Estimation Of Moisture Content Research Articles

SI-Traceable Water Content Measurements in Solids, Bulks, and Powders

Methods such as Karl Fischer titration and Loss-on-Drying, commonly used for estimating moisture content in samples, have been in existence for many years, but have difficulties obtaining a direct calibration chain toward water content. In recognition of this challenge, the joint research project, METefnet, was funded by the European Metrology Research Programme in 2012. The goal of METefnet is to establish a European metrology infrastructure for water content measurement and to develop primary standards for unambiguous determination of water mass fraction in materials. Here, we describe the primary standard developed by Danish Technological Institute in METefnet. This standard establishes traceability of the water content of a sample to dewpoint temperature. The standard only measures water, and the measurement result is not affected by other components.

Field performance of three real-time moisture sensors in sandy loam and clay loam soils

ABSTRACTThe study was conducted to evaluate HydraProbe (HyP), Campbell Time Domain Reflectometry (TDR) and Watermarks (WM) moisture sensors for their ability to estimate water content based on calibrated neutron probe (NP) measurements. The three sensors were in-situ tested under natural weather conditions over a 3-yr period in a sandy loam and clay loam soils planted to grass. The HyP, TDR and WM sensors were evaluated for their ability to estimate soil moisture contents by comparing their outputs with those of NP measurements. Results showed that HyP, TDR and WM provided different estimates of soil moisture contents in both soils. Nevertheless, our work suggests that soil moisture sensors including those used in this study can be made suitable for irrigation scheduling without in-situ calibrations by simply setting the upper and lower irrigation trigger limits for each sensor and each soil type. The upper trigger point occurs directly after irrigation event (near field capacity) and the lower trigger point is based on about 50% depletion of available water in the crop rootzone and is occurs prior to irrigation refill. This approach can significantly help irrigators to achieve their irrigation scheduling and productivity goals without consuming any time onsite or soil specific calibrations.

Use of hyperspectral imaging for the prediction of moisture content and chromaticity of raw and pretreated apple slices during convection drying

ABSTRACTThe feasibility of using spectral reflectance information in the visible—near infrared (400–1,000 nm) region to estimate moisture content (gW/gDM) and chromaticity (CIELAB) of apple slices was investigated during convection drying. Apple slices were pretreated with hot water blanching (50 and 70°C), acid application (citric and ascorbic), and combinations thereof before drying at 50 and 70°C. Prediction models for the space-averaged spectral reflectance curves were built using the partial least square regression method. A three-component partial least square regression (PLSR) model satisfied the minimal root mean square error (RMSE) criterion for predicting moisture content (avg. RMSEP = 0.13, r2 = 0.99); importantly, the critical wavelengths remained the same across all pretreatments (540, 817, 977 nm). Similarly, PLSR modeling showed that the optimal set of wavelengths (in terms of RMSE) were invariant across pretreatment for CIELAB a* prediction (543, 966 nm) and CIELAB b* prediction (510, 664, 714, 914, 969 nm). The stability of the information content of these wavelengths across pretreatments indicates their independence of color changes. Additionally, the spatial information in the hyperspectral images was exploited to visualize the performance of the predictive models by pseudo-coloring their values for each pixel in a single apple slice across different drying times. This visualization of spatial distribution of predicted moisture content and chromaticity changes shows significant potential for use in online monitoring of the drying process.

GROUND-BASED REMOTE SENSING FOR ESTIMATING THE MOISTURE CONTENT OF DIFFERENT SOIL TYPES

Soil moisture information has been used for irrigation scheduling, site-specific management of diseases and pests, and improving crop yield prediction. Spectral remote sensing offers the potential to provide more information for making better-informed management decisions in real time. In contrast, the tradition methods for irrigation management such as tensiometers and oven dry for estimating moisture content are generally time consuming, numerous observations are required to characterize them. The aim of this study was to investigate the suitability of hyperspectral reflectance sensor to estimate the moisture content of different soils. For that the spectral indices of soil were tested to assessment the moisture content by wetted the soil from dry to saturation conditions. The results showed that the three water spectral indices R960/R940, R970/R940 and R970/R900 showed close and highly significant associations with moisture content of sandy soil, and coefficients of determination reach up to R2 = 0.98. The three water spectral indices R878/R862, R956/R926 and R1056/R994 showed close and highly significant associations with moisture content of sandy loam soil, and coefficients of determination reach up to R2 = 0.84. As well as the three water spectral indices R956/R924, R956/R926 and R956/R9284 showed close and highly significant associations with moisture content of clay soil, and coefficients of determination reach up to R2 = 0.86. In conclusion, the use of spectral remote sensing may open an avenue in irrigation management for fast, high-throughput assessments of water status of soil samples.

Effect of measurement temperature on power transformer insulation diagnosis using frequency‐domain spectroscopy

Frequency-domain spectroscopy (FDS) is a widely accepted method for the estimation of moisture content in oil-paper insulation of power transformer. Researchers have shown that measurement temperature is an important factor that not only shifts the tan δ curve both horizontally and vertically with respect to frequency axis but also affects the value of paper-moisture content of transformer insulation. This implies FDS data measured at different temperatures yields different results even if the insulation under consideration remains more or less unaffected. Availability and construction of master curve for in-service real-life units might not always be available. This study proposes a method that is capable of predicting the profile of tan δ curve at different measurement temperatures. Existing expressions available for predicting paper-moisture does not consider the effect of change in measurement temperature. This study also proposes modification of existing expression to predict the moisture content of insulation paper at any measurement temperature. In addition, this study outlines a method to evaluate the value of activation energy ( E a ) from the insulation response. The discussed technique is first tested successfully on data recorded from a laboratory sample. Thereafter, the method is applied on data collected from a real-life power transformer.

Estimation of the Instantaneous Soil Surface Moisture Content in Cold Seasons by using Optical and Thermal Remote Sensing Data under Clear Sky

Estimation of the Instantaneous Soil Surface Moisture Content in Cold Seasons by using Optical and Thermal Remote Sensing Data under Clear Sky

Soil Moisture Content Estimation Based on Sentinel-1 and Auxiliary Earth Observation Products. A Hydrological Approach.

A methodology for elaborating multi-temporal Sentinel-1 and Landsat 8 satellite images for estimating topsoil Soil Moisture Content (SMC) to support hydrological simulation studies is proposed. After pre-processing the remote sensing data, backscattering coefficient, Normalized Difference Vegetation Index (NDVI), thermal infrared temperature and incidence angle parameters are assessed for their potential to infer ground measurements of SMC, collected at the top 5 cm. A non-linear approach using Artificial Neural Networks (ANNs) is tested. The methodology is applied in Western Crete, Greece, where a SMC gauge network was deployed during 2015. The performance of the proposed algorithm is evaluated using leave-one-out cross validation and sensitivity analysis. ANNs prove to be the most efficient in SMC estimation yielding R2 values between 0.7 and 0.9. The proposed methodology is used to support a hydrological simulation with the HEC-HMS model, applied at the Keramianos basin which is ungauged for SMC. Results and model sensitivity highlight the contribution of combining Sentinel-1 SAR and Landsat 8 images for improving SMC estimates and supporting hydrological studies.

The optical trapezoid model: A novel approach to remote sensing of soil moisture applied to Sentinel-2 and Landsat-8 observations

The “trapezoid” or “triangle” model constitutes the most popular approach to remote sensing (RS) of surface soil moisture based on coupled thermal (i.e., land surface temperature) and optical RS observations. The model, hereinafter referred to as Thermal-Optical TRAapezoid Model (TOTRAM), is based on interpretation of the pixel distribution within the land surface temperature - vegetation index (LST-VI) space. TOTRAM suffers from two inherent limitations. It is not applicable to satellites that do not provide thermal data (e.g., Sentinel-2) and it requires parameterization for each individual observation date. To overcome these restrictions we propose a novel OPtical TRApezoid Model (OPTRAM), which is based on the linear physical relationship between soil moisture and shortwave infrared transformed reflectance (STR) and is parameterized based on the pixel distribution within the STR-VI space. The OPTRAM-based surface soil moisture estimates derived from Sentinel-2 and Landsat-8 observations for the Walnut Gulch and Little Washita watersheds were compared with ground truth soil moisture data. Results indicate that the prediction accuracies of OPTRAM and TOTRAM are comparable, with OPTRAM only requiring observations in the optical electromagnetic frequency domain. The volumetric moisture content estimation errors of both models were below 0.04cm3cm−3 with local calibration and about 0.04–0.05cm3cm−3 without calibration. We also demonstrate that OPTRAM only requires a single universal parameterization for a given location, which is a significant advancement that opens a new avenue for remote sensing of soil moisture.

The statistical structure of the field of surface soil layer moisture from ground-based and satellite observations

The following data was used: the archives of measurements of available water capacity carried out at Roshydromet network of stations and satellite measurements of relative humidity of the upper soil layer from ASCAT data (from the MetOp satellites). The statistical structure of the field of available water capacity in the upper 10- and 20-cm soil layers is assessed. The correlations between the Earth remote sensing data and data from agrometeorological stations are revealed. The procedure of automatic data checking from ground-based observations is developed. The algorithm is suggested for statistically optimal conversion of the Earth remote sensing data to the estimate of moisture content in the upper soil layer.

MOISTURE CONTENT ESTIMATION BASED ON A THERMAL ANALYSIS METHOD APPLIED TO SAND

MOISTURE CONTENT ESTIMATION BASED ON A THERMAL ANALYSIS METHOD APPLIED TO SAND

Field Measurements of Moisture Content in Black Spruce Logs with Unilateral Magnetic Resonance

Abstract The development of portable unilateral magnetic resonance (UMR) devices permits nondestructive characterization of wood moisture content (MC) in the field. In this study, six Picea mariana Mill. logs were measured. UMR measurements of MC were taken in four different spots displaced 15 cm from the end of each log. UMR measurements were also taken at the midpoint longitudinally for three of the six logs. The end goal of this study was to demonstrate a viable approach to estimating the whole-sample MC in the field. In the case of the species studied, there is a significant difference in MC between sapwood and heartwood regions. The sapwood MC is approximately three times greater than the heartwood MC. However, the volume of heartwood is greater than sapwood in wood logs. The sapwood region contains most of the water; therefore a measurement in the sapwood, coupled with sapwood-to-heartwood volume proportions and an estimate of heartwood MC, provide a viable estimate of bulk MC of logs. Results indicate that both measurement spots (15 cm displaced from the end and at the midpoint longitudinally) give good predictions of log MC. The UMR measurement signal-to-noise ratio decreases and variability in the total sapwood signal of the four spots, displaced 15 cm from the end, increases as drying progresses. The increase in variability is because of the appearance of a drying front at some measurement spots. The UMR device and technique provide a good tool to measure MC of logs in the field.

A TDR Array Probe for Monitoring Near‐Surface Soil Moisture Distribution

Core Ideas A TDR array has been developed for soil moisture profiling. The sensor provides eight incremental measurements at centimeter‐depth resolution. Permittivity, evaporation rate, and soil moisture profile were determined. Near‐surface soil conditions (i.e., moisture and temperature) moderate mass and energy exchange at the soil–atmosphere interface. While remote sensing offers an effective means for mapping near‐surface moisture content across large areas, in situ measurements, targeting those specific remotely sensed soil depths, are poorly understood and high‐resolution near‐surface measurement capabilities are lacking. Time domain reflectometry (TDR) is a well‐established, accurate measurement method for soil dielectric permittivity and moisture content. A TDR array was designed to provide centimeter‐resolution measurements of near‐surface soil moisture. The array consists of nine stainless steel TDR rods spaced 1 cm apart, acting as waveguide pairs to form eight two‐rod TDR probes in series. A critical aspect of the design was matching the spacing of the coaxial cable–TDR rod transition to avoid unwanted reflections in the waveforms. The accuracy of the TDR array permittivity measurement (±1 permittivity unit) was similar to that of conventional TDR as verified in dielectric liquids. Electric field numerical simulations showed minimal influence of adjacent rods during a given rod‐pair measurement. The evaporation rate determined by the TDR array compared well with mass balance data in a laboratory test. Near‐surface soil moisture profile dynamics were monitored at centimeter‐depth resolution using the TDR array in a field experiment where volumetric moisture content estimates (0–8 cm) were within 2% of conventional three‐rod TDR probes averaging across 0 to 8 cm and from 1‐ to 3‐cm depths.

A gamma-ray scattering technique for estimation of density and moisture content of wood

ABSTRACTA densitometer system, operating in a non-destructive and non-invasive way, is presented to investigate the density and moisture variation in wood samples of Pinus roxburghii (known as chir pine). The inherent ability of Compton scattering can ascertain quantitative information of electron density of the target material. A well collimated beam of 662 keV gamma rays from 137Cs radioactive source has been used to extract the information of density from interior of sample by recording scattered spectra with NaI(Tl) scintillation detector. An inverse matrix approach for unfolding of observed pulse-height distribution to a true photon spectrum is used, by choosing bin mesh (E1/2) of 0.025 (MeV)1/2, for the measurements of scattered spectra. The regression lines, obtained from data of scattered spectra, provide the density and moisture content of selected wood sample. The adjusted R2 value 0.984 for fitted curve, justifies the linear dependence of scattered intensity upon wood density. Also, Compton scatter measurements results that the technique is less sensitive beyond wood thickness of ∼110 mm due to overlying scatter components in the measured spectrum.

Moisture content correction: Implications of measurement errors on tree- and site-based estimates of biomass

Accurate estimates of biomass are required for relating ecosystem functioning to atmospheric carbon regulation. Biomass may be directly measured through field sampling, which can then be used to calibrate biomass predictions from remote sensing and/or modelling. Field sampling generally entails measuring the fresh mass of individual trees or shrubs and then estimating the moisture contents of a representative sub-samples, which are then used to calculate dry mass. Because any errors in the estimation of the moisture content (MC) correction are translated proportionally to the biomass prediction of an individual tree or shrub, care is required to ensure MC estimates are unbiased and as precise as possible. There are numerous different protocols currently applied to attain MC, with these differing in accuracy (bias and precision) and cost of implementation. A dataset of MC of above-ground biomass (AGB) of 1396 individuals (trees or shrubs) was used to assess which protocols for within- and among-individual sampling are likely to provide the most cost-effective estimates of MC within acceptable bounds of accuracy. Monte-Carlo analysis was used to explore key sources of error in within-individual MC estimation. Results suggest these MC estimates may be based on at least the bole and crown components of AGB, with bias resulting if MC is based on stem wood only, particularly in young (or small) individuals. Little gain in accuracy was attained with more intensive sub-sampling (e.g. into foliage, twig, branches, bark, and stem wood components). Moreover, further efficiencies may be gained by applying existing empirical models to estimate the proportion of AGB that is crown based on easily measured variables such as stem diameter, thereby avoiding the resource-intensive process of partitioning to obtain fresh weights measurements of components. However to minimise bias, it is important to undertake MC sampling at each study site, and to stratify sampling among-individuals by both appropriate taxonomic grouping (e.g. plant functional type) and age-class. For a given plant functional type-by-size (or age) strata at a given site a precision of about 4% coefficient of variation of the average MC estimate can be achieved with intensive within- and among-individual sampling. However a precision of 8–10% is achievable using our recommended less intensive but more efficient protocol; derive an average MC for at least six individuals, and for each individual, intensively sub-sample bole and crown components for MC, which is then applied to the fresh weights of these components. This latter estimate may be obtained from partitioning of the AGB, or for the highest efficiency, from predictions obtained from the application of existing representative empirical relationships of partitioning based on the size of the individual.

Effective Saturated Hydraulic Conductivity for Representing Field-Scale Infiltration and Surface Soil Moisture in Heterogeneous Unsaturated Soils Subjected to Rainfall Events

Spatial heterogeneity in soil properties has been a challenge for providing field-scale estimates of infiltration rates and surface soil moisture content over natural fields. In this study, we develop analytical expressions for effective saturated hydraulic conductivity for use with the Green-Ampt model to describe field-scale infiltration rates and evolution of surface soil moisture over unsaturated fields subjected to a rainfall event. The heterogeneity in soil properties is described by a log-normal distribution for surface saturated hydraulic conductivity. Comparisons between field-scale numerical and analytical simulation results for water movement in heterogeneous unsaturated soils show that the proposed expressions reproduce the evolution of surface soil moisture and infiltration rate with time. The analytical expressions hold promise for describing mean field infiltration rates and surface soil moisture evolution at field-scale over sandy loam and loamy sand soils.

A regression approach to the mapping of bio-physical characteristics of surface sediment using in situ and airborne hyperspectral acquisitions

Remote sensing has been successfully utilized to distinguish and quantify sediment properties in the intertidal environment. Classification approaches of imagery are popular and powerful yet can lead to site- and case-specific results. Such specificity creates challenges for temporal studies. Thus, this paper investigates the use of regression models to quantify sediment properties instead of classifying them. Two regression approaches, namely multiple regression (MR) and support vector regression (SVR), are used in this study for the retrieval of bio-physical variables of intertidal surface sediment of the IJzermonding, a Belgian nature reserve. In the regression analysis, mud content, chlorophyll a concentration, organic matter content, and soil moisture are estimated using radiometric variables of two airborne sensors, namely airborne hyperspectral sensor (AHS) and airborne prism experiment (APEX) and and using field hyperspectral acquisitions by analytical spectral device (ASD). The performance of the two regression approaches is best for the estimation of moisture content. SVR attains the highest accuracy without feature reduction while MR achieves good results when feature reduction is carried out. Sediment property maps are successfully obtained using the models and hyperspectral imagery where SVR used with all bands achieves the best performance. The study also involves the extraction of weights identifying the contribution of each band of the images in the quantification of each sediment property when MR and principal component analysis are used.

A method to estimate wood surface moisture content during drying

A method to estimate the surface moisture content below the fibre saturation point that is a function of the surface temperature, wet- and dry bulb temperatures, equilibrium moisture content, and fibre saturation point was evaluated. The method is based on the premise that the surface temperature is solely influenced by the surface moisture content and the climate that the surface is exposed to. The prediction model contends that the surface moisture content is equal to the fibre saturation point when the surface temperature is equal to the wet bulb temperature, and equal to the equilibrium moisture content when the surface temperature is equal to the dry bulb temperature, with a linear interpolation between those two points. The model thus predicts that the average moisture content of a thin piece of veneer can be predicted with fairly good accuracy. Also, when drying boards in a fast changing climate, e.g. fan reversals in industrial kilns, the surface temperature and surface moisture content should change as abruptly as the climate does. Additionally, the surface moisture content should correlate to the known drying phases, with a consistently high surface moisture content during the capillary phase when the wet line is close to the surface, and a quickly decreasing surface moisture content when the wet line moves into the wood during the transition to the diffusion phase. The prediction model was tested in these three scenarios and the results suggest that the basic premise is reasonable, and that the method is useful for surface moisture content estimation.

Experimental assessment of electrical properties of lateritic soils as an alternative non-destructive method for compaction monitoring

Soil stabilisation has been widely used in Nigeria to improve the geotechnical properties of soils in roads and other engineering construction sites. In this study, electrical resistivity properties of pre-treated mechanically compacted lateritic soils from Ibadan, SW-Nigeria were investigated. The intent is to develop a cheap and easy method of estimation of maximum dry density (MDD) and optimum moisture content (OMC) from the corresponding electrical resistivity measurements. The results show that the effective electrical resistivity (EER) of compacted lateritic soils corresponding to the OMC and MDD varies from 23 to 103 Ωm (mean 55.7 Ωm) for Standard Proctor compaction, 50–184 Ωm (mean 96.4 Ωm) for West African level compaction and 44–308 Ωm (mean 132 Ωm) for Modified AASHTO Proctor compaction suggesting that EER increases with increasing compactive effort. However, modified AASHTO compaction with cement addition revealed EER of 14–28 Ωm (mean 18.5 Ωm) implying that EER decreases with increasing moisture content and cement content. A simple relationship revealed that EER of cement-treated mechanically compacted soil is directly proportional to MDD due to the density enhancement as a result of pozzolanic reaction and inversely proportional to the cement content as more moisture is required for the pozzolanic reaction leading to decrease in EER. This study has demonstrated the use of electrical resistivity measurements as an alternative, time and cost-effective in situ method of predicting the status and quality of mechanically compacted soils at construction sites.

Prediction of water content and normalized evaporation from oil sands soft tailings surface using hyperspectral observations

The paper addresses the challenge of measuring water content and evaporative fluxes from oil sands soft tailings surfaces using hyperspectral observations. Hyperspectral time-series laboratory observations were collected from four different mature fine tailings (MFT) samples displaying variations in swelling potential and bitumen concentration. The samples were allowed to evaporate from an initial state of water saturation to an air-dried state. From these data, several spectral features were evaluated to predict water content and normalized evaporation rate from the optically sensed portion of the tailings surface (less than a few hundred micrometres). For the samples tested, the best estimate of moisture content was achieved using the normalized soil moisture index (NSMI) index (coefficient of determination R2 = 0.97). The absolute reflectance at 1920 nm was found to be the best spectral estimator of normalized evaporation (R2 = 0.97), with the NSMI index also being valuable (R2 = 0.95). In both instances, the NSMI index may be of value for estimations attempted in the field. Remote estimation of moisture content and evaporation could help tailings managers assess the drying process to determine when the deposit has stopped drying at the surface and decide when the next lift should be deposited. In future efforts, the models obtained from this laboratory investigation will be assessed for their applicability in field settings and validated using concurrent sampling.

Structural health assessment of historical timber structures combining non-destructive techniques: The roof of Giotto's bell tower in Florence

Examining the timber structure supporting the roof of Giotto's bell tower in Florence, this paper discusses the combination of non-destructive (NDT), wave-based methods for the characterization of timber structural elements. In particular, it analyses the on-site applicability of selected wave-based techniques for the identification of decay, damage, defects, and moist areas in structural timber. The applied NDT techniques are IR termography, microwave reflectometry, time-of-flight tomography, and mapping by means of elastic waves. Experimental results are compared with data obtained by means of consolidated NDT techniques, such as the electric resistance method for moisture content estimation and the drill-resistance test for decay characterization. These can be considered non-destructive, although they are invasive. The wave-based NDT methods are found to be a value-added complement to routine methodologies for a holistic diagnosis of timber members. Normal practice based on visual inspection, decay detection through point measurements of drill resistance, and moisture content estimation through local readings of electric resistance, can be substantially improved through full-field, multi-sensor, multi-resolution imaging. Nevertheless, while the diverse NDT methods illustrated here can be useful for screening large areas in a completely non-invasive way, local measurements (i.e., the drill resistance and the electric resistance measurements) are still necessary.