Soil Particle Size Distribution Research Articles

Characterizing hydrological-sensitive areas of the Kinyerezi river sub-catchments in Dar es Salaam, Tanzania using the topographic index approach

Abstract Several areas experience frequent floods due to anthropogenic activities. Among them, is the Dar es Salaam city, which experiences frequent floods along the Msimbazi River, whose flows originate from different tributaries including the Kinyerezi River. This study aims to evaluate the hydrological-sensitive areas of the Kinyerezi River sub-catchments using topographic index values (λ*) that enable the identification of areas with a higher probability of generating surface runoff. A digital elevation model was utilized to delineate the Kinyerezi River sub-catchment characteristics using ArcGIS 10.4. Soil infiltration rates (Ks) on selected open places were determined using a Guelph permeameter. Soil particle size distributions were analyzed and the λ* values were evaluated. The results showed the particle size distribution contains sand and silt-clay ranging from 46 to 84% and 16 to 53%, respectively. The Ks ranged from 0.6 to 7.8 mm/h while the sub-catchment KS3 scored the highest λ* value of about 10.7. Hence, there is a higher probability for generating surface runoff. Sub-catchment KS16 scored the smallest λ* value of 5.7, perceived to generate less surface runoff. Low-impact development practices capable of capturing runoff and enabling infiltration, evaporation, and detention should be employed in sub-catchments with higher λ* values.

IntraPD model: Leaching of heavy metals from naturally contaminated soils

This paper presents a novel method for predicting the migration of heavy metal contaminants in soils that contain heavy metal pollutants deep within the particles, which may cause delayed leaching. The proposed approach, the intraparticle pore-diffusion (IntraPD) model, incorporates both intraparticle diffusion and sorption equilibrium and is utilized to simulate batch leaching tests of heavy metal-contaminated soils using the finite difference method. The IntraPD model can solve the leakage of heavy metals from contaminated soil particles of arbitrary particle size distribution as a one-dimensional, polar-symmetric problem in the spherical coordinate system, assuming the soil particles to be porous perfect spheres. The findings from the simulation demonstrate a notable impact of soil particle size distribution on both the leaching rate and the amount of contaminants. Specifically, the coefficient of uniformity, which indicates the ratio of the maximum to minimum particle size, was identified as a significant factor influencing the leaching rate. When the coefficient of uniformity is less than or equal to 5, it has a combined effect on the leaching rate. However, when the coefficient of uniformity exceeds 5, the maximum particle size becomes the primary determinant of the leaching rate. The proposed model provides a valuable tool for accurately simulating batch leaching tests of naturally contaminated soils with diverse particle size distributions.

On evaluating the hypothesis of shape similarity between soil particle-size distribution and water retention function

Two pedotransfer functions (PTFs) are available in the literature enabling the soil water retention function (WRF) to be estimated from knowledge of the soil particle-size distribution (PSD), oven-dry soil bulk density (b), and saturated soil water content (s): i) the Arya and Heitman model (PTF-AH) and ii) the Mohammadi and Vanclooster model (PTF-MV). These physico-empirical PTFs rely on the hypothesis of shape similarity between PSD and WRF, and do not require the calibration of the input parameters. In the first stage, twenty-seven PSD models were evaluated using 4,128 soil samples collected in Campania (southern Italy). These models were ranked according to the root mean square residuals (RMSR), corrected Akaike Information Criterion (AICc), and adjusted coefficient of determination (R2adj). In the second stage, three subsets of PSD and WRF data (DS-1, DS-2, and DS-3), comprising 282 soil samples, were used to evaluate the two PTFs using the best three PSD models selected in the first stage. The hypothesis of shape similarity was assumed as acceptable only when the RMSR value was lower than the field standard deviation of the WRFs (*), which is viewed as a tolerance threshold and computed from the physically-based scaling approach proposed by Kosugi and Hopmans (1998). In the first study area (DS-1), characterized by a fairly uniform, loamy textured volcanic soil, the PTF-AH outperformed the PTF-MV and both PTFs provided reasonable performance within the acceptance threshold (i.e., RMSR < *). In the other two heterogeneous field sites (DS-2 and DS-3, characterized by soil textural classes that span from clay and clay-loam to loam and even sandy-loam soils), the PTF-MV (with 3% to 6% RMSR surpassing *) outperformed the PTF-AH (with 8% to 30% RMSR surpassing *) and the majority of RMSR values were larger than those obtained in the original studies. The mean relative error (MRE) revealed that the PTF-MV systematically underestimates the measured WRFs, whereas the PTF-AH provided negative MRE values indicating an overall overestimation. The outcomes of our study provide a critical evaluation when using calibration-free PTFs to predict WRFs over large areas.

Effective soil particle size distributions and critical size of enrichment/depletion in splash erosion for loessial soil

Effective soil particle size distributions and critical size of enrichment/depletion in splash erosion for loessial soil

The effect of adding weights and the forward speed of the agricultural tractor on some mechanical properties using the moldboard plow

The study was conducted during the agricultural season (2017-2018) and the size distribution of soil particles was (10.5% sand, 51.7 clay, 38.25 silt) so soil texture is clay soil to find out the effect of adding weights on the wheels of the agricultural tractor using the moldboard plow by measuring some indicators, including the drawbar power, soil resistance penetration, tillage depth achieved, and the soil disturbed volume and the field was divided according to a split plot arrangement under Randomized Complete Block Design with three replications. The results of the study showed that the addition of weights on the wheels of the tractor (310) kg recorded the lowest value for drawbar power and highest value for the tillage depth achieved, and the soil disturbed volume, while not adding weights (0) recorded the lowest value for the soil resistance penetration. The forward speed (3.3) km.h-1 excelled in recording the lowest value of the drawbar power and highest value of tillage depth achieved, while the third speed (7.7) km.h-1 excelled in recording the highest value of the soil disturbed volume and the lowest value of soil resistance penetration. The interaction between adding weights on the wheels of the tractor (310) kg and the forward speed (3.3) km.h-1 registry the less value the drawbar power and the highest value for soil resistance penetration and tillage depth achieved, while the addition of weights on the wheels tractor (310) kg and the forward speed (7.7) km.h-1 registry the highest value of the soil disturbed volume.

Grain size characteristics of surface sediment in the Jilantai Salt Lake Protection System after long‐term wind‐sand activities

AbstractIn order to explore the influence of vegetation on homogeneity of surface particle size distribution (PSD) and heterogeneity of soil structure, observations, theory, and multifractal results were synthesized to highlight the evolution of the soil particle composition in the Jilantai Salt Lake Protection System (Jilantai system) after long‐term wind‐sand activities and its soil structure characteristics. From flowing sand dune to saline‐alkali wasteland areas, the mean grain size and surface particle sorting degree gradually increased and decreased, respectively, whereas the shape of the particle frequency curve gradually changed from extremely positive deviation to negative deviation, and the peak shape of the curve gradually changed from narrow to wide. Furthermore, the inhomogeneity of the soil particle composition gradually decreased, whereas the range of the soil PSD gradually increased, and the soil increasingly became fine‐grained. Therefore, the contents of clay and silt in shelterbelt soil increased by 16% and 18.36%, respectively, over 1986 levels. Additionally, clay and silt play a vital role in determining soil particle parameters such as standard deviation (SD), skewness (SKI), and monofractal (D), while vegetation factors are the main controlling factors of clay and silt. In conclusion, the Jilantai system could increase heterogeneity and homogeneity and decrease the concentration of soil PSD by changing the sedimentary environment, while this affect depends largely on the fractional vegetation cover, vegetation height, and light penetrating porosity. Moreover, the multifractal and particle parameters could describe the soil structure characteristics and sedimentary process, respectively, after long‐term wind‐sand activities.

Spatial Variations and Distribution Patterns of Soil Salinity at the Canal Scale in the Hetao Irrigation District

Soil salinization is a major factor impacting global crop yields. To explore the spatial distribution and influencing factors of soil water and salt in typical canals of the Hetao irrigation district, regional soil information was monitored at fixed locations. In this study, classical statistics, geostatistics, and spatial autocorrelation methods were used to conduct quantitative analyses of soil salt content, water content, soil particle size distribution, and groundwater depth. The variation coefficient of the soil salt content in the 20–40 and 40–60 cm soil layers was between 10% and 100%, which corresponds to a medium degree of variation; the other soil layers had strong degrees of variation. The soil moisture content in each layer varied moderately. The gold coefficients of soil salt content and water content were less than 0.25, and the Z value was greater than 0, showing a strong spatial correlation and certain spatial agglomeration characteristics, which were mainly affected by structural factors in the study area. The distribution patterns of soil water and salt were affected by soil particle size. Sand content decreased with increasing depth, soil salt was negatively correlated with sand content, and soil water was positively correlated with sand content. Soil salinity was significantly affected by groundwater depth and increased with decreasing groundwater depth, following an exponential relationship. When the groundwater depth exceeded 1.7 m, the soil salt content exhibited small changes with groundwater depth. The results of this study could play a guiding role in terms of understanding the degree of soil salinization surrounding canals in the Hetao irrigation area and adjusting land management strategies over time.

The response of organic carbon fractions in sediment to rainfall characteristics and slope lengths: Based on four-years on-site monitoring data

The effect of soil erosion processes on the properties of sediment and organic carbon fractions is not well understood under complex erosion environments, such as various rainfall characteristics and transport distances, which leads to a gap in knowledge regarding the role of soil erosion in the global carbon cycle. This study investigated the impact of different rainfall characteristics (patterns and parameters) and slope lengths (5 m ∼ 20 m) on the sediment yield, particle size distribution (PSD) and properties of organic carbon fractions on China’s Loess Plateau. The results show that runoff was highest under rainfall pattern A (extreme rainfall), while the sediment concentration peaked under rainfall pattern B (heavy rainfall), with significant correlation with slope length, rainfall intensity, kinetic energy, rainfall erosivity and precipitation (p less than 0.05). Silt- and clay-sized fractions were transported as primary particles and enriched under rainfall patterns B and C with no differences between slope lengths. The enrichment ratio (ER) of sediment, effective and ultimate particles were primarily influenced by rainfall intensity-related parameters. In contrast, the aggregation ratio (AR) tended to be influenced by rainfall kinetic energy. The content and loss of organic carbon fractions correlated to rainfall parameters and slope length, although no significant difference was observed between different rainfall patterns and slope lengths. Lost organic carbon fractions were predominantly Mineral-associated organic carbon (MOC), with great enrichment under rainfall pattern C and rapid depletion as the slope length increased. Structural equation models (SEM) indicated the effect of rainfall characteristics and slope length on organic carbon loss was mainly due to the regulation of soil loss and particle size distribution of sediment in selective transport erosion processes. We highlighted the need to consider the effect of soil erosion and particle size distribution comprehensively on the carbon cycle from the perspective of organic carbon fractions to describe the potential effects of soil erosion on the carbon budget quantitatively, especially in complex environmental conditions with consideration of scale effect.

Responses of soil aggregate stability and soil erosion resistance to different bedrock strata dip and land use types in the karst trough valley of Southwest China

Soil aggregate stability is an important index that reflects soil quality and anti-erosion ability and strongly affects soil processes and functions. Bedrock strata dips (dip and anti-dip slopes) and land use types primarily influence soil aggregate stability, whereas the detailed mechanisms are unclear in karst trough valley. Therefore, to explore the effects of bedrock strata dip and land use type on soil aggregate stability in karst trough valleys, soils were collected from five major land use types (abandoned land, grassland, pepper fields, corn fields and forest) on dip and anti-dip slopes. The soil was fractionated into macroaggregates and microaggrates using dry and wet sieving analysis. The soil particle size distributions in the macroaggregates and microaggregates were measured in conventional laboratories. The results showed significant differences in soil aggregate stability among different bedrock strata dips, slope positions, and land use types (P < 0.05). The variation ranges of macroaggregates and microaggregates in the pepper fields of the dip slope were higher than those on the anti-dip slope. Comparing all land use types, the forest of the anti-dip slope had >0.25 mm water-stable aggregates (85.31%) and mean weight diameter (2.67 mm) on the upper slope compared to that in the other slope positions of the dip slope. In addition, the dip slope had a higher percentage of aggregate destruction (35.57%) than the anti-dip slope (29.81%), and the soil erodibility factor value of the natural forest of the dip/anti-dip slope was significantly lower than that of the other land use types (P < 0.05). When the content of large macroaggregates was larger, the soil macroaggregate weight was greater. When the failure rate of the soil aggregates was lower, the stability of the soil structure was better. Overall, these results suggest that natural forests can significantly improve the stability of soil aggregates, thereby improving soil erosion resistance. Therefore, natural recovery measures should be implemented on dip/anti-dip slopes of karst trough valleys.

Understanding the balance between soil conservation and soil water storage capacity during the process of vegetation restoration in semi‐arid watersheds in the Loess Plateau, China

AbstractIn the Loess Plateau, gaining insights into the water storage and soil retention functions of diverse vegetation types, especially, in the semi‐arid watersheds is crucial for identifying the key factors necessary to ensure sustainable development and achieve land degradation neutrality. In this study, five different land use types such as forest, shrub, artificial grass, and natural grasslands were surveyed from 2014 to 2020. Meanwhile, bare land was also used as a control plot. The trade‐off between erosion mitigation and water consumption indicator was quantified based on the ecosystem services perspective benefits. Our results showed that there are significant differences among different land use types (p &lt; 0.05): natural grassland &gt; shrubs &gt; artificial grassland &gt; forests. Vegetation restoration was able to change the soil particle size distribution, increasing clay and silt content, and decreasing sand particles. During the growing season, surface soil water storage decreased in all land use types coinciding with the higher decrease in the control plot. The change in surface water storage in the forest was the most stable, with a decrease of 0.13 mm. The trade‐off between erosion mitigation and water consumption indicator was less than 0 for all vegetation types, which indicates a synergistic effect on soil conservation and water storage benefit. Our results demonstrated that shrubs can register the most balanced benefit of water storage and soil preservation. This is a solid basis for the selection of specific vegetation types and the optimization of the watershed landscape in the middle reaches of the Yellow River, characterized by vulnerable areas due to aridification.

Quantifying Soil Particle Settlement Characteristics through Machine Vision Analysis Utilizing an RGB Camera

Soil particle size distribution is a crucial factor in determining soil properties and classifying soil types. Traditional methods, such as hydrometer tests, have limitations in terms of time required, labor, and operator dependency. In this paper, we propose a novel approach to quantify soil particle size analysis using machine vision analysis with an RGB camera. The method aims to overcome the limitations of traditional techniques by providing an efficient and automated analysis of fine-grained soils. It utilizes a digital camera to capture the settling properties of soil particles, eliminating the need for a hydrometer. Experimental results demonstrate the effectiveness of the machine vision-based approach in accurately determining soil particle size distribution. The comparison between the proposed method and traditional hydrometer tests reveals strong agreement, with an average deviation of only 2.3% in particle size measurements. This validates the reliability and accuracy of the machine vision-based approach. The proposed machine vision-based analysis offers a promising alternative to traditional techniques for assessing soil particle size distribution. The experimental results highlight its potential to revolutionize soil particle size analysis, providing precise, efficient, and cost-effective analysis for fine-grained soils.

The role of abrasion in cyclically sheared soil–structure interfaces

A limiting factor in the drive to deliver performance-based design is the lack of knowledge regarding the constitutive behaviour of soil–structure interfaces, particularly in the case of cyclic loading. A series of experiments was undertaken using both a traditional interface shear apparatus (shearing a large body of soil grains over a structural interface) and a novel single-particle interface shear apparatus (involving shearing a single grain over a structural interface). In both cases the soil was sheared across the interface in a cyclical manner (more than 1500 cycles per test). For the traditional apparatus, a clear change in soil particle size distribution and abrasive wear of the structural interface occurs after many cycles. This change results in a significant increase of the interface friction ratio, which is the main parameter used in traditional design – increasing from approximately 0·2 (11°) to 0·7 (35°). The single-particle apparatus validated the results – where a significant increase in the friction ratio after many cycles was also observed. The novel interface behaviour presented in this paper may lead to improved interface constitutive models and consequently more economic and safer geotechnical designs.

Particle size effects on the axial pull-out and push-in behaviour of roots

For smaller plant roots in coarse-grained soils, large relative size of soil particles compared to roots can affect their axial resistance. Even for the larger roots of trees, particle size effects may be important, e.g. when testing 1:N scale models of tree uprooting in a geotechnical centrifuge. In this study the distinct element method (DEM) was used to investigate this problem. The sinker root of a centrifuge model tree root system under axial loading was analysed, with its simulated behaviour compared with finite element method (FEM) simulations, where the soil was modelled as a continuum and hence did not incorporate particle size effects. Both were validated against laboratory tests. Considering the same prototype size and soil particle size distribution, different scale factors/g-levels were applied to model roots, hence varying the ratio of root diameter (dr\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${d}_{\\rm r}$$\\end{document}) to mean particle size (D50\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${D}_{50}$$\\end{document}). Even at the lower dr/D50\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${d}_{\\rm r}/{D}_{50}$$\\end{document} values investigated (6–21), particle size effects on end-bearing capacity were negligible upon push-in of the root. In contrast, effects on shaft resistance (for pull-out) were significant and were interpreted by a simplified analytical model developed in this study using a combination of cavity expansion and root-particle size ratio. The absolute size of the root analogues considered was also representative of small diameter roots present in other plant species at 1:1 scale, making the analytical model also applicable to crop-lodging problems and for defining input parameters for analyses of nature-based solutions (NBS) using vegetation (e.g. for slope stabilisation).

Factors affecting soil treatment with the microbially induced carbonate precipitation technique and its optimization

The microbially induced carbonate precipitation (MICP) technique has been used to increase mechanical strength, reduce permeability, and fix radionuclides of soils, etc. To achieve effective soil cementation by MICP, 3 aspects should be considered: MICP efficiency, bacterium retention (in soils after injections), and precipitation uniformity. Here, experiments and statistical analyses were conducted to understand the parameters affecting the 3 aspects. Moreover, the parameters leading to better performance in these aspects were designed and used to conduct MICP soil cementation with varying the number of injections. The results present that temperature and OD600nm of bacterial suspension are the most important parameters affecting MICP efficiency, followed by reaction time, pH, and concentration of cementation solution, and they are all statistically significant. As these parameters increased, MICP efficiency (ratio of CaCO3 formed to Ca2+ added) first increased quickly and then slowly or decreased. The soil particle size distribution and injection rate affected bacterium retention greatly. Smaller particle sizes, wider particle-size-distribution spans, and slower injection rates are beneficial to bacterium retention. However, higher injection rates favour precipitation uniformity. Finally, the unconfined compressive strength (UCS) of the bio-treated soil can be increased further by increasing the number of injections.

Effects of moisture content on strength and compression properties of foundation soils of cultural relics in areas flooded by the Yellow River

This study investigated the effects of soil moisture content on the strength and deformation properties of the foundation soils of cultural relics. Our goal is to inform the formulation and implementation of the repair scheme for cultural relics above the foundation soils and help protect cultural relics. Soil samples with five different moisture contents were prepared and used in unconfined compression, triaxial, and consolidation tests. Several mechanical parameters were determined under different soil moisture contents: failure morphology, compressive strength, compressive modulus, and compressibility coefficient. Based on the test results, the soil cohesion and angle of internal friction were obtained using Mohr’s circle. Regions where the mechanical parameters were particularly sensitive to moisture content were located during the consolidation test. These were also the regions where the soil’s compressive modulus declined rapidly, which was detrimental to the overall stability and safety of overlying structures. The internal structure and particle size distribution of the foundation soils supporting cultural relics were determined by scanning electron microscopy. Constitutive parameters of soils were determined by the triaxial test and consolidation test. It was also found that when the soil moisture content exceeded the optimal level, the foundation soils were very likely to pose a risk to the safety of the overlying cultural relics. The moisture content of foundation soils supporting cultural relics deserves special attention in engineering practice.

Development of land-use-specific pedotransfer functions for predicting bulk density of acidic topsoil in eastern Himalayas (India)

Soil bulk density (BD), although a key input parameter in many soil functions is often overlooked in soil studies, including surveys. Direct measurements over a large area are slow and expensive, especially in resource-poor mountain ecosystems. For soils of eastern Himalayan ecosystems, cost-effective indirect methods such as pedotransfer functions (PTFs) are lacking. We developed seven landuse-specific PTFs for BD estimation using a soil particle size distribution (sand, and silt) and soil organic carbon database of 1206 sampling sites. Land uses were 3 uncultivated (dense forests-DF, open forests-OF, and grasslands-GL), 3 cultivated (shifting cultivation-SC, upland agriculture -UA, lowland paddy-LP), and a perennial plantation (PL). PTFs were developed using five machine learning algorithms (MLAs) and a multi-linear regression (MLR). The best PTFs were chosen based on cross-validation performance with the values of the greatest coefficient of determination (R2) and the smallest root mean square error (RMSE). In addition, the relative performance of thirteen (13) documented PTFs was evaluated on soils in the region. Among the MLAs, the artificial neural network (ANN) showed the best BD prediction for the whole dataset (R2: 0.58, RMSE: 0.09 Mg m−3) and four (e.g. GL, UA, SC, and LP: R2 of 0.65 to 0.69, RMSE of 0.06 to 0. 09 Mg m−3) of the seven land use classes. For the remaining three land uses (e.g., DF, OF and PL), based on the greatest R2 values (0.55 to 0.75), PTFs based on random forests (RF) made the best predictions. However, considering the smallest RMSE values (0.06–0.08 Mg m−3), ANN-PTFs were another option for these three land uses. Of the land uses, the best prediction for BD was obtained for PL (R2: 0.75), while the DF with variable soil properties had the lowest predictive performance (R2: 0.55). The performance of MLA-based PTFs such as the support vector machine (SVM), ridge regression (RR), and extreme gradient boosting (XGB) and MLR-PTFs were lower than the ANN-PTFs and RF-PTFs. The precision of BD prediction for 13 published PTFs was inconsistent and inferior (R2: 0.13 to 0.39) to the ANN-PTFs and RF-PTFs (R2: 0.55 to 0.75) developed in this study. Since PTFs are very region-specific, we suggest ANN-PTFs to estimate the BD of grasslands and cultivated soils while the RF-PTFs (based on the greatest R2) for dense and open forests and plantation soils in the eastern Himalayas and similar mountain ecosystems.

Efficiency of Different Soil Sterilization Approaches and Their Effects on Soil Particle Size Distribution

Efficiency of Different Soil Sterilization Approaches and Their Effects on Soil Particle Size Distribution

Predicting the interrill erosion rate on hillslopes incorporating soil aggregate stability on the Loess Plateau of China

The Water Erosion Prediction Project (WEPP) model is a physical process-based model that can predict both interrill and rill erosion on hillslopes. The interrill erodibility (Ki) is quantified by the soil particle size distribution, which is a key parameter in WEPP model. However, the important effects of soil structure on soil erodibility are ignored, which seriously affects the prediction accuracy of the model. In this study, simulated rainfall experiments (60, 90, 120 mm h−1) were performed to improve the prediction equation of interrill erosion incorporating the aggregate instability index (As). Rare earth elements (REEs) were employed as tracers to distinguish interrill and rill erosion on slopes in a box (2 m long, 0.5 m wide, 0.4 m deep) with gradients of 10°, 20° and 30°. The Le Bissonnais method was used to determine the soil aggregate stability. The results showed that aggregate stability played a crucial role in interrill erosion under similar runoff rates. The improved equation contains four parameters, As, runoff rate (q), rainfall intensity (I) and slope gradient (Sf), with a coefficient of determination (R2) of 0.81 and model efficiency (ME) of 0.79. This equation exhibits greatly improved efficiency in estimating the interrill erosion rate compared to the WEPP model. Furthermore, a new equation incorporating the As, flow velocity (v), flow depth (h) and hydraulic gradient (J) was developed, with R2 of 0.90 and ME of 0.89. This study provides a deeper understanding of the mechanism of interrill erosion and improves upon the physical process-based soil erosion model.

The relationship between the granulometric composition of grassland soils and their content of mineral nitrogen and organic carbon

The study analysed the relationship between the granulometric composition of grassland soils as determined by laser diffraction and their content of mineral forms of nitrogen and organic carbon. The content of mineral forms of nitrogen (NO 3-N and NH 4-N) in soil samples – after their extraction with 1% solution K 2SO 4, was determined by flow colourimetry. Soil organic carbon content was determined using the Tyurin method. The study examined soil samples collected from 169 control and measurement sites located in different regions of Poland in terms of conditions for agricultural production. Statistical analyses of the research results showed that the grain size of grassland soils had a significant effect on their ammonium nitrogen content but not on their nitrate nitrogen and organic carbon content. In this respect, it was found that there was a positive correlation between the share of the sand fraction and the content of ammonium nitrogen in soils and an opposite relation between the share of coarse silt, fine silt and clay and the content of the aforementioned component. Results of the analyses differ considerably from the results of studies by other authors on the influence of soil grain size distribution on the content of mineral nitrogen and organic carbon in soils based on classical methods of measurements of soil particle size distribution. There is a need to develop solutions to convert and compare results obtained by laser diffraction and standard methods.

A systematic approach to predicting and mapping soil particle size distribution from unknown samples using large mid-infrared spectral libraries covering large-scale heterogeneous areas

Soil spectroscopy has the potential to replace wet chemical methods. However, high prediction accuracy of unknown samples is necessary to confidently map predicted values across large spatial scales. This study developed a systematic approach using MIR spectroscopy to predict soil particle size of 9,009 unknown samples, representing an area of approximately 35,716 km2 in Ireland. A systematic approach for MIR spectroscopy combined with chemometrics was augmented by including spectral control charts to identify unrepresentative spectra in predicting of unknown samples. Moreover, ∼2% of the predicted values (external validation) were selected, covering a wide range of clay, sand and silt, and analysing them using the classical reference method. This step assesses the accuracy of predicted values and provided confidence when projecting predicted values onto soil particle size maps at multiple regional scales.The MIR models were based on the support vector regression algorithm, and were built using a calibration dataset of ∼1,000 mineral and organo-mineral (MOM) soils, i.e., non-peat soils, analysed using the pipette method. The model was used to predict soil particle size from 9009 unknown samples described as MOM soils. Spectral control charts correctly identified 97.59% of the peat soils (3078 out of 3154 samples) as ‘out of control’ samples, which the spectral model should not predict, and about 90% of the MOM soils (5254 out of 5855 samples) were classified as ‘under control’ samples, which the spectra models can predict. The accuracy calculated for the ∼2% of samples selected from the MOM unknown samples (n = 5254) was similar to the accuracy in the internal validation set (n = 280), with R2val values of 0.90, 0.84 and 0.71, RMSEP values of 2.21, 4.31 and 3.91%; RPIQval values of 4.97, 3.71 and 2.30, for clay, sand and silt prediction, respectively. This systematic approach can predict soil attributes using large spectral libraries, providing confidence for building regional and national scale soil maps.