Moisture Measurement Techniques Research Articles

On Various Soil Moisture Measurement Techniques Available in the Literature

The sustainability and health of soil associated with its productivity and health are closely related to soil moisture. The amount of water or moisture in the soil is an important parameter in the mobility of nutrients in the soil, in soil reclamation studies, and in the washing-transportation and mixing of fertilizers and other chemicals applied to the soil into the ground water. On the other hand, it has become important today not only to minimize water consumption but also to accurately measure the amount of moisture in the soil so that proper amount of water that the plant needs can be circulated to the root zone of the plant. In this context, information was given about various measurement methods for determining soil moisture (direct and indirect - thanks to correlations) existing in the literature, and among these studies, especially the studies on microwave methods were examined. Comparison results of the dielectric constant values obtained for three different soil samples with different gravimetric volumetric moisture rates by one of the calibration-independent non-resonant microwave measurement methods, which has a high application potential and is different from the existing calibration-requiring microwave measurement methods, and the dielectric constant values predicted by the Mironov model in the literature are presented. The comparison result showed that this new type of microwave measurement method has a high potential for measuring the moisture value of soil samples

Prediction of Soil Moisture Content from Sentinel-2 Images Using Convolutional Neural Network (CNN)

Agriculture is closely associated with food and water. Agriculture is the first source of food but the biggest consumer of freshwater. The population is constantly increasing. Smart agriculture is one of the means of achieving food and water security. Smart agriculture can help improve water management and increase agricultural production, thus counteracting rapid population growth requirements. Soil moisture estimation is a critical step in agricultural water management. Soil moisture measurement techniques in situ are point measurements, labor-intensive, time-consuming, tedious, and expensive. We propose, in this research, a new approach to predict soil moisture over vegetation-covered areas from Sentinel-2 images based on a convolutional neural network (CNN). CNN architecture (3) consisting of six convolutional layers, one pooling layer, and two fully connected layers has achieved the highest prediction accuracy. Three well-known criteria including coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) are utilized to measure the accuracy of the proposed algorithm. The Red Edge 3, NIR, and SWIR 1 are the most appropriate Sentinel-2 bands for retrieving soil moisture in vegetation-covered areas. Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDVI) are the best indicators. The use of the indicator is more proper than the use of the single Sentinel-2 band as input data for the proposed CNN architecture for predicting soil moisture. However, using combinations “that consist of some number of Sentinel-2 bands” as input data for CNN architecture is better than using each indicator separately or all of them as a group. The best values of the performance metrics were achieved using the sixth combination (R2=0.7094, MAE=0.0277, RMSE=0.0418) composed of the Red, Red Edge 1, Red Edge 2, Red Edge 3, NIR, and Red Edge 4 bands as input data to the CNN architecture (3), as well as by using the fifth combination (R2=0.7015, MAE=0.0287, RMSE=0.0424) composed of the Red Edge 3, NIR, Red Edge 4, and SWIR 1 bands.

High-Sensitivity and Compact Time Domain Soil Moisture Sensor Using Dispersive Phase Shifter for Complex Permittivity Measurement

This article presents a time domain transmissometry soil moisture sensor (TDT-SMS) using a dispersive phase shifter (DPS), consisting of an interdigital capacitor that is loaded with a stacked four-turn complementary spiral resonator (S4-CSR). Soil moisture measurement technique of the proposed sensor is based on the complex permittivity sensing property of a DPS in time domain. Soil relative permittivity which varies with its moisture content is measured by burying the DPS under a soil mass and changing its phase difference while excited with a 114-MHz sine wave (single tone). DPS output phase and magnitude are compared with the reference signal and measured with a phase/loss detector. The proposed sensor exhibits accuracy better than ±1.2% at the highest volumetric water content (VWC = 30%) for sandy-type soil. Precise design guide is developed and simulations are performed to achieve a highly sensitive sensor. The measurement results validate the accuracy of theoretical analysis and design procedure. Owning the advantages of low profile, low power consumption, and high sensitivity makes the proposed TDT-SMS a good candidate for precision farming and internet of things (IoT) systems.

Inter-Comparison of Proximal Near-Surface Soil Moisture Measurement Techniques

Precision agriculture is experiencing substantial development through the improved availability of cost-effective instruments for data collection. This includes ground-based proximal sensing technologies that are able to compete with satellite and aircraft observation systems, due to low operational costs, high operational flexibility, and high spatial resolution. This article was therefore designed to compare the performance of multiple sensing systems mounted on a smart buggy platform. A number of proximal sensing technologies were then evaluated and intercompared for their accuracy in retrieving high resolution near-surface soil moisture. The sensors tested included an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> -band microwave radiometer (ELBARA III), a global navigation satellite system reflectometer sensor (LARGO), and an electromagnetic induction sensor (EM38). Data were collected during the fifth Soil Moisture Active Passive Experiment (SMAPEx-5) in Yanco, NSW, Australia, in September 2015. Observations from each sensor were converted to surface soil moisture values which were in turn evaluated against reference measurements obtained by <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> soil moisture measurements. The sensing technologies tested here have been individually assessed by many other studies, but within different regions and environments including surface condition, local weather, observing height, size of footprint, etc. Consequently, this article has used a single platform to intercompare the different sensors to be evaluated concurrently. Results from this article indicated that the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> -band microwave radiometer achieved the best performance in retrieving surface soil moisture. The average RMSE and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> were found to be 0.055 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> and 0.68 for ELBARA III, 0.084 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> and 0.51 for LARGO, and 0.090 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> and 0.32 for the EM38.

A Convolutional Neural Network Algorithm for Soil Moisture Prediction from Sentinel-1 SAR Images

Achieving the rational, optimal, and sustainable use of resources (water and soil) is vital to drink and feed 9.725 billion by 2050. Agriculture is the first source of food production, the biggest consumer of freshwater, and the natural filter of air purification. Hence, smart agriculture is a “ray of hope” in regard to food, water, and environmental security. Satellites and artificial intelligence have the potential to help agriculture flourish. This research is an essential step towards achieving smart agriculture. Prediction of soil moisture is important for determining when to irrigate and how much water to apply, to avoid problems associated with over- and under-watering. This also contributes to an increase in the number of areas being cultivated and, hence, agricultural productivity and air purification. Soil moisture measurement techniques, in situ, are point measurements, tedious, time-consuming, expensive, and labor-intensive. Therefore, we aim to provide a new approach to detect moisture content in soil without actually being in contact with it. In this paper, we propose a convolutional neural network (CNN) architecture that can predict soil moisture content over agricultural areas from Sentinel-1 images. The dual-pol (VV–VH) Sentinel-1 SAR data have being utilized (V = vertical, H = horizontal). The CNN model is composed of six convolutional layers, one max-pooling layer, one flatten layer, and one fully connected layer. The total number of Sentinel-1 images used for running CNN is 17,325 images. The best values of the performance metrics (coefficient of determination (R2=0.8664), mean absolute error (MAE=0.0144), and root mean square error (RMSE=0.0274)) have been achieved due to the use of Sigma naught VH and Sigma naught VV as input data to the CNN architecture (C). Results show that VV polarization is better than VH polarization for soil moisture retrieval, and that Sigma naught, Gamma naught, and Beta naught have the same influence on soil moisture estimation.

Techniques for ground-based soil moisture measurement: a detailed overview

Techniques for ground-based soil moisture measurement: a detailed overview

Dynamic groundwater recharge simulations based on cosmic‐ray neutron sensing in a tropical wet experimental basin

AbstractAlthough cosmic‐ray neutron sensing (CRNS) is probably the most promising noninvasive proximal soil moisture measurement technique at the field scale, its application for hydrological simulations remains underexplored in the literature so far. This study assessed the use of CRNS to inversely calibrate soil hydraulic parameters at the intermediate field scale to simulate the groundwater recharge rates at a daily timescale. The study was conducted for two contrasting hydrological years at the Guaraíra experimental basin, Brazil, a 5.84‐km², a tropical wet and rather flat landscape covered by secondary Atlantic forest. As a consequence of the low altitude and proximity to the equator low neutron count rates could be expected, reducing the precision of CRNS while constituting unexplored and challenging conditions for CRNS applications. Inverse calibration for groundwater recharge rates was used based on CRNS or point‐scale soil moisture data. The CRNS‐derived retention curve and saturated hydraulic conductivity were consistent with the literature and locally performed slug tests. Simulated groundwater recharge rates ranged from 60 to 470 mm yr–1, corresponding to 5 and 29% of rainfall, and correlated well with estimates based on water table fluctuations. In contrast, the estimated results based on inversive point‐scale datasets were not in alignment with measured water table fluctuations. The better performance of CRNS‐based estimations of field‐scale hydrological variables, especially groundwater recharge, demonstrated its clear advantages over traditional invasive point‐scale techniques. Finally, the study proved the ability of CRNS as practicable in low altitude, tropical wet areas, thus encouraging its adoption for water resources monitoring and management.

Soil conditions in the “donga” soils in subhumid zone in West Africa

Water erosion threatens large areas around the world. “Donga” is one of the witnesses of gully erosion in northern Benin, which induces serious threats to the natural habitats. This study was conducted to evaluate soil moisture content in different donga types (“microdongas”, “mesodongas”, and “megadongas”) and its variation at different topographic levels. The thermogravimetric soil moisture measurement technique was used for moisture estimation on saturated and unsaturated soil. Data were analyzed through analysis of variance test and t test with SAS software. The results showed that soil moisture content varied according to donga types. On unsaturated soil, higher difference (2.75%, p = 0.0328) was obtained in mesodongas at the middle followed by megadongas at the middle (2.6%, p = 0.034). On saturated soil, higher difference was obtained in mesodongas at the upstream (6.51%, p &lt; 0.0001) at downslope (4.55%, p = 0.0032) and in the middle (4.32%, p = 0.0328) followed by microdongas at the upstream (2.25%, p &lt; 0.0001). The findings in this paper should be useful to researchers looking for soil moisture information in subarid and subhumid zone at different topographic levels to develop afforestation strategies based on species that can make the best use of soil water.

A Review on Moisture Measurement Technique in Agricultural Silos

Moisture content (MC) is that the weight of water contained in paddy and other grans expressed in percent. Moisture content is typically mentioned the wet basis which means the whole weight of the grain including the water (MCwb). Accurate MC testing is very important in managing and selling paddy and rice because depending on the aim rice has completely different ideal MC. Inaccurate MC measurements lead to lower head rice once milled at wrong moisture content, additional drying cost and loss of quality if paddy is dried too much, spoilage if the grain is just too wet in storage, additional drying cost and harvesting loss if paddy is harvested wetter than necessary and Weight loss (loss in profit) if grain is sold too dry. This paper intends to review the available techniques of moisture content measurements, its principles and sources of inaccuracies. Relevant properties of cereal grain also are studied with their impact on moisture content, temperature, density and humidity. There are several ways of grain moisture detection such as drying technique, resistance technique, capacitance technique, microwave technique, neutron technique, V/F Conversion, Ftir spectroscopic technique and Microcontroller technique. Current MC of grains are based- on sampling and individual single point measurement, so far, there is no available overall measurement of MC in silo, but by using tomography method can measurement MC in whole silo and investigate the efficiency and accuracy of localization of moisture distributions sensing in agricultural silo by using Gaussian algorithm.

Evaluation of the Performance of TDR and Capacitance Techniques for Soil Moisture Measurement

Abstract Though researchers have employed various techniques (gravimetric, electromagnetic, neutron scattering, heat pulse, microwave, and optical remote sensing techniques) for soil moisture measurement, dielectric-based techniques (Time Domain Reflectometry [TDR] and capacitance technique [CT]) have gained much more popularity, mainly due to revolutionary developments in the fields of electronics and data communication systems. However, the suitability and relative performance of these techniques for moisture measurement of soils is a point of debate. Hence, in order to address this issue, extensive studies were conducted on soils of entirely different characteristics, compacted at various compaction states (dry densities and water contents) by employing TDR and capacitance probes. Subsequently, the dielectric constant of the soil and its bulk electrical conductivity were obtained using these probes and compared against each other and those computed from Topp’s equation, which is a well-established relationship between the dielectric constant of the soil and its volumetric moisture content. An attempt was also made to correlate Ka values obtained from the dielectric techniques and Topp’s equation with those of the Time Propagation (TP) Mixing model, which incorporates the properties of the soil matrix as well. It has been observed that the Ka-TDR matches well with the Ka-Topp and Ka-TP, while the best match has been observed between Ka-TDR and Ka-Topp as compared to the Ka-CT. As such, the study demonstrates clearly that Topp’s equation, which ignores the soil-specific parameters, is capable of determining the soil moisture content appropriately. This study proposes an empirical equation that relates dielectric constants obtained from Topp’s equation to those obtained from TDR, CT, and the TP Mixing model. Such a relationship can be further utilized for estimating the volumetric soil moisture content.

Local- and Plot-Scale Measurements of Soil Moisture: Time and Spatially Resolved Field Techniques in Plain, Hill and Mountain Sites

Soil moisture measurement is essential to validate hydrological models and satellite data. In this work we provide an overview of different local and plot scale soil moisture measurement techniques applied in three different conditions in terms of altitude, land use, and soil type, namely a plain, a mountain meadow and a hilly vineyard. The main goal is to provide a synoptic view of techniques supported by practical case studies to show that in such different conditions it is possible to estimate a time and spatially resolved soil moisture by the same combination of instruments: contact-based methods (i.e., Time Domain Reflectometry—TDR, and two low frequency probes) for the time resolved, and hydro-geophysical minimally-invasive methods (i.e., Electromagnetic Induction—EMI, Ground Penetrating Radar—GPR, and the Electrical Resistivity Tomography—ERT) for the spatially resolved. Both long-term soil moisture measurements and spatially resolved measurement campaigns are discussed. Technical and operational measures are detailed to allow critical factors to be identified.

Microwave Sensing of Moisture Content and Bulk Density in Flowing Grain and Seed

Abstract. Current techniques for rapid moisture measurement of grain and seed through sensing the dielectric properties in the 1 to 200 MHz frequency range require correction for density fluctuations and therefore are not suitable for reliable measurements on flowing grain. Density-independent moisture sensing in grain and seed is possible at microwave frequencies and has been successfully demonstrated on static samples. Bulk density of flowing grain can also be sensed simultaneously with moisture content. Although the theoretical basis for density-independent grain moisture measurement is expected to be useful for flowing materials, successful use has not previously been demonstrated. A laboratory flowing grain system was built for tests of microwave moisture measurement that were conducted on shelled field corn, wheat, and soybeans. Appropriate software was written to control a microwave network analyzer for the necessary attenuation and phase measurements, and tests were run on flowing grain and seed materials at high and low moisture levels and at low, medium, and high flow rates. Results confirmed that moisture readings obtained on static and flowing grain and seed agreed well, demonstrating the usefulness of the microwave density-independent technique for monitoring moisture content of flowing grain and seed. Bulk density determinations of static and flowing grain and seed also agreed well, indicating the usefulness of the technique for monitoring bulk density when desired.

Visualizing Large Data Sets: Spatial and Temporal Soil Moisture Regime Dynamics

Core Ideas • A novel technique is developed for displaying large soil moisture data sets • Spatial and temporal soil moisture regime characteristics are captured • System dynamics are conveyed without plotting subjective profiles or histories Despite constituting a small portion of global water, soil moisture controls regional to continental precipitation patterns, soil biogeochemistry, C and nutrient cycling, watershed rainfall–runoff response, and vegetation patterning. While advanced, spatially and temporally distributed soil moisture measurement and prediction techniques are necessary for improving understanding of vadose zone processes, they generate a wealth of data that are difficult to visualize in a manner that conveys salient features of system dynamics. Specifically, visualizations using soil moisture profiles or time series require subjective selection of times or locations, respectively, and inevitably fail to capture the majority of the data. We developed a method for visualizing the complete soil moisture regime using time series data measured or simulated along a one‐dimensional spatial domain, which maintains the spatial relationship of measurement locations and conveys a sense of the variability of soil moisture at each location ordinate without the subjectivity of selecting representative soil moisture profiles for plotting. This technique is capable of conveying relevant features of soil moisture dynamics, such as the influence of soil texture, precipitation, plant water use, and groundwater interactions, by using (i) simulated soil moisture data from an ecohydrological model and (ii) field data collected using an advanced, spatially distributed measurement technique. Visualization techniques such as this one will be useful for developing insight into vadose zone processes and validating sophisticated vadose zone models with field data.

Correlation between near infrared spectroscopy and electrical techniques in measuring skin moisture content

Near infrared (NIR) spectroscopy technique serves as an important tool for the measurement of moisture content of skin owing to the advantages it has over the other techniques. The purpose of the study is to develop a correlation between NIR spectrometer with electrical conventional techniques for skin moisture measurement. A non-invasive measurement of moisture content of skin was performed on different part of human face and hand under control environment (temperature 21 ± 1 °C, relative humidity 45 ± 5 %). Ten healthy volunteers age between 21-25 (male and female) participated in this study. The moisture content of skin was measured using DermaLab® USB Moisture Module, Scalar Moisture Checker and NIR spectroscopy (NIRQuest). Higher correlation was observed between NIRQuest and Dermalab moisture probe with a coefficient of determination (R2) above 70 % for all the subjects. However, the value of R2 between NIRQuest and Moisture Checker was observed to be lower with the R2 values ranges from 51.6 to 94.4 %. The correlation of NIR spectroscopy technique successfully developed for measuring moisture content of the skin. The analysis of this correlation can help to establish novel instruments based on an optical system in clinical used especially in the dermatology field.

Simple infrared techniques for measuring beach surface moisture

ABSTRACTKnowledge of surface moisture on beaches is vital for aeolian process studies because moisture increases transport thresholds and limits mass flux. A number of beach surface moisture measurement techniques have been employed in the field, including sample extraction, commercial soil moisture sensors, and remote sensing techniques. Each method has significant limitations in the context of aeolian process studies. This study was designed to test infrared optic techniques for measuring beach surface moisture. A simple infrared sensor (narrow‐band radiometer) was developed to measure beach surface moisture content. The accuracy and practical usability of the narrow‐band radiometer were assessed in comparison to a commercial handheld spectroradiometer. Field calibrations conducted at Cape San Blas, Florida and Padre Island, Texas indicated that the narrow‐band radiometer performed quite well. The R2 values exceeded 0·98 in each case, and the standard error averaged about 1% moisture content compared with gravimetric moisture contents determined from 1·5 mm deep surface scrapes. The performance of the two instruments was found to be comparable, with the narrow‐band radiometer slightly outperforming the spectroradiometer. In practical applications, the narrow‐band radiometer also has logistical advantages and is better suited to measure large numbers of points. Copyright © 2012 John Wiley &amp; Sons, Ltd.

Assessing vertical soil moisture dynamics using multi-frequency GPR common-midpoint soundings

Soil moisture measurement techniques are of utmost importance to vadose zone hydrologists. Surface hydrogeophysical methods, such as ground-penetrating radar (GPR), have the capacity to provide field-scale soil moisture information across a range of depth scales. This paper presents an extensive field study using multi-frequency (i.e., 225 MHz, 450 MHz, 900 MHz) GPR common-midpoint (CMP) soundings to monitor a complete annual cycle of soil moisture conditions at three distinct sites. We examine the use of normal-moveout (NMO) velocity analysis applied to CMP data for monitoring highly dynamic vertical soil moisture conditions in a mid-latitude climate consisting of wetting/drying and freeze/thaw cycles with varying degrees of magnitude and vertical velocity gradient. NMO velocity analysis is used to construct interval-velocity-depth models at a fixed location collected every 1–4 weeks. These time-lapse models are combined to construct temporal interval-velocity fields, which are converted into soil moisture content using an appropriate petrophysical relationship. Using these moisture fields, we were able to characterize the vertical distribution and dynamics of soil moisture in the shallow vadose zone. Although the use of multiple antenna frequencies provided varying investigation depths and vertical resolving capabilities, optimal characterization of soil moisture conditions was obtained with high-frequency 900 MHz antennas. The integration of direct ground wave and NMO velocity data from a single CMP sounding allowed us to better refine the shallow soil moisture profile and underlying vadose zone conditions during seasonal wetting, drying and freezing cycles. This study demonstrates the capacity of GPR to characterize vertical moisture dynamics, and highlights the importance of collecting high-resolution data along the air–soil interface to resolve the water content profile from the surface down to the deeper vadose zone conditions.

A Review on Microwave Based Moisture Measurement System for Granular Materials

In the recent years, development of a non-destructive and non-contacting type moisture measurement system has attracted considerable interest. Because of their inherent nature of being non- destructive, ability to travel through non-conductive medium and having deep penetrative properties, Microwaves have been the traditional choice in this kind of research. This paper is a comprehensive review of Microwave Based Measurement System used for grains and pulses. In this paper, moisture measurement and calibration techniques for the system are presented. The objective of the paper is to provide the readers a broad perspective of the various techniques.

New in situ techniques for the estimation of the dielectric properties and moisture content of soils

Two original in situ HF techniques of dielectric characterization in two wide bands have been developed in order to estimate the moisture content of soils by complex impedance measurement. These techniques are based on the capacitive effect (1–20 MHz) and on the propagation of electromagnetic waves at high frequencies (0.1–4 GHz). The two measurement techniques use straight conductors that are inserted into the soil. Specific inversion algorithms were developed to estimate the apparent real permittivity of the soil versus frequency from the complex impedance. The validation of both instruments was made in the laboratory in the presence of dry and wet sands. In situ experiments were also made at high frequencies. These complementary devices should enlarge the range of usual soil moisture measurement techniques.

Development of an electrical time domain reflectometry (ETDR) distributed moisture measurement technique for porous media

In this paper, a novel electrical time domain reflectometry (ETDR) measurement technique capable of measuring moisture distribution profile in a porous medium is presented. A signal calibration algorithm to interpret the ETDR waveform based on an empirical relation between moisture content and differential impedance of the medium was developed. The transient distribution of the moisture content in a concrete block covered with fibre reinforced polymer laminate on one end surface was experimentally measured. The experimental results were then compared with the solution of a finite element analysis. Good agreement was shown for the trend of the transient moisture distribution profile. It was demonstrated that the ETDR distributed moisture sensor developed in the current study was capable of measuring the variation of the moisture content distribution in a porous medium.

Principles for Microwave Moisture and Density Measurement in Grain and Seed

The importance of cereal grain moisture content in determining time of harvest and in preserving grain quality is described. Techniques for moisture measurement, including electronic moisture meters, are also discussed briefly, and the need for better moisture sensing techniques for modern agricultural on-line moisture monitoring is described. Principles of microwave free-space measurements involving attenuation and phase-shift determination are explained, and density-independent functions of the grain permittivity are presented that permit reliable moisture sensing applicable to moving grain in which bulk density variation occurs. Three different approaches are discussed for determining moisture content and bulk density of grain from microwave measurement of the dielectric properties. A new moisture calibration function, based on complex-plane plots of dielectric constant and loss factor, each divided by bulk density, is described, which promises a universal calibration for different types of grain and seed. This important advantage should encourage commercial development for practical use.