Soil-water Characteristic Curve Data Research Articles

Models for Considering the Thermo-Hydro-Mechanical-Chemo Effects on Soil–Water Characteristic Curves

The soil–water characteristic curve (SWCC) is widely used as a tool in geotechnical, geo-environmental, hydrology, and soil science fields for predicting and interpreting hydro-mechanical behaviors of unsaturated soils. Several previous studies focused on investigating the influence of initial water content, stress history, temperature, and salt content on the SWCC behavior. However, there is still limited understanding to be gained from the literature on how we can systematically incorporate the influence of complex thermo-hydro-mechanical-chemo (THMC) effects into interpreting and predicting the behavior of unsaturated soils. To address that knowledge gap, in this study, the coupled influence of temperature, initial stress state, initial density, soil structure, and chemical solution effects was modeled using established SWCC equations from the literature. The methodology for incorporating the coupled effects of these influential factors is presented herein. Furthermore, we evaluated the SWCC models proposed in this study, enabling us to provide a comprehensive discussion of their strengths and limitations, using the published SWCC data from the literature. The developments outlined in this paper contribute toward facilitating a rigorous approach for analyzing the THMC behaviors of unsaturated soils.

Use of osmotic tensiometers in the determination of soil-water characteristic curves

Soil-water characteristic curve (SWCC) correlates the water content of a soil to its soil suction, which is a very important property of unsaturated soils. Osmotic tensiometers (OTs) have shown their capability in high soil suction measurement. This study tried to use OT combined with a pressure plate and WP4C dewpoint potentiometer to determine the SWCC of a residual soil. Three OTs with different measuring ranges (900 kPa, 1200 kPa, 2300 kPa) were prepared for soil suction measurement. The temperature effect on the pressure variations of OTs was illustrated based on Flory-Huggins polymer theories and an appropriate calibration equation was proposed to eliminate the temperature effect on the accuracy of soil suction measurement using OT. The OT showed a fast response in soil suction measurement and the equilibrium can be established in 10–15 min during SWCC measurement. Comparison of the SWCC data obtained from the pressure plate, OT, and WP4C dewpoint potentiometer proves that the OT had good performance in the determination of SWCC, especially for the transition zone (i.e., 10–1500 kPa suction range), by providing more data points to define the SWCC in a shorter period. The results show that the usage of OT will shorten the time required for the determination of SWCC and could be considered as a new and reliable technique in SWCC measurement.

Prediction of soil water characteristic curves based on low suction section and inflection point

Abstract Given the cumbersome determination method of the Soil Water Characteristic Curve (SWCC), the collapsible loess (silty clay loam) in Lanzhou was taken as the research object to explore a symmetrical prediction method for SWCC in a low suction section on the inflection point, and to determine the optimal suction section and the inflection point. The results showed that in the range of 0–7,000 cm suction, the spatial variation coefficient (CV) of soil saturation of each bulk density increased with the increase of suction. Soil saturation showed weak spatial variability when suction <800 cm, and moderate spatial variability when suction ≥800 cm. Using a bulk density of 1.58 g/cm3 as an example, the SWCC determined by the symmetry of the bending point was compared with the measured data of 0–300, 0–500, 0–800 and 0–1,000 cm suction sections. It was found that the measured soil saturation of SWCC determined by the data for the 0–800 cm suction section was the most consistent with the predicted value. The measured and predicted saturation points of the SWCC were most consistent with suction segments of 0–800 cm. SWCC data of different textures and bulk density were used to verify the prediction method at low suction section and an inflection point of 0–800 cm. It was found that the average absolute error and root mean square error of statistical indicators were close to 0, and the correlation coefficient was greater than 0.9915. The actual and predicted values of each soil parameter were linearly correlated. This method of predicting SWCCs with low suction and inflection points ensures both a high degree of curve fitting and the accuracy of characteristic soil parameters, providing a simple method for the prediction of SWCCs and guidance for managing soil water in loessial areas.

Effect of Cr on the performance of Fredlund and Xing (1994)'s equation in best fitting soil-water characteristic curve data

Fredlund and Xing (1994)'s equation is one of most popular equations in best fitting the soil-water characteristic curve (SWCC) data. It is commonly considered that the parameters of the equation such as a, n and m are the fitting parameters and Cr is an input value, which is commonly recommended that Cr to be1500 kPa or 3000 kPa. Based on the analysis in this paper, it is observed that setting Cr to be equal to 1500 kPa or 3000 kPa may downgrade the performance of Fredlund and Xing (1994)'s equation in best fitting the SWCC data of soils with a high air-entry value (AEV). It is recommended the air-entry value (AEV) of the soil is roughly estimated before the best fitting process and set Cr to be 100 times of the estimated AEV for the best regression analysis.

A new framework to determine general multimodal soil water characteristic curves

A soil water characteristic curve (SWCC) model named as discrete-continuous multimodal van Genuchten model with a convenient parameter calibration method is developed to describe the relationship between soil suction and the water content of a soil with complex pore structure. The modality number N of the SWCC in the proposed model can be any positive integer (the so-called multimodal or N-modal SWCC). A unique set of parameters is determined by combining curve fitting and a graphical method based on the shape features of the SWCC in the log s–log Se plane. In addition, a modality number reduction method is proposed to minimize the number of parameters and simplify the form of SWCC function. The proposed model is validated using a set of bimodal and trimodal SWCC measurements from different soils, which yield a strong consistency between the fitted curves and the measured SWCC data. The uniqueness in the set of parameters provides the possibility to further improve the proposed model by correlating the parameters to soil properties and state parameters.

Estimating soil-water characteristic curve based on soil type and best-fitting regressions derived from a simplified method using Aburra Valley dataset

In unsaturated soil mechanics, many attempts have been made to estimate the SWCC based on soil texture and grain-size distribution. This paper proposes a simplified method to estimate the soil-water characteristic curve (SWCC) for both coarse and fine-grained soils using SWCC data and machine learning computer code in the Aburra Valley. Fredlund and Xing parameters has been used to estimate the SWCC correlations. Soil samples collected from field survey were subjected to laboratory testing, SWCCs were estimated using filter paper method. Each SWCC data set from Aburra Valley was fitted with Fredlund and Xing curve using multiple regression analysis, correlations were derived for those four parameters based on predictors derived from machine learning. The proposed method gives a good estimation and low residual errors of the SWCC.

Soil-water characteristic curves of bentonites in isochoric conditions during wetting: measurement and prediction

The determination of the soil-water characteristic curve (SWCC) of compacted bentonites in the isochoric condition is a prerequisite for unsaturated flow simulations in several geoenvironmental applications. The SWCC data are, however, not readily available for many compacted bentonites over a wide suction range due to difficulties associated with the testing. In this work, wetting SWCCs of four Indian bentonites of different plasticity were established experimentally at compaction dry densities of 1.4, 1.6, and 1.8 Mg/m3 in isochoric conditions using two independent laboratory techniques in different suction ranges. The modified Kovács (MK) model was extended to simulate the SWCC data of the Indian bentonites. Empirical relationships between MK model parameters and compaction dry density for these bentonites were established. A theoretical procedure for the estimation of SWCCs of the compacted bentonites based on the basic bentonite properties and proposed correlations was proposed and validated on the available wetting SWCC data of compacted GaoMiaoZi (GMZ), MX80, and FEBEX bentonites from the literature studies. The proposed method predicts the wetting SWCCs of compacted powder bentonites, in volume-restrained condition, from the basic properties satisfactorily. The proposed model is an approximate method for predicting the SWCCs of bentonites in the absence of measured data and in understanding the influence of dry density and plasticity.

Irrigation Scheduling Based on Wireless Sensors Output and Soil-Water Characteristic Curve in Two Soils.

Data-driven irrigation planning can optimize crop yield and reduce adverse impacts on surface and ground water quality. We evaluated an irrigation scheduling strategy based on soil matric potentials recorded by wireless Watermark (WM) sensors installed in sandy loam and clay loam soils and soil-water characteristic curve data. Five wireless WM nodes (IRROmesh) were installed at each location, where each node consisted of three WM sensors that were installed at 15, 30, and 60 cm depths in the crop rows. Soil moisture contents, at field capacity and permanent wilting points, were determined from soil-water characteristic curves and were approximately 23% and 11% for a sandy loam, and 35% and 17% for a clay loam, respectively. The field capacity level which occurs shortly after an irrigation event was considered the upper point of soil moisture content, and the lower point was the maximum soil water depletion level at 50% of plant available water capacity in the root zone, depending on crop type, root depth, growth stage and soil type. The lower thresholds of soil moisture content to trigger an irrigation event were 17% and 26% in the sandy loam and clay loam soils, respectively. The corresponding soil water potential readings from the WM sensors to initiate irrigation events were approximately 60 kPa and 105 kPa for sandy loam, and clay loam soils, respectively. Watermark sensors can be successfully used for irrigation scheduling by simply setting two levels of moisture content using soil-water characteristic curve data. Further, the wireless system can help farmers and irrigators monitor real-time moisture content in the soil root zone of their crops and determine irrigation scheduling remotely without time consuming, manual data logging and frequent visits to the field.

Analysis of Partially Saturated Clayey Slopes Using Finite Element Method

According to Bishop's equation of effective stress for partially saturated soils, matric suction can increase the effective stress that is subjected to negative pore water pressure. The shear strength of soil is controlled by the effective stress and, hence, the increase in shear strength that is due to soil suction can affect slope stability. This paper presents slope stability analysis that includes the effects of soil suction for partially saturated soils under different groundwater conditions.Using pore/fluid stress elements and appropriate soil water characteristic curve data for the soil properties, the soil was modeled by considering groundwater table fluctuations and negative pore pressure in partially saturated zones. This paper presents the outputs that were supported by the pore/fluid stress elements, which include the void ratio, pore pressure, equivalent plastic deformation, strength reduction factors, and vertical effective stress, and discusses the contribution of negative pore water pressure in the slope stability analysis and/or for reference in slope remediation design.

Comparison of Soil–Water Characteristic Curves in One-Dimensional and Isotropic Stress Conditions

Understanding unsaturated soil behavior is key to the design of foundations and embankment structures. Geotechnical engineers have applied net normal stress and matric suction to these engineering problems. Water retention activity in soils is used to predict seepage problems and stability of slope failures. Soil–Water Characteristic Curve (SWCC) tests contribute largely to matric suction interpretation. Determination of SWCCs in the laboratory is usually done using a pressure plate apparatus where vertical or confining stress cannot be applied. Mathematical models of SWCC though commonly accepted in geotechnical engineering practices, do not take into consideration stress conditions such as the difference between a one-dimensional condition and isotropic confining conditions. This study conducted SWCC tests of a silt soil under one-dimensional and isotropic confining stress conditions and focused on the differences between these types of SWCC data sets. Vertical and isotropic confining stresses ranging from 100 to 600 kPa were applied under both stress conditions. SWCCs appears to be affected by the influence of different stress conditions. Lateral pressure and confinement on an isotropic compression condition caused the soil specimen to become dense in void structure and consequently, soil moisture flow movement decreased. This probably induced high retention activities in the silt soil specimen. The study further suggests that the current SWCC models require further development to take into consideration the effect of different stress conditions.

Comparison of Soil–Water Characteristic Curves from Conventional Testing and Combination of Small-Scale Centrifuge and Dew Point Methods

Soil–water characteristic curve (SWCC) is an important unsaturated soil property relating the water content of a soil to soil suction and it is conventionally measured using Tempe cell, pressure plate and salt solution methods. However, these tests are tedious and time consuming. The SWCC measurements using fast and efficient methods are required for engineering designs such as excavation, slope protection, retaining wall and landfill cover designs. This paper describes the testing procedures and apparatuses associated with rapid measurements of a complete SWCC of a residual soil as obtained from combined measurements using a small-scale centrifuge and dew point methods. The SWCC test results obtained using these alternative methods were compared with the SWCC data from Tempe cell, pressure plate and salt solution methods. Shrinkage tests were carried out in this study to incorporate the volume change of soil into SWCC. The experimental data from all SWCC tests were evaluated using first order analysis with 95% confidence interval for determination of upper and lower bounds of SWCC. The analysis results showed that the SWCC data obtained from tests using small-scale centrifuge and dew point methods were in good agreement with those obtained from Tempe cell, pressure plate and salt solution methods. This indicates that the combination of small-scale centrifuge and dew point methods can be used to generate a complete curve of SWCC for the residual soil. In addition, the time required to perform SWCC tests using the alternative methods is shorter than the SWCC tests using the conventional methods.

Uncertainty of Soil Water Characteristic Curve Measurements Using an Automated Evaporation Technique

Core Ideas Replicate‐specimen measurement of SWCCs was performed with an automated technique. Inter‐specimen uncertainty for SWCC parameters was quantified. A comparison of automated evaporation technique vs the standard hanging column is presented. Soil water characteristic curve (SWCC) measurements are used to estimate hydrologic parameters for a variety of engineering and agricultural applications. The SWCC parameterization is often based on a single measurement or with little or no consideration and/or quantification of the uncertainty in collection of SWCC data. Uncertainty in the SWCC data stems from random variability in pore geometry associated with irregular granular media. Additionally, a substantial opportunity exists in SWCC measurements for systematic or experimental errors that can increase uncertainty. This study utilized an evaporation method for measuring 10 SWCCs for each of four different test soils. One low‐plasticity and three high‐plasticity silty sand soils were sampled from the Sagehen Creek Experimental Watershed in Sierra County, California. The uncertainty in the SWCC measurements was quantified by the distribution and variability of van Genuchten parameters evaluated via nonlinear regressions on each set of SWCC data. Despite a careful, replicated specimen preparation, variability in the measured SWCC data was indicated by variability of estimates of van Genuchten's fitting parameters α and n and residual volumetric water content θr, suggesting that packing specimens to identical dry densities does not produce identical SWCC measurements for a single soil type. For the soils tested in this study, replicate specimen testing resulted in uncertainty in α between ×/1.2 and ×/1.5 the geometric mean estimate for α, between ±2 and ±6% of the mean estimate for n, and between ±2 and ±6% for θr. Additional testing is required before applying these uncertainties generally to soils of different textural classifications.

Effects of residual suction and residual water content on the estimation of permeability function

Soil-water characteristic curve (SWCC), which defines the relationship between water amount in the soil and matric suction, contains key information for the application of unsaturated soil mechanics principles to engineering practice. Best fit equations are commonly used for representation of the SWCC for unsaturated soils. Normally, these best fit equations are mathematically continuous and governed by a few fitting parameters. Either volumetric water content, θw or normalized volumetric water content, Θ, is adopted in the different best fit equations. If θw is used to establish SWCC, the parameter related to residual suction, Cr needs to be defined prior to fitting process of SWCC data. On the other hand, if Θ is used to develop SWCC, the residual volumetric water content, θr, needs to be defined prior to fitting process of SWCC data. Results of analyses in this study indicate that the performance of the best fit equation is not affected by the value of Cr, but it is significantly affected by the value of θr. As a result, the performance on the estimation of the permeability function is also affected by the value of θr. Different types of soils are used to investigate the effect of Cr and θr on the performance of the best fit equation and the estimation of the permeability function.

Predicting available water of soil from particle-size distribution and bulk density in an oasis–desert transect in northwestern China

Summary A detailed understanding of soil hydraulic properties, particularly the available water content of soil, (AW, cm3 cm−3), is required for optimal water management. Direct measurement of soil hydraulic properties is impractical for large scale application, but routinely available soil particle-size distribution (PSD) and bulk density can be used as proxies to develop various prediction functions. In this study, we compared the performance of the Arya and Paris (AP) model, Mohammadi and Vanclooster (MV) model, Arya and Heitman (AH) model, and Rosetta program in predicting the soil water characteristic curve (SWCC) at 34 points with experimental SWCC data in an oasis–desert transect (20 × 5 km) in the middle reaches of the Heihe River basin, northwestern China. The idea of the three models emerges from the similarity of the shapes of the PSD and SWCC. The AP model, MV model, and Rosetta program performed better in predicting the SWCC than the AH model. The AW determined from the SWCCs predicted by the MV model agreed better with the experimental values than those derived from the AP model and Rosetta program. The fine-textured soils were characterized by higher AW values, while the sandy soils had lower AW values. The MV model has the advantages of having robust physical basis, being independent of database-related parameters, and involving subclasses of texture data. These features make it promising in predicting soil water retention at regional scales, serving for the application of hydrological models and the optimization of soil water management.

New approach to improve soil-water characteristic curve to reduce variation in estimation of unsaturated permeability function

The unsaturated permeability function is often estimated from the soil-water characteristic curve (SWCC) of a soil. A complete SWCC measurement can improve the estimation of the unsaturated permeability function. In most laboratories, the SWCC can be measured up to a suction of 100 kPa using a Tempe cell. However, complete measurement of the SWCC is an expensive and time-consuming task. Therefore, this paper presents a new approach to estimate SWCC data points beyond 100 kPa suction to complement the SWCC measured up to a suction of 100 kPa. The new SWCC is then used to estimate the unsaturated permeability function. The proposed approach uses knowledge of the grain-size distribution curve and measured SWCC data at 100 kPa suction to estimate the SWCC data points beyond 100 kPa suction. To verify the proposed procedure, SWCC tests were conducted over a wide range of suctions for coarse kaolin and a triaxial permeameter system was used to directly measure unsaturated permeability of the coarse kaolin. The proposed procedure is found to reduce the variation between unsaturated permeability functions estimated by various estimation models.

Influence of Mineral Montmorillonite on Soil Suction Modeling Parameters of Natural Expansive Clays

Expansive soils exhibit swell/shrink behavior with fluctuating moisture conditions arising from seasonal changes. Pore-water interactions occurring at the micro scale level of the soil specimen during swelling are mainly caused due to adsorptive forces and diffuse double layer charges on the clay particles. This chemical behavior is mainly attributed due to the presence of clay minerals such as Montmorillonite and is hypothesized that there is a strong correlation between soil water–suction relationship and percent clay mineral Montmorillonite. In the present research, an attempt is made to establish this relationship by studying natural compacted expansive clays and studying their respective soil water characteristic curve (SWCC). Four high plasticity expansive clays are selected and studied for mineralogy, expansive behavior and unsaturated properties. Soil water characteristic curves of these soils are determined from pressure cell technique and filter paper method. SWCC data was fitted against Van Genuchten and Fredlund and Xing models and the obtained model parameters are compared with the percent clay mineral in the soil. Test results from this research reemphasized the fact that that clayey soils with higher percentages of Montmorillonite content exhibited higher swelling behavior. Test results also showed that there is inconsistency with pore distribution SWCC modeling parameters with varying mineral content. Addressing the relationship between the percent Montmorillonite in a soil to SWCC modeling parameters is the main outcome.

Effects of soil–water characteristic curve and relative permeability equations on estimation of unsaturated permeability function

Unsaturated permeability function can be estimated by theoretical models from soil–water characteristic curve (SWCC). To date, there are numerous estimation models that can be used to obtain the unsaturated permeability function from SWCC. However, each model results in a different estimation curve. The reason for this difference is not well understood.In this study, the available SWCC equations and the available relative permeability (kr) equations were combined to form a matrix of unsaturated permeability estimation models. The matrix of unsaturated permeability estimation models was used to study the effect of SWCC equations and relative permeability (kr) equations as controlling factors in the estimation of unsaturated permeability function. The study was conducted using twenty sets of published experimentally measured SWCC and unsaturated permeability data (kw). The effects of the SWCC equations and kr equations on a variation of estimated unsaturated permeability functions are presented in this paper. It was found that the SWCC equation has a more significant effect on the estimation of unsaturated permeability function than that of the kr equation.

Non-Contact Sensing System to Measure Specimen Volume During Shrinkage Test

The shrinkage curve provides information of value for the interpretation of soil-water characteristic curve data. However, there is need for an accurate and precise volume measurement technique during the shrinkage test. This paper presented an inexpensive automated digital image processing technique, which allowed accurate and precise measurements of the soil specimen volume. The volume was computed by accurately measuring the radius and height over the entire lateral surface of specimen. The proposed volume measurement technique involved projecting a structured light laser on the soil specimen in order to provide the reference points for measurements. A 360° view of the specimen was then captured using a camera. High resolution images were then processed using functions developed within MATLAB. The computations also allowed the reconstruction of a 3D mesh model of the specimen. A validation test on a dummy object showed that the error in radius and height measurements at more than 75 % measurement points was less than ±0.05 and ±0.07 mm, respectively. A 99 % accuracy was achieved in the volume measurement of the soil specimen.

Effect of range of soil–water characteristic curve measurements on estimation of permeability function

The most commonly used indirect method to determine unsaturated permeability of soil is to estimate the unsaturated permeability function from soil–water characteristic curve and saturated permeability. The suction range that soil–water characteristic curve (SWCC) can be measured in the laboratory depends on the type of equipment used for measurement. As the estimation models use the available measured SWCC data to obtain the unsaturated permeability function, the estimated permeability function can be affected by the number of measured data of SWCC and the suction range over which the SWCC data are measured. Therefore, there is a need to investigate the effect of the range of SWCC measurements on the estimation of unsaturated permeability function. In this study, the effect of the range of SWCC measurements is investigated through different estimation models that are based on four different best-fit soil–water characteristic curve equations and three different relative permeability equations. It was found that the range of SWCC measurements greatly affect the estimated permeability functions. It was also found that the effect of the range of SWCC measurements is more significant than the selected best-fit SWCC equation used.

Soil–Water Characteristic Curve of Gypseous Soil

The soil–water characteristic curve (SWCC), also known as soil–water retention curve, is a key tool in assessing the behavior and properties of unsaturated soil. The SWCC of gypseous soil with 0, 5, 15 and 25 % gypsum content was determined, using tensiometric plate, osmotic membrane and vapour equilibrium techniques, with suction pressures ranging between 10 and 1,000,000 kPa. The effect of two compaction efforts, standard and modified, was examined on the SWCC of soil samples. The water-holding capacity of soil samples increased with increasing gypsum content and applied compaction effort. Mercury porosimetry tests and scanning electron microscope images revealed that compaction and the presence of gypsum increased the number of capillary pores. These changes in the pore size distribution of soil samples induced modifications in the volumetric water content at air-entry value of the tested samples. All experimental SWCC data were fitted using the Fredlund and Xing (Can Geotech J 31(4):521–532, 1994) and Van Genuchten (Soil Sci Soc Am J 44:892–898, 1980) models. Results showed that a high coefficient of determination (R2) can be achieved by using both models to fit the experimental results of gypseous soil SWCC.