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An increasing number of electromagnetic (EM) sensors are deployed to measure volumetric soil water content (θ) for agricultural, ecological, and geotechnical applications. While impedance and capacitance sensors generally operate at frequencies between 20–300 MHz, time domain‐reflectometry (TDR) and‐transmissometry (TDT) function in the GHz range. In general, lower frequency sensors are less expensive but more sensitive to confounding effects of salinity, temperature, and soil textural variations. To simplify sensor application, factory‐supplied calibrations are often provided for different porous media types such as mineral, organic, and saline soils, or soilless‐substrates. The objective of the presented study was to evaluate the performance of eight commercially available EM moisture sensing systems (TDR 100, CS616, Theta Probe, Hydra Probe, SM300, Wet2, 5TE, 10HS) in seven well‐characterized and texturally varying soils using a standardized approach. The validity of factory supplied‐calibration relationships was evaluated and the influence of soil properties on the EM responses for θ measurements was observed. Results indicate that the factory‐supplied calibration relationships for groups of mineral and organic soils in general performed well, but some inconsistences were identified and suggestions for improvement are discussed. Soil‐specific calibrations from this study yielded accuracies of around 0.015 m3m−3 for 10HS, SM300, and Theta Probe, while lower accuracies of about 0.025 m3 m−3 were found for TDR100, CS616, Wet2, 5TE, and the Hydra Probe. These results are based on mineral soils having a large variation in texture, electrical conductivities below 2 dS m−1, organic matter below 10%, and specific surface areas of less than 50 m2 g−1.

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(1999), using the model of Turcotte (1986) and Tyler and Wheatcraft (1992), also found that three domains A particle-size distribution (PSD) constitutes a fundamental soil characterized the cumulative PSD of 19 soils. They assoproperty correlated to many other soil properties. Accurate representations of PSDs are, therefore, needed for soil characterization and ciated the power exponent in each domain with fractal prediction purposes. A power-law dependence of particle mass on dimensions defining scaling in the clay, silt, or sand particle diameter has been used to model soil PSDs, and such powerdomains. law dependence has been interpreted as being the result of a fractal A distribution of particle sizes reflects the relative distribution of particle sizes characterized with a single fractal dimenbalance of weathering and pedogenetic processes. Prision. However, recent studies have shown that a single fractal dimenmary minerals, generally present in the sand-and siltsion is not sufficient to characterize a distribution for the entire range size fractions, originate from weathering of a parent of particle sizes. The objective of this study was to apply multifractal material, while clay minerals are the result of weathering techniques to characterize contrasting PSDs and to identify multifracand synthesis of new minerals. The different origin of tal parameters potentially useful for classification and prediction. The the various size fractions may explain the various scaling multifractal spectra of 30 PSDs covering a wide range of soil textural classes were analyzed. Parameters calculated from each multifractal domains observed in soil PSD (Wu et al., 1993; Bittelli spectrum were: (i) the Hausdorff dimension, f(␣); (ii) the singularities et al., 1999). Grout et al. (1998) found that a single of strength, ␣; (iii) the generalized fractal dimension, D q ; and (iv) fractal dimension obtained from the model of Tyler their conjugate parameter the mass exponent, (q), calculated in the and Wheatcraft (1992) did not describe adequately the range of moment orders (q) of between Ϫ10 and ϩ10 taken at 0.5 distribution of particle sizes of three soils, and proposed lag increments. Multifractal scaling was evident by an increase in the multifractal techniques as a promising alternative to difference between the capacity D 0 and the entropy D 1 dimensions characterize PSD. Multifractal distributions may be best for soils with more than 10% clay content. Soils with Ͻ10% clay suited to represent the multiplicative action of the varicontent exhibited single scaling. Our results indicate that multifractal ous pedogenetic processes acting on a parent material parameters are promising descriptors of PSDs. Differences in scaling and resulting in a given distribution of particle sizes. properties of PSDs should be considered in future studies.

Atrazine (6-chloro-N2-ethyl-N4-isopropyl-1,3,5-triazine-2,4-diamine) is retained against leaching losses in soils principally by sorption to organic matter, but the mechanism of sorption has been a matter of controversy. Conflicting evidence exists for proton transfer, electron transfer, and hydrophobic interactions between atrazine and soil humus, but no data are conclusive. In this paper we add to the database by investigating the role of (i) hydroxyatrazine (6-hydroxy-N2-ethyl-N4-isopropyl-1,3,5-triazine-2,4-diamine) and (ii) hydrophobicity in the sorption of atrazine by Brazilian soil humic substances. We demonstrate, apparently for the first time, that hydroxyatrazine readily forms electron-transfer complexes with humic substances. These complexes probably are the cause of the well-known strong adsorption by humic acids and they may be the undetected cause of apparent electron-transfer complexes between soil organic matter and atrazine, whose transformation to the hydroxy form is facile. We also present evidence that supports the important contribution of hydrophobic interactions to the pH-dependent sorption of atrazine by humic substances.

and nutrient exploration have been obtained (Stelluti et al., 1998), and cone penetrometers have been used Soil mechanical impedance affects root growth and water flow, extensively in soil science studies to identify natural and controls nutrient and contaminant transport below the rooting and induced compacted layers (Henderson, 1989) or to zone. Among the soil parameters affecting soil strength, soil water content and bulk density are the most significant. However, field predict related soil properties (Ayers and Bowen, 1987). water content changes both spatially and temporally, limiting the Among the soil parameters that affect PR, soil water application of cone penetrometers as an indicator of soil strength. content and bulk density are the most significant (Vaz-Considering the presence of large water content variations within a quez et al., 1991). For example, Stitt et al. (1982) consoil profile and across a field and the large influence of water content ducted a comprehensive study of factors affecting PR on soil strength, there is need for a combined penetrometer-moisture in coarse-textured soils in the Atlantic Coastal Plain, probe to provide simultaneous field water content and soil resistance and used stepwise regression to relate mechanical immeasurements. Such a probe was developed, which uses the time pedance to various measured soil properties. The highdomain reflectometry (TDR) technique to determine water content est correlation coefficients were found for a regression and its influence on soil penetration resistance. The coiled TDR moismodel that included soil water content, soil particle ture probe consists of two parallel copper wires, each 0.8 mm in roughness and bulk soil density. Shaw et al. (1942) condiameter and 30 cm long, coiled around a 5-cm-long polyvinyl chloride (PVC) core with a 3-mm separation between wires. Calibration curves cluded that soil moisture is the dominant factor influencrelating the soil bulk dielectric constant measured by the coiled probe ing the force required to push a penetrometer into the to water content were obtained in the laboratory for a Columbia soil, with PR increasing as the moisture content define sand loam (coarse-loamy, mixed, superactive, nonacid, thermic creased. In an experimental study by Henderson et al. Oxyaquic Xerofluvent), a Yolo silt clay loam (fine-silty, mixed, non-(1988) it was found that PR was only slightly affected acid, thermic Typic Xerorthent), and washed sand, and data were with a decrease of soil water content to ≈70% of field analyzed based on a mixing model approach. Subsequently, field excapacity. However, the PR increased exponentially with periments were conducted to measure simultaneously the penetration a further reduction of the water content of the sandy soil. resistance (PR) and water content along a soil profile. Results showed This study showed that PR increased with an increase of a detailed water content profile with excellent correlation with the bulk density across the whole measured water content gravimetric method...

Soil strength as measured by cone penetrometers depends on severa 1 parameters, but it is mostly affected by the soil water content ({})and bulk density (p). In order to better understand the effect of lhe water content and bulk density on soil strength we developed a combined penetrometer-coiled TOR probe to determine simultaneously the depth distribution of penetration resistance and water content in a soil profile. Field experiments carried out for a Yolo soil allowed the fitting of the effect of O and p using a combined power-exponential equation. Using the cornbined cone penetrollleter-TOR probe data, the fitted equation rnay be used to estimate soil bulk density.

The Arya and Paris (AP) model predicts soil water retention curves from soil particle‐size distribution (PSD) data based on the similarity between these two functions. The AP model estimates pore radius (ri) from the radius (Ri) of spherical particles by scaling pore length with a parameter α. This paper evaluates the performance of the AP model with representative Brazilian soil types using three constant α values: α = 1.38, 0.938 (literature values), and 0.977, (obtained in the present work); and a α‐variable approach, where α is determined as a function of soil water content (θ). The study was performed with 104 soil samples collected in three sites. The soil PSD curves were obtained with an automatic soil particle analyzer based on the attenuation of γ‐ray by dispersed soil particles falling in a liquid medium and the soil water retention were measured with tension table and Richard chamber methods. The best mathematical representation of the α = f(θ) relationship was obtained with a first‐order exponential decay equation [α = 0.947 + 0.427exp(−θ/0.129)] that provided values of α in the range from 1.37 (θ = 0 m3 m−3) to 0.96 (θ = 0.6 m3 m−3). The root mean square deviation values of estimated and measured θ were 0.062 m3 m−3 for α = f(θ), 0.073 m3 m−3 for α = 0.977, 0.080 m3 m−3 for α = 0.938, and 0.136 m3 m−3 for α = 1.38. Therefore, for these set of soils the α‐variable approach and the constant ones using 0.977 and 0.938 presented the best estimation for the soil water retention relationships.