Dielectric Properties Of Soil Research Articles

Effect of vermicompost additive on physical, chemical and dielectric properties of soil and its modeling

The present study focuses on the effects of vermicomposting on various soil properties, particularly emphasizing the dielectric characteristics of soil. Vermicomposting is known to significantly enhance soil fertility and improve its physical aspects such as aeration, porosity and water retention. In this analysis, a modified probe arrangement has been employed to determine how varying levels of vermicompost influence the soil’s dielectric properties within the radio and microwave spectrum (10 MHz-14 GHz). A modified Dak-12 open-ended coaxial probe, paired with a vector network analyzer, was utilized for this purpose to overcome the drawbacks of standard arrangement. The results show that vermicompost strongly affects the soil’s physical attributes (pH, bulk density, porosity) and also its chemical properties, along with its dielectric behavior. The study further explored the role of different factors such as the concentration of vermicompost, frequency and temperature on soil’s dielectric response. To accurately and swiftly gauge these effects, Response Surface Methodology (RSM) has been employed to predict the dielectric properties (ε’ and ε’’) of the soil. The high precision of these models, with R 2 values of 0.9729 for ε’ and 0.9487 for ε’’, underscores their effectiveness in evaluating the impact of vermicompost on various soil properties.

Soil-Specific Calibration Using Plate Compression Filling Technique and Monitoring Soil Biomass Degradation Based on Dielectric Properties

Accurate estimation of soil water content (SWC) is crucial for effective irrigation management and maximizing crop yields. Although dielectric property-based SWC measurements are widely used, their accuracy is still affected by soil variability, soil–sensor contact, and other factors, making the development of convenient and accurate soil-specific calibration methods a major challenge. This study aims to propose a plate compression filling technique for soil-specific calibrations and to monitor the extent of soil biomass degradation using dielectric properties. Before and after biodegradation, dielectric measurements of quartz sand and silt loam were made at seven different water contents with three different filling techniques. A third-order polynomial fitting equation explaining the dependence of the dielectric constant on the volumetric water content was obtained using the least-squares method. The suggested plate compression filling method has a maximum mean bias error (MBE) of less than 0.5%, according to experimental results. Depending on the water content, silt loam’s dielectric characteristics change significantly before and after biodegradation. The best water content, measured in gravimetric units, to encourage the decomposition of biomass was discovered to be 24%. It has been demonstrated that the plate compression filling method serves as a simple, convenient, and accurate alternative to the uniform compaction method, while the dielectric method is a reliable indicator for evaluating biomass degradation. This exploration provides valuable insights into the complex relationship between SWC, biomass degradation, and soil dielectric properties.

Stubble Burning Effect On Soil’s Dielectric Behavior: An Exploration Of Machine Learning-Based Modelling Approaches

ABSTRACT Stubble burning is a conventional technique of residue management that has affected the physio-chemical properties of the soils. In soil sciences, dielectric properties of soils using radio and microwave-based remote sensing have huge applications. Thus, presented paper has studied the burning effects of stubble on soil’s physical, chemical and dielectric properties ( ε ′ and ε ′′ ). Moreover, the experimentally observed soil’s dielectric data has been explored with various classical Machine Learning (ML) and Neural Network (NN) based regression models. The soil samples were taken from the fields of Punjab, India, in the October-November months following a multistage soil sampling method. Then, Dak-12 open-ended coaxial probe (DOCP) has been used in alliance with a two-port Vector Network Analyzer (VNA) E5071C, Agilent Technologies, to investigate the dielectric properties of soil samples. The obtained results indicate that physio-chemical and dielectric properties have been strongly affected by burning as well as because of the presence of high concentrations of ash residues. ε ′ and ε ′′ variations with depth indicate that ash residues can seep up to depths of 10 cm in a single burning process. Moreover, the continuous burning of stubble can have permanent effects on soil’s properties. Among considered regression models, the Deep NN-based regression model has given the most accurate predictions of the regressor variables ε ′ and ε ′′ , with a root-mean-square-error (RMSE) of 0.06 and 0.07, respectively. Stubble burning has visible effects on physical, chemical as well as dielectric properties of soil. The burning of stubble damages natural ecosystem and essential nutrients which decrease fertility of soil. Also, the resultant residue ash becomes permanent part of soil profile and alters basic properties of soil. Moreover, exploration of ML-based regression models suggests the tremendous applications of data-centric models in soil and material sciences.

Surface soil moisture estimate from Sentinel-1 and Sentinel-2 data in agricultural fields in areas of high vulnerability to climate variations: the Marche region (Italy) case study

AbstractSurface soil moisture is a key hydrologic state variable that greatly influences the global environment and human society. Its significant decrease in the Mediterranean region, registered since the 1950s, and expected to continue in the next century, threatens soil health and crops. Microwave remote sensing techniques are becoming a key tool for the implementation of climate-smart agriculture, as a means for surface soil moisture retrieval that exploits the correlation between liquid water and the dielectric properties of soil. In this study, a workflow in Google Earth Engine was developed to estimate surface soil moisture in the agricultural fields of the Marche region (Italy) through Synthetic Aperture Radar data. Firstly, agricultural areas were extracted with both Sentinel-2 optical and Sentinel-1 radar satellites, investigating the use of Dual-Polarimetric Entropy-Alpha decomposition's bands to improve the accuracy of radar data classification. The results show that Entropy and Alpha bands improve the kappa index obtained from the radar data only by 4% (K = 0.818), exceeding optical accuracy in urban and water areas. However, they still did not allow to reach the overall optical accuracy (K = 0.927). The best classification results are reached with the total dataset (K = 0.949). Subsequently, Water Cloud and Tu Wien models were implemented on the crop areas using calibration parameters derived from literature, to test if an acceptable accuracy is reached without in situ observation. While the first model’s accuracy was inadequate (RMSD = 12.3), the extraction of surface soil moisture using Tu Wien change detection method was found to have acceptable accuracy (RMSD = 9.4).

Time-domain transmission sensor system for on-site dielectric permittivity measurements in soil: A compact, low-cost and stand-alone solution

Dielectric-based measurement techniques have been shown to be very effective in determining the properties of various materials. These techniques have been widely used in a variety of fields and applications. Time Domain Transmission (TDT) techniques have grown in popularity because they are practical, non-destructive, provide measurements in real time and produce accurate measurements that are independent of multiple reflections. TDT techniques, on the other hand, are mostly performed with specialized bulky laboratory equipment, such as a Vector Network Analyzer (VNA) which makes TDT measurements prohibitively costly and unpractical. In fact, few works in the literature have reported portable on-site TDT systems. The aim of this paper is to design and implement a dedicated, compact, and low-cost microwave Time Domain Transmission (TDT) sensor for measuring superficial soil dielectric properties on-site. Our sensor uses a time-delay measurement technique over a microstrip transmission line to estimate the dielectric properties of the soil under test. Measurement results show that the computed mean absolute error (MAE) is less than 1.2 when compared to a calibrated dielectric assessment kit (DAK) with soils containing less than 20 % of water (ε′r<5.0), implying that our TDT sensor system can obtain on-site measurements in relatively dry soils with acceptable accuracy.

Remote Microwave Soil Drought Index Considering Dielectric Properties of Soil

Remote Microwave Soil Drought Index Considering Dielectric Properties of Soil

Fluctation moisture properties in the application of soil dielectric measurement in the North Bengkulu District, Indonesia

Information about soil moisture in the root layer is very important in evaluating water availability for plants, erosion rates and various other hydrological characteristics. Previous research has found a technology for measuring soil dielectric properties as a soil moisture estimator that can be carried out quickly in the field. The purpose of this study was to apply dielectricity technology in estimating the characteristics of soil moisture in situ in the field at the North Bengkulu in Bengkulu Province. Five land units in North Bengkulu Regency, Indonesia, have been selected as experimental sites. At each location, the soil profile was excavated to a depth of 100 cm, the basic characteristics of the soil in each layer were described in the field and analyzed in detail in the laboratory. The variables measured in the field are the measurement of the dielectric properties of the soil, the effective depth of the soil, the horizon and the characteristics of each horizon. The variables analyzed in the laboratory were texture, organic matter in each layer, aggregate stability at 0-10 cm layer, field soil moisture at the time of measurement, and groundwater characteristics. The relationship between the data on the basic characteristics of the soil with the soil moisture balance variable in the laboratory analysis and measurements of dielectric properties in the field, was then determined using regression analysis. The results showed that the five locations studied had different profile characteristics and groundwater fluctuations. Of the four independent variables tested (percentage of sand, silt, clay and organic carbon) then the content of sand and clay can be used as predictors of the water content of field capacity. Because the four independent variables have a very weak correlation with permanent wilting point water, the available water content can only be predicted from the sand and clay content.

Detection of hydrocarbon spills by means of a coaxial impedance dielectric sensor

Leakages from storage tanks or pipes frequently produce pollution of soils and groundwater reservoirs by hydrocarbons. Common practices for monitoring and characterising site contamination involve soil drilling, sampling and chemical analysis, complemented with geophysical surveys. This study evaluates the presence of paraffin oil inside soil pores by means of dielectric permittivity measurements, using a coaxial impedance device in laboratory-scale models. The real dielectric permittivity of unsaturated sand is measured before, during and after a contamination process. Monitoring small variations in real dielectric permittivity allows detection of the partial replacement of air (κ′ = 1) by paraffin oil (κ′ ≈ 2) in soil pores. These variations in soil dielectric properties enable pollution levels to be assessed, knowing in advance the κ′ of the soil at the initial stage and measuring the influence of oil and water content on κ′. The technique proposed can also be used for monitoring the lateral extension of a contaminant plume and can be successfully applied at the laboratory scale for oil leakage detection by periodically monitoring changes in the soil dielectric permittivity.

Dielectric behavior of soil as a function of frequency, temperature, moisture content and soil texture: a deep neural networks based regression model

Dielectric behavior of soil has utmost applications in microwave remote sensing and soil treatment. In the present study, the soil's dielectric properties (Ɛ' and Ɛ") were measured using the vector network analyzer and an open-ended coaxial probe (85070E, Agilent Technologies) in the region of 0.2 to 14 GHz. The observed results showed that Ɛ' and Ɛ" strongly depend on frequency, texture, moisture content and temperature. A deep neural network (DNN) based multivariable regression model has been developed to model their behavior, using experimentally observed data to learn its parameters automatically. It shows a five-fold cross-validation root mean square errors (RMSE) of 0.0258 and 0.0336, and R2-scores of 1.0000 and 0.9998, between actual recorded and predicted values of Ɛ' and Ɛ", respectively. The results of the proposed DNN-based model have been compared with the response surface method (RSM) based model; among these, the DNN-based model shows significantly better results. Further, the DNN-based estimates of Ɛ' and Ɛ" for loam texture at a moisture content of 18% (i.e. in between observed experiments of 15% and 20%) are made and plotted with actual observed values at 15% and 20% to verify the predictive ability of the proposed DNN-based model. It shows an acceptable estimate of dielectric properties and the effectiveness of the fast and innovative DNN-based approach for predicting soil's dielectric properties depending upon multiple factors.

Dielectric properties of soils and assessment of their hydrothermal state under snow cover based on radio-echo sounding data

Dielectric properties of soils and assessment of their hydrothermal state under snow cover based on radio-echo sounding data

Dielectric Properties of Soils of India at Radio and Microwave Frequencies: A Review

Dielectric properties of soils are important in the field of geophysical exploration, agriculture, and remote sensing, as these directly affect the performance of electromagnetic sensors. Soils vary from region to region due to variation in texture, temperature, demography, and environment, so area wise dielectric properties of soil differ significantly and depend upon frequency, moisture content, bulk density, and salinity. India has a wide variety of soils and numerous researchers have studied dielectric properties of many states of India. However, due to difference in technique used, frequency of interest, and soil type, it is difficult to generalize dielectric behavior of soils of India as a whole. In this review, we present a systematic state wise analysis of all reported dielectric data on soils of India at radio and microwave frequencies.

Dielectric Properties of Soils Affected by Sewage Waste Pollution

Soil pollution has become one of the major issues in current era. Increasing population, industrialization, and human activities have contributed immensely to increase in sewage waste. Undisposed and poorly managed sewage waste has contaminated soil and water resources badly and affected their dielectric properties. In this study, the dielectric properties of soil affected by sewage waste pollution have been presented in the broadband frequency region of 200 MHz to 14 GHz with the use of open ended coaxial probe method. Moreover, the effect of contamination on soil pH has also been recorded. The results showed that the values of dielectric constant (Ɛ’) and dielectric loss factor (Ɛ’’) increases with escalation of contaminant content. The regression equations for Ɛ’, Ɛ’’, and pH values are also generated in this work. The results presented in this paper can be helpful in developing new approaches to study soil pollution and its type in comparison to conventional soil study approaches.

Improvement in Modeling Soil Dielectric Properties During Freeze-Thaw Transitions

Soil freeze-thaw cycles have a profound impact on heat and water fluxes at the land-atmosphere interface and transport in soils. Microwave remote sensing is a widely used technique to detect near-surface soil freeze/thaw states due to significant changes in dielectric properties associated with water phase transitions in soils, where uncertainty remains. This letter proposes a new parameterization scheme for the estimation of unfrozen water content to improve the modeling of soil dielectric properties during freeze-thaw transitions. Predictions from the new model referred to as Zhang-Zhao&#x2019;s model were compared with dielectric measurements during thawing processes of soil samples collected from Baoding (silty clay soil), Zhangjiakou (loamy sandy soil), and Zhengzhou (clay loam soil) in China. The mean biases of the predictions were 3.25 (4.44 and 2.07 for the thawed value and frozen value, respectively) and 1.54 (2.22 and 0.88 for the thawed value and frozen value, respectively) for the real part and imaginary part, respectively. The model-predicted soil complex relative permittivity (CRP) was highly correlated with measurements, with correlation coefficients ranging from 0.7944 to 0.9865. The normalized root mean square errors of the predictions were 13.72&#x0025; (real part) and 25.41&#x0025; (imaginary part).

Simple and Effective Design Concept for Constructing In-Situ Soil Dielectric Property Sensor With Dual Low-Cost COTS Microwave Modules

Simple and Effective Design Concept for Constructing In-Situ Soil Dielectric Property Sensor With Dual Low-Cost COTS Microwave Modules

Field Dielectric Sensor for Soil Pollution Application

This paper presents a new dielectric sensor which could be used for assessment and evaluation of soil pollution in the field. The new device determines the dielectric properties of soil from the measured soil impedances. The dielectric properties used as indirect method to estimate type and pollution content in soil. The new device was calibrated and validated for accurate measurement of soil dielectric properties in the frequency range of 1 kHz to 30 MHz. The new proposed dielectric sensor was used to measure the dielectric properties of clean and contaminated soil. The measured dielectric properties of soil using the proposed sensor could be used to estimate soil moisture content, hydrocarbon diesel and salinity in sand soil. The results also show that the dielectric properties of clay soil were higher than the dielectric properties of san due to existing bound water in clay minerals. Further testing is necessary to evaluate the effects of other parameters such as temperature and various type of soil prior to adopt the sensor for field testing.

Analyzing the behavior of GPR wave propagation in zinc contaminated soil combining the dielectric properties—experimental study

There is a very strong link between the behavior of ground penetrating radar (GPR) wave propagation in zinc-contaminated soil and the dielectric properties of soil. This relationship can be of significant use in the practices of quick detecting the degree of pollution in zinc-contaminated soil. In this research, measurements were conducted on the zinc-contaminated soil samples with different soil index properties (i.e., zinc ion concentration, wet density and moisture content). The radar reflection wave data of the common midpoint and common-offset sounding mode were obtained by using the 600 MHz antenna, and the relative permittivity was measured using the vector network analyzer. The attribute analysis of radar reflection wave shows that the wave velocity is affected by wet density and moisture content, but independent of zinc ion concentration. Both the amplitude and the peak frequency decrease with the increase in zinc ion concentration, wet density and moisture content. For the soil dielectric properties, the metal ions can change the conductivity of solution in soil, affecting the imaginary part of relative permittivity, but with little effect on the real part. The positive correlations between the relative permittivity with density and moisture content are caused by the variation of three-phase composition of soil. Besides, the measured soil dielectric properties and the radar reflected wave attributes confirm each other, which can well explain the change rules of electromagnetic wave velocity, amplitude and central frequency. The presented results can increase understanding and confidence on GPR for quantitative monitoring and detecting of zinc-contaminated soil.

Study of Effect of Potassium Nitrate and Ammonium Sulphate on Dielectric Properties of Soil at X and J-Band Microwave Frequencies

Microwave has prominent role in the present era due to its application in remote sensing. Present investigation is emphasized to explore the impact of potassium nitrate and ammonium sulphate on dielectric traits of soil samples by exposing it to X and J-band microwave frequencies. For this two different soil samples were collected from Jalna and badnapur of Maharashtra. The infinite sample method was employed for the determination of dielectric constant (e’), dielectric loss (e”), AC Conductivity and Relaxation Time of the soils. The variation in values of all the parameters of these samples mixed with different concentration of potassium nitrate and ammonium sulphate were then measured at fixed frequency X-band (6 GHz) and J-band (9.86 GHz).

Kinetics and Optimization by Response Surface Methodology of Aerobic Bioremediation. Geoelectrical Parameter Monitoring

This study aimed to investigate the kinetics of an aerobic bioremediation process of diesel oil removal by indigenous microorganisms, and to define the optimal operative conditions by means of response surface methodology. This was carried out by setting up a series of microcosms (200 g of soil), polluted with the same diesel oil concentration (70 g·kg−1 of soil), but with different water contents (u%) and carbon to nitrogen (C/N) ratios. The process was monitored by: (1) residual diesel oil concentration, to measure the removal efficiency, and (2) fluorescein production, to check the microbial activity. These two parameters were the objective variables used for the analysis of variance (ANOVA) and response surface methodology (RSM). The results allowed the interactions between u% and C/N to be defined and the optimal range to be adopted for each. The process kinetics was modeled with first- and second-order reaction rates; slightly better results were achieved for the second-order model in terms of parameter variability. Biological processes like degradation may have effects on dielectric properties of soil; an open-ended coaxial cable was used to measure the dielectric permittivity of microcosm matrices at the start and after 130 days of bioremediation. The evolution of the real and the imaginary components of dielectric permittivity provided results that supported the evidence of a biodegradation process in progress.

Measurement and modelling of soil dielectric properties as a function of soil class and moisture content

In this study, four textural classes of soil (Clay, Clay Loam, Loam, and Loamy Sand) were used to investigate the dielectric properties of soils, using a vector network analyser with an open-ended coaxial probe kit at room temperature (25 ± 2°C) in the 700–7000 MHz microwave frequency range. Four levels of soil moisture content (oven dry, 33% field capacity, 66% field capacity and 100% field capacity) were maintained to perform the experiment with three replication and three observation each. The results showed that, with increasing soil moisture, from oven dry conditions to 100% field capacity, both the real (Dielectric Constant) and imaginary (Loss Factor) components of the dielectric properties increased; however, the responses were not linear. The dielectric properties of oven dry soils were very low compared with the soils with higher moisture content. Therefore, soil moisture was the major contributor to the dielectric behaviour of soil. The dielectric properties of sandy soil were much lower than the other soils; however, the dielectric loss factor of the Dookie clay soil was higher compare with the other soils. Models were developed to explain the dielectric properties of soils as a function of frequency and moisture content. The goodness of fit (r2) for these models varies between 0.952 for the Dookie Sandy Soil to 0.997 for the Dookie Loam Soil, suggesting that these models were adequate to describe the dielectric properties of these soils over the range of frequencies and moisture contents assessed in this study. Another model was developed to estimate the expected penetration depth of electromagnetic waves in these soils, based on the model of the dielectric properties. It was clear that penetration decreases with both frequency and moisture content. Low frequencies penetrate further into the soils than higher frequencies. Similarly, dry soils allow further penetration than moist soils.

Study on influence and compensation for soil compactness on volumetric water content measurement

Volumetric water content measurements based on soil dielectric properties are affected by soil compaction. Today’s commercial products produce substantial measurement error as they do not account for the influence of soil compaction. This paper presents a portable soil volumetric moisture content sensor based on the principle of standing wave rate and simultaneous soil compactness measurement. The coupling relationship between soil compactness and soil volumetric moisture content can be easily observed by converting them into polar coordinates. A modified soil volumetric moisture content model based on the soil compactness is also established to support the operation of the proposed sensor.