Important Soil Parameters Research Articles

A new method to estimate the soil freezing characteristic curve

The soil freezing characteristic curve (SFCC) defines the relationship between unfrozen water content and temperature. It is an important soil parameter in cold regions, but it is not easy to obtain, especially in the field. This paper proposes a method to indirectly estimate the SFCC for both fine-grained and coarse-grained soils by using the one-measurement SFCC method. From regression analysis, the parameters of the van Genuchten SFCC model can be expressed as functions of an adjustable parameter x. The SFCC of a soil sample contained three different zones, and sensitivity analysis indicated that the measured point in Zone 2 provided the most reliable SFCC estimation results. The proposed model and four widely acknowledged models were compared and evaluated with 33 fine-grained soils and 9 coarse-grained soils. The results showed that the proposed model provided the best estimation of the SFCC among the five models. This result also indicated that the proposed model provided a better estimation of the SFCC for fine-grained soils. This study provides a reliable approach to develop an SFCC estimation model with the one-measurement SFCC method.

Modeling of Soil Cation Exchange Capacity Based on Chemometrics, Various Spectral Transformations, and Multivariate Approaches in Some Soils of Arid Zones

Cation exchange capacity is a crucial metric for managing soil fertility and promoting agricultural sustainability. An alternative technique for the non-destructive assessment of important soil parameters is reflectance spectroscopy. The main focus of this paper is on how to analyze and predict the content of various soil cation exchange capacities (CEC) in arid conditions (Sohag governorate, Egypt) at a low cost using laboratory analysis of CEC, visible near-infrared and shortwave infrared (Vis-NIR) spectroscopy, partial least-squares regression (PLSR), and Ordinary Kriging (OK). Utilizing reflectance spectroscopy with a spectral resolution of 10 nm and laboratory studies with a spectral range of 350 to 2500 nm, 104 surface soil samples were collected to a depth of 30 cm in the Sohag governorate, Egypt (which is part of the dry region of North Africa), in order to accomplish this goal. The association between the spectroradiometer and CEC averaged values was modeled using PLSR in order to map the predicted value using Ordinary Kriging (OK). Thirty-one soil samples were selected for validation. The predictive validity of the cross-validated models was evaluated using the coefficient of determination (R2), root mean square error (RMSE), residual prediction deviation (RPD), and ratio of performance to interquartile distance (RPIQ). The results indicate that ten transformation methods yielded calibration models that met the study’s requirements, with R2 > 0.6, RPQ > 2.5, and RIQP > 4.05. For evaluating CEC in Vis-NIR spectra, the most efficient transformation and calibration model was the reciprocal of Log R transformation (R2 = 0.98, RMSE = 0.40, RPD = 6.99, and RIQP = 9.22). This implies that combining the reciprocal of Log R with PLSR yields the optimal model for predicting CEC values. The CEC values were best fitted by four models: spherical, exponential, Gaussian, and circular. The methodology used here does offer a “quick”, inexpensive tool that can be broadly and quickly used, and it can be readily implemented again in comparable conditions in arid regions.

Prediction of hysteretic soil and water characteristic curve of loess based on multifractal theory and improved physical statistics

Soil and water characteristic curve (SWCC) is an important soil parameter which is used to estimate various parameters to describe unsaturated soil hydrodynamic properties. Due to the large span of soil matric suction, this procedure is time-consuming and difficult to measure it in the laboratory. However it is of great significance to find a scientifically efficient and economically viable method to predict SWCC of loess soil. Based on the measurement of soil–water characteristic curves in the laboratory, this study predicted the drying curve (DC) based on the soil particle size distribution (PSD) fractal theory. It also used the domain model to predict the wetting curve (WC) based on the pore distribution, and finally obtained the complete soil–water characteristic curve of loess. These procedures improved the research status which using the drying curve to instead of the wetting curve, and this replace usually leads to a large calculation error and underestimates the safety of the slope. The method proposed in this study can quickly obtain the hysteretic soil–water characteristic curve of loess based on only the soil particle size distribution, improve the correlative calculation accuracy of unsaturated loess, and play an important role in predicting the hydraulic parameters of loess soil.

AGRONOMIC EFFICIENCY OF REKAL REMINERALIZER IN SOYBEAN AND MAIZE CROPS

Remineralization regards using rocks as both conditioners and nutrient sources for agricultural soils; it also works as essential basis for degraded or depleted soil recovery. The aim of the present assay is to assess the performance of Rekal remineralizer and its effects on soybean and maize cultures, which were used as test plants. The following soil types were used in the experiment: Yellow Oxisol with sandy loam texture and Red Oxisol with clayey texture. The research was carried out in greenhouse, at the Agronomics School of Federal University of Goiás, Goiânia City, Goiás State. Experimental treatments consisted in using different Rekal remineralizer doses (0, 30, 60, 120 and 240 kg ha-1 K2O) to compare the results to those of FMX remineralizer products and potassium chloride (KCl), at the dose of 60 kg ha-1. Plant development variables (height, diameter and number of leaves), soil and leaf potassium content, calcium and magnesium content, CEC and soil base saturation, soybean grain yield, maize green mass yield and the relative efficiency of Rekal using in comparison to both FMX remineralizer and potassium chloride synthetic fertilizers were assessed. Results have shown that Rekal remineralizer presents agronomic efficiency comparable to that of KCl and FMX remineralizer. Using Rekal remineralizer can improve and keep important soil parameters, such as CEC, soil base saturation and calcium, magnesium and potassium content.

Impact of Different Fertility Levels and Liquid Biofertilizers on Biological Properties and Nutrient Content of Soil under Wheat (Triticum aestivum L.) Crop

A field experiment was conducted during Rabi 2019 at the Instructional Farm of Agronomy, Rajasthan College of Agriculture, Udaipur. The treatments comprised of four levels of fertility i.e. control, 75, 100 and 125% RDF and four levels of liquid biofertilizers i.e. control, Azotobacter, PSB and Azotobacter + PSB. The experiment was laid out in factorial randomized block design replicated thrice taking wheat var. Raj.-4238 as test crop. The Recommended dose of fertilizer (RDF) was 100:60:40 kg ha-1 of N: P2O5: K2O. The results of the study demonstrated a significant increase in several important soil parameters in the post-harvest wheat fields. This increase was observed as we applied higher levels of fertilizers and liquid biofertilizers, specifically up to the point where we used 100% of the recommended dose of fertilizers (RDF) and a combination of Azotobacter and Phosphate Solubilizing Bacteria (PSB). The application of increased fertility levels and the use of Azotobacter + PSB as liquid biofertilizers led to significant improvements in soil microbial biomass, microbial populations and enzyme activities, enhancing the overall health and fertility of the post-harvest wheat soil. Additionally, significant increases in sulphur and micronutrients (Zn, Cu Fe and Mn) in soil with the application of 100% RDF.

Estimation of P retention capacity by the water content of soil kept with a saturated NaCl solution in a desiccator

ABSTRACT Phosphorus (P) retention capacity is an important soil parameter for site-specific nutrient management in croplands as well as a diagnostic criterion for classifying Andic properties. Air-dried soil water content is positively correlated with P retention capacity and has been proposed as a simple P retention capacity index; however, air humidity can affect the water content of air-dried soils. Therefore, in the present study, we 1) tested whether the water content of air-dried soils can be stabilized when they are kept with a saturated sodium chloride (NaCl) solution in a closed desiccator and 2) developed a model for predicting P retention capacity across various soil types. We tested 306 soil samples from paddy rice fields in Madagascar, exhibiting P retention capacities of 10.1–96.1%. Placing a saturated NaCl solution with the soil samples in a closed desiccator for one week kept the relative humidity inside the desiccator at 57–66%, regardless of the temperature and relative humidity outside the desiccator. The accuracy of the model predicting P retention capacity by soil water content was higher when soils were kept with the saturated NaCl solution [R2 = 0.870; root mean square error (RMSE) = 8.30] than without the solution (R2 = 0.812; RMSE = 9.96) at room temperature. The high correlation between P retention capacity and soil water content was mainly attributed to Al oxides. Additionally, the reproducibility of soil water content was enhanced by this method under different relative humidity conditions. However, compared with room temperature, controlling the temperature at 15°C and 30°C did not further improve the accuracy of the model when the soils were kept in the desiccator with saturated NaCl solution, although soil water content was higher at 30°C than at 15°C and room temperature. Therefore, we conclude that soil P retention capacity can be simply and accurately estimated with high reproducibility according to the water content of soils kept with saturated NaCl solution in a closed desiccator for one week at a room temperature.

Role of in-situ point instruments in the estimation of variability in soil saturated hydraulic conductivity

ABSTRACT Saturated hydraulic conductivity (Ks ) is among the most important soil parameters for modeling hydrological processes, and its field-scale variability plays a significant role for soils subjected to light and moderate rainfalls. It is often assessed by either making point-scale measurements using permeameters and infiltrometers or coupling probabilistic models with field-scale infiltration experiments under natural/artificial rainfall conditions. The former requires numerous measurements across the study area, and the latter is constrained by the infiltration experiment’s rainfall pattern, thereby restricting these approaches to only partially resolving the spatial variability of Ks , over a field. This study investigated the applicability of three in situ infiltration devices – the double-ring infiltrometer, Commonwealth Scientific and Industrial Research Organisation (CSIRO) version of the tension permeameter, and Guelph permeameter – using a Bayesian framework. Results indicate the disparate estimates of Ks distribution parameters obtained from each instrument’s infiltration data. Using field-scale rainfall-runoff data, a posterior coarsening method is proposed to reconcile the point estimates from different instruments.

Shifted excitation Raman difference spectroscopy for soil component identification and soil carbonate determination in the presence of strong fluorescence interference

AbstractDetailed knowledge about soil composition is an important prerequisite for many applications, for example precision agriculture. Current standard laboratory methods are complex and time‐consuming but could be complemented by non‐invasive optical techniques. Its capability to provide a molecular fingerprint of individual soil components makes Raman spectroscopy a very promising candidate. A major challenge is strong fluorescence interference inherent to soil, but this issue can be overcome effectively using shifted excitation Raman difference spectroscopy (SERDS). A customized dual‐wavelength diode laser emitting at 785.2 and 784.6 nm was used to investigate 117 soil samples collected from an agricultural field along a distance of 624 m and down to depths of 1 m. To address soil spatial heterogeneity, a raster scan approach comprising 100 measurement spots per sample was applied. Based on the Raman spectroscopic fingerprint extracted from intense fluorescence interference by SERDS, 13 mineral soil constituents were identified, and even closely related molecular species could be discriminated, for example polymorphs of titanium dioxide and calcium carbonate. For the first time, the capability of SERDS is demonstrated to predict the calcium carbonate content as an important soil parameter using partial least squares regression (R2 = 0.94, root mean square error of cross‐validation RMSECV = 2.1%). Our findings demonstrate that SERDS can extract a wealth of spectroscopic information from disturbing backgrounds enabling qualitative and quantitative soil analysis. This highlights the large potential of SERDS for precision agriculture but also in further application areas, for example geology, cultural heritage and planetary exploration.

Characterization of soils on consolidated limestone and its relations to grassland vegetation

Understanding the relations between soil features and plant responses is important for agricultural production and nature conservation. The aim of this study was to investigate the importance of the influence of soils? physical and chemical features on the composition of plant species and richness in grasslands studied on the limestone massif in eastern Serbia (Mt. Rtanj). The data set included 22 phytosociological releves, the same number of corresponding mixed soil samples (0-10 cm depth) and 8 soil profiles. Two vegetation types were distinguished by numerical classification as Saturejion montanae and Festucion valesiacae. The results of detrended correspondence analysis (DCA) indicated that the most important soil parameters affecting species composition in dry grasslands were humus, the content of calcium, soil exchange capacity and base saturation, in addition to total acidity, pH and soil depth. The communities of both vegetation types are developed on Leptosols and Phaeozems. Under similar physical and chemical conditions of the soil, the grassland vegetation exhibits differences in floristic composition.

Mathematical Model for Estimation of Shear Parameters of Alluvial Soils of Kamrup Metro District (Assam, India) from Index Properties

ABSTRACT Projects related to Geotechnical Engineering require thorough ground study to know the soil behaviour thus making it necessary to determine the strength and stability parameters of soil. The soils of Assam are primarily of four types viz., Alluvial (old and new), Piedmont, Hill and Lateritic soils with the alluvium abundantly available in the state. The most important soil parameters are the shear strength parameters, namely, cohesion (c) and angle of internal friction (Φ) which can be obtained using triaxial tests with different drainage conditions. But one triaxial test may take weeks to complete and are very expensive. Moreover, for large projects it is practically preposterous to conduct large number of triaxial tests. Hence, an alternate way is to develop a relation between different parameters which enable us to determine others. The main objective of this study is establishing prediction models that allow the shear parameters to be predicted from soil index properties. For this, three prediction models are developed by combining various soil parameters viz., Liquid Limit (LL), Plastic Limit (PL), Specific Gravity (G) and Optimum Moisture Content (OMC) using Multivariate Regression Analysis (MRA) and Artificial Neural Network (ANN). The results show better performance for ANN than MRA.

Quantifying surface soil organic carbon distribution globally during the COVID-19 pandemic using satellite data

Soil organic carbon (SOC) is an important soil parameter of agricultural soils, ensuring food security and agricultural sustainability. It plays a critical role in the global carbon budget and carbon sequestration. Spatial mapping of SOC can help develop sustainable management approaches to enhance soil carbon sequestration and mitigate greenhouse gas emissions and adverse environmental effects. However, quantifying Spatio-temporal distributions of SOC at the global level is complex because of high land heterogeneity and several climatic and hydrologic influential parameters. The main goal of this study was to quantify the annual global SOC change focusing on cropland using daily soil moisture active passive (SMAP) satellite SOC data. The specific objectives of this study were to assess annual SOC change globally, quantify the annual SOC distribution before and during the COVID-19 pandemic, and evaluate change in SOC on cropland during the study period. Results showed an increase of annual SOC on cropland in several countries in 2020 compared to 2019, which can be attributed to the direct and indirect impact of partial and complete lockdowns due to the COVID-19 pandemic. The change in SOC between 2015 and 2019 was considerably different from the SOC change between 2019 and 2020. For example, between 2019 and 2015, 45.6% of the global area showed a decrease in SOC 0 to 25 g C m−2 and 30.4% area showed an increase in SOC 0 to 25 g C m−2. However, between 2020 and 2019, 11.4% of the global area showed a decrease in SOC 0 to 25 g C m−2, and 55.4% area showed an increase in SOC 0 to 25 g C m−2. There is a good relationship between lockdown measures and improvement in SOC, as 48 out of 50 highly infected countries showed increased SOC in 2020 than in 2019. This study suggests better land use management practices can help enhance carbon sequestration and improve soil health.

Nutrient Status of Soils from the Kaleshwaram Project Command Area of Erstwhile Nizamabad District in Telangana State

A research was conducted to study the fertility status of soils from kaleshwaram project command area of erstwhile Nizamabad district in Telangana. A total of 72 geo-referenced soil samples collected from surface (0-15cm) by using GPS coordinate. Samples were analysed for important soil parameters viz., pH, EC, available macronutrients (N, P, K) and micronutrients (Fe, Zn, Mn, Cu). Correlation study was done to study the relation between the various soil properties. The soil pH and EC showed wide variation that soils are low acidic to medium alkaline in reaction and low salinity. Whereas available N content is low (75 to 298 kg ha-1), available P2O5 content medium to high (18-358 kg ha-1) and available K2O content low to high (90 to 630 kg ha-1). The soil available Zn, Cu, Fe and Mn contents of surface soils are very low to adequate. Correlation study depicts that soil reaction was negatively related with soil available N, P2O5, Fe and Mn. the results of the study area showed that these soils are need proper management, supplement with organic manures and inorganic fertilisers.

Standoff High-Frequency Electromagnetic Induction Response of Unsaturated Sands: A Tank-Scale Feasibility Study

Standoff electromagnetic induction (EMI) measurements of complex conductivity and complex permittivity for engineering soil properties have the potential to revolutionize the way the US Army handles route planning and infrastructure assessment. An unmanned aerial system (UAS) based EM platform for soil interrogation would have wide reaching impact in a variety of applications including: civil infrastructure inspection, in-theater ingress and egress routing, reduction of false positives in IED detection, and permafrost mapping, among many others. Traditional frequency domain EMI instruments assess conductivity at low-frequencies, generally in the range of 1–20 kHz; however, recent advancements have resulted in instrumentation targeting a broadband range of frequencies, from 10 kHz through 20 MHz. This advancement, known as high-frequency electromagnetic induction (HFEMI) allows the potential to evaluate frequency domain relaxation effects in soils by acquiring both the in phase and quadrature response of the secondary field from the soil. Relaxation phenomena such as induced polarization and dielectric permittivity are related to important soil properties that can potentially be exploited using this HFEMI system. While conductivity measurements using the quadrature component of the EMI response are well established in EMI instrumentation, understanding of the relationship between direct electrical measurements and standoff HFEMI measurements is lacking. In an effort to illuminate this relationship between various electrical and electromagnetic methods at a scale suitable for soil property estimation, we perform side-by-side measurements using galvanic geoelectrical methods (ERT, IP), electromagnetics, time-domain reflectometry (TDR) and ground penetrating radar (GPR). We compare HFEMI obtained quadrature and in-phase responses to ERT, IP, TDR and GPR measurements. A tank-scale test cell was developed for comparison of the above methods and allowed assessment of sand at varying saturation levels. Further, the HFEMI response at varying heights above the sand surface was also assessed. Qualitative observations are reported in an initial attempt to relate the HFEMI response to important soil parameters.

Recent Advances in Chemical Sensors for Soil Analysis: A Review

The continuously rising interest in chemical sensors’ applications in environmental monitoring, for soil analysis in particular, is owed to the sufficient sensitivity and selectivity of these analytical devices, their low costs, their simple measurement setups, and the possibility to perform online and in-field analyses with them. In this review the recent advances in chemical sensors for soil analysis are summarized. The working principles of chemical sensors involved in soil analysis; their benefits and drawbacks; and select applications of both the single selective sensors and multisensor systems for assessments of main plant nutrition components, pollutants, and other important soil parameters (pH, moisture content, salinity, exhaled gases, etc.) of the past two decades with a focus on the last 5 years (from 2017 to 2021) are overviewed.

Results of the study of pH and organic matter in the surface soil of Ulaanbaatar

This work summarizes the results of a study into such important urban soil parameters as soil actual (pH) and potential acidity (pH) and soil organic matter content (SOM) in the surface soil of Ulaanbaatar. The soil pH in Ulaanbaatar is slightly alkaline, with a median pH value of 7.36 (actual acidity) and 6.93 (potential acidity), and they were found to be the highest in the industrial zone as compared to other zones in the city. The median value of organic matter content in Ulaanbaatar surface soil was 5.61%, with a high variability in the industrial (C.V.-119%) and transport (C.V.-55.34%) zones. The SOM mean value in urban soil is less than the background value in surface soil from natural area, indicating to increasing compaction and reduction of porosity of soil in urban areas. Also, organic matter content have decreased relatively to previous data, reflecting the urbanization process and such long-term processes as aerial urban fallout.

Critical-State Shear Strength and Pore Pressure of Granular Materials

Abstract The plane-strain critical-state friction angle is an important soil parameter in the design of geotechnical projects. The static angle of repose, which is the same as the plane-strain crit...

Evolution of Tensile Properties of Compacted Red Clay under Wet and Dry Cycles

Tensile strength is an important soil parameter that affects the stability of structures built on clayey soils. This paper presents an experimental study of the change of tensile properties of red clay during wet-dry cycles. Cyclic wet-dry tests were performed on compacted red clay specimens with different initial water contents and dry densities. Direct tensile tests and Brazilian split tests were then conducted on these specimens to determine the soil strengths. The effects of initial water content, initial dry density, number of wet-dry cycles, and crack rate on the tensile properties of red clay were investigated. The results demonstrate that the tensile strength of red clay is generally 1.566 times the splitting strength. Both the tensile strength and splitting strength are negatively correlated with the initial water content but are positively correlated with the initial dry density. Because of the presence of desiccation cracks, the tensile strength goes on reducing under wet-dry cycles. The tensile strength can be expressed by a power function of the initial water content, initial dry density, and crack rate. The proposed equation is useful to evaluate the tensile strength of cracked soils subjected to wet-dry cycles.

Comparison of factor of safety using different method of analysis for slope stability

Currently, the construction of slope is increasing, thus, the risk of slope to fail also increase. The series of landslide happen to the man-made slope has been recorded since in the early of 1993 until now. Many efforts such as treating the critical slope, redesigned the failed slope, and analyze the stability of the slope have been done. However, the landslide is still happening in Malaysia. The factor of safety (FOS) from the stability analysis that has been used might not be adequate to determine the safety of the slope in Malaysia. Therefore, in this study, the optimum factor of safety is obtained by using three methods of slice, Bishop’s Simplified method, Spencer method, and Morgenstern-Price method which have been used in many projects. A study place is selected in Ladang Balau, Semenyih, in Selangor and from the CIU test, the important soil parameter for slope is extracted for analysis of slope stability using SLOPE/W and manual calculation. The lambda for Spencer method and Morgenstern-Price method was generated for further discussion on the relationship between lambda and factor of safety. The data generated from both calculation method, from manual and software, were discussed and next the ideal method to achieve the optimum factor of safety determined. The factor of safety for every method basically are influenced by the interslice shear force presence but not Bishop’s Simplified method as moment equilibrium is insensitive towards interslice force function. For lambda, the factor that influenced the value is the function used; constant and half-sine function, however, for Bishop’s Simplified method, the lambda is equal to zero as the method ignored the interslice shear force. The Morgenstern-Price method has been chosen to be the best method to generate a good factor of safety.

Particle Size Distribution of Various Soil Materials Measured by Laser Diffraction—The Problem of Reproducibility

Particle size distribution is an important soil parameter—therefore precise measurement of this characteristic is essential. The application of the widely used laser diffraction method for soil analysis continues to be a subject of debate. The precision of this method, proven on homogeneous samples, has been implicitly extended to soil analyses, but this has not been sufficiently well confirmed in the literature thus far. The aim of this study is to supplement the information available on the precision of the method in terms of reproducibility of soil measurement and whether the reproducibility of soil measurement is characterized by a normal distribution. To estimate the reproducibility of the laser diffraction method, thirteen various soil samples were characterized, and results were analysed statistically. The coefficient of variation acquired was lowest (3.44%) for silt and highest for sand (23.28%). Five of the thirteen tested samples were characterized by a normal distribution. The fraction content of eight samples was not characterized by normal distribution, but the extent of this phenomenon varied between soils. Although the laser diffraction method is repeatable, the measurement of soil particle size distribution can have limited reproducibility. The main cause seems to be small amounts of sand particles. The error can be amplified by the construction of the dispersion unit. Non-parametric statistical tests should be used by default for soil laser diffraction method analysis.

Reduced soil fauna decomposition in a high background radiation area.

Decomposition of litter and organic matter is a very important soil ecosystem function where soil fauna play an important role. Knowledge of the responses in decomposition and soil fauna to different stressors is therefore crucial. However, the extent to which radioactivity may affect soil fauna is not so well known. There are some results showing effects on soil fauna at uranium mines and near Chernobyl from relatively high levels of anthropogenic radionuclides. We hypothesize that naturally occurring radionuclides affect soil fauna and thus litter decomposition, which will covary with radionuclide levels when accounting for important soil parameters. We have therefore used standardised litterbags with two different mesh sizes filled with birch leaves (Betula pubescens) to assess litter decomposition in an area with enhanced levels of naturally occurring radionuclides in the thorium (232Th) and uranium (238U) decay chains while controlling for variation in important soil parameters like pH, organic matter content, moisture and large grain size. We show that decomposition rate is higher in litterbags with large mesh size compared to litterbags with a fine mesh size that excludes soil fauna. We also find that litter dried at room temperature is decomposed at a faster rate than litter dried in oven (60⁰C). This was surprising given the associated denaturation of proteins and anticipated increased nutritional level but may be explained by the increased stiffness of oven-dried litter. This result is important since different studies often use either oven-dried or room temperature-dried litter. Taking the above into account, we explore statistical models to show large and expected effects of soil parameters but also significant effects on litter decomposition of the naturally occurring radionuclide levels. We use the ERICA tool to estimate total dose rate per coarse litterbag for four different model organisms, and in subsequent different statistical models we identify that the model including the dose rates of a small tube-shape is the best statistical model. In another statistical model including soil parameters and radionuclide distributions, 226Ra (or uranium precursory radionuclides) explain variation in litter decomposition while 228Ra (and precursors) do not. This may hint to chemical toxicity effects of uranium. However, when combining this model with the best model, the resulting simplified model is equal to the tube-shape dose-rate model. There is thus a need for more research on how naturally occurring radionuclides affect soil fauna, but the study at hand show the importance of an ecosystem approach and the ecosystem parameter soil decomposition.