Saturated Permeability Coefficient Research Articles

Probabilistic back analysis of reservoir landslide considering hydro-mechanical coupled observations

Precisely assessing statistical parameters to characterize spatial soil variability presents a significant challenge in probabilistic slope stability analysis, primarily due to inherent soil uncertainties and limited field-specific data. Probabilistic back analysis, recognized as an effective and reliable technique, offers a rational method for utilizing observational data to invert parameters. Nevertheless, previous investigations into parameter inversion for slope stability analysis have seldom considered the coupling of hydro-mechanical characteristics in reservoir landslides. This study proposes a novel integrated Bayesian framework to perform back analysis of reservoir landslides, incorporating the spatial variability of hydro-mechanical parameters. Within this framework, a hypoplastic constitutive model is developed to characterize the step-like deformation of the reservoir slope. The posterior knowledge of the saturated permeability coefficient and shear strength parameters is obtained by collecting field monitoring data of the underground water level and ground displacement. The Maliulin landslide, located in the Three Gorges Reservoir area of China, is used as an illustrative example to validate the proposed framework through back analysis of spatially variable soil parameters and probabilistic stability analysis. The results demonstrate that the proposed Bayesian updating framework significantly reduces the uncertainties associated with statistical values of soil parameters, providing more accurate and reasonable updated soil parameters for probabilistic slope stability analysis.

Anti-seepage performance and oxygen barrier performance of the three-layered landfill cover system comprising neutralized slag under extreme climate conditions

For acidic industrial solid wastes, an effective cover system is needed to reduce the rainwater infiltration and oxygen intrusion, thus reducing the generation of acid mine drainage (AMD) from wastes. A three-layered cover using low-permeability neutralized slag (abbreviated as TCNS) at the bottom of the traditional capillary barrier cover is proposed, in line with the novel concept of “waste protecting waste”. This study investigates the anti-seepage performance and oxygen barrier performance of TCNS under extreme climate conditions, through laboratory column test and numerical simulations. The results show that the water content of the neutralized slag (NS) layer remained stable (i.e., changed by less than 0.02) under either extremely wet condition or extremely dry condition. Under extremely wet condition (i.e., heavy rainfall corresponding to a 50-year return period), no water percolation was observed at the cover bottom; under extremely dry conditions, oxygen diffusion was greatly impeded, e.g., after 208 days of column test, the SO42− concentration in the AMD of the exposed (i.e., uncovered) waste rock was 4.6 times higher than that of the waste rock covered by TCNS. Numerical simulations considering two realistic climate conditions (i.e., humid and arid) showed that TCNS were effective in controlling water percolation and oxygen intrusion. The saturated permeability coefficient (ks) and initial saturation degree (Se) of the NS layer have significant effects on the performance of TCNS, i.e., decreasing ks or increasing Se can effectively reduce the water percolation and oxygen flux. In sum, TCNS is an effective barrier for controlling water percolation and oxygen intrusion, even in extreme climate conditions. Consequently, it can effectively minimize AMD leakage and thus reduce geological disasters such as groundwater contamination.

Finite Element Method-Peridynamics Coupled Analysis of Slope Stability Affected by Rainfall Erosion

Rainfall is a pivotal factor resulting in the cause of slope instability. The traditional finite element method often fails to converge when dealing with the strongly nonlinear fluid–solid coupling problems, making it impossible to fully analyze the sliding process under the state of slope instability. Therefore, this paper uses the coupling of peridynamics (PD) and the finite element method (FEM) to propose a data exchange mode between the seepage field and the deformation field. The influencing factors of fine particle erosion during rainfall are further considered. According to the damage mechanism of the slope sliding process to the original structure of the soil, a modified erosion constitutive relationship is proposed, which takes into account the destructive effect of plastic deformation on coarse particles. Then, the influence of rainfall duration, rainfall intensity, erosion, and initial saturated permeability coefficient on slope stability was simulated and analyzed. This paper provides a novel concept for slope stability analysis and safety evaluation under rainfall conditions.

Numerical Simulation of Rainfall-Induced Erosion on Infiltration and Slope Stability

In slopes where a mixture of coarse and fine particles is present, the infiltration of rainfall can cause the migration of fine particles. This migration alters the hydraulic properties of the soil and has implications for slope stability. In this study, the slope under investigation is a tailings dam composed of loosely consolidated soil with a wide particle size distribution. Due to rainfall infiltration, fine particles tend to migrate within the voids of the coarse particle framework, leading to changes in hydraulic properties and inducing slope instability. The classical internal erosion constitutive model, known as the Cividini and Gioda erosion criterion, is commonly used to predict the behavior and effects of fine particle erosion in geotechnical engineering. However, certain parameters in this erosion criterion equation, such as long-term density, are challenging to obtain through experiments. To investigate the coupled evolution of seepage and erosion within landfill slopes under the influence of rainfall infiltration and to understand the mechanisms of slope instability, this research assumes the erosion of fine particle suspension and adopts the Worman and Olafsdottir erosion criterion to establish a coupled model of unsaturated seepage and internal erosion. The developed model simulates the coupled response of seepage and erosion in unsaturated landfill slopes under three different rainfall intensities. It is then combined with the infinite slope model to quantitatively analyze the impact of fine particle migration on soil permeability and slope stability. The numerical simulations provide the following findings: The Worman and Olafsdottir erosion criterion, unlike the Cividini and Gioda erosion criterion, only requires the determination of the soil’s gradation curve to estimate the erosion rate. Internal erosion primarily occurs within the leading edge of moisture penetration, accelerating the advancement of the wetting front and reducing slope stability. When the rainfall intensity is lower than the saturated permeability coefficient, the influence of internal erosion can be disregarded. However, under rainfall intensities equal to or greater than the saturated permeability coefficient, considering internal erosion results in a difference in the depth of the wetting front of up to 34.2 cm after 6 h in the R2 scenario. The safety factor without considering internal erosion is 1.12, whereas considering internal erosion yields safety factors between 1.08 and 1.09. In the R3 scenario, the difference in the depth of the wetting front reaches 53.8 cm after 6 h, with a safety factor of 1.12 without considering internal erosion and safety factors between 1.06 and 1.07 when considering internal erosion.

Analysis of pipeline leakage in unsaturated stratum: A new seepage-diffusion model

Accurate prediction of the spread of fluids leaking from underground pipelines is crucial for risk assessment. In this study, we developed a method for predicting the diffusion range of pipeline seepage fluids within an unsaturated stratum. First, we derived a seepage–diffusion equation based on the generalized Darcy’s law and subsequently analyzed the mechanism of fluid diffusion in the unsaturated stratum. We then constructed a model for the seepage–diffusion of a pipeline leakage fluid, incorporating variables such as the saturation, permeability coefficient, diffusion pressure, and diffusion distance of soil microelements across various time intervals, using a stepwise algorithm in tandem with the Green–Ampt model and VG–Mualen permeability coefficient function. We investigated the influence of fluid self-gravity, saturated permeability coefficient, initial saturation, and intra-pipe pressure on the diffusion distance of the pipeline leakage fluid in an unsaturated stratum, focusing on specific cases. The results indicate that an increase in the saturated permeability coefficient, initial saturation, and intra-pipe pressure leads to an increase in the fluid diffusion distance. A simulation test was conducted to validate the proposed seepage–diffusion model. The findings of this study can be employed to predict the diffusion range of pipeline leakage fluids in various formation types, providing a vital foundation for pipeline leakage accident management.

Time-dependent probabilistic evaluation of rainstorm-induced shallow landslides considering influence of impermeable bedrock

ABSTRACT A time-dependent probabilistic evaluation method is proposed for assessing the stability of soil slopes during rainstorm events. The method considers multiple failure scenarios, including sliding along the wetting front and shallow soil–rock interface. The application of the method is demonstrated by a typical rainstorm-induced shallow landslide in Zhejiang Province, China. The results indicate that the landslides occurred when the failure probability exceeded a certain level, providing references for real-time landslide warnings. Moreover, the factors influencing the probabilistic results have been investigated. A two-dimensional limit state surface is used to explain the change of slope failure scenarios during the rainfall process, confirming the controlling role of the impermeable bedrock surface. The probabilistic evaluation results using the actual rainfall data can better reflect slope performance via comparing the computed failure probability using idealised rainfall patterns and actual rainfall data. Additionally, the parameter sensitivity analysis shows that the matric suction, the effective cohesion and the effective internal friction angle significantly influence the slope performance during the early stage of rainfall. However, during the later stage of rainfall, the saturated permeability coefficient becomes the most sensitive parameter. The applicability of the proposed method was further verified via three other typical rainstorm-induced shallow landslide cases.

An Inversion Study of Reservoir Colluvial Landslide Permeability Coefficient by Combining Physical Model and Data-Driven Models

The saturated permeability coefficient (ks) is a key parameter for evaluating the seepage and stability of reservoir colluvial landslides. However, ks values obtained from traditional experimental methods are often characterized by large variations and low representativeness. As a result, there are significant deviations from actual observations when used in seepage field calculations for reservoir landslide analysis. This study proposes an intelligent inversion method that combines a physical model and a data-driven model for reservoir landslide ks based on actual groundwater level (GWL) monitoring data. This method combines Latin Hypercube Sampling (LHS), unsaturated flow finite element (FE) analysis, particle swarm optimization algorithm (PSO), and kernel extreme learning machine model (KELM). Taking the Hongyanzi landslide in Sichuan Province, China, as the research object, the GWL of the landslide under different ks was first obtained by LHS and transient seepage FE analysis. Then, a nonlinear functional relationship between ks and the landslide GWL was fitted based on the PSO-KELM model. Finally, the optimal landslide ks was obtained by minimizing the root-mean-squared error between the predicted and actual GWL using the PSO. A global sensitivity analysis was also conducted on the ks of different rock and soil layers to reveal their control rules on the calculation of landslide GWL. The research results demonstrate the feasibility of the proposed method and provide valuable information for similar landslides in practice.

Calculation of and Key Influencing Factors Analysis on Equivalent Resilient Modulus of a Submerged Subgrade.

To calculate and analyze the equivalent resilient modulus of a submerged subgrade, a constitutive model considering the effect of saturation and matrix suction was introduced using ABAQUS's user-defined material (UMAT)subroutine. The pavement response under falling weight deflectometer (FWD) load was simulated at various water levels based on the derived distribution of the resilient modulus within the subgrade. The equivalent resilient modulus of the subgrade was then calculated using the equivalent iteration and weighted average methods. Based on this, the influence of the material and structural parameters of the subgrade was analyzed. The results indicate that the effect of water level rise on the tensile strain at the bottom of the asphalt layer and the compressive strain at the top of the subgrade is obvious, and its trend is similar to an exponential change. The equivalent resilient modulus of the subgrade basically decreases linearly with the rise in the water level, and there is high consistency between the equivalent iteration and weighted average methods. The saturated permeability coefficient and subgrade height have the most significant effect on the resilient modulus of the subgrade, which should be emphasized in the design of submerged subgrades, and the suggested values of the resilient modulus of the subgrade should be proposed according to the relevant construction conditions.

Experimental Investigation of Water Infiltration Law in Loess with Black Locust (Robinia pseudoacacia) Roots

Physical model experiments are increasingly applied in the study of the water infiltration law in loess with roots. In the past, due to differences in study objects and the limitations of measuring techniques, the infiltration law in loess with roots is rarely evaluated by using appropriate indoor physical model experimental data. In order to investigate the law of water infiltration in loess with roots, we designed a new soil column experimental device that can automatically collect data and images. By comparing the soil column experiment data of loess, we analyzed variables in root contents (the ratio of root mass to dry soil mass) and root types. Roots with diameters of 0–2 mm, 2–5 mm, and 5–10 mm are defined as type I, type II, and type III, respectively. It was found that the water infiltration rate, water-holding capacity, and saturated permeability coefficient increase with the increase in root content. In loess containing different root types, the root types were found to improve the rate of water infiltration, water-holding capacity, and saturated permeability coefficient in the soil. The root types were ranked in descending order in terms of their impact: root type II had the highest improvement, followed by root type III, and then root type I. The phenomenon of circumferential flow existed when water infiltrated loess with roots. Root content and root type would affect the radius of circumferential flow, infiltration path, and cross-section. When calculating the saturated permeability coefficient of loess with roots, ignoring the effect of circumferential flow would lead to a higher result.

Assimilating Seismic Data And Soil Basic Information to Predict Near-surface Permeability And Water Content

Soil permeability plays a key role in the study of earth sciences for agriculture and forestry. Because the traditional laboratory measurement is time-consuming and laborious, and only discrete profile data can be obtained. In this paper, a simple and efficient method using soil transfer function (PTFs), is proposed to estimate permeability and other parameters indirectly by seismic wave observation. Based on Biot’s theory establishing the relationship between shear-wave velocity and permeability, and the basic soil information in the study area, including land survey, logging and drilling data, using the PTFs constraint to estimate saturated hydraulic conductivity, soil components, saturated water content and residual water content may favor the physical corrections of the PTFs. The results show that there are three distinct layers of permeability in the study area, consistent with the velocity structure. The measured basic information further verifies the accuracy of the saturated permeability coefficient estimation, which shows the reliability of the improved PTFs. The established near surface permeability estimation method by integrating seismic wave observation and soil basic information may provide further assimilation for parameter estimation combining geophysical observation and hydrogeographic statistics.

Research on the saturated/unsaturated seepage laws of ionic rare earth ore under different leaching conditions

The seepage law of the ionic rare earth leaching process plays an important role in the efficient development and utilization. The saturation permeation test of ionic rare earth under different leaching conditions was carried out using the variable head method, and the influence of type, concentration, and leaching path on the saturation permeability coefficient was revealed. The relationship between the water content and the matric suction of ionic rare earths under different leaching conditions was measured with the Geo-Experts pressure plate apparatus, and the soil-water characteristic curves under different leaching conditions were obtained. Based on the soil-water characteristic curve model, the unsaturated permeability coefficient function of ionic rare earths under different conditions was studied. The results show that the saturated-unsaturated permeability coefficients of ionic rare earths are pure water, 3% (NH4)2SO4, and 3% MgSO4, in descending order, when the type of leaching solution is different. For different concentrations of the leaching solution, when the concentration of (NH4)2SO4 increases from 2% to 5%, the saturated permeability coefficient first increases and then decreases. The matrix suction is an important factor affecting the unsaturated permeability coefficient when the ore body is unsaturated, and the unsaturated permeability coefficient decreases with the increase of the leaching solution concentration under the same matric suction. The seepage law is related to the leaching path, and the permeability coefficient increases when leaching at high concentrations followed by low concentrations, in reverse order, the permeability coefficient decreases. The research results can provide theoretical guidance for the design of injection parameters, and improve the theory of in-situ leaching.

Probabilistic Analysis of Highly Nonlinear Models by Adaptive Sparse Polynomial Chaos: Transient Infiltration in Unsaturated Soil

Polynomial chaos expansion (PCE) is widely adopted in geotechnical engineering as a surrogate model for probabilistic analysis. However, the traditional low-order PCE may be unfeasible for unsaturated transient-state models due to the high nonlinearity. In this study, a temporal-spatial surrogate model of adaptive sparse polynomial chaos expansions (AS-PCE) is established based on hyperbolic truncation with stepwise regression as surrogate models to improve computational efficiency. The uncertainty of pore water pressure of an unsaturated slope under transient-state rainfall infiltration considering hydraulic spatial variability is studied. The saturated coefficient of permeability [Formula: see text] is chosen to be spatial variability to account for the soil hydraulic uncertainty. The effects of location and time and the performances of AS-PCE are investigated. As rainfall goes on, the range of the pore pressure head becomes larger and the spatial variability of [Formula: see text] has little influence in the unsaturated zone with high matric suction. The pore pressure head under the water table suffers more uncertainty than it in the unsaturated zone. The [Formula: see text] in the high matric suction zone has a trend of rising first and then falling. Except for the high matric suction zone, the [Formula: see text] rise over time and they are almost 1 at the end of the time. It can be concluded that the AS-PCE performs better for low matric suction and positive pore pressure head and the fitting effect gradually increases as the rainfall progresses. The quartiles and at least up to second statistical moments can be characterized by the AS-PCE for transient infiltration in unsaturated soil slopes under rainfall.

The distribution of Van Genuchten model parameters on soil-water characteristic curves in Chinese Loess Plateau and new predicting method on unsaturated permeability coefficient of loess.

The unsaturated permeability coefficients are often used to solve geotechnical problems associated with unsaturated soils. But it is very difficult to measure. However, the unsaturated permeability coefficients can be predicted by the Soil-water Characteristic Curves (SWCCs). The Van Genuchten Model (VG model) is very rife as it's smooth and good fitting, thus, it has the most research data. Therefore, the research data on VG model parameters (α, n, θs and θr) of Malan loess in Chinese Loess Plateau are collected in the past two decades to obtain the spatial distribution characteristics of parameters. The trend surface analysis method is employed to clarify the regional scale distribution and the variation regular pattern on ArcGIS. Then the linear regression method is utilized to fit the relationship between suction and water content in three different regions of Chinese Loess Plateau, which is divided according to the properties and particle gradation. By using this relationship and the trend surface analysis contour map, the unsaturated permeability coefficient of the sample can be predicted after measuring the saturated permeability coefficient. The example verification shows that the difference between the prediction results and the experimental results is very small when the sample has the lower saturation, and the deviation is slightly larger if it has the higher saturation, but they are all within the acceptable range. This method not only saves the test cost, but also considers the physical properties of the loess in the three different regions of the Loess Plateau. With the improvement of data and the gradual improvement of sampling density, the prediction accuracy will gradually improve. It can provide convenience for solving the engineering problems of loess and water and other engineering applications.

A NEW FRACTAL MODEL FOR PREDICTING SATURATED SOIL PERMEABILITY UNDER DIFFERENT DEFORMATION

The permeability coefficient and air-entry value of saturated soil are important hydraulic properties, which play an important role in engineering applications. Subsoil supporting foundation is subjected to stress and undergoes deformation; the saturated permeability coefficient of such deformed soil is of practical importance. With the help of fractal theory, based on the different fractal forms of Tao–Kong model, CCG model, Mualem model, and soil–water characteristic curve, this paper derives the saturated permeability coefficient models under four deformation conditions, considering the saturation permeability coefficient is inversely proportional to the square of the air-entry value and directly proportional to the square of the maximum aperture of the soil. Combining the prediction method of air-entry value under deformation conditions, four prediction methods for the permeability coefficient of deformed saturated soil are established and the method proposed in this paper is validated by the measured value of the saturated permeability coefficient of the deformed soil. As observed, the predicted values of the four methods for clay, silt loam, sandy loam and sandy soil under deformed conditions are in acceptable agreement with the measured values, and the prediction results of the second prediction method are the closest to the measured values.

A METHOD FOR PREDICTING UNSATURATED SOIL PERMEABILITY COEFFICIENT BASED ON CLAY CONTENT

The unsaturated permeability coefficient is of importance to study the behavior of the water seepage and contaminant transport in unsaturated soils. The direct measurement of the unsaturated permeability coefficient is time consuming and laborious. Therefore, indirect approaches are usually applied to obtain the unsaturated permeability coefficient. However, indirect methods still have some drawbacks. An indirect method is usually fitted through the soil–water characteristic curve of a special type of soil, which also requires a large workload and its application is limited. To overcome these drawbacks, a fractal model of the relative permeability coefficient of unsaturated soils has been deduced in this study based on the relation between clay contents and fractal dimensions in terms of mass. A new fractal simple prediction method of unsaturated soil absolute permeability coefficient associated with the new fractal model has also been proposed by combining the simple relation between saturated permeability coefficient and air-entry value. The method is validated with the experimental data of existing literature, and the result shows that the proposed model has a higher prediction accuracy.

Factors affecting the permeability of the growing media used in bioretention systems

Bioretention systems reduce rainfall runoff and improve runoff quality in “low impact development practices”. However, existing studies have rarely focused on factors that affect the permeability of the media used in bioretention systems. Experiments were conducted to simulate runoff suspended solid (SS) load into bioretention systems. The media permeability performances of 10 types of bioretention systems were analyzed. The influence of different factors (media composition, media thickness, plants, influent load, and submerged area) on the permeability of the media in bioretention systems was discussed. The results show that the saturated permeability coefficients of the devices with SS influent finally maintained at 9.77–72.63% of the initial K values and reached the asymptotic values. Different design factors considerably influenced the permeability performance of bioretention systems. The proper composition of the materials in the media layer improves penetration performance, but attention also needs to be paid to its anti-clogging performance to maintain better permeability after construction. Although designs that reduce the thickness of the media layer have a high initial permeability coefficient and will improve initial permeability, they are not conducive to the maintenance of permeability after construction. Plants with thicker rhizomes and fewer fibrous roots are more conducive to maintaining the permeability of the facility. The increase in influent SS load has a more adverse effect on the permeability of the device compared to the increase in hydraulic load. Setting submerged zone reduces the initial permeability of the facility, the anti-clogging performance of the device, and is not conducive to the maintenance of permeability after the system has been constructed.

Evaluation of hydro-mechano-chemical behaviour of bentonite-sand mixtures

Bentonite-sand mixtures are widely used in engineering barrier of deep geological disposal of high-level radioactive nuclear waste and anti-seepage barrier of civil geotechnical engineering. Under the action of groundwater solution infiltration and external stress, the hydro-mechanical (HM) behaviour of bentonite-sand mixtures, i.e. the swelling characteristics and permeability, will change. Once the anti-seepage and filtration effect is weakened or lost, the pollutants will spread to the biosphere. Therefore, it is necessary to study the swelling characteristics and permeability of bentonite-sand mixtures under coupled mechano-chemical (MC) effect and to establish corresponding prediction model. For this reason, swelling tests under salt solution with different concentrations are conducted on pure bentonite and its mixtures with 30%, 70% and 90% sand contents, the compression tests are carried out on saturated samples, and the saturated permeability coefficient k of the sample under each load is calculated by Terzaghi's one-dimensional consolidation theory. The concepts of true effective stress p e , montmorillonite void ratio e m and critical sand content α s are introduced to determine the e m - p e relationship and finally the k - e m relationship of bentonite-sand mixtures. It is found that when the sand content α ≤ α s , the e m - p e relationship of the mixture is linear and independent of the salt solution concentration, and when α > α s , the e m - p e relationship of bentonite-sand mixture is bi-linear with the true effective deviatoric stress p esα as the intersection. In addition, the e m - k relationship also shows the linear trend when α ≤ α s , and the slope of the line increases with the increase of the salt solution concentration. When α > α s , the k - e m relationship will deviate from the linear relationship. Moreover, the larger the sand content is, the farther the deviation is. On the basis of summing the regularity, a model for predicting the HM behaviour of bentonite-sand mixture under the coupled MC effect is proposed. By comparing the swelling and permeability test results with model prediction results of different types of bentonite and its sand mixtures, the predictive model is verified. The study on the HM behaviour of bentonite-sand mixtures under salt solution infiltration and the model establishment can provide experimental and theoretical basis for the design and construction of anti-seepage engineering by bentonite-sand mixtures.

Mechanical response for rainfall-induced landslides on jointed gas pipelines

Current theoretical solutions for the influence of landslides on existing structures are generally conducted on the assumption of fine weather and provide little attention on the rainfall intensity and duration risk. Furthermore, previous studies on the interaction mechanics between landslides and pipelines seldom take account of the impacts of joints. This paper provides an analytical method to estimate the deformation and internal force of jointed gas pipelines caused by landslides considering the rainfall infiltration mechanism. By introducing the modified Green-Ampt model under the assumption of stratification, the unbalanced thrust method is derived to efficiently predict the landslide thrust force triggered by rainfall. Then, the Pasternak two-parameter foundation model is employed for the mechanical response of gas pipelines due to the landslide thrust force considering the influence of joints and gas transmission pressure. The accuracy of the presented analytical solution is verified by comparisons with in-situ and model test observed data. It is revealed that the presented solution can provide a prediction of deformation for pipelines induced by landslides in good agreements. Finally, the parametric analyses are performed for the safety assessment of gas pipelines, including amount and rotational stiffness of pipeline joint, saturated permeability coefficient and rainfall intensity.

Experimental Study on Permeability Anisotropy of Unsaturated Compacted Loess

This study investigates the permeability characteristics of unsaturated compacted loess by focusing on the anisotropy parallel and perpendicular to the compaction. Three tests are conducted on compacted loess: permeability test, soil-water characteristic curve test, and scanning electron microscope (SEM) test. Samples are maintained and tested at different dry densities under optimal moisture conditions. Test results showed that the horizontal saturated permeability coefficient of compacted loess was larger than in the vertical direction, showing obvious anisotropy. Based on the saturated permeability coefficient, the permeability coefficient of unsaturated compacted loess can be predicted according to the soil-water characteristic curve fitted using the van Genuchten model combined with the Childs and Collis-Geroge model. The relational formula was established between the unsaturated permeability anisotropy ratio and the matrix suction through introducing a pore connectivity-tortuosity parameter, which represents the relationship between unsaturated permeability anisotropy ratio and matrix suction. The difference of pore characteristics between horizontal and vertical directions of compacted loess is the main reason for the permeability anisotropy.

Simplified Relation Model of Soil Saturation Permeability Coefficient and Air-Entry Value and Its Application

Based on the Tao and Kong (TK) model and the fractal model of the soil–water characteristic curve, a simplified model of the relationship between the saturated permeability coefficient and the air-entry value is established in this study: ks = k0ψa−2. It is shown that the saturated permeability coefficient of soil is determined by its maximum pore size. In order to facilitate the mutual prediction of saturation permeability coefficient and air-entry value, based on the data of five types of soil in the UNSODA database, the comprehensive proportionality constant k0 of the five types of soil were obtained: sand k0 = 0.03051; clay k0 = 0.001878; loam k0 = 0.001426; sandy loam k0 = 0.009301; and silty clay loam k0 = 0.0007055. Based on the obtained comprehensive proportionality constant k0 and the relationship model between saturated permeability coefficient and air intake value, the air-entry value of five kinds of soils in the existing literature and the SoilVision database were calculated. Comparing the calculated air-entry value with the measured one, the results showed that the model simplifies the traditional air-entry value prediction method to some extent and can effectively predict the air-entry value of different types of soil. On the whole, the model better predicts the air-entry value for sandy, clay, and silty clay loam than loam and sandy loam.