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Thorough knowledge of soil lithology and its properties are of considerable importance to agriculture. These parameters have a direct impact on water permeability and the content of the water in soil, which represent significant factors in crop yield, decisively determining the design of irrigation systems and farming processes. In the framework of this study, and considering the inevitable impacts of climate change, the rational management of water resources and the optimization of irrigation through innovative technologies become of significant importance. Thus, we propose an interdisciplinary approach based on robust techniques from the allied fields of earth (geological mapping, geophysical methods) and soil sciences (sampling, mechanical analysis) assisted by statistics and GIS techniques. Clay or the sum of clay and silt soil content is successfully determined from the normalized chargeability using induced polarization and electrical resistivity techniques. Finally, we distinguished three classes (S1, S2 and S3) considering the clay or the sum of clay and silt soil content in the study area (a) based on the dry period geophysical data and (b) using as classification criterion the spatial distribution of the geological formations. [ABSTRACT FROM AUTHOR]

Reaching the land-related UN Sustainable Development Goals (SDGs) and similar goals articulated by the EU Green Deal (GD) by 2030 presents a major challenge and requires a pragmatic approach focused on joint learning by land users (mostly farmers), researchers and other stakeholders in "Living Labs" and system experiments at experimental farms of research organizations. Defining specific indicators and thresholds for ecosystem services in line with land-related SDGs is crucial to establish "Lighthouses" that can act as inspiring examples if they meet the various thresholds. This exploratory paper discusses indicators and thresholds for an arable farm operating on marine, calcareous light clay soils in the Netherlands. Studies of a system experiment are used to discuss and test operational methodology to be widely applied when characterizing many "Living Labs" in future, as planned by the European Union. The important role of soils in contributing to ecosystem services is discussed in terms of soil health. Recommendations are made for innovative methodology to be associated with all land-related SDGs. Satisfying the thresholds of ecosystem services, which will vary by soil type, region and farm type, can be the basis for farm subsidies, such as the Common Agricultural Policy (CAP). Research on Living Labs and in system experiments has to be judged by different criteria than those associated with traditional linear research. The important contributions of soils to achieve ecosystem services are framed in terms of soil health and are the most effective way to promote soil science in a by now widely desired inter- and transdisciplinary context. [ABSTRACT FROM AUTHOR]

• Traditional methods for soil specific surface area (SSA) are costly and laborious. • We propose models to estimate SSA from a single hygroscopic water content (w h) • Separate SSA models are developed for soil samples grouped by clay mineralogy. • Considering soil clay mineralogy in SSA models significantly improved performance. • Models based on w h were superior to models based on texture, carbon or CEC. The soil specific surface area (SSA) is an important variable for soil science and geoenvironmental engineering applications, but traditional measurement methods are difficult and time-consuming. Regression models or pedotransfer functions are often used to estimate SSA from other soil properties (e.g., clay content and cation exchange capacity), but these models do not consider the impact of clay mineralogy. Hygroscopic water content (w h) is intimately linked to these soil properties, which suggests that w h may be a better parameter for SSA estimation. This study (i) proposes regression models that estimate SSA from w h at different relative humidity values (5 to 90%) for kaolinite-rich samples (KA), illite-rich or mixed clay samples (IL/MC), montmorillonite-rich samples (ML), and a combination of all samples (ALL) and (ii) compares the performance of the w h models to other published models that comprise clay, silt and soil organic carbon contents and cation exchange capacity. We found that the sample-specific w h regression models accurately estimated SSA for KA, IL/MC and ML samples. For KA and IL/MC samples, the performance of the KA model (e.g., for adsorption, average RMSE = 10.5 m2/g) and IL/MC model (average RMSE = 21.3 m2/g) were better than the ALL-calibration model (KA: average RMSE = 18.7 m2/g; ML: average RMSE = 22.4 m2/g). For ML samples, similar model performance between the ML-calibration model (average RMSE = 41.4 m2/g) and the ALL-calibration model (average RMSE = 41.1 m2/g) was observed. In addition, the model performance of regression models based on w h was superior to models published in the literature that are based on clay, silt and soil organic carbon contents and cation exchange capacity. Overall, this study confirms that a single measure of w h can provide reliable estimates of the SSA while revealing a significant impact of clay mineralogy on model performance. [ABSTRACT FROM AUTHOR]

Heavy clay soils are globally widespread but their poor drainage and poor aeration limit their use for agriculture. This study was designed to test the effect of the amendment of biochar (BC) from woody shrubs on drainage/saturated hydraulic conductivity (Ksat), soil aeration/air capacity, available water capacity and biomass and grain yields of maize. In a field experiment, BC from Gliricidia sepium was applied in planting basins or rip lines at 2.5% and 5% w/w in addition to a control without BC. The maize biomass and grain yields were higher in BC treated plots compared to control (p<0.05) during the 2012 and 2013 seasons. There was no significant difference in the yields between 2.5% and 5% BC treatments (e.g. grain yield were 6.6 and 8.1 t ha-1 in 2012 and 9.3 and 10.3 t ha-1 in 2013 compared to control with 4.2 and 6.7 t ha-1 in 2012 and 2013, respectively). Soil from the same field site was also mixed with a similar woody shrub BC from Eupatorium adenophorum in the laboratory at rates of 2.5%, 5% and 10% BC w/w and a control without BC. The mixtures were then incubated and subjected to two wet-dry cycles for two weeks. Core samples were taken from the incubated soil and tested for bulk density, Ksat and pF measurements. Total porosity and moisture at field capacity and wilting point were 72.3%, 43.7% and 23.7%, respectively, and not affected by BC amendment (p>0.05). In contrast, bulk density decreased linearly by 0.011±0.002 g cm-3 per percent BC added (p<0.001). Ksat and air capacity of the soil were 288 cm day-1 and 30.9%, respectively falling within the generally accepted optimal range. Both Ksat and air capacity followed a significant quadratic relation (p<0.05) upon BC addition, decreasing at low BC doses, reaching a minimum at 3–5% BC and increasing at higher doses. Results allowed a partial attribution of the yield increases to changes in soil physical properties such as changes in bulk density and not clearly to Ksat and air capacity. [ABSTRACT FROM AUTHOR]

[Display omitted] • Soil sampling methods were assessed using 720 samples at two locations. • Calculated composite sampling decreased significant effects especially in sandy soils. • Sampling in-row resulted in greater crop effect on research results. • Soil enzyme activities required more samples compared to other soil properties. • A Monte Carlo simulation can be used to estimate needed sample size. A wide variety of soil sampling methods have been adopted, yet limited research has addressed how sampling methods can impact research results particularly for spatially variable soil properties. To address these concerns, we intensively sampled two existing soil health trials in Texas for analysis of soil extracellular enzymatic activities (EEAs), permanganate oxidizable C (POXC), soil organic C (SOC), and pH. The data generated was used to quantify the effect of composite sampling, sampling position (in-row vs between-row), and number of samples on statistical results. We compared a Monte Carlo simulation approach with a traditional power analysis to quantify the impact of the number of samples on our results. Calculated composite sampling resulted in lower statistically significant results compared to discrete sampling, demonstrating lower sensitivity of composite sampling. Sampling in-row resulted in greater values specifically for EEAs, pH, POXC, and SOC. Simulation generated estimated number of samples were mainly driven by the effect size and spatial variation. EEAs were highly variable, resulting in a higher estimated number of samples as compared to other soil properties such as POXC and SOC. In our study with two sites, soil with greater clay content resulted in overall lower estimated number of samples compared to a relatively sandy soil, demonstrating a greater sampling requirement for sandy soil. The simulation approach had a weak correlation with traditional power analysis. The simulation predicted lower estimated number of samples when compared to power analysis, which can help save cost in the long run. Overall, factors like composite sampling, sampling in-row vs between-row, and number of samples taken did impact research results. The impact of these sampling strategies on soil parameters of interest needs to be investigated to achieve the most accurate research results in soil science. [ABSTRACT FROM AUTHOR]

Effective pretreatment of spectral reflectance is vital to model accuracy in soil parameter estimation. However, the classic integer derivative has some disadvantages, including spectral information loss and the introduction of high-frequency noise. In this paper, the fractional order derivative algorithm was applied to the pretreatment and partial least squares regression (PLSR) was used to assess the clay content of desert soils. Overall, 103 soil samples were collected from the Ebinur Lake basin in the Xinjiang Uighur Autonomous Region of China, and used as data sets for calibration and validation. Following laboratory measurements of spectral reflectance and clay content, the raw spectral reflectance and absorbance data were treated using the fractional derivative order from the 0.0 to the 2.0 order (order interval: 0.2). The ratio of performance to deviation (RPD), determinant coefficients of calibration (), root mean square errors of calibration (RMSEC), determinant coefficients of prediction (), and root mean square errors of prediction (RMSEP) were applied to assess the performance of predicting models. The results showed that models built on the fractional derivative order performed better than when using the classic integer derivative. Comparison of the predictive effects of 22 models for estimating clay content, calibrated by PLSR, showed that those models based on the fractional derivative 1.8 order of spectral reflectance ( = 0.907, RMSEC = 0.425%, = 0.916, RMSEP = 0.364%, and RPD = 2.484 ≥ 2.000) and absorbance ( = 0.888, RMSEC = 0.446%, = 0.918, RMSEP = 0.383% and RPD = 2.511 ≥ 2.000) were most effective. Furthermore, they performed well in quantitative estimations of the clay content of soils in the study area. [ABSTRACT FROM AUTHOR]

Understanding the effects of external organic and inorganic components on soil fertility and quality is essential for improving low-yielding soils. We conducted a field study over two consecutive rice growing seasons to investigate the effect of applying chemical fertilizer (NPK), NPK plus green manure (NPKG), NPK plus pig manure (NPKM), and NPK plus straw (NPKS) on the soil nutrient status, enzyme activities involved in C, N, P, and S cycling, microbial community and rice yields of yellow clayey soil. Results showed that the fertilized treatments significantly improved rice yields over the first three experimental seasons. Compared with the NPK treatment, organic amendments produced more favorable effects on soil productivity. Notably, the NPKM treatment exhibited the highest levels of nutrient availability, microbial biomass carbon (MBC), activities of most enzymes and the microbial community. This resulted in the highest soil quality index (SQI) and rice yield, indicating better soil fertility and quality. Significant differences in enzyme activities and the microbial community were observed among the treatments, and redundancy analysis showed that MBC and available N were the key determinants affecting the soil enzyme activities and microbial community. The SQI score of the non-fertilized control (0.72) was comparable to that of the NPK (0.77), NPKG (0.81) and NPKS (0.79) treatments but significantly lower compared with NPKM (0.85). The significant correlation between rice yield and SQI suggests that SQI can be a useful to quantify soil quality changes caused by different agricultural management practices. The results indicate that application of NPK plus pig manure is the preferred option to enhance SOC accumulation, improve soil fertility and quality, and increase rice yield in yellow clayey soil. [ABSTRACT FROM AUTHOR]

• A regular evaluation of satellite soil moisture (SM) products was conducted. • Their accuracies in detecting SM anomalies and seasonality were identified. • l -band products can effectively capture SM seasonality over forest covers. • Products had difficulties in detecting SM variations over organic-rich soils. • AMSR2 showed higher accuracy to detect SM seasonality over arid areas. Satellite-based soil moisture (SM) products exhibit distinct error patterns at various timescales. Knowledge of their accuracy characteristics for capturing different SM signals is significant for many real-world applications in soil sciences. This study conducted a comprehensive evaluation of the following eight satellite-based SM products: the Soil Moisture and Ocean Salinity-Institut National de la Recherche Agronomique and Centre d'Etudes Spatiales de la BIOsphere version 2 (SMOS-IC-V2), the Level 3 (L3) Soil Moisture Active Passive V7 (SMAP-V7), the combined European Space Agency Climate Change Initiative V06.1 (ESA CCI-V06.1), the L3 SMOS V3, the L3 Advanced Microwave Scanning Radiometer (AMSR2) V3 from the Japan Aerospace Exploration Agency (JAXA), the L3 Land Parameter Retrieval Model (LPRM) C1- and X- band AMSR2 V001, and the Chinese FengYun-3B V1. By using >1,500 sites from the International Soil Moisture Network and triple collocation analysis, this study aimed to identify not only the relative strengths of the products for detecting original SM signals, short-term SM anomalies, and long-term SM seasonality, but also the impacts of land cover, soil organic carbon (SOC), and soil texture on their retrieval accuracy. In terms of capturing the temporal dynamics of SM anomalies, SMAP-V7 outperformed SMOS-IC-V2 and ESA CCI-V06.1. In arid and semi-arid areas, LPRM C1-band AMSR2 V001 outperformed SMOS-ICV2 and SMAP-V7, in terms of detecting SM seasonality. SMAP-V7, SMOS-ICV2, and ESA CCI-V06.1 effectively captured SM seasonality over most forest zones and effectively detected short-term SM anomalies over croplands and grasslands. The l -band products showed the highest accuracy in terms of capturing the temporal dynamics of all the SM signals when the clay fraction was in the range of 20 %–25 %. Most products had difficulties in detecting SM variations over bare deserts, sandy and clay soils, and soils rich in organic matter (SOC content > 8.72 %). [ABSTRACT FROM AUTHOR]

Copyright of Canadian Geotechnical Journal is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A large amount of field and experimental data has been devoted to rectangular excavations thus far. In contrast, very few data were available for cylindrical excavations, especially those with large diameters in thick soft clay deposits. Via a comprehensive instrumentation program on a unpropped (self-supported) cylindrical excavation constructed by the bottom-up method in Shanghai soft clay, the characteristics of this large-sized circular excavation were extensively investigated. This cylindrical shaft was a part of a large-scale deep foundation pit excavated by the central-island technique. The investigated items included (1) lateral wall deflections, (2) vertical wall movements, (3) lateral ground movements, (4) ground settlements, (5) subsurface settlements, (6) basal heaves, (7) vertical column movements, (8) column stresses, and (9) variation of pore pressures along depth and artesian water levels. Analysis of the field data indicates that discharging of the deep artesian water was one of the key factors affecting the excavation behaviors. The influence zone of basal heave caused by soil removal (stress relief) reached very deep soil layers, far beyond the depths reported in literature. Column movement and stress were shown to be reliable indicators of the relative movement between basal soils, diaphragm walls, and interior columns. Finally, the comparisons of this study with other bottom-up excavations in Shanghai, including 11 cylindrical excavations, 92 building basement excavations, and eight metro station excavations, demonstrate that self-supported (unpropped) cylindrical excavations had much stronger capabilities of resisting deformation than both multipropped regular basement excavations (in terms of deformation magnitudes) and long and narrow metro station excavations (in terms of scale of influence zones). For cylindrical shafts, their diameters, and not wall penetration ratios, played a dominant role in the determination of excavation behaviors. However, when the shaft diameter reached 90 m or more, the advantage of cylindrical shafts over rectangular pits in constraining wall deflection was no longer obvious. [ABSTRACT FROM AUTHOR]

This paper reports an investigation of the influence of waste stone powder and lime on the geotechnical properties of clayey soil. The plasticity and changes in the chemical properties of the soil with pH test when mixed with varying proportions of waste stone powder and lime were investigated. The results show significant reduction in plasticity and increasing in the pH value of clayey soil with increasing amount of waste stone powder and lime. Also there is a decrease in liquid limit and increase in plastic limit with increasing waste stone powder and lime content. The behavior of the geotechnical properties of the clayey soil when blended with waste stone powder and lime indicates that these materials are a good modifier for this soil. [ABSTRACT FROM AUTHOR]

Abstract: Soils with subsoil clay accumulation account for more than 20% of the global land surface. These soils are characterized by vertical differences with respect to soil texture and increasing bulk density below the topsoil, which in turn affects root penetration into the subsoil. Biopores are preferential pathways for roots and assist in overcoming physical barriers like high density soil layers. An integration of these relationships into cropping systems models at the field scale is on-going. This paper presents a new approach to model the effect of biopores on root development in soils with clay accumulation at the plot scale. In this approach, the effect of biopores on root elongation rate depends on bulk density and on a biopore-root growth threshold (MPRT), which is the biopore volume at which the resistance of soil strength to root penetration is completely offset by the density of the biopores. The approach was integrated into a model solution of the model framework SIMPLACE (Scientific Impact assessment and Modeling PLatform for Advanced Crop and Ecosystem management). MPRT was parameterized for spring wheat using the inverse modeling approach based on root observations from a multi-factorial field experiment on a Haplic Luvisol. The observed biopore densities (>2mm diameter) were between 300 and 660poresm−2 (equivalent to a volumetric proportion of 0.38–0.83%) depending on the preceding crop. Observed soil bulk densities ranged between 1.31 and 1.62gcm−3. For spring wheat, the best fit between simulated and observed root densities in different layers was obtained with a MPRT of 0.023m3 m−3 (equivalent to 2.3% of soil volume). The mean simulated total above ground biomass was sensitive to MPRT and had the best agreement with observed values when a MPRT between 0.023 and 0.032 m3 m−3 was used in the simulations. Scenario simulations with the parameterized model at the same site demonstrate the importance of biopores for biomass production of short-cycle spring wheat when prolonged dry spells occur. The simulations allow a rough quantification of the biopore effects with respect to root elongation rate and biomass production at the plot scale with the potential to be extended to the field scale. [Copyright &y& Elsevier]

A comprehensive study of expansive soil behavior includes understanding the surface phenomena of clay particles within the soil matrix. This research studies four micro-scale properties of four remolded expansive soils--matric suction, pH, surface conductance and percentage of montmorillonite--in order to predict soil swelling. An approach to approximate surface conductance is presented. Linear regression analyses were undertaken in an attempt to predict percent swell and swell pressure based on each of these micro-scale properties. Matric suction was found to be the most accurate predictor of the swelling behavior of the studied soils, which were initially compacted at optimum moisture content. Surface conductance, which is a combination of specific surface area, cation exchange capacity and cation mobility, also gave good predictions, except for one soil with high acidity. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Geotechnical Journal is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Regression models were developed to estimate the optimum moisture content and maximum dry density of clayey and fine-grained soils using physical and index properties from 30 soil samples collected in Central Italy and 41 soils described in the literature. The liquid limit of the soils analyzed ranged between 18 and 82%, the plasticity index between 1 and 51%, and specific gravity between 2.47 and 3.09. The most significant regression variables were the specific gravity and the Atterberg limits. The developed models are accurate and can be used as a simple tool to approximate the maximum dry density and optimum water content of clayey and fine-grained soils. [ABSTRACT FROM AUTHOR]

Abstract: An analysis of results from published laboratory tests on Jossigny silt and Barcelona clayey silt is presented to confirm the existence of a unique capillary bonding function linking the quotient between unsaturated and saturated void ratio, at the same mean average skeleton stress, to a single capillary bonding scalar variable. The analysis confirms that the same capillary bonding function applies to both normally consolidated and critical stress states. The above two experimental sets with the addition of further published data for Speswhite Kaolin are also used to study the relationship between unsaturated critical shear strength, mean average skeleton stress and capillary bonding variable. The results of such analysis are assessed in the light of a similar modelling framework proposed in the literature. [Copyright &y& Elsevier]

X-ray micro-computed tomography (μ CT) scanning is a proven technique with applications in geoscience, soil science, and geotechnical engineering. Here we apply the technique to investigate the effects of cation treatments on clayey soil micro-fabric in a frozen state. We imaged six suites of frozen cation-treated soils (montmorillonite, kaolinite, illite, illite-smectite, chlorite, and Copper River heterogeneous soil) at a resolution of 8.17 μm. Although this resolution was insufficient to observe differences in microaggregate formation as a result of cation treatment, we did observe micro-lenticular ice structures in the smectite-bearing soils that were invisible to the unaided eye. Quantitative analysis of the morphometric parameters from the illite-smectite and Copper River sample suites provided results that supported the visual observations, with the Copper River heterogeneous soil being more frost susceptible than illite-smectite, regardless of cation treatment. The μ CT results of these small soil cores also indicate that within the Copper River suite, the Ca2+-treated and Na+-treated samples are the most and least frost susceptible, respectively, which is in agreement with previous frost heave testing. Results from this study indicate that μ CT morphometric parameters can be used to quantify micro-lenticular ice lens formation in small samples and to serve as a quality control on sample preparation. • Uses μ CT scanning to visualize micro-fabric changes as a result of cation treatment on clayey soils • Provides images with high resolution (8.17 µ m), which is not typical for µ CT scanning of frozen soils • Discusses how μ CT scanning revealed the presence of ice lensing in certain types of soils and cation treatments [ABSTRACT FROM AUTHOR]

Comments on a study which estimated the field hydraulic conductivity of compacted clay. Relationship between hydraulic conductivity and effective stress; Development of equations to relate change in hydraulic conductivity as a function of effective stress; Relationship between permeability and void ratio for soil types.