Soil Water Retention Curve Parameters Research Articles

Developing novel ensemble models for predicting soil hydraulic properties in China’s arid region

Accurately quantifying the mass (water, nutrients, and carbon) and energy exchange processes between the Earth’s atmosphere, biosphere, and lithosphere requires the accurate parameterization of soil hydraulic properties (SHPs) and their spatial heterogeneity. Because direct measurements of SHPs are difficult, time-consuming, and impossible at larger spatial scales, various pedotransfer functions (PTFs) have been developed in the last few decades, providing divergent estimates of SHPs from readily measurable variables. However, existing PTFs are mostly developed for specific regions and may not be suitable for other pedoclimatic conditions. Here, PTFs were developed using multiple machine-learning algorithms to estimate SHPs and examined the weaknesses and strengths of each method in estimating the average and variability of SHPs across China’s arid region. The optimal PTFs were applied to a 1 × 1 km2 regional map of texture and bulk density, thus producing maps of the saturated hydraulic conductivity (Ks), the parameters of the van Genuchten (VG) formulation, field capacity (θfc), wilting point (θwp), plant available water (θpa), and soil macroporosity (ϕm) in the 0–2 m soil profile throughout the region. The results indicate that the ensemble model with the averaging method (EMA) is the most robust for estimating all SHPs. The EMA-PTFs for Ks yielded the best performance for sand textures, followed by sandy loam, loam, silty loam, silty clay loam, loamy sand, and clay loam textures. There were no significant differences in estimating soil water retention curve parameters among the different soil texture classes. Using the same observed data set, we demonstrated that the new EMA-PTFs outperformed those of existing PTFs, such as Rosetta and HYPRES, with RMSE values decreasing by 25–83 % depending on the SHPs. Furthermore, our SHP datasets exhibited significantly deeper soil profiles and higher accuracy than other available regional and global SHP products. The VG retention parameter α shows the greatest variation vertically throughout the 0–2 m soil profile, followed by ln(Ks), θr, θpa, θfc, θwp, ϕm, θs and n. All SHPs exhibit much lower variability in the desert than in other areas, likely due to the homogeneous particle size distribution of desert areas. This study provides more accurate SHP estimates in China’s arid region than the existing SHP products by developing advanced PTFs and highlights the inconsistency in SHPs among different global or regional products; the uncertainties induced by PTFs should thus be considered in future terrestrial biosphere modeling.

Spatial relationships between the van Genuchten soil-water retention curve parameters and photosynthetic gas exchange variables in a wheat field

Photosynthetic gas exchange indices can be used to assess spatial variation of crop growth and yield on the field. Spatial variation of soil parameters can be an important tool to assess and manage crop growth status and product quality in the field, given the impact of soil on photosynthetic function. The purpose of this study was to evaluate the spatial relationships between the van Genuchten (vG) soil water retention curve parameters, soil properties and the photosynthetic gas exchange indices in a wheat field with an extension of 200 ha. Different variables of soil and plant were determined at the 100 nodes of a nearly regular grid (150 m × 150 m) over the whole field. The range of variograms showed high variability for photosynthetic parameters and vG parameters, and greater continuity for soil parameters. Photosynthesis was significantly correlated with saturated soil water content (θs) (r = 0.26*), θ1500kPa (permanent wilting point) (0.21*), porosity (r = 0.31**), bulk density (r = −0.32**) and clay content (r = 0.24*). Cross correlogram and linear model of coregionalization of sub-stomatal CO2 concentration (Ci) and stomatal conductance (gs) with photosynthetic rate (A) and transpiration (E) showed opposite relation with soil and hydraulic properties. Regressing of maps showed that a large part of the total variation in A (66%), Ci (79%) and gs (37%) was explained by soil variables. Also, from the visual inspection of the interpolated maps the field can be divided in zones characterized by different soil properties and these maps could be effectively used by farmers to improve wheat yield. On the other hand, results of this study may enhance understanding of the soil properties and soil hydraulic parameters effects on gas exchange parameters of the plant and delineation of the field in homogeneous zones that could be advantageously used by farmers to make informed decisions in site-specific management.

The effect of stress-dependent SWRC on the load carrying capacity of the slope subjected to the drying-wetting path

The stability and load capacity of structures resting on compacted soil slopes is one of the major concerns in Geotechnical Engineering practice. The mechanically compacted earthen slopes are prone to the dynamic exchange of flux flow, resulting in varying saturation levels across their entire configuration. The soil water retention curve (SWRC) is a property which significantly controls the stability and load capacityof structures resting on these compacted soil slopes. The parameters of a typical SWRC are affected by net stress and climatic changes in field conditions, adding more complexity in evaluating the load capacity and stability of structures resting on these compacted soil slopes. To analyze this issue critically, the load capacity of a footing resting on an unsaturated compacted soil slope under year-long arid climatic conditions has been evaluated numerically in the present study. The effect of net stress has been considered by assessing the stress-dependent SWRC of chosen soil under the wetting and drying cycle at various net confinementsof 10 kPa, 100 kPa, and 200 kPa in the laboratory. Key parameters of the SWRCs under drying and wetting cycles were incorporated to evaluate the load capacity of the footing resting on the unsaturated soil slope.

Parameter estimation of soil water retention curve with Rao-1 algorithm

The soil water retention curve (SWRC) has a significant role in determining the unsaturated properties of soil. A stochastic optimization algorithm named Rao-1 algorithm is employed to estimate the parameters of the SWRC model in this paper. The Rao-1 algorithm is a simple heuristic search algorithm containing only addition and multiplication operations. This paper introduces the method and its application in the determination of soil water retention model parameters in detail. In this study, van Genuchten model is used to depict the SWRC for its good fitting capacity, and parameters of the van Genuchten model are determined using Rao-1 algorithm. The feasibility and efficiency of the method are validated via the experimental results of 24 soil samples of 12 soil textural classes. Besides, the performance of Rao-1 algorithm is compared with that of Particle Swarm Optimization algorithm, Differential Evolution algorithm, and RETC program. Through comparative analysis, Rao-1 algorithm outperforms other methods in determining SWRC parameters.

Soil-water characteristic curves and their estimated hydraulic parameters in no-tilled and conventionally tilled soils

Tillage loosens soil, reduces bulk density, alters soil structure and pore size distribution, consequently affecting the shape of the soil-water retention curve (SWRC) and related hydraulic properties and parameters in the top layer of soil. Knowledge of SWRC and hydraulic properties are needed for many soil, agronomic, irrigation, hydrological and environmental studies. This work compares the effect of no-tillage (NT) and conventional tillage (CT) practices on SWRCs and their estimated parameters at 0–15 and 15–30 cm soil depths based on soil samples collected in 2014, 2015, 2016, and 2017. Undisturbed soil cores were extracted using stainless steel cylinders (8 cm in diameter and 5 cm in height) from 0 to 15 cm and 15–30 cm depths in planted corn rows. Soil core sampling was replicated five times in a randomized block design. Soil cores were saturated prior to measurement by the capillarity method and SWRC were measured using the HYPROP evaporative method. Measured soil-water retention curve data were fitted for no-tilled and tilled soils using the van Genuchten (vG) equation for each depth. Results indicated that differences existed in SWRC properties and estimated parameters of vG equation between the two tillage management practices. Averaged across 4 years and two depths, the SWRC parameters α, n, and θs were significantly greater under CT than under NT, however, θr was not affected by tillage. The higher α, n, and θs values in CT were likely associated with greater soil loosening and disturbance induced by CT operations, thereby forming greater macroporosity and pore volume that, in turn, caused a decrease in bulk density in CT compared to NT. Regardless of the tillage method, SWRCs enable growers and researchers to select farming and irrigation management practices that improve water use efficiency, sustain crop productivity and maintain environmental quality.

MesoSoil v2.0: An updated soil physical property database for the Oklahoma Mesonet

AbstractSoil moisture data from the Oklahoma Mesonet have been used in numerous fields within the Earth sciences, including agriculture, hydrology, and meteorology. Soil matric potentials measured by heat dissipation sensors at Oklahoma Mesonet stations have been converted to soil volumetric water content estimates using soil water retention curve parameters estimated by the Rosetta pedotransfer function. Recently, an improved version of Rosetta, Rosetta3, was released. Informed by this new pedotransfer function and soil sampling at additional locations, an improved version of the Oklahoma Mesonet soil physical property database, MesoSoil v2.0, has been created. This article presents this new soil database, compares soil water retention parameters estimated using Rosetta3 with those derived from the original Rosetta model, and describes the effects of changes in those parameters on estimated volumetric water content. Using the Rosetta3 model led to changes in the estimated water retention parameters, most notably decreases in the parameter α, which is related to the inverse of the air‐entry potential. These changes resulted in volumetric water content estimates that differed from those based on Rosetta1, with mean absolute differences averaging 0.02 cm3 cm–3 across all site‐years and the greatest differences occurring during wet periods. The mean volumetric water content estimated using the Rosetta3 parameters across more than 100 sites was not significantly different from that determined by soil sampling. The updated database is publicly available and may be found here: http://soilphysics.okstate.edu/data.

Influence of Uncertainty of Soil Hydraulic Parameters on Stability of Unsaturated Slopes Based on Bayesian Updating

In geotechnical engineering, the soil water retention curve (SWRC) is key to solving problems arising from unsaturated soil, and the methodology used to obtain the SWRC parameters is crucial for investigating rainfall infiltration and slope stability. However, on-site measurements of soil data are expensive and time-consuming, and therefore, there is high uncertainty in the SWRC parameters due to the limited amount of data available. This study explores the impact of uncertainty in SWRC parameters on unsaturated soil slope seepage and stability under rainfall conditions. Bayesian updating was initially used to update the posterior distribution of the SWRC parameters of the model and in situ soil. Subsequently, a Markov Chain Monte Carlo (MCMC) method was used to generate random samples, and the uncertainty of the parameters was analyzed. Additionally, SWRC parametric models with different confidence intervals were created, and a hydraulic coupled model was used to evaluate the influence of the SWRC parameters (with different confidence intervals) on slope seepage and stability under rainfall conditions. The results indicated that the parameters α and n affecting the air entry value of the soil and the pore size distribution, respectively, increased as the confidence interval percentile increased. The changes in these two parameters increased the effect of rainfall on the pressure head and volumetric water content of the soil. After rainfall infiltrated the slope, the soil volumetric water content and the internal suction stress of the soil increased, resulting in a reduction in the local factor of safety (LFS) and, hence, a decrease in the stability of the slope. These results show that the predictions for the pressure head and volumetric water content were affected by the uncertainty in the SWRC parameters, leading to errors in the slope stability analysis.

Importance of volumetric shrinkage curve (VSC) for determination of soil–water retention curve (SWRC) for low plastic natural soils

The study of unsaturated behavior of soils pivots around the relationship between soil suction and the amount of water content present in the soil mass, which is termed as soil–water retention curve (SWRC). The drying SWRC is generally determined by neglecting the volume change behavior of the soil for low plastic soils. Such a procedure is bound by an inherent assumption that the soil exhibit zero or negligible volume change and can lead to approximations in important SWRC parameters, including saturated volumetric water content, residual water content, and fitting parameters, which are essential for the estimation of unsaturated hydraulic characteristics of the soil. This study deals with the determination of SWRC parameters for a range of soils starting from non-plastic to high plastic soils, with and without considering volume change characteristics. For this purpose, the SWRC of six different natural soils were experimentally measured using a miniature tensiometer (T5) and a dew point potentiometer (WP4C), while the VSC of the used soils were measured using the balloon method. Efforts were made to critically understand the influence of no volume change assumption on the SWRC parameters, unsaturated hydraulic conductivity function, and flow of water through 1D soil column. The experimental results indicated that the no volume change assumption underpredicted the water retention curves of low plastic soils, and this error in SWRC increases with the soil plasticity. The measured VSC of the used soils further revealed that there could be a range of saturated volumetric water content (VWC) depending on the initial state of the soil sample, which also influences the sensitivity of the SWRC parameters. Therefore, the present study proposed a new methodology to determine unambiguous SWRC (in terms of VWC-suction) for a particular soil type combining both the measured VSC data and SWRC data. Based on the obtained results, it was recommended that the details of VSC must be incorporated along with the measured SWRC data for soils having plasticity and clay content higher than 15 and 11%, respectively.

Pedotransfer functions for estimating soil water retention properties of northern China agricultural soils: Development and needs*

AbstractMany agro‐environmental studies focusing on the efficient management of soils and water resources make use of soil water simulation models. Reliable soil hydraulic properties are critical for ensuring the accuracy of model simulations. However, soil hydraulic parameters in northern China are generally derived using external pedotransfer functions (PTFs) that do not take into account the specificities of local edaphoclimatic conditions due to the lack of a better alternative. Therefore, the main objective of this paper was to develop PTFs for estimating the soil water retention curve (SWRC) in northern China agricultural soils (named PTF‐ANC). A total of 440 soil horizons were collected from the existing literature. A flexible soil‐textural conversion program was first developed to harmonize soil particle‐size data into the United States Department of Agriculture (USDA) classification system. The SWRC parameters of the van Genuchten model were also generated by curve fitting. Then, the PTF‐ANC were developed using artificial neural networks, with soil texture and bulk density being used as input data and with a basic three‐layer back‐propagation neural network. The PTF‐ANC showed an acceptable accuracy when predicting the SWRC, indicating a strong application potential for northern China soils. Comparison of estimates with two widely used external PTFs also showed that these were not suitable for characterizing the SWRC of northern China agricultural soils. This is due to the fact that the main soil textures (silt and silty loam textures) found in northern China soils were misrepresented in those external soil databases. Overall, this paper presented the absolute necessity of developing specific PTFs for northern China agricultural soils.

Determining the Unsaturated Hydraulic Properties of Cohesionless Soils: An Integrated Experimental and Inverse Modeling Approach

Abstract A simple, inexpensive and quick method for measuring the van Genuchten soil water retention curve (SWRC) model parameters for cohesionless soil is presented. The proposed method is an integration of laboratory testing and numerical modeling. The experimental testing consists of multistage bottom-top water imbibition of a dry sand column while recording pore pressure at the inlet. The experiment is then simulated numerically using Hydrus 1D, and the van Genuchten SWRC model parameters are determined through inverse modeling to match the recorded pore pressures. The soil column flushing includes multiple flow stoppages and resumptions, all before permeating one pore volume of water. The flow stoppage results in a time-dependent redistribution of moisture near the waterfront that is controlled by the unsaturated hydraulic properties of the soil and is reflected by changes in the pore pressure measurements. The uniqueness of this method comes from the simple experimental setup and the multistage flushing that can reduce the testing time by a factor of 30 compared with other methods. The results from testing three different sands with different grain size distributions are presented. The new method generated consistent results from multiple specimens tested at a range of flow rates for the three sands. The hypothesis behind moisture redistribution during flow stoppage was confirmed through a combination of experimental and numerical observations. The van Genuchten SWRC parameters obtained from the new method were comparable to those obtained using the conventional hanging column test for Sands B and C and available data in the literature. Sand A could not be tested using the hanging column test because of its large particle size, which demonstrates the wide range of soils that can be tested using the new proposed method.

Splintex 2.0: A physically-based model to estimate water retention and hydraulic conductivity parameters from soil physical data

Soil water retention curve (SWRC) and hydraulic conductivity curve (SHCC) are functions that contribute to the understanding and modeling of hydraulic processes in the vadose zone of the soil. However, their measurement is often difficult and expensive becoming impractical the large-scale monitoring. Pedotransfer functions (PTFs) are, therefore, an alternative to estimate SWRC and SHCC data. Most PTFs are usually calibrated with data from local soils and may be uncertain when applied to soils with different morphological properties. On the other hand, PTFs with a physico-empirical basis have as advantage their wide application. Splintex 1.0 is a physico-empirical model developed in BASIC language that is based on the particle size distribution and other basic soil information. This model estimates the parameters of the van Genuchten-Mualem equation that compose the SWRC without requiring prior calibration and the saturated hydraulic conductivity (Ks) using a texture-PTF. A second version with a user-friendly computational interface is presented to improve the estimates of the SWRC parameters and to introduce the estimation of the SHCC parameters with different PTFs, which are based on two physically-based models that can be applied universally. Computational procedures and equations of Splintex 2.0 were written in C++ language and the performance of both model versions was tested for different soil texture classes. The performance analysis was carried out using the Pearson correlation coefficient and the mean absolute and root mean square errors. Splintex 2.0 yielded good performance in the quantification of water retention data, showing its application to any soil class. As an advantage, the conductivity data can be estimated without the need of Ks and SWRC parameters.

Soil physical and hydraulic properties in the Donato stream basin, RS, Brazil. Part 2: Geostatistical simulation

ABSTRACT Geostatistical simulation has been the most promising and used technique for the analysis of uncertainties of soil physical and hydraulic properties, with high spatial heterogeneity. This study carried out a stochastic analysis of saturated hydraulic conductivity (Ksat) and soil water retention curve parameters in the Donato stream basin, located in the municipality of Pejuçara, in the state of Rio Grande do Sul, Brazil, with geographic coordinates between 28º 25’ 34” S and 53º 40’ 30” W, and 28º 24’ 50” S and 53º 41’ 30” W, 590 m of altitude. Soil samples were collected during the period from August to November of 2012. Sequential Gaussian simulation technique was used to generate 100 random fields of each variable. The results showed great uncertainties for Ksat and the parameter α of the soil water retention curve. The uncertainties between the percentiles 5 and 95% for Ksat indicated values from 24 to 44 cm d-1, and for the parameter α, the uncertainties could be estimated from 0.622 to 1.122 cm-1.

Evaluating pedotransfer functions of the Splintex model

The soil water retention curve (SWRC) is an essential hydraulic function for the understanding and modelling of soil hydraulic processes. Its direct determination is time consuming and sometimes expensive because it requires extensive sampling, especially when spatial and temporal variation of soil hydraulic properties are an issue. The use of pedotransfer functions (PTFs) is a viable alternative to predict the parameters of SWRC from more easily determined soil attributes. Splintex is a physically based engineering model containing two PTFs to estimate SWRC parameters and saturated hydraulic conductivity, but its performance and functionality have not yet been fully evaluated and disseminated for soil science. We examined the functionality of the PTFs available in Splintex to estimate parameters of the Van Genuchten–Mualem (VGM) SWRC equation with a laboratory‐measured dataset containing information on particle size, bulk and particle density, saturated water content and parameters of the SWRCs. In addition, we tested the performance of both PTFs for deriving some soil physical–structural variables calculated from estimated SWRC parameters. Compared with VGM parameters fitted to the laboratory dataset, the model performed well. Its predictive performance for soil air capacity, relative field capacity and soil physical–structural quality indices was also evaluated. The performance of Splintex for estimating the VGM parameters depended on the combined effect of all input variables rather than on isolated correlations between an input variable and a model parameter.Highlights Splintex provides two PTFs to estimate the Van Genuchten–Mualem parameters of the SWRC. In addition to PTF1 input, PTF2 needs an additional soil water content–retention observation. Performance of Splintex‐PTF1 against measured data and ‐PTF2 prediction is presented. PTF2 provided better results than PTF1 for estimating SPQ indices.

Influence of soil hydraulic variability on soil moisture simulations and irrigation scheduling in a maize field

Hydrological models play a crucial role for their ability to simulate water movement from soil surface to groundwater and to predict onset of stress conditions within agricultural fields. However, optimal use of mathematical models requires intensive, time consuming and expensive collection of soil related parameters. Typically soils to be characterized exhibit large variations in space and time as well during the cropping cycle, due to biological processes and agricultural management practices: tillage, irrigation, fertilization and harvest. This paper investigates the variability of soil hydraulic properties over a cropping cycle between April and September 2015, within a surface irrigated maize field (6 ha) located in northern Italy.To this aim, undisturbed and disturbed soil samples were collected from different locations within the study area and at different depths, during three measuring campaigns, at the beginning, in the middle of the cropping season and after the harvest. For each soil sample, several parameters were monitored: organic matter and bulk density together with soil hydraulic parameters. Soil parameters of Soil water retention curve parameters were measured following the evaporation method, while the saturated hydraulic conductivity was determined in the laboratory using the well-known falling head method. Results show that soil properties, mainly the saturated hydraulic conductivity, are subjected to significant variations. The variability of these parameters was taken into consideration when simulating soil moisture using FEST-WB model. An improvement in soil water content simulations was observed as compared to field measurements with implications on prediction of water stress conditions that is fundamental for irrigation scheduling.

Effects of tillage on the soil water retention curve during a fallow period of a semiarid dryland

Tillage practices have a significant influence on the soil hydro-physical properties. The objective of this work was to evaluate the effect of tillage on the α (a scaling factor) and n (a pore size distribution parameter) van Genuchten soil water retention curve parameters during an 18-month long fallow period in a semiarid dryland. Three different tillage systems employed during 23 years of trials were compared: conventional (CT), reduced (RT) and no-tillage (NT). Measurements of soil bulk density (ρb) and the soil water retention curve θ(ψ) were performed at 0–10, 10–20 and 20–30cm soil depths. The θ(ψ) was determined with the Time Domain Reflectometry (TDR)-pressure cells at the following pressure heads: 0.5, 1.5, 3, 10, 50, 100, 500 and 1500kPa. From these data, α, n and the SDexter index were evaluated. The 0–40cm depth soil volumetric water content, θ, was also measured in the field using the TDR technique. Compared with CT and RT, NT had the highest θ values during all the fallow period. No significant influence of soil depth on θ(ψ) was observed in all tillage treatments at each sampling date. Although under consolidated soil conditions no significant differences in ρb and the water content at saturation (θs) were observed among tillage treatments, NT had the highest and lowest values of ρb and θs, respectively. The loosening of soil due to tillage practices in CT and RT significantly decreased ρb and increased θ at the wet-end section of θ(ψ). Post-tillage rainfall resulted in significant decreases in θs, α and the maximum value of the pore size distribution (PSDmax). The different soil structure created by mouldboard ploughing (CT) and chiselling (RT) explained the higher PSDmax under RT than CT. The most important changes in θ(ψ) followed the first copious effective rainfall events (>10mm) after tillage. These facts enabled the soil to recover the pre-tillage water retention curve shapes and the van Genuchten parameters pre-tillage values. Effective rainfall events in the late fallow had a minor effect on the water retention curve. Although tillage tended to increase n, this change was not significant. The SDexter index, which was also affected by tillage, was greater than 0.035 during all the fallow period, indicating good soil physical quality.

Deforestation effects on soil quality and water retention curve parameters in eastern Ardabil, Iran

The land use change from natural to managed ecosystems causes serious soil degradation. The main objective of this research was to assess deforestation effects on soil physical quality attributes and soil water retention curve (SWRC) parameters in the Fandoghlou region of Ardabil province, Iran. Totally 36 surface and subsurface soil samples were taken and soil water contents measured at 13 suctions. Alfa (α) and n parameters in van Genuchten (1980) model were estimated by fitting SWRC data by using RETC software. The slope of SWRC at inflection point (SP) was calculated by Dexter (2004) equation. The results indicated that with changing land use from forest (F) to range land (R) and cultivated land (C), and also with increasing soil depth from 0–25 to 75–100 cm in each land use, organic carbon, micropores, saturated and available water contents decreased and macropores and bulk density increased significantly (P < 0.05). The position of SWRC shape in F was higher than R and C lands at all soil depths. Changing F to R and C lands and also increasing soil depth in each land use significantly (P < 0.05) increased α and decreased n and SP. The average values of SP were obtained 0.093, 0.051 and 0.031 for F, R and C, respectively. As a result, deforestation reduced soil physical quality by affecting SWRC parameters.

Comparison Of Selected Pedotransfer Functions For The Determination Of Soil Water Retention Curves

Abstract Soil water retention curves were measured using a sandbox and the pressure plate extractor method on undisturbed soil samples from the Borská Lowland. The basic soil properties (e.g. soil texture, dry bulk density) of the samples were determined. The soil water retention curve was described using the van Genuchten model (Van Genuchten, 1980). The parameters of the model were obtained using the RETC program (Van Genuchten et al., 1991). For the determination of the soil water retention curve parameters, two pedotransfer functions (PTF) were also used that were derived for this area by Skalová (2003) and the Rosetta computer program (Schaap et al., 2001). The performance of the PTFs was characterized using the mean difference and root mean square error.

Hysteresis and Uncertainty in Soil Water-Retention Curve Parameters

AbstractAccurate estimates of soil hydraulic parameters representing wetting and drying paths are required for predicting hydraulic and mechanical responses in a large number of applications. A comprehensive suite of laboratory experiments was conducted to measure hysteretic soil-water characteristic curves (SWCCs) representing a wide range of soil types. Results were used to quantitatively assess differences and uncertainty in three simplifications frequently adopted to estimate wetting-path SWCC parameters from more easily measured drying curves. They are the following: (1) αw=2αd, (2) nw=nd, and (3) θsw=θsd, where α, n, and θs are fitting parameters entering van Genuchten’s commonly adopted SWCC model, and the superscripts w and d indicate wetting and drying paths, respectively. The average ratio αw/αd for the data set was 2.24±1.25. Nominally cohesive soils had a lower αw/αd ratio (1.73±0.94) than nominally cohesionless soils (3.14±1.27). The average nw/nd ratio was 1.01±0.11 with no significant depen...

Aerodynamic method for obtaining the soil water retention curve

A new method for the rapid plotting of the soil water retention curve (SWRC) has been proposed that considers the soil water as an environment limited by the soil solid phase on one side and by the soil air on the other side. Both contact surfaces have surface energies, which play the main role in water retention. The use of an idealized soil model with consideration for the nonequilibrium thermodynamic laws and the aerodynamic similarity principles allows us to estimate the volumetric specific surface areas of soils and, using the proposed pedotransfer function (PTF), to plot the SWRC. The volumetric specific surface area of the solid phase, the porosity, and the specific free surface energy at the water-air interface are used as the SWRC parameters. Devices for measuring the parameters are briefly described. The differences between the proposed PTF and the experimental data have been analyzed using the statistical processing of the data.

Simulation of water permeability processes in chernozems of the Kamennaya Steppe

The physical and hydrophysical properties of ordinary chernozems from the Kamennaya Steppe were studied for the experimental support of a soil water infiltration model. Increased fissuring and density of the plow horizon were noted because of the dry weather conditions, which caused high infiltration values. The soil water retention curve parameters were calculated from the experimentally determined particle-size distribution, the bulk density of the soil, the solid phase density, the organic matter content, and the physicomechanical and soil-hydrological constants using the known pedotransfer functions and the Voronin secant method. A model experiment with different input parameters was performed. It was shown that the best experimental support of the model included parameters calculated by the Voronin method with the following approximation by the van Genuchten function.