely used method for improving the strength of soft soil; the design of preloading parameters mainly relies on the construction of a trial site or engineering judgment. The theoretical basis of this method is still weak. Thus, this paper proposes a settlement characteristic model under preloading conditions, which was verified by utilizing in situ data from an airport runway construction site. In addition, the influences of design parameters on such settlement characteristics as preloading height and thickness of backfill soil were analyzed. It was found that preloading height is the key parameter affecting the settlement characteristics of preloading treatment. In addition, sensitivity analysis was conducted on the preloading height design using an analytical model, and the results show that the thickness of soft soil is the critical factor affecting the preloading height. In that case, accurate site investigation is significant for the preloading design of soft soil. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to develop an appropriate machine learning model for predicting soil compaction degree while also examining the contribution rates of three influential factors: moisture content, electrical conductivity and temperature, towards the prediction of soil compaction degree. Design/methodology/approach: Taking fine-grained soil A and B as the research object, this paper utilized the laboratory test data, including compaction parameter (moisture content), electrical parameter (electrical conductivity) and temperature, to predict soil degree of compaction based on five types of commonly used machine learning models (19 models in total). According to the prediction results, these models were preliminarily compared and further evaluated. Findings: The Gaussian process regression model has a good effect on the prediction of degree of compaction of the two kinds of soils: the error rates of the prediction of degree of compaction for fine-grained soil A and B are within 6 and 8%, respectively. As per the order, the contribution rates manifest as: moisture content > electrical conductivity >> temperature. Originality/value: By using moisture content, electrical conductivity, temperature to predict the compaction degree directly, the predicted value of the compaction degree can be obtained with higher accuracy and the detection efficiency of the compaction degree can be improved. [ABSTRACT FROM AUTHOR]

The paper presents the research steps necessary to evaluate the effects of human activities on the soils of the Sureanu Mountains and to create an integrated cartographic model that will highlight areas with qualitatively and/or quantitatively degraded soils. The first stage consisted in the acquisition of information necessary for correlations between different data sets, for theoretical modeling, and for guiding future field research. This stage resulted in the creation of an ARCGIS database, with vector and raster data. The second stage consisted mainly of field research and recording the data obtained. 349 soil thickness measurements were made from as many observation points. Soil samples were taken from 115 observation points, which were dried and are to be ground for laboratory physico- chemical analyses. [ABSTRACT FROM AUTHOR]

This study demonstrates the efficacy of employing Rhizopus oryzae fungus inoculum as a potential solution to improve soil erodibility in coastal environments. A set of unconfined compression tests is conducted on Miami Beach sand treated with a R. oryzae inoculum. Our findings suggest that the R. oryzae fungus inoculum effectively improves the stability of sand by acting as a natural binding agent. This finding aligns with previous studies that utilized different Rhizopus species, such as Rhizopus oligosporus, to improve sand properties. However, a notable difference is observed; the R. oryzae-treated sand exhibits remarkable durability, maintaining significant strength over an extended period without water or dietary supply. The durability is likely attributable to the morphological characteristics of R. oryzae that extensively branches its mycelial network. This paper shares the new discovery to the bio-geotechnics research community, potentially allowing for the customization of soil improvement process by choosing between the fast-acting R. oligosporus and the longer-lasting R. oryzae. [ABSTRACT FROM AUTHOR]

This paper established a numerical model for the structure system in a soil–structure interaction using MATLAB 23.2 and ANSYS 24.1 software and validated the effectiveness and accuracy of a simplified nonlinear calculation model for soil–structure interaction through the numerical simulation results. Meanwhile, a list of key parameters was identified according to their influence on the simplified model, including the free field area, site soil parameters, equivalent soil area, superstructure size and number of stories, and input seismic waves. On this basis, a series of parametric investigations were carried out with the validated simplified model, by varying the selected key parameters. The research findings demonstrated that the simplified calculation model exhibited excellent accuracy and efficiency, and was capable of reflecting the nonlinear response of the structural system. It is applicable to the field of dynamic response analysis of the superstructure, considering soil–structure interaction. [ABSTRACT FROM AUTHOR]

Geography is a discipline rooted in the idea of 'earth writing', yet until recently human geographers had left the study of the very matter of the earth – the soil beneath our feet – to natural scientists. If human geographers – amongst other humanities scholars – have begun to address human-soil relationships there is a need to attend to meanings invested in and generated by being with the soil. This paper attempts to address this by analysing the relationship with the soil by those who made their living by tilling and tending it, rural agricultural workers, those who laboured on (and in) the soil. Specifically, it focuses on the 'long 19th century', the period at the start of which when labourers remained the largest occupational sector but when agricultural 'improvement', industrialisation and rapid urbanisation were challenging human-soil entanglements. Drawing upon novels, poetry and biographical writing, this paper plots three key ways in which the relationship between rural workers and the soil was figured: as the link to the past; as inheritance, the promise of the future; and through the affective nature of tilling. In so thinking about these multi-layered meanings, the paper shows not only the value of excavating past human-environmental entanglements but also the need to adopt a cultural geographical methodology and sensibility. In sum, it is shown that soil was a crucible not just of life but of meaning in life. [ABSTRACT FROM AUTHOR]

The Peters–Durner–Iden (PDI) model system for describing soil hydraulic properties (SHP) has been developed over a decade. Inspired by Rien van Genuchten's seminal work, the PDI system focuses on an efficient and simple parameterization of water retention curves and hydraulic conductivity curves (HCC) across the entire soil moisture spectrum. By combining capillary and non‐capillary components for water retention and conductivity, it aims to reconcile mathematical simplicity and insights on water adsorption and film flow in soils. Recent developments have reduced the number of free parameters of the conductivity model to zero, enhancing the model's applicability in cases of limited data availability. The first reduction was achieved by a prediction of absolute non‐capillary conductivity based on the consideration of film and corner flow on the pore scale, and the second by a prediction of absolute capillary conductivity by a capillary bundle model. This allows a complete characterization of SHP over the entire moisture range with only four retention curve parameters. The inclusion of a maximum pore size in the capillary conductivity model prevents an unrealistic drop of the HCC near saturation. This paper provides a comprehensive overview of the PDI model system, emphasizing its conceptual features and mathematical details. An Excel sheet and a Python code stored in a repository are provided for accessibility. Core Ideas: Compact and comprehensive mathematical overview of the current PDI system.The model integrates elements of capillary and non‐capillary soil water storage and conductivity in a simple manner.Hydraulic conductivity can be completely predicted from the retention curve.Improved applicability in cases where conductivity data are scarce or available only in a limited moisture range. [ABSTRACT FROM AUTHOR]

The rise of industrialized agriculture, coupled with a global demographic shift toward urbanization, has marginalized every‐day connections between individuals and soils. This societal shift has led to a decline in the appreciation of and cultural identity with soils. Amid a broader movement aimed at fostering soil awareness and environmental action, many artists and designers have been instrumental in bringing soils to the cultural mainstream, figuring their esthetic, social, political, and ecological dimensions. Contemporary artists place great importance on the underlying idea of animating soils through artistic practice, often transcending the physical artifact itself to assign agency to soils and the myriad beings that occupy them. Artists harness a multitude of media to articulate human‐soil relationships. From the early environmental art movements of the 1960s and 1970s to contemporary works centered on urban and industrial brownfields, soils' multifaceted roles in CO2 transformation, water and nutrient cycling, agriculture, and as living bodies buffering against pollution have become ground for public discourse. What could this mean for the vadose zone in terms of reflecting on material flows in porous media beyond understandings of soil physics? In this paper, we draw on over 20 years of experience in studying the portrayal of soil in various arts genres to deliberate the potential of creative thinking about and thinking with the vadose zone. Core Ideas: Soil scientists need to actively engaging with artists, designers, and cultural practitioners to bring soil topics to a wider audience.We support fostering teaching collaboration across disciplines and transdisciplinary exchange.We aspire to reform the structure of research funding. [ABSTRACT FROM AUTHOR]

In this paper, a series of true triaxial tests with different intermediate principal stress ratios are conducted on both the lunar soil simulant and the sandy soils on earth using the discrete element method. An advanced discrete element servomechanism based on polyhedral specimen configuration is implemented such that true triaxial loading paths can be implemented under low confining pressure without introducing severe stress concentration. The high frictional angle and apparent cohesion of the lunar simulant are captured by employing a highly efficient contact model that fuses rolling resistance and van der Waals forces. The employed micro-scale parameters are calibrated based on the triaxial test results of the CSU-LRS-1 lunar soil simulant. The simulation results show that the lunar soil simulant exhibits lower shear strength with an increasing intermediate principal stress ratio. Generally, although the lunar soil simulant has a greater void ratio than that of sandy soils, the former exhibits significantly stronger shear-induced dilatancy and higher shear strength. The evolution of the load-bearing structure is quantified through a contact-normal-based fabric tensor. The interplay between internal structure evolution and external loadings can well explain the difference in mechanical behavior between lunar soil simulant and sandy soils on earth. [ABSTRACT FROM AUTHOR]

The first and fully validated smoothed particle hydrodynamics (SPH) model is presented to tackle coupled flow–deformation problems in unsaturated porous media that undergo large deformation and post-failure behaviour. Unlike the commonly adopted double-layer SPH framework for saturated soils, this paper presents a three-phase single-layer SPH model capable of predicting anisotropic seepage flows through porous media and their complete time-dependent transition from unsaturated to saturated states, as well as their influence on the mechanical behaviour of the porous media and vice versa. The mathematical framework is developed based on Biot's mixture theory and discretised using the authors' recently developed novel SPH approximation scheme for the second derivatives of a field quantity. The soil is modelled using a suction-dependent elastoplastic constitutive model, expressed in terms of effective stress and suction. In addition, an adaptive two-timescale scheme is proposed for the first time to address existing challenges in solving coupled-flow large-deformation problems that involve a significant difference in the timescale required for the solid and fluid phases. The capability of the proposed SPH model was demonstrated through fundamental consolidation tests and a large-scale rainfall-induced slope failure experiment. Very good agreements with theoretical solutions and experimental results are achieved, suggesting that the proposed SPH model can be readily extended to solve a wide range of large-scale geotechnical applications involving coupled unsaturated seepage–deformation problems. [ABSTRACT FROM AUTHOR]

Pile-supported embankments, with advantages of high bearing capacity and effectiveness, have been widely used for constructing embankments on soft ground. The long-term load transfer and cumulative deformation mechanism caused by traffic loading are crucial to pile-supported embankment design and maintenance. A three-dimensional (3D) finite-element model of a pile-supported embankment to investigate its long-term load transfer and cumulative deformation mechanism under traffic loading is presented in this paper. The dynamic nonlinear behavior of the soft ground is considered by a simplified dynamic constitutive model that that has been effectively incorporated into the Abaqus program. In comparison with the results of published literatures, the applicability and accuracy of the proposed finite-element model are well verified at first. Then, the long-term load transfer and deformation mechanism are revealed by investing the soil arching and the cumulative deformation with a series of 3D numerical modeling. Furthermore, the influences of traffic loading type, speed of the vehicle, pile spacing, and total number of layers of grid on the long-term load transfer and deformation mechanism of the pile-supported embankment are investigated. [ABSTRACT FROM AUTHOR]

Geosynthetics have increasingly been applied to geotechnical engineering works due to their numerous advantages, including cost-effectiveness and their significant role in sustainable development. When geosynthetics are used as reinforcement in earth structures, such as embankments, retaining walls and bridge abutments, soil–geosynthetic interface shear behavior is a critical parameter involved in the design. This paper presents a series of monotonic and cyclic/post-cyclic pullout tests carried out to examine the apparatus scale effect on the pullout response of a geogrid embedded in two different soils. To assess the small-scale equipment feasibility, comparisons were made between pullout test parameters derived from small- and large-scale equipment. The test results indicate that, under a low confining stress of 25 kPa, using a smaller-sized apparatus results in lower values of geogrid pullout resistance and maximum mobilized shear stress, but higher values of confined tensile stiffness at low strains. On the other hand, as the confining stress increases (i.e., 50 kPa and 100 kPa), the difference between the results becomes less significant and similar trends are observed regardless of the equipment type. Adopting small-scale equipment enables obtaining soil–reinforcement interaction parameters using test procedures that are less time-consuming than those associated with large-scale pullout tests. However, proper scale effect correction factors may be considered for more consistent estimates of the interface strength parameters under low normal stress values. [ABSTRACT FROM AUTHOR]

In this paper, a study of the cyclic plastic creep phenomenon during cyclic loading was performed. The plastic creep phenomena in the field of soil cyclic loading are defined as a process that occurs under a medium stress state and leads to excessive accumulation of plastic strains. Recent literature shows the existence of plastic creep, which is a part of the shakedown theory for cohesive soils. Nevertheless, when the soil is subjected to a relatively small stress state, the axial plastic strain may occur as a phenomenon called abation, where plastic strain increment occurs in a constant decreasing manner. Cyclic triaxial tests were performed to understand the abation. The results indicate a specific phase in soil response, such as pre-failure stages marked by pore pressure increase and subsequent effective stress reduction, indicating a steady state during repeating loading. In this paper, the proposition of a cyclic plastic creep mechanism based on test results is presented. The soil response was divided into three phases based on the pore pressure, stress paths, resilient modulus, and plastic strain change analysis. [ABSTRACT FROM AUTHOR]

Increased warming in the Arctic is of great concern. This is particularly due to permafrost degradation, which is expected to accelerate microbial breakdown of soil organic carbon, with its further release into the atmosphere as carbon dioxide (CO2). The fine-scale variability of CO2 fluxes across highly mosaic Arctic tundra landscapes can provide us with insights into the diverse responses of individual plant communities to environmental change. In the paper, we contribute to filling existing gaps by investigating the variability of CO2 flux rates within different landscape units for dominant vegetation communities and plant species across typical tundra of the southern part of the Taimyr Peninsula, Siberia. In general, the variability of soil CO2 flux illustrates a four-fold increase from non-vascular vegetation, mainly lichens and mosses (1.05 ± 0.36 µmol m−2 s−1), towards vascular plants (3.59 ± 0.51 µmol m−2 s−1). Barren ground ("frost boils") shows the lowest value of 0.79 ± 0.21 µmol m−2 s−1, while considering the Arctic "browning" phenomenon, a further substantial increase of CO2 flux can be expected with shrub expansion. Given the high correlation with top soil temperature, well-drained and relatively dry habitats such as barren ground and non-vascular vegetation are expected to be the most sensitive to the observed and projected temperature growth in the Arctic. For mixed vegetation and vascular species that favor wetter conditions, soil moisture appears to play a greater role. Based on the modeled seasonal pattern of soil CO2 flux and precipitation records, and applying the rainfall simulations in situ we outlined the role of precipitation across enhanced CO2 emissions (i.e., the "Birch" effect). We found that a pulse-like growth of soil CO2 fluxes, observed within the first few minutes after rainfall on vegetated plots, reaches 0.99 ± 0.48 µmol m−2 s−1 per each 1 mm of precipitation, while barren ground shows 55–70% inhibition of CO2 emission during the first several hours. An average additive effect of precipitation on soil CO2 flux may achieve 7–12% over the entire growing season, while the projected increased precipitation regime in the Arctic may strengthen the total CO2 release from the soil surface to the atmosphere during the growing season. [ABSTRACT FROM AUTHOR]

Soil concrete is a material produced by mixing the soil at the site with a hydraulic binder. This paper aims to study the influence of the nature of binder on the physical and mechanical properties of soil concrete. For the mixtures, three types of soil were chosen and studied: sandy clay with a granular class of 0/5 (SA5), laterite with a granular class of 0/5 (LA5), and laterite with a granular class of 0/10 (LA10). Three different cements were used: CEM I 52.5, CEM II 42.5, and CEM III 32.5, with cement contents of 150 and 250 kg/m3. The soil concretes were designed for a constant spread of 32–33 cm measured on a mini-slump. The results showed that LA5-based soil concrete has a higher water content of about 8.8% more than SA5 and LA10-based soil concretes. For all the mixtures, the lowest porosity values were obtained with CEM III 32.5, followed by CEM I 52.5, and finally CEM II 42.5. For the three types of cement and the same soil granular size, the compressive strength, static, and dynamic modulus of SA5-based soil concretes are higher than LA5. It was noted that the mechanical properties of soil concretes made with CEM III 32.5 are higher than those made with CEM I 52.5 and CEM II 42.5. Regardless of the type of cement used, the mechanical properties obtained on LA10-based soil concrete are higher than those on LA5-based soil concrete. [ABSTRACT FROM AUTHOR]

Soil properties can vary significantly within a given site, making geotechnical analysis highly amenable to a probabilistic treatment in which properties are described statistically. The random finite-element method (RFEM) is the only method available to properly account for spatial variability of soil properties and has been applied to numerous geotechnical applications. Of all the commonly encountered soil properties, permeability is generally considered to be one of the most variable. The current paper revisits steady seepage beneath a sheet pile wall of varying length in spatially random soil of finite depth, with a focus on the exit gradient. The spatial correlation length of permeability is shown to have a striking influence on the statistics of the exit gradient, with a pronounced worst-case spatial correlation length corresponding to the highest probability of downstream piping and erosion. [ABSTRACT FROM AUTHOR]

Achieving climate targets requires mitigation against climate change but also understanding of the response of land and ocean carbon systems. In this context, global soil carbon stocks and their response to environmental changes are key. This paper quantifies the global soil carbon feedbacks due to changes in atmospheric CO 2 , and the associated climate changes, for Earth system models (ESMs) in CMIP6. A standard approach is used to calculate carbon cycle feedbacks, defined here as soil carbon-concentration (βs) and carbon-climate (γs) feedback parameters, which are also broken down into processes which drive soil carbon change. The sensitivity to CO 2 is shown to dominate soil carbon changes at least up to a doubling of atmospheric CO 2. However, the sensitivity of soil carbon to climate change is found to become an increasingly important source of uncertainty under higher atmospheric CO 2 concentrations. [ABSTRACT FROM AUTHOR]

This paper presents the design of an integrated potato-planting machine capable of full-film covering, creating micro-ditches on ridges, and covering seed rows with soil. The machine addresses the challenges of traditional methods, allowing for mechanized planting with complete film coverage and individual seed row soil covering. The key components of the prototype were analyzed and designed. This includes the seeding system, the pointed wing-shaped trencher for creating micro-ditches, and the straddling film-mulching device. Additionally, the operating mechanism of these core components was analyzed. Field trials demonstrated an 85% success rate for seed depth placement under the film. The machine also achieved a 90% qualified index for seed potato spacing, with a 6% repetitive seeding rate and a 3% missed seeding rate. Furthermore, the qualified rate for covered soil width on seed rows was 94%, and the qualified rate for covered soil thickness was 93%. The adjacent row spacing achieved an 88% success rate. The degree of mechanical damage to the exposed surface of the mulch film was minimal, at only 30.2 mm2/m2. These results meet all the national and industry standards. The successful field trials confirm the effectiveness of the machine in performing integrated fertilization, sowing, ridging, full-film covering, and seed row soil covering. Compared to traditional methods, this machine significantly reduces labor intensity for farmers and enhances the economic value of potato planting. [ABSTRACT FROM AUTHOR]

Cement-stabilized soil is a commonly used pavement base/bottom base material. Adding a suitable curing agent to cement-stabilized soil can effectively reduce the dosage of cement, meet the strength requirements, and also greatly improve its water stability. In this paper, three kinds of cement dosage (6%, 8%, and 10%) of cement-stabilized soil were selected to add a 0.04% organic liquid curing agent, and then compared with high-dose cement (10% and 12%)-stabilized soil. The influence of wetting–drying cycles on the mechanical properties of the five stabilized soils was discussed. The mineral composition of cement-stabilized soils before and after the addition of a curing agent was analyzed by X-ray diffraction (XRD), and the microscopic morphology of 10% cement-stabilized soils with a curing agent was studied by scanning electron microscopy (SEM). The macroscopic test shows that the unconfined compressive strength of solidified cement-stabilized soil can be divided into three stages with the increase in the times of the wetting–drying cycles, which are the rapid decay stage, stable enhancement stage, and stable decay stage. The wetting–drying stability coefficient first increases, and then decreases with the increase in the times of the wetting–drying cycles. The microscopic test shows that the addition of a curing agent can enhance the content of hydration products in the cement-stabilized soil specimen; at the curing age of 28 d, with the increase in the times of the wet–dry cycles, the structure of the solidified cement-stabilized soil gradually broke down. The surface porosity P and pore diameter d showed an overall upward trend but decreased at the fifth wetting–drying cycle. The pore orientation weakened. The results show that the resistance of cement-stabilized soil with a curing agent is obviously better than that of cement-stabilized soil under wet–dry conditions. [ABSTRACT FROM AUTHOR]

Soil-improvement techniques with binders are used in several geotechnical engineering applications as a sustainable solution for the reuse of waste soils. Due to their inherent complexity and their mechanical behaviour, pyroclastic soils are generally considered waste geomaterials in their natural state. Lime treatment of pyroclastic soils can be considered a viable solution for their reuse in geotechnical applications. In this paper, some peculiar features of the chemo-physical evolution and mechanical behaviour of lime-treated pyroclastic soils are evidenced through a multi-scale experimental investigation. While, for clayey soils, the fine fraction is mainly responsible for ion exchange and pozzolanic reactions induced by lime, for pyroclastic soils, pozzolanic reactions are dominant processes due to the low quantity of clay minerals along with the abundance of aluminates and silicates as the main constituents of their amorphous phase. The link between the phenomena detected at the microscale level, the mineralogical composition, and the macroscopic behaviour of two lime treated pyroclastic soils of different origin is explored through a multiscale approach. [ABSTRACT FROM AUTHOR]

The assessment of soil contamination in the vicinity of integrated siderurgical plants is of outmost importance for agroecosystems and human health, and sensitive techniques should be employed for accurate assessment of chemical elements (metals, potential toxic elements, rare earths, radioelements) in soil and further evaluation of potential ecological and safety risk. In this paper a total of 45 major, minor and trace elements (Al, As, Au, Ba, Br, Ca, Cd, Ce, Co, Cr, Cs, Cu, Dy, Eu, Fe, Hf, Hg, I, K, La, Mg, Mn, Mo, Na, Nd, Ni, Pb, Rb, Sb, Sc, Sm, Sn, Sr, Ta, Tb, Th, Ti, Tm, U, V, W, Y, Yb, Zn and Zr) were quantified in soils located around a large siderurgical works (Galati, SE Romania) using instrumental neutron activation analysis (INAA) in combination with X-ray fluorescence (XRF) and inductively coupled plasma mass spectrometry (ICP–MS). The statistical analysis results and vertical distribution patterns for three depths (0–5 cm, 5–20 cm, 20–30 cm) indicate inputs of toxic elements in the sites close to the ironmaking and steelmaking facilities and industrial wastes dumping site. For selected elements, a comparison with historical, legislated and world reported concentration values in soil was performed and depth migration, contamination and toxic risk indices were assessed. The distribution of major, rock forming elements was closer to the Upper Continental Crust (UCC), and to the Dobrogea loess, a finding confirmed by the ternary diagram of the incompatible trace elements Sc, La and Th, as well as by the La to Th rate. At the same time, the La/Th vs. Sc and Th/Sc vs. Zr/Sc bi-plots suggested a felsic origin and a weak recycling of soils' mineral components. [ABSTRACT FROM AUTHOR]

This paper proposes an efficient geotechnical reliability analysis framework that integrates the advantages of the first-order reliability method (FORM) and the Karhunen-Loève expansion (KL) to evaluate the reliability of spatially variable soil slopes. The improved Hasofer-Lind-Rackwitz-Fiessler (iHLRF) recursive algorithm is adopted to implement the FORM procedure when coupled with finite element codes for slope stability analysis, and the KL is used to reduce the dimension of random variables representing the soil random fields. To enhance the accuracy of the failure probability estimated by KL-iHLRF, the importance sampling (IS) is also conducted in this study, resulting in an innovative slope reliability analysis framework, KL-iHLRF-IS. It is found that although the FORM analysis by itself may not be able to confidently estimate the failure probability of spatially variable soil slopes because of the very high dimension of random variables and the strong nonlinearity of the limit state function, it provides useful information on the design point values for KL-iHLRF-IS to rapidly compute the failure probability. The efficiency of KL-iHLRF-IS for slope reliability analysis is illustrated by three example slope case studies. The proposed framework is particularly useful when fast yet accurate slope reliability analysis using the finite element method is needed. [ABSTRACT FROM AUTHOR]

Background and aims: The frequent occurrence of extreme rainfall events results in soils experiencing drying–rewetting (DRW) cycles. Such rewetting can lead to a surge in soil CO2 emissions; however, the main regulatory factors involved in this priming effect are unclear. Methods: In this study, we conducted a meta-analysis using data extracted from 43 published papers, to determine the direct regulatory factors involved in the priming effect of soil CO2. Results: The results indicated that the priming effect of rewetting on soil CO2 emissions was influenced by ecosystem type, soil properties, climatic factors, and the number of DRW cycles. The priming effect was the highest in cropland but the lowest in grassland when taking flux values observed before rewetting as the control group. It was also greater in acidic soils (pH < 6.5) and soils with a high clay fraction (clay ≥ 30%) than in other soils. The effect size (lnRR) of soil CO2 emissions was exponentially related to the mean annual precipitation (MAP), and decreased with increases in MAP. In DRW experiments, the priming effect of the first rewetting on soil CO2 emissions was the largest, an effect that gradually decreased with the number of DRW cycles, before disappearing completely. Most importantly, soil moisture influenced the peak time and the pulse time of the priming effect: the greater the change in soil moisture, the longer the peak time duration; the higher the maximum soil moisture content after rewetting, the longer the pulse time duration; and the lower the initial soil moisture content, the bigger the priming effect. Conclusion: Generally, physical mechanisms, especially soil moisture, directly regulate the CO2 priming effect during DRW cycles. Thus, this study provides a theoretical basis for assessing and predicting the impact of future precipitation changes on soil carbon cycling. Future studies should also carefully monitor any changes in soil microorganisms in response to changes in soil moisture during DRW cycles, because these appear to be significantly involved in CO2 release from soils. [ABSTRACT FROM AUTHOR]

The primary source of soil compaction is weight bearing down on the soil, which occurs frequently on agricultural land due to foot movement, livestock tramples, or the heavy weight of farm equipment. The primary cause of significant soil compaction is the driving of heavy machinery over moist soils. In this paper, the negative side of soil compaction and its influence on soil physical and chemical characteristics at the Awash Melkassa farm field located in Ethiopia were investigated. Compaction of soil test was taken at three different depths which are 10 cm, 20 cm, and 30 cm with the help of a hydraulically operated cone penetrometer integrated into the tractor. The three depths were expanded into 15 sample locations (designated as point A to point O) to collect 35 data points on soil compaction using a hydraulic-powered Spot-on digital soil cone penetrometer across a 0.6-hectare farmland area. A correlation analysis was conducted on the 15 sample points (A to O) to assess soil compaction in the field. In addition, soil samples were collected from specific farm locations at depths ranging from 0 to 10 cm, 10–20 cm, and 20–30 cm for subsequent physical and chemical tests in the laboratory. During the harvesting season, sample location A exhibited the highest soil compaction values, reaching 6,159 kPa, while the lowest values were observed at sample point F, measuring 327 kPa. For the seeding season, the sample point B showed the highest soil compaction values at 6,052 kPa, while the lowest values were recorded at sample point K, measuring 563 kPa. Moreover, the data indicates a consistent increase in soil compaction with depth during both experimental seasons. The laboratory test for soil texture revealed that the soil composition was classified as a clay loam, consisting of 36.7% sand, 30.3% clay, and 33% silt. The moisture content ranged from a high of 16.04% to a low of 13.97%. In addition, it was observed that total organic carbon, organic matter, and total nitrogen levels tend to rise with increased soil compaction, and conversely, decrease as soil compaction decreases. This study's insights are invaluable for agricultural mechanization. Given the substantial weight of farm machinery, comprehending soil properties and their correlation with compaction rates is imperative for optimizing farming practices. [ABSTRACT FROM AUTHOR]

Wildfires pose one of the greatest threats to the world's forests soils. After exposure to fire, forests lose many of their ecological functions; moreover, the repercussions can extend well beyond the forest itself, as the erosive processes attributable to the combustion of vegetation and the soil's lack of protection against rainfall are likely to impact any areas of a catchment, contaminating reservoirs, estuaries and aquifers. A forest fire is not solely, therefore, an environmental issue, but also a social and economic problem. The recovery of a forest is heavily dependent on just how the soil has been affected and how rapidly the latter can be restored. Fire intensity is critical in understanding the temporal evolution of the forest, while its location--a clear determinant of its climate and the ecosystem it occupies--can undermine the functionality of the forest system and is critical in determining the duration of the effects of the fire episode. This paper undertakes a review of the literature with the aim of understanding what might be understood when studies speak of the long-term effects of fire on the soil and when a soil might be considered to have recovered from these effects. What is evident is that many variables have a role to play and that not all soil properties recover at the same rate; indeed, some may never be restored to pre-fire levels. [ABSTRACT FROM AUTHOR]

The impact of climate change has become increasingly severe in forests, where droughts and strong winds on the one hand and extreme rainfall events on the other hand can damage forest ecosystems. To mitigate the effects of drought and enhance soil water retention capacity, three types of soil conditioners (SCs), labeled SC_R, SC_CG, and SC_ZZC, were developed as part of the European project ONEforest. All the conditioners are based on Xanthan gum and have different types and amounts of fillers with diverse cellulose fiber lengths. These can offer the potential to optimize the SC characteristics, e.g., water absorption, water retention, and mechanical stability. This paper focuses on the influence of fillers in the SCs on the geotechnical properties of forest soils from Ljubelj in the Alpine part of Slovenia (S1), Catalonia, northeastern Spain (S2), and Heldburg, Germany (S3). The results show an increase of 53% to 100% in the water absorption of treated soil. A less favorable impact of the SCs was found on the drained shear strength and the compressibility. The drained shear strength of untreated forest soils in a saturated state was S1 c′ = 4.4 kPa, φ′ = 33.5°; S2 c′ = 1.4 kPa, φ′ = 30.0°; and S3 c′ = 12 kPa, φ′ = 28.0°. The addition of SCs results in a reduction in the drained shear strength of saturated mixtures. The reduction depends on the dosage of added SC—whether it is a low (L) or a high (H) dosage. For instance, when the soil S1 was treated with a low dosage of the soil conditioner SC_R, it demonstrated a cohesion (c′) of 11 kPa and a friction angle (φ′) of 27.0°. However, increasing the dosage of the SC_R led to a decrease in both the cohesion and the friction angle for the same soil (c′ = 7.7 kPa, φ′ = 25.0°). Additionally, the type of soil conditioner also impacts the drained shear strength. Among the mixtures with a high dosage of the SC_R, SC_CG, or SC_ZZC, those containing the SC_CG with the longest fibers stand out, demonstrating the highest friction angle. Therefore, longer fibers can be a promising component of the SCs to reduce the negative influence of XG on the mechanical properties of treated soils. [ABSTRACT FROM AUTHOR]

Featured Application: Landowners, regional and national governments, and researchers can use predictions of the soil hydrological properties created in this work, such as wilting point, field capacity, macroporosity, and total available water content, to characterize soils for soil management decisions in New Zealand, e.g., in terms of irrigation requirements, or for policy, e.g., nutrient budgets and regulations. This paper describes a new pedotransfer function (PTF) for the soil water content of New Zealand soils at seven specific tensions (0, −5, −10, −20, −40, −100, −1500 kPa) using explanatory variables derived from the S-map soil mapping system. The model produces unbiased and physically plausible estimates of the response at each tension, as well as unbiased and physically plausible estimates of the response differences that define derived properties (e.g., macroporosity and total available water content). The PTF is a development of an earlier model using approximately double the number of sites compared with the earlier study, a change in fitting methodology to a semi-parametric GAM Beta response, and the inclusion of sample depth. The results show that the new model has resulted in significant improvements for the soil water content estimates and derived quantities using standard goodness-of-fit measures, based on validation data. A comparison with an international PTF using explanatory variables compatible with variables available from S-map (EUPTF2) suggests that the model is better for prediction of soil water content using the limited information available from the S-map system. [ABSTRACT FROM AUTHOR]

Based on 14 months of ethnographic research, this paper analyzes soil management within the plantation model of farmingin order to understand the extent to which life on large-scale monocultural farms can be controlled and directed toward extractiveproduction. Transnational soy farmers in Western Bahia Brazil 'correct' soils in the region to make them productive and marshal thisagronomic work to claim that they have added value to the land by 'building it up'. Still, the permeability of the plantation keepstransnational farmers from achieving their dreams of control. [ABSTRACT FROM AUTHOR]

Future field work tasks will require mountain tractors to pass through rough terrain with limited human supervision. The wheel–soil interaction plays a critical role in rugged terrain mobility. In this paper, an algorithm for the estimation of soil characteristic parameters based on the Simpson numerical integration method and Gauss–Newton iteration method is presented. These parameters can be used for passability prediction or in a traction control algorithm to improve tractor mobility and to plan safe operation paths for autonomous navigation systems. To verify the effectiveness of the solving algorithm, different initial values and soils were selected for simulation calculations of soil characteristic parameters such as internal friction angle, settlement index, and the joint parameter of soil cohesion modulus and friction modulus. The results show that the error was kept within 2%, and the calculation time did not exceed 0.84 s, demonstrating high robustness and real-time performance. To test the applicability of the algorithm model, further research was conducted using different wheel parameters of electric mountain tractors under wet clay conditions. The results show that these parameters also have high accuracy and stability with only a few iterations. Thus, the estimation algorithm can meet the requirements of quickly and accurately identifying soil characteristic parameters during tractor operation. A criterion for the passability of wheeled tractors through unknown terrain is proposed, utilizing identified soil parameters. [ABSTRACT FROM AUTHOR]

Purpose: Soil contamination is one of the most pressing environmental problems on a global scale. However, assessing the shape and size of an area where pollution occurs, and the spatial variation in the pollution level, is a complex issue. Field magnetometry is a cheap and fast tool for soil pollution assessment. The purpose of the paper is to systematically describe the history, current state, and potential future applications of geostatistical methods in field magnetometry. Materials and methods: The article was written based on over a hundred outstanding scientific papers describing soil research around the world using field magnetometry and geostatistical methods, combined with various secondary variables such as geochemical and diffuse reflectance spectroscopy measurements of soil as well as satellite observations. Results and discussion: Geostatistical methods allow for the optimal use of the magnetometric method in areas with different types of soils such as forests, arable fields, meadows, fallow lands, and urban areas as well as for the determination of spatial variability parameters of magnetic susceptibility. The use of geostatistical methods in field magnetometry also allows for a more accurate determination of other soil and environmental parameters significantly affecting the value of magnetic susceptibility, which must be taken into account when conducting field measurements. Conclusions: Both geostatistics and field magnetometry are considered groundbreaking methods in pedological research but even greater results arise from the simultaneous use of these methods. The synergy effect resulting from the use of geostatistical methods in field magnetometry allowed for the achievement of many significant scientific and practical findings. Especially, the cokriging method plays an increasingly important role in magnetometric research, thanks to the integration of magnetic susceptibility measurements with other types of measurements. [ABSTRACT FROM AUTHOR]

Predicting the cleaning time required to remove a thin layer of soil is a challenging task and subject of current research. One approach to tackle this problem is the decomposition into physical sub-problems which are modelled separately and the subsequent synthesis of these models. In this paper, an existing model for adhesive detachment is extended for the prediction of the cleaning time of cohesively separating soil layers. The extension is based on measurements of the pull-off forces and their correlation to the local water mass fraction. The resulting new model is validated using cleaning experiments with starch in a fully developed channel flow. Furthermore, an inhomogeneous soil distribution and its effect on cleaning results like cleaning time and removal rate is investigated. It is shown that accounting for the local soil distribution in the model leads to a significant improvement of the prediction of the cleaning behaviour. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of spatial variability of soil elastic modulus on the longitudinal responses of the existing shield tunnel to the new tunnel undercrossing using a random two-stage analysis method (RTSAM). The Timoshenko–Winkler-based deterministic method considering longitudinal variation in the subgrade reaction coefficient and the random field of the soil elastic modulus discretized by the Karhunen–Loeve expansion method are combined to establish the RTSAM. Then, the proposed RTSAM is applied to carry out a random analysis based on an actual engineering case. Results show that the increases in the scale of fluctuation and the coefficient of variation of the soil elastic modulus lead to higher variabilities of tunnel responses. A decreasing pillar depth and mean value of the soil elastic modulus and an increasing skew angle strengthen the effect of the spatial variability of the soil elastic modulus on tunnel responses. The variabilities of tunnel responses under the random field of the soil elastic modulus are overestimated by the Euler–Bernoulli beam model. The results of this study provide references for the uncertainty analysis of the new tunneling-induced responses of the existing tunnel under the random field of soil properties. [ABSTRACT FROM AUTHOR]

This paper dealt with the study of the analysis and interpretation of spatial variability using the Kriging technique in geostatistics. The objectives of this work are; to interpolate the values of regionalized variables; to express the spatial variation after using the logarithmic transformed for the original scale; observations for two groups of soil data; To reduce the level of pollution in the soil by studying the characteristics of the estimates. The ordinary kriging procedure is used to estimate the best linear unbiased estimator. The experimental semi-variogram function is applied as a tool to give the idea of spatial distribution after using the logarithmic transformations of the origin data. This method assumes the isotropy. Also, a robust estimate (Matheron's and Haslett's, Cressie-Hawkins) was applied to minimize some prediction scores. Data adopted in this work is taken from Mosul city in Iraq, for some soil spatial real data. Each data contains (100) real soil data of (PH) and (NO3). Our finding results illustrate the variance is itself for all directions of the compass: East-west, North-south, Northeast, and Northwest. The model describes (94%) nearest the Gaussian model of (PH), and (92%) nearest the spherical model of the total variability of (NO3) after comparing the results models between the original scale and the lognormal data by obtain the fitting model of soil data with the formulas of kriging. In conclusion, we show the qualities of the estimation rely on the ratio distances. Behaviors of continues of the phenomenon or observations and low coefficient of variation, which leads to improved efficiency in spatial distribution The support of results show that Matheron's and Haslett's robust estimators had better performance than Cressie Hawkins's robust soil data comparison with the curves of variogram function, because the small effect of outlier values on the estimates it is clear from this effect that pollution may be large by correctly knowing the weight restrictions for the level of pollution, and reducing the level of pollution depends practically and for a long period on the stationarity of some estimates. All computations are carried out in Matlab language. [ABSTRACT FROM AUTHOR]

The paper presents the results of systematic investigations on the gamma dose rates in air, natural radioactivity in soil and the dependence of radioactivity on the mineralogy of soils in the environs of the Belagavi, Karnataka, India. The gamma dose rates were measured using a portable survey metre and the activity in soils were measured using NaI(Tl) based gamma ray spectrometer and the mineral composition was studied using FTIR spectroscopy. The activity of 40K varies from 72.52 to 324.76 Bq kg−1 with an average of 153.17 Bq kg−1. The 226Ra activity varies from 16.53 to 70.53 Bq kg−1 with an average value of 23.88 Bq kg−1 and the activity of 232Th varies from 10.95 to 59.07 Bq kg−1 with an average value of 25.75 Bq kg−1. Elevated levels of 226Ra, 232Th and 40K in soils were observed in some part of Belagavi, which was traced to the mineralogy of the region. The higher activity of natural radionuclides poses radiological implications to the population of the region. The activity utilisation index was found to be is above the normal levels in some locations. The pattern of distribution of radionuclides in the region was studied using SPSS statistical software. The soil with clay minerals Haematite, Calcite, Kalonite, Albite and Feldspar showed higher radionuclide content. [ABSTRACT FROM AUTHOR]

The non-destructive study of soil micromorphology via computed tomography (CT) imaging has yielded significant insights into the three-dimensional configuration of soil pores. Precise pore analysis is contingent on the accurate transformation of CT images into binary image representations. Notably, segmentation of 2D CT images frequently harbors inaccuracies. This paper introduces a novel three-dimensional pore segmentation method, BDULSTM, which integrates U-Net with convolutional long short-term memory (CLSTM) networks to harness sequence data from CT images and enhance the precision of pore segmentation. The BDULSTM method employs an encoder–decoder framework to holistically extract image features, utilizing skip connections to further refine the segmentation accuracy of soil structure. Specifically, the CLSTM component, critical for analyzing sequential information in soil CT images, is strategically positioned at the juncture of the encoder and decoder within the U-shaped network architecture. The validation of our method confirms its efficacy in advancing the accuracy of soil pore segmentation beyond that of previous deep learning techniques, such as U-Net and CLSTM independently. Indeed, BDULSTM exhibits superior segmentation capabilities across a diverse array of soil conditions. In summary, BDULSTM represents a state-of-the-art artificial intelligence technology for the 3D segmentation of soil pores and offers a promising tool for analyzing pore structure and soil quality. [ABSTRACT FROM AUTHOR]

Antioxidants (AOX) in soils originate mainly from secondary plant metabolites and are pivotal in many redox processes in environment, maintaining soil quality. Still, little is known about the influence of land uses on their accumulation in soil. The aim of the paper was to determine the content of these redox-active compounds in the extracts of A horizons of abandoned fallows, arable and woodland soils. Total antioxidant capacity (TAC) of soils under various uses and vegetation was evaluated in different soil extracts using Folin-Ciocâlteu method. The contribution of humic acids to TAC was determined and antioxidant profiles estimated using the chromatographic GC–MS method. Forest soils exhibited the highest TAC (15.5 mg g−1) and AOX contents (4.34 mg g−1), which were positively correlated with soil organic carbon content. It was estimated that humic acids contribute to over 50% of TAC in soils. The main phenolics in woodland A horizons were isovanillic and p-hydroxybenzoic acid (p-HA), while esculetin and p-HA predominated in the abandoned fallows due to the prevalence of herbaceous vegetation. Cultivated soils were the most abundant in p-HA (56.42%). In the studied topsoils, there were considerable amounts of aliphatic organic matter, which role in redox processes should be further evaluated. [ABSTRACT FROM AUTHOR]

The fragility curve expresses the probability that an asset exceeds some serviceability state for a given level of environmental perturbation or other loadings. It is an important component in the quantitative risk analysis and resilience evaluation of infrastructure exposed to natural hazards. Incidences of over-settlement of embankments are increasingly reported due to more intense and longer-duration rainfall events. This paper develops fragility curves for the rainfall-induced embankment settlement. For this purpose, an embankment incorporating enhanced seepage and displacement analysis within unsaturated soil conditions is modelled based on a reported case history. A Monte Carlo simulation is used for rainfall infiltration and embankment deformation analysis under various rainfall scenarios. Probability values are obtained to achieve three levels of damage states in terms of road embankment settlement. The parametric analysis produces the exceedance probability curves for various rainfall intensities, saturated permeabilities and embankment slope angles. This work offers an efficient tool for assessing fragility to rainfall-induced excessive settlement of embankments. [ABSTRACT FROM AUTHOR]

Recently, numerous spatial prediction methods with diverse characteristics have been developed. Selecting an appropriate spatial prediction method, along with its data preprocessing and parameter settings, presents a challenging task for many users, especially for non-experts. This paper addresses this challenge by exploring the potential of automated machine learning method proposed in artificial intelligent domain to automatically determine the most suitable method among various machine learning methods. As a case study, the automated machine learning method was applied to predict the spatial distribution of soil subgroups in Heshan farm. A total of 110 soil samples and 10 terrain variables were utilized in the designed experiments. To evaluate the performance, the proposed method was compared to each machine learning method with default parameters values or parameters determined by expert knowledge. The results showed that the proposed method typically achieved higher accuracy scores than the two alternative methods. This suggests that automated machine learning performs effectively in scenarios where numerous machine learning methods are available and offers practical utility in reducing the dependence on users' expertise in spatial prediction. However, a more robust automated framework should be developed to encompass a broader range of spatial prediction methods, such as spatial statistic methods, rather than only focusing on machine learning methods. [ABSTRACT FROM AUTHOR]

Climate change is a pressing global concern with far-reaching implications and its impact on soil properties is a critical aspect that warrants comprehensive investigation. This abstract delves into the multifaceted effects of climate change on soil, highlighting the intricate relationships between climate patterns and soil characteristics. Rising temperatures associated with climate change contribute to increased evaporation rates, leading to changes in soil moisture levels. These alterations can influence soil structure, affecting porosity, compaction and water retention capacity. Additionally, shifting precipitation patterns may result in changes to soil erosion and sedimentation rates, impacting nutrient cycling and the overall fertility of the soil. The increase in extreme weather events, such as floods and droughts, intensifies soil erosion and nutrient loss. Changes in temperature and precipitation also influence microbial activity and diversity in the soil, impacting crucial processes like decomposition and nutrient mineralization. These alterations in microbial communities can further cascade into shifts in soil organic matter content and nutrient availability. Furthermore, the interaction between climate change and soil properties extends to the realm of soil carbon sequestration. Altered conditions may affect the balance between carbon inputs and outputs, influencing the capacity of soils to act as carbon sinks. Understanding these complex dynamics is imperative for sustainable land management practices and developing strategies to mitigate the adverse effects of climate change on soil properties. This review paper throws light on the complex interplay between climate change and soil properties underscoring the need for interdisciplinary research to unravel the intricacies of this relationship. Such knowledge is indispensable for formulating effective adaptation and mitigation strategies to safeguard soil health, ensuring the resilience of ecosystems and global food security in the face of ongoing climate challenges. [ABSTRACT FROM AUTHOR]

Regarding a novel and low-carbon composite pile, the MgO-carbonated composite pile (MCP) is formed by a pervious concrete pile (inner core) at the center of a deep magnesia (MgO) mixing column (outer core) subjected to forced carbonation. The shaft resistance of the MCP is primarily governed by the interface of pervious concrete–carbonated soil. Understanding the interface's shear behavior and strength is crucial for the design and safety assessment of the MCP. In this paper, a series of direct shear tests were conducted to analyze the shear behaviors of the pervious concrete–carbonated soil interface. The aim was to evaluate the impact of key influence factors such as carbonation time, MgO content, and initial water content on the interface friction capacity. Furthermore, a practical prediction model for interface shear strength was proposed, taking into account the aforementioned factors. The test results revealed that the peak shear strength of the specimen under 12 h of carbonation time reached 508 kPa, representing a 94% increase compared to the specimens without forced carbonation. The curves of shear stress versus tangential displacement of the inner–outer cores interface exhibited both strain-hardening and -softening behaviors. The proposed linear model exhibited excellent predictive accuracy for interface shear strength, with a regression coefficient exceeding 0.8. Based on multiple linear analysis, MgO content emerged as the most significant factor affecting the interface shear strength of the MCP, followed by vertical effective stress. [ABSTRACT FROM AUTHOR]

Although cemented soil as a subgrade fill material can meet certain performance requirements, it is susceptible to capillary erosion caused by groundwater. In order to eliminate the hazards caused by capillary water rise and to summarize the relevant laws of water transport properties, graphene oxide (GO) was used to improve cemented soil. This paper conducted capillary water absorption tests, unconfined compressive strength (UCS) tests, softening coefficient tests, and scanning electron microscope (SEM) tests on cemented soil using various contents of GO. The results showed that the capillary water absorption capacity and capillary water absorption rate exhibited a decreasing and then increasing trend with increasing GO content, while the UCS demonstrated an increasing and then decreasing trend. The improvement effect is most obvious when the content is 0.09%. At this content, the capillary absorption and capillary water absorption rate were reduced by 25.8% and 33.9%, respectively, and the UCS at 7d, 14d, and 28d was increased by 70.32%, 57.94%, and 61.97%, respectively. SEM testing results demonstrated that GO reduces the apparent void ratio of cemented soil by stimulating cement hydration and promoting ion exchange, thereby optimizing the microstructure and improving water resistance and mechanical properties. This research serves as a foundation for further investigating water migration and the appropriate treatment of GO-modified cemented soil subgrade. [ABSTRACT FROM AUTHOR]

Deep soil moisture data have wide applications in fields such as engineering construction and agricultural production. Therefore, achieving the real-time monitoring of deep soil moisture is of significant importance. Current soil monitoring methods face challenges in conducting the large-scale, real-time monitoring of deep soil moisture. This paper innovatively proposes a real-time prediction approach to deep soil moisture combining GNSS-R data and a water movement model in unsaturated soil. This approach, built upon surface soil moisture data retrieved from GNSS-R signal inversion, integrates soil–water characteristics and soil moisture values at a depth of 1 m. By employing a deep soil moisture content prediction model, it provides predictions of soil moisture at depths from 0 to 1 m, thus realizing the large-scale, real-time dynamic monitoring of deep soil moisture. The proposed approach was validated in a study area in Goodwell, Texas County, Oklahoma, USA. Predicted values of soil moisture at a randomly selected location in the study area at depths of 0.1 m, 0.2 m, 0.5 m, and 1 m were compared with ground truth values for the period from 25 October to 19 November 2023. The results indicated that the relative error (δ) was controlled within the range of ±14%. The mean square error (MSE) ranged from 2.90 × 10 − 5 to 1.88 × 10 − 4 , and the coefficient of determination ( R 2 ) ranged from 82.45% to 89.88%, indicating an overall high level of fitting between the predicted values and ground truth data. This validates the feasibility of the proposed approach, which has the potential to play a crucial role in agricultural production, geological disaster management, engineering construction, and heritage site preservation. [ABSTRACT FROM AUTHOR]

The temperature distribution around the offshore burial pipeline is an important factor affecting its safety design and economic operation. The traditional test method cannot obtain the continuous temperature distribution of soil owing to the constraints of placing measurement sensors in soil. The transparent soil model test is an alternative method to realize the visualization research of soil temperature. In this paper, a relationship between the temperature of transparent soil and pixel intensity was first established. Then, the transparent soil test and numerical simulation, considering the natural convection, were carried out to study the temperature distribution around the submarine pipeline during start-up and stable operation. The influence of buried depth and pipeline diameter was analyzed. The results suggest that the continuous temperature distribution can be obtained visually by using a transparent soil test, and the observed heating zone of influence extended to a radial distance of 2.6 pipe diameters. The numerical analysis results show that the influence zone of the temperature of pipeline is a distance of four pipeline diameters at a temperature difference of 45 °C. The buried depth and pipeline diameter have little influence on the influence zone. In addition, the contour curves of soil temperature around the pipeline with different diameter are similar in shape. With the decrease in the buried depth of pipeline, the temperature gradient of soil around the pipeline decreases, which is caused by the natural convection. [ABSTRACT FROM AUTHOR]

Research on the military-technogenic burden on the natural environment as a result of international conflicts is relevant since military operations cause catastrophic consequences for the environment and natural resources, which can lead to irreversible disturbances in ecosystems. The study is devoted to the examination of the impact of military-technogenic loads on the soils of military training grounds. The paper considers methods of soil sampling and their analysis for the content of heavy metals and other chemical compounds and determines the impact of this load on the ecosystem and possible consequences for human health. The influence of military activity on the soil quality of military training grounds, in particular in the Cherkasy region, is analysed. The study includes the determination by X-ray fluorescence and atomic emission method of the content of various elements in the soil. The results showed a substantial iron content, which may be due to the use of explosives in military exercises. It is noted that despite the fact that exceeding the norms of maximum permissible content concentration, no heavy metals were recorded in the examined soils, and the maximum lead content approached the maximum permissible concentration, which requires further monitoring and control of this parameter. Ph determination showed a slightly acidic soil condition in combat exercise sites, which can affect plant fertility and growth. The content of nitrogen, phosphorus, potassium, and boron was assessed, and the results showed a lack of these nutrients for normal plant development. It is established that soil damage as a result of military operations can have a long-term negative impact and pose a threat to residents and territories. The results of the tests indicate a slight technogenic load at the sites of military exercises. The detected contamination of the examined samples is insubstantial, which indicates that the impact of military activities on the soil condition is limited. The results of the study will help to understand the possible health risks for people living near military training grounds and respond appropriately to protect their health. [ABSTRACT FROM AUTHOR]

Soil health business models can lead to the maintenance of sustainable and competitive agriculture. The agricultural policy in the EU pursues different incentives to encourage adoption of environmentally oriented practices. Investments in soil health can lead to significant benefits not only for the environment but for society as well. The aim of this paper is to present the methodological approach for assessing new incentives for soil health business models in the frame of the NOVASOIL project. The goal is to investigate the opportunities and gaps of new incentives for redirection of financial streams and policy support measures for provision of innovative soil health technologies. The methodology includes two phases. The first one comprises of targeting new incentives for soil health and then identifying the corresponding gaps and opportunities. The second one continues the analysis with assessing the selected incentives with the BOCR-ANP model. [ABSTRACT FROM AUTHOR]

Heavy metals migrate easily and are difficult to degrade in the soil environment, which causes serious harm to the ecological environment and human health. Thus, soil heavy metal pollution has become one of the main environmental issues of global concern. Plant-growth-promoting rhizobacteria (PGPR) is a kind of microorganism that grows around the rhizosphere and can promote plant growth and increase crop yield. PGPR can change the bioavailability of heavy metals in the rhizosphere microenvironment, increase heavy metal uptake by phytoremediation plants, and enhance the phytoremediation efficiency of heavy-metal-contaminated soils. In recent years, the number of studies on the phytoremediation efficiency of heavy-metal-contaminated soil enhanced by PGPR has increased rapidly. This paper systematically reviews the mechanisms of PGPR that promote plant growth (including nitrogen fixation, phosphorus solubilization, potassium solubilization, iron solubilization, and plant hormone secretion) and the mechanisms of PGPR that enhance plant–heavy metal interactions (including chelation, the induction of systemic resistance, and the improvement of bioavailability). Future research on PGPR should address the challenges in heavy metal removal by PGPR-assisted phytoremediation. [ABSTRACT FROM AUTHOR]