Determination Of Soil Water Retention Curve Research Articles

Performance of the Tensiometer Method for the Determination of Soil-Water Retention Curves in Various Soils

Abstract The soil-water retention curve (SWRC) describes the relationship between the soil matric suction and the water content of an unsaturated soil. It is an essential tool in geotechnical engineering and agriculture and is, for example, used in the analysis of unsaturated soil conditions such as those found in tailings dams and in analyzing the water retention capacity of agricultural land. Conventional methods used to obtain the SWRC are laborious and often rely on empirically derived equations to describe the curve. These test procedures can take weeks to complete and usually rely on indirect methods of measuring suction. Recent advances in the development of affordable high-capacity tensiometers (HCTs), the only devices capable of producing a direct and continuous measurement of high matric suctions, enable the introduction of the tensiometer method for the rapid determination of continuous SWRCs. The method requires an HCT, a digital laboratory balance, and a means of sample volume measurement if volume changes are relevant. The method involves continuously monitoring the mass and matric suctions generated in a naturally desaturating soil sample. The method has thus far seen limited implementation owing to the need for measuring specimen volume change to describe the hydraulic and volumetric behavior fully. The performance of the tensiometer method was investigated by determining SWRCs of five different soil types and then comparing them to the SWRCs determined from the filter paper method. A novel method, based on photogrammetry, was adopted for volume change measurement to produce SWRCs for soils that undergo shrinkage during drying. Excellent agreement between the methods was found for both the nonplastic soils and plastic soils tested.

A simplified directly determination of soil-water retention curve from pore size distribution

Numbers fitting-curve equations have been proposed to predict soil-water retention curve (SWRC) whose parameters have no definitude physical meaning. And these methods with precondition of measuring SWRC data is time-consuming. A simplified directly method to estimate SWRC without parameters obtained by fitting-curve is proposed. Firstly, the total SWRC can be discretized into linear segments respectively. Every segment can be represented by linear formulation and every turning point can be determined by the pore-size distribution (PSD) of Mercury Intrusion Porosimetry (MIP) tests. The pore diameters governing the air-entry condition (AEC) and residual condition (RC) can be determined by the PSDs of MIP test. The PSD changes significantly during drying in SWR test, so the determination of AEC and RC should use the PSD under corresponding suction conditions. Every parameter in proposed equations can be determined directly by PSD without curve-fitting procedure and has definitude physical meaning. The proposed equations give a good estimation of both unimodal and bimodal SWRCs.

Determination of soil-water retention curve: an artificial intelligence-based approach

Soil Water Retention Curve (SWRC) is a fundamental relationship in unsaturated soil mechanics, knowledge of which is essential for determining major mechanical and hydraulic properties of unsaturated soils. There are several empirical, semi-empirical and physically-based models which have been proposed to date for estimating SWRC. While the physically-based models which employ the basic soil characteristics such as grain-size and pore-size distributions are regarded superior to purely empirical models, their Achilles’ heel is the several simplifying assumptions based on which these models are constructed, thereby, restricting their applications and influencing their accuracy. Given the complexity of the soil porous structure, one may resort to the new inference techniques rather than mechanistic modelling to find the relationship among soil physical characteristics and the retention properties. Therefore, an alternative approach to purely empirical relationships as well as physically-based and conceptual models for determining SWRC is the use of Artificial Intelligence (AI) based techniques to acquire a relationship for SWRC based on the soil basic properties, especially grain size distribution and porosity. Among AI-based methods, Multi-Gene Genetic Programming (MGGP), often used to establish a close form equation for a complex physical system, offers a suitable alternative to the current approaches. In this study, a database compromising of 437 soils (containing various soil types, namely, sand, clay, silt, loam, silt loam, clay loam, sandy loam, sandy clay loam, silty clay loam, silty clay, and loamy sand soils) was used along with MGGP to establish a relationship among suction, saturation, porosity and grain size distribution. The proposed equation had a reasonable agreement with the experimental data compared to the other grain-based and physically-based models.

Determination of soil-water retention curve from a transient air-water two-phase outflow experiment

Knowledge of soil-water retention curve (SWRC) is essential in modeling water and air movement in soils. A new method based on air-water two-phase flow inverse solution was proposed to rapidly determine the SWRC from a transient outflow experiment. The experiment was designed to produce coupled air and water flow in soil pores, and the outflow evolution was measured during the transient processes. Air-water two-phase flow simulations combined with grid search parameter estimation algorithm were developed to determine the optimal parameters in the van Genuchten model by minimizing the difference between predicted and measured outflow data. The proposed method was validated against the transient outflow experiment and a multistep outflow test reported in the literature. The results showed that the cumulative outflow predicted from the optimal parameters matched well with the measured data. The good agreements concluded that the proposed method was reliable and feasible to determine the SWRC for unsaturated soils.

A new procedure for the determination of soil-water retention curves by continuous drying using high-suction tensiometers

Soil-water retention curves (SWRCs) can be determined using high-suction tensiometers (HSTs) following two different procedures that involve either continuous or discrete measurement of suction. In the former case, suction measurements are taken while the sample is permanently exposed to the atmosphere and the soil is continuously drying. In the latter case, the drying or wetting process is halted at different stages to ensure equalization within the sample before measuring suction. Continuous drying has the advantage of being faster; however, it has the disadvantage that the accuracy of mass measurements (necessary for the determination of water content) is affected by the weight and stiffness of the cable connecting the HST to the logger. To overcome this problem, an alternative continuous drying procedure is presented in this paper in which two separate but nominally identical samples are used to obtain a single SWRC; one sample is used for the mass measurements, while a second sample is used for suction measurements. It is demonstrated that the new continuous drying procedure gives SWRCs that are similar to those obtained by discrete drying.