Freezing experiments on unsaturated sand, loam and silt loam
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Abstarct Estimating soil-water flow during ground freezing is important for understanding factors affecting spring farming, soil microbial activity below the frozen soil, and permafrost thawing behavior. In this study, we performed a column freezing experiment using three different unsaturated soils (sand, loam and silt loam) to obtain a detailed dataset of temperature, water-content and pressure-head change under freezing conditions. The liquid water content and pressure head in the three soils decreased with decreasing temperature. Three soil temperature stages were found: unfrozen, stagnating near 0˚C and frozen. The temperature and duration of the stagnation stage differed among the soil types. The changes in liquid water content and pressure head during the freezing process were highly dependent on the soil-water retention curve. Water flowed through the frozen area in silt loam and sand, but no water flux was observed in the frozen loam. The freezing soil columns tended to contain more liquid water than estimated from retention curves measured at room temperature, especially at the early stage of freezing.Keywords:
Silt
Pressure head
Throughout the American west, irrigated agriculture has been targeted to increase water-use efficiency because of increased urban demands. Soil-moisture sensors offer a method to achieve efficiency improvements, but have found limited use primarily because of high cost and lack of soil-specific calibration equations. In this paper, the Decagon EC-20 soil-moisture sensor (a low-cost capacitance sensor) has been examined and a unique laboratory-calibration method has been developed. Field-and laboratory-calibration equations were developed for six soil types (sand, sandy loam, silt loam, loam, clay loam, and clay) in the Middle Rio Grande Valley for alfalfa and grass hay fields. The average absolute error in volumetric water content for field calibration was 0.430 m3/m3, and 0.012 m3/m3 for the laboratory calibration. The factory-calibration equation for the EC-20 was also evaluated and found to yield an average absolute error of 0.049 m3/m3. In this study, it was found that the EC-20 is a reliable, cost-effective, and accurate sensor, and it is recommended that the laboratory-calibration method presented in this paper be used to obtain maximum accuracy. It is also recommended that the field calibration of the EC-20 soil-moisture sensor be foregone, as this type of calibration exhibits large error rates that are associated with colocation of samples, voids, organic residues, and root densities. Additionally, it was found that the field-calibration method was time-consuming, covered a small range of moisture content values, and was destructive to the area around installed sensors, which could lead to additional measurement errors.
Capacitance probe
Silt
Soil test
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Summary Time‐domain reflectometry (TDR) is being used increasingly for measuring the moisture content of porous media. However, successful application for measuring water in soil has been limited to non‐deformable soils, and it would be a valuable extension of the technique if it could be used for soils that shrink on drying. We have recently investigated its application to soils rich in clay and organic matter and peats. Here we propose a method for determining moisture content in deformable soils based on the relation between the dielectric constant, K , and the volumetric moisture content, Θ, measured by TDR. Parallel TDR probes with a length of 15 cm and a spacing of 2 cm were placed horizontally in soil cores with a diameter of 20 cm and height of 10 cm taken from a forest. The soil is very porous with large proportions of both silt and clay. The sample weight and travel time of the electromagnetic wave guided by parallel TDR probes were simultaneously measured as a function of time, from saturation to oven‐dryness during which the core samples shrank considerably. Vertical and horizontal components of shrinkage were also measured to take the air‐exposed region of TDR probe into account in the determination of K . The effect of deformation on volumetric moisture content was formulated for two different expressions, namely actual volumetric moisture content (AVMC) and fictitious (uncorrected) volumetric moisture content (FVMC). The effects of air‐exposure and expressions of volumetric moisture content on the relation between K and Θ were examined by fitting the observations with a third‐order polynomial. Neglecting the travel time in the air‐exposed part or use of the FVMC underestimated the Θ for a given K . The difference was more pronounced between AVMC and FVMC than between two different dielectric constants, i.e. accounting for air‐exposure, K ac , and not accounting for air‐exposure, K au . When the existing empirical models were compared with the fitted results, most underestimated the relation based on the AVMC. This indicates that published empirical models do not reflect the effect of deformation on the determination of Θ in our forest soil. Correct use of the Θ expression has more impact on determining moisture content of a deformable soil than the accommodation of travel time through the air‐exposed region of TDR probe.
Reflectometry
Silt
Shrinkage
Saturation (graph theory)
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Different textured soils (sandy loam, silty clay loam and clay) from Manas County, Xinjiang were researched with indoor spectral reflectance, continuum removal was used to process soil spectra curve, and correlation analysis was made about normalized spectral reflectance and water content for modeling. The results show that different textured soils have reflectance in a order that clay>silty clay loam>sandy loam; the critical points of field capacity in sandy loam, silty clay loam and clay were 20.01%, 24.10% and 30.43% respectively, and water content was inversely proportional to spectral reflectance below such critical points while proportional above the points. Within 1390-1623 nm band, the negative correlation coefficients of soil water content and normalized spectra reflectance show better negative correlation and reaching significant levels, R2 of the model established for soil water content prediction exceeded mostly 0.8, and the average relative error of the model was 10%. The model could accurately reflect the soil moisture content, Its advantages such as accuracy, non-destruction and rapidness provide a new approach to measuring soil water content.
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