Hydraulic Conductivity Function Research Articles

Prediction of permeability characteristics of mine slurries and sediments using finite-strain framework by optimisation algorithms

Determining the permeability characteristics of mine tailing slurries through laboratory finite-strain consolidation tests is costly due to the extensive testing required. An alternative approach involves back-predicting hydraulic conductivities from settling column test data. This study employed settlement and excess pore pressure data as inputs in optimising the permeability parameters using the finite-strain consolidation (FSC) framework. The proposed approach used the finite difference method to solve the governing equation for FSC in the forward analysis. Two novel variants of the Artificial Bee Colony (ABC) algorithm, namely the Modified Artificial Bee Colony (MABC) and the Hybrid Artificial Bee Colony (HABC) algorithms, were used to back-predict the hydraulic conductivity function parameters from the FSC test data. These models predicted the permeability characteristics using the temporal variation of the settlements for six slurries and excess pore pressure dissipation data for four slurries. The performance of the proposed algorithms along with Hybrid Particle Swarm Optimisation (HPSO) was compared with the conventional optimisation algorithms, viz., PSO, ABC, and Quantum PSO (QPSO). The HABC and HPSO exhibited remarkable stability, consistently converging to identical solution sets across multiple iterations, thereby outperforming other algorithms in this study. Despite its higher time complexity by HABC relative to the other evaluated methods, this complexity is warranted for enhanced robustness. The current study is helpful in brining practical and reliable methodologies for estimating the hydraulic conductivity function from field-scale conductivity (FSC) data, providing critical insights for the safe and efficient management of slurry wastes.

Numerical evaluation of vertical and horizontal distances for nitrogen attenuation from Onsite Sewage treatment and disposal systems (OSTDS)

Onsite Sewage Treatment and Disposal Systems (OSTDS) used for domestic wastewater treatment are a source of nitrogen (ammonium and nitrate) contamination to groundwater and surface water. One way to manage the contamination is to establish setback distances for nitrogen attenuation through nitrification and denitrification reactions within the setback distances. Determining the setback distances requires investigating nitrogen attenuation as a function of distance from OSTDS. While field investigations have been conducted, there have been few modeling investigations. Using an ArcGIS-based Nitrogen Load Estimation Toolkit, this study simulates nitrogen attenuation for over 20,000 OSTDS at five study areas across Florida, where a third of households are served by OSTDS. Different from conventional studies that only consider the horizontal distances (between an OSTDS and a surface water body that receives OSTDS effluents), this study also considers the vertical distances (between an OSTDS drainfield and water table beneath the drainfield) to account for the nitrogen reactive transport processes in the vadose zones and groundwater aquifers, making the assessment of nitrogen attenuation more comprehensive. Modeling results yield the following three empirical but quantitative relations: (1) vertical attenuation rate as a function of vertical distance and saturated hydraulic conductivity (Ks) available in the Soil Survey Geographic Database, (2) horizontal attenuation rate as a function of horizontal distance and Ks, (3) total attenuation rate as a multiplication of the vertical and horizontal attenuation rates. These relations can be used to determine nitrogen attenuation within vertical and horizontal distances to OSTDS for practical management of OSTDS nitrogen contamination.

Optimization‐based pore network modeling approach for determination of hydraulic conductivity function of granular soils

AbstractA wide range of applications of unsaturated hydraulic conductivity is well known in geotechnical, hydrological, and agricultural engineering fields. The standard prediction models for hydraulic conductivity function overlook the complexity of soil pore structure and employ a simplistic approach based on the bundle of capillary tubes. This study proposes an alternative approach employing pore network models calibrated to match soil water retention data to predict the hysteretic hydraulic conductivity function of granular soils. A novel approach to constructing a multidirectional pore network built on an irregular lattice with variable coordination numbers is presented for the realistic representation of soil voids. The geometric and topological parameters of the pore network model are optimized using the genetic algorithm, and adequate pore‐scale processes (piston‐like advance and corner flow during drainage and piston‐like advance, pore body filling, and snap‐off during imbibition) are modeled to get reasonable predictions of hysteretic hydraulic conductivity functions over the entire suction range of granular soils. Comparisons between the pore network model results, standard physically based models, and measured data for a variety of granular soils show that the proposed pore network has a superior performance over other models and compares favorably to the experimental data.

Comparing mini-disk infiltrometer, BEST method and soil core estimates of hydraulic conductivity of a sandy-loam soil

Saturated, Ks, and near-saturated, K, soil hydraulic conductivity control many hydrological processes but they are difficult to measure. Comparing methods to determine Ks and K is a means to establish how and why these soil hydrodynamic properties vary with the applied method. A comparison was established between the Ks and K values of a sandy-loam soil obtained, in the field, with the BEST (Beerkan Estimation of Soil Transfer parameters) method of soil hydraulic characterization and an unconfined MDI (mini-disk infiltrometer) experiment and, in the laboratory, with a confined MDI experiment and the CHP (constant-head permeameter) method. Using for the BEST calculations the soil porosity instead of the saturated soil water content yielded 1.4–1.1 times higher estimates of Ks and K, depending on the pressure head, and differences decreased in more unsaturated soil conditions. The confined MDI experiment yielded 22 % - 77 % higher K values than the unconfined MDI experiment, depending on the established pressure head, h0, and differences were not significant for h0 = −1 cm. In the close to saturation region, the soil hydraulic conductivity function predicted with BEST did not generally agree well with the Ks and K values obtained in the laboratory by a direct application of the Darcy’s law. In particular, BEST yielded a 5.6 times smaller Ks value than the CHP method and up to an 8.1 times higher K value than the MDI. Overall, i) the two application methods of the MDI yielded relatively similar results, especially close to saturation, and ii) there was not a satisfactory agreement between the field (BEST) and the laboratory (MDI plus CHP) determination of soil hydraulic conductivity close to saturation, unless a comparison was made with the same soil water content. The detected differences were probably attributable to soil spatial variability, overestimation of Ks in the laboratory due to preferential flow phenomena, underestimation of Ks in the field due to air entrapment in the soil and infiltration surface disturbance, inability of BEST to describe the actual soil hydraulic conductivity function at the sampled field site. Testing BEST predictions of Ks and K in other soils appears advisable and combining the MDI and CHP methods appears a rather simple means to make these checks. These additional investigations could improve interpretation of the differences between methods, which is an important step for properly selecting a method yielding Ks and K data appropriate for an intended use.

Variability in the measured soil‒water characteristic curve with respect to the numbers of specimens

The soil‒water characteristic curve (SWCC) defines the relationship between the amount of water in soil and soil suction. The SWCC is commonly used to estimate the hydraulic conductivity function (HCF) and the shear strength function (SSF). Therefore, an accurate determination of the SWCC is crucial for implementing the principles of unsaturated soil mechanics. The SWCC is commonly determined from a limited number of experimental data because SWCC measurements are time-consuming and costly. As a result, the minimum number of required soil specimens is crucial for a SWCC test when considering the accuracy of the determined SWCC and the experimental expenses. In this study, both engineered from sand and kaolin mixtures and residual soils from Bukit Timah Formation in Singapore are selected to prepare soil specimens for SWCC measurements. The SWCCs obtained from the specimens with engineered soil are consistent, while those from specimens with residual soil are slightly scattered. This indicates that one specimen is sufficient to determine the SWCC for engineered soil samples, while a minimum of two specimens should be prepared for the determination of SWCC for residual soil samples from Bukit Timah Formation.

In-situ Measurement of Unsaturated Hydraulic Conductivity Function by a New Point Source Field Dripper Method (NPSFDM)

In-situ Measurement of Unsaturated Hydraulic Conductivity Function by a New Point Source Field Dripper Method (NPSFDM)

In-Situ Measurement of Unsaturated Hydraulic Conductivity Function by Point Source Field Dripper Method Using Newly Developed Micro Irrigation Simulator for wheat Field

In-Situ Measurement of Unsaturated Hydraulic Conductivity Function by Point Source Field Dripper Method Using Newly Developed Micro Irrigation Simulator for wheat Field

Slope stability analysis of cement and silica fume stabilized expansive soil slope

The objective of this study was to assess the impact of chemical stabilization on slope stability using water retention test data. The analysis focused on hypothetical expansive soil with a 10 m height and a 34° angle. Two critical unsaturated hydraulic properties were considered: (1) soil water retention curve and (2) hydraulic conductivity function. Chemical stabilizers were introduced at varying percentages relative to cement content, with silica fume (SF) partially replacing portions of the cement. The influence of stabilizers on slope stability was evaluated by examining changes in the factor of safety (FOS) with different stabilizer concentrations. Generally, the FOS increased with higher cement content, with further improvement observed when cement was partially replaced by silica fume. Additionally, the addition of silica fume enhanced water retention capacity, as evidenced by altered pore pressure distribution and water table levels post-rainfall infiltration.

Deriving an unsaturated hydraulic conductivity function based on ergun equation

Computational Fluid Dynamics (CFD) is a widely-used numerical technique for simulating flow phenomena, particularly unsaturated flow, which involves two-phase flow. This type of flow can be effectively modeled using the Volume of Fluid (VOF) method. The key to accurately depicting unsaturated flow is the unsaturated hydraulic function (K-function), which connects flow velocity to the hydraulic gradient. However, employing the VOF method alongside the commonly used Ergun equation for modeling porous media can result in an unrealistic K-function. This, in turn, often leads to unrepresentative models of unsaturated flow. This study focuses on determining the equivalent particle diameter, an essential factor in the Ergun equation, and uses this to derive an improved K-function. The modified K-function exhibits promising results, closely matching experimental data and outperforming other empirical methods. This improved function could enhance the description and simulation of unsaturated flows.

Development and Application of an IoT-Based System for Soil Water Status Monitoring in a Soil Profile.

Soil water content (θ), matric potential (h) and hydraulic conductivity (K) are key parameters for hydrological and environmental processes. Several sensors have been developed for measuring soil θ-h-K relationships. The cost of such commercially available sensors may vary over several orders of magnitude. In recent years, some sensors have been designed in the framework of Internet of Things (i.e., IoT) systems to make remote real-time soil data acquisition more straightforward, enabling low-cost field-scale monitoring at high spatio-temporal scales. In this paper, we introduce a new multi-parameter sensor designed for the simultaneous estimation of θ and h at different soil depths and, due to the sensor's specific layout, the soil hydraulic conductivity function via the instantaneous profile method (IPM). Our findings indicate that a second-order polynomial function is the most suitable model (R2 = 0.99) for capturing the behavior of the capacitive-based sensor in estimating θ in the examined soil, which has a silty-loam texture. The effectiveness of low-cost capacitive sensors, coupled with the IPM method, was confirmed as a viable alternative to time domain reflectometry (TDR) probes. Notably, the layout of the sensor makes the IPM method less labor-intensive to implement. The proposed monitoring system consistently demonstrated robust performance throughout extended periods of data acquisition and is highly suitable for ongoing monitoring of soil water status.

Coupled hydro‐mechanical pore‐scale modeling of biopore‐coated clods for upscaling soil shrinkage and hydraulic properties

AbstractEarthworms and plant roots are vital for macropore formation and stabilization. The organo‐mineral coating of biopore surfaces also regulates macropore‐matrix mass exchange during preferential flow. The influence of finer‐textured burrow coatings on macroscopic soil properties during shrinkage could potentially be assessed by upscaling pore‐scale hydraulic and mechanical simulations. The aim was to investigate the influence of micro parameters (particle size, stiffness, and bond strength) on macro parameters (i.e., shrinkage curve and soil hydraulic properties). Drainage experiments and simulations were carried out using biopore‐coated clod‐size samples compared to those without coating. Simulations were performed using a two‐phase pore‐scale finite volume coupled with discrete element model (DEM‐2PFV). The structural dynamics was characterized by analyzing the pore volume and soil shrinkage curve obtained from numerically determined data. The soil hydraulic parameters were described using uni‐ and bimodal van Genuchten (vG) functions. The drainage simulations revealed hydro‐mechanical dynamics characterized by Braudeau‐shrinkage curve subdomains: The matrix‐only samples, with lower particle bond strength, exhibited relatively higher shrinkage. The coated samples, with higher particle stiffness and bond strength, displayed greater hydro‐mechanical stability. The numerically determined initial value of the saturated hydraulic conductivity (Ks) was about 70 times larger for matrix‐only samples than for coated samples. As expected, for the nonrigid soil structures, constant Ks, α, and n values for bimodal vG model resulted in prediction errors. Upscaling DEM‐2PFV pore‐scale model outcomes quantifies micro‐coating effects on macro hydro‐mechanics. This yields void ratio‐based soil water retention and hydraulic conductivity functions, advancing macroscopic soil hydraulic models and enhancing structured soil flow and transport descriptions.

Measurement and Modeling of the Saturated Hydraulic Conductivity Functions of Collapsible and Expansive Soils

Measurement and Modeling of the Saturated Hydraulic Conductivity Functions of Collapsible and Expansive Soils

Prediction of the hydraulic conductivity function for unsaturated soils over the entire suction range

The hydraulic conductivity function (HCF) refers to in this paper is the variation of hydraulic conductivity over the entire suction range from 0 to 106 kPa. Most of the available HCF models in the literature are derived based on capillary theory and have limitations in the explanation of HCF in the high suction range. Recently, several models have been proposed for accounting for the thin film flow dominated by the adsorbed water in the high suction range. However, these models require measured HCF data for describing the thin film flow, which is time-consuming. In this study, a mathematically continuous and simple model is proposed for predicting the HCF. The model has physically meaningful parameters for predicting the HCF. In this model, the residual suction estimated from the soil–water characteristic curve (SWCC) is used to distinguish the capillary and adsorption-dominated regions, and a correction operator that considers the thin film flow is introduced. The performance of the model was validated using the measured and published experimental data for various soils. In addition, the proposed model is successfully applied in a numerical investigation of the hydraulic behavior of a capillary barrier system, highlighting the role of the thin film flow.

Hydraulic characterization of Pwales aquifer in Malta Island preparatory for planning managed aquifer recharge (MAR) pilot plant

Whitin the aim to reduce the water demand by increasing water use efficiency and providing alternative water resources, and mainly to meet the demand of good quality irrigation water for agriculture, the Energy and Water Agency of Malta is planning to develop a Managed Aquifer Recharge pilot plant in Pwales Valley to improve the quantitative and qualitative status of the groundwater body. For this reason a detailed hydraulic characterization of the valley was carried out. Specifically, hydraulic properties of the rocks that constitute strata atop of the Pwales aquifer were determined by means of both laboratory measurements on samples and field test carried out in the studied area. The water retention and hydraulic conductivity functions, which relate the matric potential, ψ, and hydraulic conductivity, K, to the water content, θ, respectively, were measured using three experimental methods because each of them allows to obtain data points in a specific wet range. The water retention and hydraulic conductivity functions were measured on samples extracted from blocks of Upper Coralline Limestone formation, that hosts the aquifer, collected in three different quarries: Ghian Tuffieha, Mellieha and San Martin areas. The measured water retention and hydraulic conductivity data were fitted with LABROS SoilView Analysis software that allows to describe the functions and obtain the parameters which are crucial for modelling the water flow and transport processes in the critical zone. In addition, large ring infiltrometer test was carried out to determine the field saturated hydraulic conductivity, Kfs, and the average infiltration rate. Knowledge of the hydraulic characteristics of the Upper Coralline Limestone, completely missing in the scientific literature, allows developing a local groundwater-flow numerical model in order to better describe and understand how the water flows from the soil to the groundwater of the valley and visualize different environmental scenarios such as the potential effects of Managed Aquifer Recharge plant in the Pwales Coastal Groundwater Body.

A framework for estimating soil water characteristic curve and hydraulic conductivity function of permeable reactive media

The unsaturated behavior of permeable reactive barriers (PRB) is a critical component in predicting the removal efficiency through the adsorption of contaminants. This study investigates the framework to estimate the soil water characteristic curve (SWCC) and hydraulic conductivity function (HCF) for iron oxide-coated sand (IOCS) and zeolite, which are common materials used in PRBs. A multistep outflow (MSO) experiment was performed and the results of the MSO experiment were used to optimize associated parameters in Kosugi's SWCC and HCF. In addition, three scenarios of optimization analysis were investigated to evaluate the best-fitting model for estimating SWCC and HCF. The low root mean square error (RMSE) of fitted parameters indicates the Kosugi model well described the observed suction profiles in MSO experiments. In addition, the lowest RMSE and coefficient of variation suggested the inclusion of the additional parameter β provided the best estimation of the three materials (clean sand, IOCS, and zeolite). The physically reasonable estimation of SWCC and HCF of the three materials from the optimized parameters suggests the proposed framework is a reasonable model for the unsaturated behavior of PRBs.

Modeling hydraulic conductivity function of frozen soil

Hydraulic conductivity function for frozen soils (HCFF) is crucial for accurately simulating the water transfer process in cold regions, impacting hydrological states and frost heave diseases. However, the HCFF model capturing the relation between hydraulic conductivity and unfrozen water content (θ) or temperature (T) remains an open question. This study delves into HCFF encompassing both empirical and prediction models. This study begins with introducing θ-form and innovative T-form empirical HCFF models, showcasing their solid performance in fitting measured hydraulic conductivity data. Furthermore, the extension of the T-form empirical model to incorporate vapor flow and bimodal soils, through the introduction of maximum vapor conductivity and weighting factors, demonstrates a closer alignment with physical mechanisms and observed trends. In terms of predicting HCFF, the study provides a theoretical foundation through statistical hydraulic conductivity models and thermodynamic equilibrium in frozen soils. Additionally, it clarifies three routes for HCFF prediction—single Soil Freeze Characteristic Curve (SFCC), single Soil Water Characteristic Curve (SWCC), and a combination of the two—and validates their effectiveness through test results and comparison of HCFF prediction outcomes using SWCC and SFCC data from specific soil samples. In practice, the empirical and prediction models are recommended for available hydraulic conductivity data and available SFCC or SWCC data, respectively. Overall, this study not only lays the theoretical groundwork for most prediction models but also presents a valid empirical equation for modeling hydraulic conductivity function tailored specifically for frozen soils.

Microstructural investigation of the unsaturated hydraulic properties of hydrochar-amended soils

Hydrochar is an urban soil amender that supports plant growth on slopes. It is a biomass-derived carbon-rich material produced by the hydrothermal carbonation process; thus, it has a different pore structure from biochar produced by pyrolysis. The effects of hydrochar on the hydraulic properties of unsaturated compacted soils and the underlying pore-level soil-hydrochar interaction mechanisms are unclear. In this study, silty-clay sand was amended by grass-derived hydrochars produced at two hydrothermal carbonisation temperatures (180 and 240 °C, denoted as H-180 and H-240, respectively) with different mass proportions (fH\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${f}_{{\ ext{H}}}$$\\end{document}). The pore and throat size distributions, water retention curves (WRCs) and hydraulic conductivity functions (HCFs) of the soils with and without amendment were measured. The results showed that hydrochar improved the soil water retention capability as the smaller hydrochar particles filled the soil pores with diameters larger than 290 μm. Compared with the increase in air-entry value made by H-180, the one made by H-240 was more substantial as this type of hydrochar altered the soil pores to be smaller in size. Hydrochar also increased the hydraulic conductivity of the soil by half to one order of magnitude due to the increase in the throat frequency and the presence of hydrochar intra-pores. One exception was the amendment by H-180 at fH\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${f}_{{\ ext{H}}}$$\\end{document} of 2.5%, wherein the HCF was reduced due to pore clogging at throat diameters less than 90 μm and more than 250 μm. Finally, amending the soil with either H-180 or H-240 at fH\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${f}_{{\ ext{H}}}$$\\end{document} of 5% always improved the WRC and HCF, thereby benefiting plant water uptake.

Application of Dynamic Model for Designing Zero Runoff System to Control Erosion in Cocoa Fields

Land degradation in cocoa plantations is mainly caused by surface runoff erosion. Surface runoff can be reduced by applying a Zero Runoff (ZRO) system. This system effectively reduces runoff when its size sufficiently infiltrates all surface runoff. This study aims to determine the size, dimensions, and location of a ZRO system that effectively increases infiltration and prevents surface runoff. The size and dimensions of the system were designed using a water balance approach, where all surface runoff is collected in the ZRO system and then infiltrated. Surface runoff was calculated using the Soil Conservation Services (SCS) method. The potential infiltration rate is a function of the soil's saturated hydraulic conductivity and the system's surface area. The saturated hydraulic conductivity of the soil was determined using the falling head method. The size and dimensions of the system were determined through model simulation based on field physical condition data using a dynamic model. The research results showed that the size and dimensions of the system depend on the amount of rainfall, the area of the catchment area, and the saturated hydraulic conductivity of the soil. From the dynamic model simulation, all surface runoff will be infiltrated if the dimensions of the zero runoff system are 1 x 1 x 0.5 m. This size can accommodate a water volume between 0 – 0,006 m3, so with a system depth of 1,000 mm, there is no surface runoff.

SWRC interpretation of iron ore tailings blends focusing on saturation assessment of dry stacking

ABSTRACT The study addresses challenges in dry stacking of fine-grained materials by blending itabirite iron ore slime tailings with coarser flotation tailings. It focuses on flow dynamics, capillary saturation, and the necessity to prevent large, saturated volumes. Geotechnical tests were conducted on various blends, deriving unsaturated hydraulic conductivity functions using Fredlund and Xing’s methodology. The Soil-Water Retention Curve data, combined with transient 1D analysis, assesses capillary rise. Results show capillary rise up to 50 meters with over 80% saturation, and also influenced by weather conditions penetrating up to 20 meters. Integrating up to 30% slime content in flotation tailings mitigates saturation issues. Empirical and numerical findings enable inferring saturation tendencies in distinct iron ore tailings mixtures, establishing a procedural framework for practical field applications.

Semi-analytical solution of pore-water pressure in unsaturated ground and infinite slope considering highly nonlinear soil hydraulic properties

A multi-exponential function (ME) is proposed to depict the highly nonlinear soil water retention curve and hydraulic conductivity function. Then, semi-analytical solution of pore-water pressure in an unsaturated infinite slope at steady state is derived using ME to depict soil hydraulic properties. The solution is verified with experimental and numerical results. It is found that ME can better describe the highly nonlinear hydraulic properties of soil than the single exponential function (SE), which is commonly-used previously. At steady state, the adoption of SE results in overestimating negative pore-water pressure (PWP; i.e., matric suction) by about 25 kPa and slope’s factor of safety (FOS) by 100% under rainfall, but underestimating negative PWP by about 50 kPa under evaporation. The difference between PWP and FOS calculated by using SE and ME becomes more significant for soil with bimodal hydraulic conductivity function than that with unimodal one. This difference reduces at a larger slope angle and deeper depth. Moreover, this difference generally increases at a lower SME/SSE, where SME and SSE represent the suction at which the unsaturated hydraulic conductivity expressed by ME and SE equals the applied rainfall intensity or evaporation rate, respectively. When SME/SSE is greater than 0.1, the difference basically diminishes.