Basic Soil Properties Research Articles

Vegetation restoration improves soil hydrological properties by regulating soil physicochemical properties in the Loess Plateau, China

Soil hydrological properties play a key role in soil hydrological processes. However, the effect of long-term vegetation restoration on soil hydrological properties and the corresponding influencing mechanisms remains poorly understood. Here, three soil hydrological properties including saturated water-holding capacity (SWHC), field capacity (FC) and saturated hydraulic conductivity (Ks), as well as several basic soil properties in the Zhifanggou watershed of the Loess plateau were investigated. The variations in SWHC, FC and Ks under different vegetation restoration types and their dominant influencing factors were analyzed. Moreover, we collected available Ks data from peer-reviewed publications to determine the land use with the largest Ks across the entire Loess Plateau. The results showed that SWHC FC and Ks were increased after 20 years of vegetation restoration. The higher Ks was found in shrubland and forest in the whole Loess Plateau. Compared with cropland, Ks in shrubland was increased by 87.10% at 0–20 cm, 48.89% at 20–40 cm, and 18.37% at 40–100 cm, respectively, indicating that the impact of revegetation on Ks were most obvious in the upper soil layer. Bulk density (BD), total porosity (TP), capillary porosity (CP), noncapillary porosity (NCP) and soil organic matter (SOM) had a significant effect on SWHC, FC and Ks for different land-use types (P < 0.01). Soil porosity (i.e., TP, CP and NCP) and BD, soil chemical properties (i.e., SOM and pH), and soil particle composition explained 93.8%, 59.2%, and 13.4% of the total variance in soil hydrological properties (i.e., SWHC, FC and Ks), respectively. This indicates that soil porosity and BD are the dominant factors affecting soil hydrological properties. Moreover, soil particle composition played an important role in regulating Ks, with the contribution of 38.6%. The established pedotransfer function (PTF) of Ks using BD, clay and silt content had a better performance than two existing PTFs. This research provides a more systematic and comprehensive understanding of the soil hydrological effect of vegetation restoration in the Loess Plateau.

The contribution of microbial activity to soil–water interactions and soil microstructural stability of a silty loam soil under moisture dynamics

Soil structure and its stability against external stresses is fundamental to various soil functions and ecosystem services. Particularly soil moisture dynamics and microbial activity can affect soil structure by promoting particle reorientation, cementation and spatio-temporal pore space remodeling. In this context, microbial exudates can serve as interparticulate binding agents and thus contribute to the formation of stable soil structures and basic physico-chemical soil properties. However, detailed interactions and relationships between microbial activity, soil pore water and the porous soil matrix itself are still unclear, especially in the context of dynamic moisture conditions. In this study, we aimed to increase the fundamental understanding of microbially-induced and moisture dynamic-affected soil microstructural stability and soil–water interactions. For this, a sterilized, untreated and substrate-enhanced silty loam soil was subjected either to constant moisture conditions or four consecutive drying-wetting cycles. At defined timepoints, soil samples were investigated for carbon dioxide release (respirometry), phospholipid fatty acid analysis, wetting behaviour (contact angle), rheological characteristics (rheometry) and water entrapment (1H nuclear magnetic resonance relaxometry) to respectively determine microbial activity, community structure and biomass, soil wettability, soil microstructural stability and the frequency distribution of water-filled pore sizes in soil (FDWPS). Results showed that substrate enhancement promoted soil microstructural stability compared to sterilized and untreated soil, whereby all soils reacted dynamically and irreversibly to the adjusted moisture conditions. Significant positive correlations were found between microbial activity, wettability, FDWPS and soil microstructural stability, which indicate that the presence of interparticulate microbial structures augmented the spatio-temporal reorganization effect induced by soil moisture dynamics. The irreversible dehydration of those interparticulate microbial structures resulted in an additional pore space cementation, water redistribution to smaller soil pores and thus a considerably increased microstructural stability due to stronger cohesive and capillary forces. The results help to understand the extent to which soil moisture dynamics can modulate microbial-induced soil processes and basic soil properties.

Method for predicting unsaturated permeability using basic soil properties

Permeability function is one of the key functions in unsaturated soil mechanics, which is often estimated from the soil water characteristic curve (SWCC) of a soil. Mualem’s permeability function which employs Van Genuchten's SWCC function is one of widely used function. However, there are two parameters in the function which need to be determined using test data and in many cases those kind of test data are not available. Empirical equations for estimating two fitting parameters (aD and n) in Mualem’s permeability function from easy to be measured basic soil properties has been proposed, i.e. aD is linked to saturated permeability (ks), and n is determined from the grain size distribution curve of a soil. The proposed method was applied to predict permeability functions of 9 soils (4 from this study and 5 from literature) with which the test data are available. Comparing the predicted and the measured values indicates that the proposed method can result in satisfaction predictions for both drying and wetting paths. It is suggested that the method can provide a first order estimation of permeability function in case there are no test data available.

Determination of Mehlich 3 Extractable Elements with Visible and Near Infrared Spectroscopy in a Mountainous Agricultural Land, the Caucasus Mountains

Soil spectroscopy is a promising alternative to evaluate and monitor soil and water quality, particularly in mountainous agricultural lands characterized by intense degradation and limited soil tests reports; a few studies have evaluated the feasibility of VIS-NIR spectroscopy to predict Mehlich 3 (M3) extractable nutrients. This study aimed to (i) examine the potential of VIS-NIR spectroscopy in combination with partial least squares regression to predict M3-extractable elements (Ca, K, Mg, P, Fe, Cd, Cu, Mn, Pb, and Zn) and basic soil properties (clay, silt, sand, CaCO3, pH, and soil organic carbon-SOC), (ii) find optimal pre-processing techniques, and (iii) determine primary prediction mechanisms for spectrally featureless soil properties. Topsoil samples were collected from a representative area (114 samples from 525 ha) located in the mountainous region of NW Azerbaijan. A series of pre-processing steps and transformations were applied to the spectral data, and the models were calibrated and evaluated based on the coefficient of determination (R2), root mean square error (RMSE), and the residual prediction deviation (RPD). The leave-one-out cross-validated predictions showed that the first derivative spectra produce higher prediction accuracies (R2 = 0.51–0.91; RPD = 1.20–2.29) for most soil properties. The evaluation of the model performance with optimal pre-processing techniques revealed that both calibration and validation models produce considerable differences in RPD values associated with sample size and the random partition of the calibration or validation subsets. The prediction models were excellent or very good (RPD &gt; 2.0) for CaCO3, SOC, sand, silt, Ca, and Pb, good or fair (1.4 &lt; RPD &lt; 2.0) for clay, K, Cd, pH, Fe, Mn, and Cu, and poor (1.0 &lt; RPD &lt; 1.4) for Mg, P, and Zn. Principal component and correlation, stepwise regression analysis, and variable importance in projection procedures allowed to elucidate the underlying prediction mechanisms. Unlike the previous studies, the spectral estimations of pH, Ca, Mg, P, Fe, Pb, and Cd concentrations were linked to their correlation with CaCO3 rather than soil organic matter, whereas Mg and P concentrations were also connected to Fe-oxides. Soil particle sizes contributed to predicting K concentration but confounded the prediction of P and Zn concentration. The weaker correlations of Mn, Cu or Zn with CaCO3, particle sizes, SOC, Fe, and spectral data yielded to their lower prediction accuracy. The major prediction mechanisms for M3-extractable elements relied on their relations with CaCO3, pH, clay content and mineralogy, and exchangeable cations in the context of their association with land use. The results can be used in mountain lands to evaluate and control the effect of management on soil quality indices and land degradation neutrality. Further studies are needed to develop most advantageous sampling schemes and modeling.

Estimation of the stability of topsoil aggregates in areas affected by water erosion using selected soil and terrain properties

The stability of soil structure is crucial for providing most of the essential functions of soil. In our previous research in a region of Chernozem soil, multiple linear regression analysis showed that soil aggregate stability within this morphologically diverse study area could be predicted using the soil organic matter content and one of the terrain attributes. Therefore, this present study aims to determine if a similar procedure can be applied to areas of different soil types, namely a Haplic Luvisol, two Haplic Cambisols, and a Calcaric Leptosol. Basic soil properties such as the organic carbon (Cox) content, Fe content, Mn content, CaCO3 content, pH, magnetic susceptibility, bulk density (ρz), electrical conductivity, and water-stable aggregate (WSA) index were measured, and terrain attributes were derived using a system for automated geoscientific analyses and a digital elevation model.It was found that it was not possible to propose similar predictive models for all locations. The models included different combinations of the Cox content, CaCO3 content, Fe content, ρz, and various terrain attributes. The Cox content was the main parameter that positively affected the WSA index values in the areas of Luvisol and Leptosol soils. Magnetic susceptibility was the main parameter that positively correlated with the WSA index in the two areas of Cambisols, and in one Cambisol area, the WSA index was also positively correlated with the ratio between amorphous and crystalline Fe forms. Negative impacts were observed for ρz (Luvisol and one Cambisol) and the CaCO3 content (Leptosol). From the terrain attributes, slope was mostly included in the predictive models. The other attributes were the catchment slope and profile curvature. The best model prediction assessed based on the coefficient of determination was found for the Leptosol area (R2 =0.69), followed by the Luvisol are (R2 =0.60) and both Cambisol areas (R2 =0.52, respectively 0.33).

Organic Matter in Riverbank Sediments and Fluvisols from the Flood Zones of Lower Vistula River

The research objective of this study was to determine whether and to what extent the form of use of Fluvisols (arable soil and grassland) of a Lower Vistula floodplain valley (Fordonska Valley, Poland) determined their relative organic matter properties, as compared with nearby riverbank sediments. Riverbank sediments were sampled from a depth of 0–20 cm, and soil samples from 0 to30 cm, all in three replicates. Basic physico-chemical soil properties were determined: texture, pH, and the contents of total organic carbon (TOC), total nitrogen (TN), dissolved organic carbon (DOC) and dissolved organic nitrogen (DON). Humic acids (HAs) were extracted by the Schnitzer method and analysed to assess their spectrometric parameters in the UV–VIS range and hydrophilic and hydrophobic properties. Riverbank sediment samples contained significantly lower TOC and TN contents than Fluvisols, regardless of land-use type. The TOC, TN, DOC and DON contents and properties of humic acids in the Fluvisol surface layer depended on land-use type, because the arable soils had significantly lower TOC, TN, DOC and DON contents than the grasslands, despite having a similar grain size (texture). Based on the A2/4, A2/6, A4/6 ratios, it was found that HA molecules isolated from the humus horizon of arable soils had a higher degree of maturity than HAs isolated from grassland soil samples. The spectrometric properties of humic acids isolated from riverbank sediments showed a higher degree of maturity than those from Fluvisols. This research showed that the properties of humic acids in Fluvisols are determined by the quantity and quality of organic matter transported in suspended matter that accumulates annually in flood valleys during flood events. The current land-use type of Fluvisols significantly influenced the properties of organic matter, and thus of humic acids. Therefore, these properties can be used to evaluate the transformation of organic matter that occurs in Fluvisols depending on the type of use.

On shapes of cumulative infiltration curves

Water infiltration into soil is the key process in the water cycle, and understanding and predicting infiltration is essential for water management. Measurements of cumulative infiltration are a common part of soil hydrological characterization. Such measurements provide the cumulative infiltration curve (CIC), i.e. dependence of the amount of infiltrated water on time. The classic, usually anticipated CIC shape is the concave increase section transitioning to the linear section. However, other shapes were also observed. The objectives of this work were (a) to use the unique large international infiltration database SWIG to define distinctly different types of CIC shapes, and (b) to see if basic soil properties, land use, and infiltration measurement method can indicate what type of non-classic CIC shapes can be expected in site-specific conditions. Examination of 5023 CIC led to the definition of 12 types of CIC shapes. About 1/3 of SWIG datasets had non-classic CIC shapes. The shape types were visually discernible in most cases. A technique was suggested to distinguish the shape types if needed. The classification tree divided all datasets with non-classic CIC shapes into most similar inside and most different from each other groups. The infiltration measurement method, the clay content, and the organic carbon content were the most influential predictors of the shape type in this classification. Several non-classic shapes were previously related to soil structure and hydrophobicity. The relatively large fraction of non-classic CIC indicates the need to design infiltration experiments accounting for possible non-classic CIC, and the need for the cautious application of common infiltration equations, most of which were developed to simulate classic CIC shapes.

How Does Land Consolidation Affect Soil Fungal Community Structure? Take Heavy Metal Contaminated Areas in Eastern China for Example

Farmland land consolidation can effectively improve the quality of farmland soil and the agricultural production level, and can effectively guarantee farmland ecology and food security, which has been widely used in the world. A large number of studies have shown that farmland consolidation has certain adjustments to the basic physical and chemical properties of soil and the content of heavy metals. As a key indicator of soil quality and ecological conditions, soil microorganisms play an important role in soil pollution restoration and the promotion of crop growth. However, there are few domestic and foreign studies on how farmland consolidation affects soil microbial properties, and there are no related reports on the mechanism of action between them, which is a blank in the field of agricultural land consolidation and soil microecology, especially in heavy metal contaminated areas. Therefore, we used the DNA sequence technology to compare fungal community structure in farmlands with and without consolidation in heavy metal contaminated areas. Our results showed that (1) farmland consolidation had a significant impact on soil microbial characteristics, which were mainly manifested as changes in microbial biomass, microbial diversity and community structure. (2) Farmland consolidation had an indirect impact on soil fungal community structure by adjusting the soil physical and chemical properties. (3) The impact of heavy metals on the fungal community structure varied significantly under different levels of heavy metal pollution in farmland consolidation areas. When the pollution was at the highest level, there existed 7 fungus genera showing a strong tolerance to heavy metals and consuming a lot of soil nutrients, of which were Melanospora, Pseudeurotium, Guehomyces, Schizothecium, Gibberella, Myrothecium, and Neurospora. In this study, an analytical method was proposed to analyze the effects of farmland consolidation on soil fungi, and the mechanism was discussed from two aspects—soil physical and chemical properties, and heavy metal content. The results shed some light on farmland consolidation, cultivated land quality evaluation and territorial space ecological restoration.

Developing pedotransfer functions using Sentinel-2 satellite spectral indices and Machine learning for estimating the surface soil moisture

To estimate the surface soil moisture (SM) using a combination of new spectral indices and methods of Random Forrest (RF) and Multiple Linear Regression (MLR), 11 pedotransfer functions (PTF1-11) were developed by combining basic soil properties (clay, silt/sand, and bulk density) and spectral indices of Sentinel-2 satellite. In this study, 124 surface soil samples were randomly taken from three regions including Telo in Tehran province, Ivaneki in Semnan province, and Borujerd in Lorestan province, Iran. The results showed that the accuracy of the RF method was considerably higher compared to the MLR method. The SM was better estimated using water spectral indices (such as Normalized Difference Water Index (NDWI) and Surface Water Capacity Index (SWCI)), along with the basic properties of soil as inputs of PTF7. In the training and testing steps, the Root Mean Square Error (RMSE) decreased from 0.041 and 0.05 (cm3 cm−3) in PTF1 to 0.028 and 0.039 in PTF7, respectively. The average values of RMSE, Akaike Information Criterion (AIC), coefficient of determination (R2) and Relative Improvement (RI) of the RF method were 0.028 (cm3 cm−3), −559, 0.79 and 0.001, and 0.038 (cm3 cm−3), −279, 0.73 and −0.006 for the training and testing steps of all PTFs, respectively. While, these values for the MLR method were 0.032 (cm3 cm−3), −542, 0.69 and 0.0003, and 0.043 (cm3 cm−3), −269, 0.63 and 0.002 for the training and testing steps, respectively. Due to the low values of MBE, it was possible to disregard the overestimation of the results. The evaluation of results for predictor importance indicated that among the basic properties, clay percent has a significant effect on estimation of SM. These results show that spectral indices alone are not suitable estimators for SM estimation. It suggests using basic soil properties and spectral indices to estimate the SM.

Mineral-associated soil organic matter: characteristics and behavior under diagenesis

The main part of soil organic matter (OM) is mineral-associated: 88 ± 11% of С and even more – 93 ± 9% of N. The aims of the given study were: 1 – to demonstrate experimentally the adsorption selectivity of organic compounds towards minerals with different physico-chemical properties (palygorskite vs montmorillonite); 2 – to characterize mineral-associated OM of buried Late Holocene palaeosols and estimate its diagenetic transformations; 3 – to investigate the OM of humin from modern soils of different genesis and Pleistocene and Holocene palaeosols and estimate its diagenetic transformations. The basic soil properties were determined using standard methods. Clay fractions (&lt;2 um) – natural organo-mineral complexes (OMC) were obtained by sedimentation, their mineralogy was studied by XRD. The elemental composition of OM was studied with CNS-analyzer. The structural characteristics of organic matter were determined with the solid-state 13C-NMR-spectroscopy and FTIR-spectroscopy, isotopic composition of C and N – by mass-spectrometry. The obtained results show that the characteristics of mineral-associated OM depends on the properties of mineral “filter” as well as the fate of OM under diagenesis: how long, in what quantity and quality it will persist. It was shown that palygorskite adsorbed predominantly O-alkyls, which are chemically strongly bound. As a result, the age of fulvic type humus in palygoskite palaeosols can reach 300 My. From other side humus of smectitic paleosols of the same age is present by deeply transformed aromatic structures (“coal”). Mineral-associated OM of buried under kurgans Holocene palaeosols contains more alkyls and carboxylic groups, is less aromatic in a comparison with OM of the respective soils. The specific feature of mineral-associated OM is its enrichment in N-compounds. The later are present by both vegetal and microbial compounds, and demonstrate the large affinity towards the mineral surfaces. The formation of chemical bounds between them provides the persistence of OM in OMC. E.g. H2O2 treatment results in preferential destruction of C-rich compounds and oxidized OM demonstrates larger C/N values. Mineral-associated OM of buried Holocene soils keeps the decreased values of C/N (7–14 vs 14–21 for OM of whole soils). Additionally they are characterized by heavier isotopic composition of δ15N in a comparison with the respective soils (5–11‰ vs 6–9‰). It could be explained either by the accumulation of microbial N, or increasing of the humification degree – the loss of aliphatic C and increasing of aromaticity. Humin is the considerable part of soil humus. Experimentally shown that OM of humins both of soils and OMC is enriched in O-alkyls and C of acetal groups. OM of humins are not homogeneous, and consists from at least two groups: mineral-associated OM and partly mineralized plant fragments. As a consequence, the content of humin in OMC is smaller in a comparison with respective soils. It is concluded that mineral-associated OM and humin as well as soil humus represent dynamic soil systems.

Geospatial Distribution of Iron in Major Sugarcane Growing Soils of Sivagangai, Tamil Nadu, India

The present study was undertaken to assess the available DTPA iron status in the major sugarcane growing soils of Southern Sivangai district, Tamil Nadu, India. A total of 500 geo referenced surface (0-30 cm) were collected from five blocks viz., Kalaiyarkovil, Padamathur, Sivagangai, Thiruppachetty and Thiruppuvanam and analyzed for basic soil properties and available DTPA iron. Simple correlation was worked out to ascertain the degree of relationship between soil properties and available DTPA iron content of soil study area. The available DTPA iron in the entire sugarcane growing soils ranged from 2.95 to 5.79 mg kg-1, 2.11 to 4.31 mg kg-1, 3.49 to 5.59 mg kg-1, 1.99 to 5.66 mg kg-1 and 3.94 to 6.39 mg kg-1 in soil samples of Kalaiyarkovil, Padamathur, Sivagangai, Thiruppachetty and Thiruppuvanam respectively. In the soil samples from Kalaiyarkovil, Padamathur, Sivagangai, Thiruppachetty, and Thiruppuvanam, the results revealed that 52, 59, 55, 53, and 51 % of the soils were deficient in available iron and 33, 29, 35, 30 and 32 % of the soils were moderate in available iron, and 15, 12, 10,5 and 17 % of the soils were sufficient in available iron. As per the nutrient index study, the soils of study area recorded very low to low fertility rating for available iron and the mean nutrient index value (NIV) ranged from 1.42 to 1.64 in the soil of the study area. SOC and CEC were found to have a beneficial impact on iron availability, whereas EC and CaCO3 levels had a negative impact on DTPA iron availability.

Сукцессии микробиотических сообществ песчаных почв в разновозрастных сосновых насаждениях лесостепной зоны

Peculiarities of transformation processes in soils should be taken into account when developing strategies for their rational use and optimization of their functions. The purpose of the work is to study the successions of soil microbiotic coenosis of azonal Al-Fe-humus sandy soils in pine forest stands of different age in the cities of the Kursk region. Traditional and innovative methods of studying the microbiological activity of soils are used in the work. Al-Fe-humus sandy soils of the forest-steppe covered with 100-year-old stands of Scots pine emit 2.1-2.3 times more CO2 than Al-Fe-humus sandy soils under 25 - and 70-year-old stands of pine and 1.5 times more than similar soils under herbaceous phytocenoses. It has been established that stands of Scots pine during 100 years of vegetation lead to significant changes in the basic properties of soils, changes in response, increase in podzolic process, changes in hydrothermal conditions, as well as increase in the biomass of the main groups of soil microorganisms (up to 38.1 times). Keywords: MICROMYCETES, ACTINOMYCETES, SANDY PODZOLS, GRAY HUMUS (TURF) SOILS, CO2 EMISSION, MICROBIOLOGICAL ACTIVITY OF SOILS

Knowledge Based Prediction of Standard Penetration Resistance of Soil Using Geotechnical Database

The current study aimed at predicting standard penetration resistance (N) of soil using particle sizes and Atterberg's limits. The geotechnical database was created subsequent to the field and laboratory testing. The sample collection points were distributed in a mesh grid pattern to have uniform sampling consistency. Artificial Neural Networks (ANN) were trained on the database to build a knowledge-based understanding of the interrelation of the given soil parameters. To check the efficacy of the model, the validation was carried out by predicting standard penetration resistance (N) for another 30 samples which were not included in the training data (444 samples). The trained ANN model has been found to predict N values in close agreement with the N values measured in the field. The novelty of the research work is the standard penetration prediction employing basic physical properties of soil. This proves the efficacy of the proposed model for the target civil engineering application. Doi: 10.28991/CEJ-SP2021-07-01 Full Text: PDF

Evaluation of the agricultural soils pollution along the Orava river using pollution indices

Agricultural soil pollution by potentially toxic elements (PTEs) is a major concern nowadays. We selected 11 Fluvisols used as arable land along the river Orava, and two study sites located outside the alluvium (1 Cambisol used as a permanent grassland, 1 Technosol classified as an environmental burden). We determined basic soil properties, total PTEs content and the mobile fraction using inductive coupled plasma mass spectroscopy. Pollution level of selected PTEs was assessed by single contamination factor (Cf) and pollution load index (PLI). The total PTEs content indicated their increased concentrations at many study sites. But the mobile form content of PTEs didn´t exceed the Slovak threshold limits in agricultural soils. Nevertheless, pollution indices reached increased values also in agricultural soils. According to the Cf, the Technosol was very high polluted by Pb (12.89), Sb (11.94), Cd (11.82), Zn (9.19); considerable polluted by As (5.75), Cu (5.70), Mo (4.86); moderate polluted by Cr (2.47), Co (1.92), Ni (1.48). For Fluvisols was confirmed moderate level of pollution, with the exception of Cr (3.24) which confirmed considerable level of pollution. Average Cf for Fluvisols ranged from 1.02 to 9.00 for Cr, from 0.87 to 1.87 for As, from 0.76 to 2.37 for Pb, from 0.61 to 3.48 from Cd. In Cambisol we recorded low level of contamination for Zn (0.87), Cu (0.99), and Pb (0.94), and a moderate level of contamination for the others PTEs. The PLI reached in Technosol 6.02, in Fluvisols 1.46 (range from 1.08 to 2.09), and in Cambisol the lowest value (1.15).

Effect of foam conditioning on performance of EPB shield tunnelling through laboratory excavation test

An appropriate application of a soil conditioning strategy during an earth pressure balance (EPB) shield operation is essential for reducing the downtime accompanied by improvements to the hydro-mechanical properties of the muck. Among the various additives used for conditioning, foam is the most widely adopted owing to its usability. In this study, to simulate EPB tunnelling and study the effects of ground and foam injection conditions in the laboratory, a lab-scale excavation test apparatus was devised. This apparatus was designed to vertically excavate the soil specimen with the simultaneous injection of foam and water, and discharge the conditioned muck. Subsequently, a series of excavation tests were conducted using artificial sandy soil to estimate the effects of the fine content, water content, and foam injection conditions, which can affect the performance of EPBs. Based on the measured torque, the weight loss of the cutter bits, and the slump of the muck from the excavation tests, the effects of foam injection parameters, namely, the foam injection ratio, foam expansion ratio, and concentration of foaming agent were discussed. The results show that the suggested laboratory excavation test can be used to qualitatively evaluate the effects of the basic soil properties and foam injection conditions on EPB shield tunnelling.

Creep Behavior of Saturated Clay in Triaxial Test and a Hyperbolic Model

As one of the basic mechanical properties of soil, the creep property of a given type soil is related to stress path, and stress level. In this paper, triaxial shear creep tests under different deviatoric stress levels were performed on both intact sample and the reconstituted sample of clay taken from Hangzhou, China. Based on the Boltzmann linear superposition principle, the creep curves of the clay sample under different levels of deviatoric stress were obtained, and the creep characteristics of the intact sample and the reconstituted sample were compared in both total stress creep analysis and effective stress creep analysis. Furthermore, the creep curves were fitted using a hyperbolic creep model. The results show that (1) under the same stress level, the creep of intact sample evolves more than that of reconstituted sample; (2) the hyperbolic creep model is suited to describe the creep characteristics of intact and reconstituted clay, and the model parameters A s and B s can be linearly correlated to the stress level D r ; (3) for the application of the hyperbolic model, the total stress analysis works better, and the model parameters A s and B s can be determined by a linear relationship with Dr.

Assessment of the soil fertility status in Benin (West Africa) – Digital soil mapping using machine learning

A soil fertility index map (SFIm) can provide key information to decision-makers in regard to spatial planning in the context of sustainable land management. The establishment of such SFIm requires basic soil properties that can be modelled for spatial mapping. The objective of this study was to take advantage of Benin soil legacy data to produce a digital SFIm at a national level based on 8 soil properties (soil organic matter, nitrogen, pH (water), exchangeable potassium, assimilable phosphorus, sum of bases, cation exchange capacity and base saturation). Specific research aims were (1) to model and develop digital soil maps, (2) to identify the key covariates influencing soil nutrients, and (3) to build an SFIm using digital maps of the soil properties. For each soil property, modelling procedures involved the use of different covariates, including soil type, topographic, bioclimatic and spectral data, along with the comparative assessment of the cubist (CB) and quantile random forest (QRF) models. Models were evaluated not only on the basis of classical error metrics (RMSE, R2) but also on the ability to predict local uncertainty based on the prediction interval coverage probability (PICP). The results revealed that CB performed marginally better than the QRF based on classical error metrics (R2, RMSE) but produced the worst uncertainty with an overestimation of the local uncertainty. This suggested that the use of accuracy plots such as PICP to evaluate models can identify accuracy problems not evident with classical error metrics. The analysis revealed that the distance to the nearest stream, which was part of topographic covariates, had strong predictive ability for all the soil properties along with the bioclimatic variables. The spatial distribution of the different classes of SFIm showed a preponderance of low fertility levels with severe limitations for crop development. A limited number of high and average fertility level soils were found in the low elevation areas of southern Benin, and policy could advocate for their sole use for agricultural purposes and promote sustainable management practices.

Hierarchical prediction of soil water content time series

Quantifying the spatial and temporal dynamics of soil moisture is an important subject in vadose zone hydrology. A 1282-day field study was conducted to provide a hierarchy of data to assess neural network simulations of field soil water content time series θ(t). Volumetric water content was determined, typically once a week, by neutron thermalization at 20-, 40-, 60-, 80- and 100-cm depths. Soil samples were taken at 60 locations between 14- and 114-cm depths to determine soil properties, water retention, and saturated hydraulic conductivity. Prediction of hydraulic parameters from basic and extended soil properties yielded low correlation coefficients. Water content could be predicted reasonably with neural networks from soil properties or hydraulic parameters (0.880 < R < 0.942). Prediction of θ(t) based solely on rainfall data was not accurate. Independent networks could accurately simulate water content from one observed θ(t) based on the Nash-Sutcliffe Model Efficiency and Percent Bias. Once a network is trained for a particular depth, accurate predictions can be made beyond the training period using observations at just one location.

Performance Characterization of Unsaturated Granular Soils Using Static and Dynamic Plate Load Test

Abstract Determination of the modulus of subgrade reaction (ks) is an essential geotechnical design parameter that describes the relationship between stress and the associated settlement of soils. The ks is typically obtained using a laborious and costly method called the plate load test (PLT), and thus, to overcome the limitations related to the PLT, determining an alternative testing technique that can easily predict the ks is a priority. The feasibility of using a light weight deflectometer (LWD), also known as the dynamic PLT, to determine the ks of unbound pavement layers was thus investigated in this research. Eighteen laboratory testing models of granular soils were prepared and tested using the dynamic PLT (LWD) in conjunction with the static PLT (PLT). The soils’ characteristics examined under both dynamic and static loading conditions were analyzed and correlated. A series of multiple nonlinear regression analyses were conducted using three groups of independent variables: (1) LWD measurements, (2) basic soil properties, and (3) LWD data plus basic soil properties. Several nonlinear regression models were developed to predict the modulus of subgrade reaction on the basis of the LWD measurements and selected soil characteristics. The results revealed that certain LWD measurements, including dynamic modulus (Ed), surface deflection (δ), and degree of compatibility (Dc), are strongly correlated with the results from PLT. Additionally, good correlations were identified between ks and maximum dry density, suggesting that using LWD measurements along with basic soil properties yields correlations with adequate prediction quality.

Allocation of foliar-P fractions of Alhagi sparsifolia and its relationship with soil-P fractions and soil properties in a hyperarid desert ecosystem

Desert vegetation in the juncture of the Qira oasis and the Taklamakan Desert typically grows on phosphorus (P)-poor soils. Alhagi sparsifolia Shap. (A. sparsifolia), as widely distributed natural vegetation in this area, not only has crucial ecological effects of wind sheltering and sand fixation, but also is an excellent forage resource. Researchers are increasingly interested in the foliar-P utilization strategy of A. sparsifolia that allows it to survive in extremely P-impoverished soils. Therefore, A. sparsifolia growing in four different soil sites with differing availability of P in this area were studied, and leaves and 0–100 cm soils were collected. Foliar total nitrogen (N), total-P and P fractions (metabolic-P, nucleic acid-P, structural-P, and residual-P) were determined. Soil labile-P (resin-P, NaHCO3-Pi, and NaHCO3-Po), moderately labile-P (NaOH-Po and NaOH-Pi), stable-P (HCl-P and residual-P), and basic soil properties were determined. Our findings showed that A. sparsifolia growth was highly likely to be limited by soil-P in this area, and the concentrations of foliar total-P and young leaf metabolic-P increased with increasing soil-P availability, while foliar-N was relatively constant. Comparatively, A. sparsifolia allocated a higher proportion of foliar-P to nucleic acid-P and a lower proportion to structural-P, as soil-P availability decreased. Moreover, foliar metabolic-P, nucleic acid-P, and structural-P had the strongest positive response to soil labile-P in topsoil. Furthermore, soil electrical conductivity (EC), labile-P, and moderately labile-P influenced foliar-P fractions. Comprehensively, variation in foliar-P allocation patterns of A. sparsifolia varied across the four soils with differing available-P and were closely related to soil-P fractions and properties. These results will help us better understand A. sparsifolia foliar-P utilization strategy and their potential responses to environmental nutrients.