Soil hydraulic conductivity function based on specific liquid–vapor interfacial area around the soil particles (original) (raw)
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Geoderma, 2006
Improvement in the prediction of soil hydraulic conductivity function is a major concern in soil physics. Zand-Parsa and Sepaskhah (2004) [Zand-Parsa, Sh., Sepaskhah, A.R., 2004. Soil hydraulic conductivity function based on specific liquidvapour interfacial area around the soil particles. Geoderma 119, 143-157] proposed a new method for the prediction of soil hydraulic conductivity function [K(h) or K(h) (where h and h are soil water pressure head and water content, respectively] based on specific liquid-vapour interfacial area around the soil particles (SLVIA). In the present paper, the SLVIA method was improved as follows: (i) a more straightforward and efficient numerical technique for the prediction of K(h) function was proposed instead of the analytical method in Zand-Parsa and Sepaskhah; (ii) saturated soil hydraulic conductivity (K s) was predicted by assumption of a linear relationship between K(h) and h for very small h ranges near saturated soil water content; (iii) the value of soil tortuosity (ratio of actual path length to the straight path length of flow) factor (Tr) was estimated by using the Newton-Raphson method, by minimizing the difference between predicted and measured saturated soil hydraulic conductivity. The K(h) curve was predicted by soil water characteristic curve and measured saturated soil hydraulic conductivity. Soil water characteristic curve was predicted by the van Genuchten method with four required soil parameters [a, n, residual soil water content (h r), and saturated soil water content (h sat) [van Genuchten, M.Th., 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soil. Soil Sci. Soc. Am. J. 44, 892-898]. A computer program (UNSATK model) written in VISUAL BASIC was used to predict the K(h) or K(h) curve. The utility of the UNSATK model was tested for three soil types (sandy, loamy, and clayey textures) selected from the literature. The uniqueness of model outputs for each selected soil was checked by different input Tr values. Model predictions yielded reasonable agreement with measured soil hydraulic conductivity data and compared favorably with the widely applied Mualem-van Genuchen method.
Predicting unsaturated hydraulic conductivity of soil based on some basic soil properties
Soil and Tillage Research, 2001
Soil hydraulic conductivity is a crucial parameter in modeling¯ow process in soils and deciding water management. In this study, by combining the non-similar media concept (NSMC) to the one-parameter model of Brooks and Corey, a new NSMCbased model for estimating unsaturated hydraulic conductivity of various soils was presented. The main inputs are soil bulk density, particle-size distribution, soil water retention characteristic and saturated hydraulic conductivity of soil. The results indicated that the NSMC-based model could generally more accurately predict unsaturated hydraulic conductivity of soils, as compared to four one-parameter models and van Genuchten±Mualem model. This study, by introducing NSMC, provided a new way to incorporate soil physical heterogeneity into soil hydraulic simulation, and hence NSMC-based approach is expected to improve ef®ciency of the existing models in the simulation of soil water¯ow.
A model for soil relative hydraulic conductivity based on the water retention characteristic curve
Water Resources Research, 2001
A simple model is proposed which predicts the relative unsaturated hydraulic conductivity function of nonswelling soils by using the first two moments of their water retention curve (WRC). The model is based on the statistical approach but uses less restrictive assumptions concerning the pore configuration than Mualem's [1976] model. The result is that the relative hydraulic conductivity (RHC) is a power function of the relative contribution of the pores filled with water. It is shown that the power value is related to the coefficient of variation characterizing the retention curve, expressed in terms of the WRC model ofAssouline et al. [1998]. Therefore a relationship is established between the RHC and the soil structure and texture, as reflected by the measured WRC. The model is calibrated on data from eight soils and tested on data from five soils, representing a wide range of soil textures, from sand to silt. The performances of the model are compared to those resulting from the application of Mualem's [1976] model to the analytical expressions of Brooks and Corey [1964] and Assouline et al. [1998] for the WRC. In most of the cases the proposed model improves the fit of the predicted RHC to the measured data, although its performance in the case of loam soils seems to be weak.
A Model to Predict the Unsaturated Hydraulic Conductivity from Basic Soil Properties
The relative hydraulic conductivity kr of unsaturated soils is typically obtained from their water retention curve (WRC). In this paper, the modified Kovács (MK) model developed to predict the WRC is combined with the Mualem model to predict the kr function using basic geotechnical properties of granular soils. The ensuing equations, which have been implemented into MATLAB, have been validated against existing solutions and against testing data. It is shown here that the predictive results show a good agreement with the experimental results obtained from tests performed by the Authors and taken from the literature. The applicability of the proposed approach is briefly discussed. RÉSUMÉ
A closed form equation for predicting the hydraulic conductivity of unsaturated soils
1980
A new and relatively simple equation for the soil-water content-pressure head curve, 8(h), is described in this paper. The particular form of the equation enables one to derive closedform analytical expressions for the relative hydraulic conductivity, K r , when substituted in the predictive conductivity models of N.T. Burdine or Y. Mualem. The resulting expressions for K r (h) contain three independent parameters which may be obtained by fitting the proposed soil-water retention model to experimental data. Results obtained with the closed-form analytical expressions based on the Mualem theory are compared with observed hydraulic conductivity data for five soils with a wide range of hydraulic properties. The unsaturated hydraulic conductivity is predicted well in four out of five cases. It is found that a reasonable description of the soil-water retention curve at low water contents is important for an accurate prediction of the unsaturated hydraulic conductivity.
Determination of Saturated Hydraulic Conductivity of Different Soil Texture Materials
2014
The hydraulic conductivity of the soil is function of soil water pressure, soil water content, and the soil moisture retention. The soil hydraulic properties are needed for understanding water balance, irrigation and transport processes. Hence, saturated hydraulic properties of surface soils influence rainfall and snowmelt into runoff and soil water storage. The hydraulic conductivity for soil material provides the ability to properly design water control structures, earthen storage water facilities and runoff forecasting. Saturated hydraulic conductivity measurement was made on different soil material, having length of soil columns 8.5 cm for constant head permeameter. Three soil columns were filled having different percentages of soil texture; and textural classified of soil sample is sandy loam soil. Porosity is determined by the saturation method for soil sample materials; the porosity is varying from 32 to 40% for sandy loam and about 43% for clay soils. The saturated hydraulic...
Comparison of Six Methods To Determine Unsaturated Soil Hydraulic Conductivity
Soil Science Society of America Journal, 1994
Knowledge of soil hydraulic properties is required for soil-water flow models. Although many studies of individual methods exist, comparisons of methods are uncommon. Therefore, we compared application ranges and results for six laboratory methods for determining hydraulic conductivity or diffusivity on eolian sand, eolian silt loam, marine sandy loam, and fluviatile silt loam. The methods, hot air, sorptivity, crust, drip inflltrometer, Wind's evaporation, and one-step outflow, fall into three groups: (i) those that only yield a conductivity curve; (ii) those that yield a simultaneous estimate of conductivity, diffusivity, water content, and pressure head; and (iii) those that yield a diffusivity curve. Diffusivities were converted to conductivities with a water retention curve. One main difference between the methods was the pressure head-water content range. Despite the large differences between the methods, the results for the first two groups tended to be similar. The results of the third group did not match well with those of the first two. It proved difficult to compare these methods correctly due to hysteresis.
Soil Research, 2013
Unsaturated soil hydraulic conductivity K is a fundamental transfer property of soil but its measurement is costly, difficult, and time-consuming due to its large variations with water content (q) or matric potential (h). Recently, C. Doussan and S. Ruy proposed a method/model using measurements of the electrical conductivity of soil core samples to predict K(h). This method requires the measurement or the setting of a range of matric potentials h in the core samples-a possible lengthy process requiring specialised devices. To avoid h estimation, we propose to simplify that method by introducing the particle-size distribution (PSD) of the soil as a proxy for soil pore diameters and matric potentials, with the Arya and Paris (AP) model. Tests of this simplified model (SM) with laboratory data on a broad range of soils and using the AP model with available, previously defined parameters showed that the accuracy was lower for the SM than for the original model (DR) in predicting K (RMSE of logK = 1.10 for SM v. 0.30 for DR; K in m s -1 ). However, accuracy was increased for SM when considering coarse-and medium-textured soils only (RMSE of logK = 0.61 for SM v. 0.26 for DR). Further tests with 51 soils from the UNSODA database and our own measurements, with estimated electrical properties, confirmed good agreement of the SM for coarse-medium-textured soils (<35-40% clay). For these textures, the SM also performed well compared with the van Genuchten-Mualem model. Error analysis of SM results and fitting of the AP parameter showed that most of the error for fine-textured soils came from poorer adequacy of the AP model's previously defined parameters for defining the water retention curve, whereas this was much less so for coarse-textured soils. The SM, using readily accessible soil data, could be a relatively straightforward way to estimate, in situ or in the laboratory, K(h) for coarse-medium-textured soils. This requires, however, a prior check of the predictive efficacy of the AP model for the specific soil investigated, in particular for fine-textured/structured soils and when using previously defined AP parameters.
Field-Obtained Soil Water Characteristic Curves and Hydraulic Conductivity Functions
Journal of Irrigation and Drainage Engineering, 2018
A compacted clay liner (test pad) was constructed and instrumented with volumetric water content and soil matric potential sensors to determine soil water characteristic curves (SWCC) and hydraulic conductivity (k) functions. Specifically, the compacted clay liner was subjected to an infiltration cycle during a sealed double ring infiltrometer (SDRI) test followed by a drying cycle. After the drying cycle, Shelby tube samples were collected from the compacted clay liner and flexible wall permeability (FWP) tests were conducted on sub-samples to determine the saturated hydraulic conductivity. Moreover, two computer programs (RETC and UNSAT-H) were utilized to model the SWCCs and k-functions of the soil based on obtained measurements including the volumetric water content ( v), the soil matric potential (), and the saturated hudraulic conductivity (k s). Results obtained from the RETC program (θ s , θ r , α, n and k s) were ingested into UNSAT-I would like to express the deepest appreciation to my thesis director, Dr. Richard A. Coffman for giving me the opportunity to conduct this research and guiding me along the way. Without his guidance, mentorship and persistent help this thesis would not have been possible. I would also like to thank my committee members, Dr. Norman D. Dennis and Dr. Michelle Bernhardt for being extraordinary committee members who showed me the road and helped to get me started on the path to this degree. I would also like to thank Cyrus Garner for assisting me to collect and reduce data for the research presented in this document. Also, a special thanks goes out to the students: