Van Genuchten-Mualem Research Articles

Estimating Soil Hydraulic Parameters Characterizing Rainwater Infiltration and Runoff Properties of Dryland Floodplains

The two-layered (0 - 50 and 50 - 250 mm) surface horizon hydraulic parameters of three dryland floodplain soil-types under aquafer water management in Postmasburg, Northern Cape Province of South Africa were estimated with HYDRUS-1D model. Time dependent water infiltration measurements at 30 and 230 mm depths from simulated rainfalls on undisturbed 1 m2 small plots with intensities of 1.61 (high), 0.52 (medium) and 0.27 (low) mm·min-1, were minimised using a two-step inversion. Firstly, separate optimisation of the van Genuchten-Mualem model parameters for the two surface-horizon layers and secondly, simultaneous optimisation for the joint two-layered horizon with first step optimal parameters entered as initial values. The model reproduced transient water-infiltration data very well with the Nash-Sutcliffe model efficiency coefficient (NSE) of 0.99 and overestimated runoff (NSE; 0.27 to 0.98). The upper surface horizon had highly optimised and variable parameters especially θs and Ks. Optimal Ks values from higher soil surface bulk-density (≥1.69 g·cm-3) were lower by at least one order of magnitude to double ring infiltrometers and water infiltration properties were different (P < 0.05) for the high rainstorm due to raindrop impact and surface crusting. Optimal α and n parameter values corresponded well with texture of the Addo (Greysols), Augrabies (Ferralsols) and Brandvlei (Cambisols) soil types. However, θs and Ksshowed greater sensitivity to model output and exerted greater influence on dryland floodplain water-infiltration and runoff characteristics. Increasing rainfall simulation period to attain near-surface saturated conditions and inclusion of surface ponding data in the inverse problem could considerable improve model prediction of hydro-physical parameters controlling surface-subsurface water distribution in fluvial environments.

Prediction of soil hard-setting and physical quality using water retention data

Hard-setting soils become hard and compact during drying, and are therefore difficult or impossible to cultivate unless they are re-wetted. This study was done to quantify the hard-setting behavior on nine soils with a wide range of texture (from sandy loam to silty clay). Repacked soil cores were prepared with least disturbance of soil aggregates (05‒4 mm). Water retention curves of the soils were measured in the matric suction range 10–15,000 hPa in different bulk densities (1.20–1.70 Mg m−3). Single-porosity van Genuchten-Mualem and dual-porosity Dexter models were fitted to the water retention data. Dexter's indices of soil physical quality (S) and hard-setting (HDexter) were calculated using the van Genuchten-Mualem parameters. Soil physical quality indices S1 and S2 (slopes of water retention curve at first and second inflection points, related to matrix and structural pore spaces, respectively) and new hard-setting indices (H1 and H2 related to matrix and structural pore spaces, respectively) were also calculated from the parameters of dual-porosity model. Tensile strength (Y) of the soil samples prepared at different bulk densities was also measured from near-saturation to oven-dry. Slopes of relationships between Y and water content were used as soil strength-based hard-setting indices. A larger slope means that the soil is more susceptible to hard-setting. The HDexter, H1 and H2 increased with an increment in the bulk density, whereas the S, S1 and S2 decreased. Significant positive relationships between hard-setting indices (HDexter and H1) and calcium carbonate content were observed. Negative linear relations were derived between S, S1 and S2, and bulk density and positive linear relations were obtained between HDexter, H1 and H2, and bulk density. Soil hard-setting and physical quality indices were significantly correlated with relative bulk density. Positive relationships were observed between soil strength-based hard-setting indices and relative bulk density, and the correlations between these indices and H2 and S1 were significantly positive and negative, respectively. These findings confirmed that the new proposed indices enable prediction of soil hard-setting behavior using only water retention data with no need to measure soil mechanical strength.

Understanding the Role of Water Flow and the Porous Transport Layer on the Performance of Proton Exchange Membrane Water Electrolyzers

In this article, we have brought a different perspective to the topic of mass transport losses in a proton exchange membrane (PEM) water electrolyzer, particularly regarding the role of water flow and the dominant mass transport mechanism in the porous transport layer (PTL). We conducted permeation experiments on a sintered Ti PTL, where we measured the pressure loss of gas that flows through its pores; furthermore, we presented a model based on the van Genuchten–Mualem capillary pressure and the Carman–Kozeny gas permeability, and we report an increase in the pressure loss with respect to the water flow, which we reported as an increase in the apparent tortuosity of the pores in the PTL. From this we conclude that the water flow exerts a shear stress on the gas flowing through the PTL, proportional to its kinetic energy, and that the gas permeation is the dominant transport mechanism within a PTL, in contrast to a one- or two-phase flow, which is more energy demanding. Finally, we propose that further wo...

Temporal estimation of hydrodynamic parameter variability in stormwater constructed wetlands – The hysteresis effect during multi-rainfall events

Constructed wetland (CW) systems are increasingly implemented as appropriate water treatment facilities, the efficiency of which varies with time due to possible malfunctions such as clogging related to excessive loads of suspended solids or inadequate CW sizing. Numerical flow modeling was used to evaluate filtering performance and to improve the design of CWs. Such modeling usually involves the so-called van Genuchten-Mualem (vGM) soil hydrodynamic parameters which are difficult to measure. This paper focuses on the sensitivity of the model with respect to the vGM parameters revealing a predominant influence of the shape parameters and the saturated conductivity of the filter on the piezometric heads, during feeding and drainage. A simple, robust and low-cost inverse modeling approach, deterministic and stochastic, for the identification of the soil hydrodynamic properties from piezometric heads measured during successive storm events is also presented. The temporal variability of hydrodynamic parameters was assessed and analyzed with regards to modeling efficiency. Principal component analysis showed that the estimated hydrodynamic parameters from the feeding and drainage sub-periods were significantly different.

Iterative filter based estimation of fully 3D heterogeneous fields of permeability and Mualem-van Genuchten parameters

The accurate modeling of flow and transport in the vadose zone for agricultural and environmental applications requires knowledge about soil parameters. Soil parameters vary in space depending on soil texture and structure. In the present synthetic study we considered spatial variation of permeability (k), inverse of capillary entry pressure head (αVG) and exponent (n) of the Mualem-van Genuchten model. The iterative Ensemble Kalman filter (IEnKF) can estimate the spatially variable soil parameters if measurements of water saturation at different locations and times are available. We used as input daily precipitation data from the Berambadi catchment (southern India). We first considered that the parameters vary horizontally but are constant in the vertical direction. In this case log (k) and log (αVG) can be estimated satisfactorily with 30%–40% reduction of RMSE (compared to open loop runs), if the initial guess of the spatial correlation lengths of the heterogeneous fields is equal to or larger than the unknown, true values. The estimation of exponent n is poorer as the reduction of RMSE is just 20%. If vertical heterogeneity of the parameters is considered the estimation of log (k) and log (αVG) is only improved for the upper 1.5 m and estimation of n is not improved. We also demonstrate that the estimation problem can be simplified when flow in the unsaturated zone is predominantly vertical. If in this case soil hydraulic parameters are estimated with IEnKF at measurement locations and afterwards interpolated with kriging, results are produced with a similar quality as with 3D-IEnKF.

Determining in-situ unsaturated soil hydraulic conductivity at a fine depth scale with heat pulse and water potential sensors

Unsaturated hydraulic conductivity (K) of surface soil changes substantially with space and time, and it is of great importance for many ecological, agricultural, and hydrological applications. In general, K is measured in the laboratory, or more commonly, predicted using soil water retention curve and saturated hydraulic conductivity. In the field, K can be determined through infiltration experiments. However, none of these approaches are capable of continuously monitoring K in-situ at fine depth scales. In this study, we propose and investigate an approach to continuously estimate fine depth-scale K dynamics under field conditions. Evaporation rate and change in water storage in a near-surface soil layer are measured with the heat pulse method. Then, water flux density at the lower boundary of the soil layer is estimated from evaporation rate, change in water storage, and rainfall or irrigation rate using a simple water balance approach. Finally, K values at different soil depths are derived using the Buckingham-Darcy equation from water flux densities and measured water potential gradients. A field experiment is performed to evaluate the performance of the proposed approach. K values at 2-, 4-, 7.5-, and 12.5-cm depths are estimated with the new approach. The results show that in-situ K estimates vary with time following changes in soil water content, and the K-water content relationship changes with depth due to the difference in bulk density. In-situ estimated K-matric potential curves agree well with those measured in the laboratory. In-situ K estimates also show good agreement with the Mualem-van Genuchten model predictions, with an average root mean square error in log10 (K, mm h−1) of 0.54 and an average bias of 0.17. The new approach provides reasonable in-situ K estimates and has potential to reveal the influences of natural soil conditions on hydraulic properties as they change with depth and time.

Recommendations and interpretations for the tortuosity and pore-connectivity parameter in undamaged cement-based materials

Unsaturated transport properties, such as hydraulic conductivity (K), are commonly viewed as durability parameters for cement-based materials. Measuring K experimentally, however, is challenging due to high-pressure requirements at low degrees of saturation. For this reason, analytical expressions for hydraulic conductivity are often employed. Possibly the most widely used model for this purpose is the van Genuchten–Mualem equation. Usage of this equation requires employment of the tortuosity and pore-connectivity parameter I, which has significant implications on K. Often, a default value of is used, which leads to misrepresentation of K at low degrees of saturation. Recent works have identified the need for proper estimation of I, however uncertainty as to the realistic range for I still exists. In this paper, recommended ranges of I are developed for undamaged cement-based materials using analytical modeling based on physical realizations of unsaturated hydraulic properties. Interpretations of I are then presented based on the derived models.

Quantify the Pore Water Velocity Distribution by a Celerity Function

Celerity and velocity of subsurface flow in soil porous medium are intimately linked with tracer transport, while only few current studies focused on their relations. This study conducted theoretical analyses based on a pore bundle model, under which celerity in unsaturated flow is equivalent to maximum velocity. Furthermore, under 3 models Brooks-Corey model and unmodified and modified Mualem-van Genuchten models, we used a celerity function to derive breakthrough curves aiming to quantify the advective tracer transport for 5 typical soil textures. The results showed that the celerity under near-saturated conditions can be 5 up to 100 times larger than the saturated hydraulic conductivity, and a small volumetric fraction (&lt;15%) of pores contributed more than half of the specific discharge. First arrival time and extensive tailing of the breakthrough curves were controlled by maximum velocity and velocity distribution, accordingly. As the kinematic ratio in the Brooks-Corey model remained constantly for each specific soil, we used it to quantify the ratio of maximum tracer velocity over average tracer velocity. We also found that a bimodal soil hydraulic function (for a dual-permeability model) may result in similar soil hydraulic conductivity functions for different parameter sets, but their celerities are different. The results showed that the proposed celerity function can assist in investigating subsurface flow and tracer transport, and the kinematic ratio could be used to predict the first arrival time of a conservative tracer.

Sensitivity and identifiability of hydraulic and geophysical parameters from streaming potential signals in unsaturated porous media

Abstract. Fluid flow in a charged porous medium generates electric potentials called streaming potential (SP). The SP signal is related to both hydraulic and electrical properties of the soil. In this work, global sensitivity analysis (GSA) and parameter estimation procedures are performed to assess the influence of hydraulic and geophysical parameters on the SP signals and to investigate the identifiability of these parameters from SP measurements. Both procedures are applied to a synthetic column experiment involving a falling head infiltration phase followed by a drainage phase. GSA is used through variance-based sensitivity indices, calculated using sparse polynomial chaos expansion (PCE). To allow high PCE orders, we use an efficient sparse PCE algorithm which selects the best sparse PCE from a given data set using the Kashyap information criterion (KIC). Parameter identifiability is performed using two approaches: the Bayesian approach based on the Markov chain Monte Carlo (MCMC) method and the first-order approximation (FOA) approach based on the Levenberg–Marquardt algorithm. The comparison between both approaches allows us to check whether FOA can provide a reliable estimation of parameters and associated uncertainties for the highly nonlinear hydrogeophysical problem investigated. GSA results show that in short time periods, the saturated hydraulic conductivity (Ks) and the voltage coupling coefficient at saturation (Csat) are the most influential parameters, whereas in long time periods, the residual water content (θs), the Mualem–van Genuchten parameter (n) and the Archie saturation exponent (na) become influential, with strong interactions between them. The Mualem–van Genuchten parameter (α) has a very weak influence on the SP signals during the whole experiment. Results of parameter estimation show that although the studied problem is highly nonlinear, when several SP data collected at different altitudes inside the column are used to calibrate the model, all hydraulic (Ks,θs,α,n) and geophysical parameters (na,Csat) can be reasonably estimated from the SP measurements. Further, in this case, the FOA approach provides accurate estimations of both mean parameter values and uncertainty regions. Conversely, when the number of SP measurements used for the calibration is strongly reduced, the FOA approach yields accurate mean parameter values (in agreement with MCMC results) but inaccurate and even unphysical confidence intervals for parameters with large uncertainty regions.

Evaluating pedotransfer functions of the Splintex model

The soil water retention curve (SWRC) is an essential hydraulic function for the understanding and modelling of soil hydraulic processes. Its direct determination is time consuming and sometimes expensive because it requires extensive sampling, especially when spatial and temporal variation of soil hydraulic properties are an issue. The use of pedotransfer functions (PTFs) is a viable alternative to predict the parameters of SWRC from more easily determined soil attributes. Splintex is a physically based engineering model containing two PTFs to estimate SWRC parameters and saturated hydraulic conductivity, but its performance and functionality have not yet been fully evaluated and disseminated for soil science. We examined the functionality of the PTFs available in Splintex to estimate parameters of the Van Genuchten–Mualem (VGM) SWRC equation with a laboratory‐measured dataset containing information on particle size, bulk and particle density, saturated water content and parameters of the SWRCs. In addition, we tested the performance of both PTFs for deriving some soil physical–structural variables calculated from estimated SWRC parameters. Compared with VGM parameters fitted to the laboratory dataset, the model performed well. Its predictive performance for soil air capacity, relative field capacity and soil physical–structural quality indices was also evaluated. The performance of Splintex for estimating the VGM parameters depended on the combined effect of all input variables rather than on isolated correlations between an input variable and a model parameter.Highlights Splintex provides two PTFs to estimate the Van Genuchten–Mualem parameters of the SWRC. In addition to PTF1 input, PTF2 needs an additional soil water content–retention observation. Performance of Splintex‐PTF1 against measured data and ‐PTF2 prediction is presented. PTF2 provided better results than PTF1 for estimating SPQ indices.

Pedotransfer functions of soil water properties to estimate the S-index

ABSTRACT One big challenge for soil science is to translate existing data into data that is needed. Pedotransfer functions have been proposed for this purpose and they can be point or parametric when estimating the water retention characteristics. Many indicators of soil physical quality have been proposed, including the S-Index proposed by Dexter. The objective of this study was to assess the use of pedotransfer functions for soil water retention to estimate the S-index under field conditions in the diversity of soils of the Paraná state. Soil samples were collected from 36 sites with textures ranging from sandy to heavy clay in the layers of 0-0.10 and 0.10-0.20 m and under two conditions (native forest and cultivated soil). Water content at six matric potentials, bulk density and contents of clay, sand and silt were determined. Soil-water retention curve was fitted by the van Genuchten-Mualem model and the S-index was calculated. S-index was estimated from water retention curves obtained by the pedotransfer function of Tomasella (point and parametric). Although the coefficient of determination varied from 0.759 to 0.895, modeling efficiency was negative and the regression coefficient between observed and predicted data was different from 1 in all comparisons. Under field conditions in the soil diversity of the Paraná state, restrictions were found in S-index estimation using the evaluated pedotransfer functions.

Relating unsaturated electrical and hydraulic conductivity of cement-based materials

ABSTRACTUnsaturated hydraulic (K) and electrical (σb) conductivity are often considered durability indicators of cement-based materials. However, K is difficult to measure experimentally. This is due to the large pressure requirements at low degrees of saturation resulting from the fine pore-size distribution of cement-based materials. As a result, the commonly-used analytical models, requiring calibration of K from experimental data, are often inaccurate at low degrees of saturation. On the other hand, measuring σb is rather straight forward. Descriptions of the relationship between σb and K may therefore be particularly valuable when K is required. In this work, we use experimental data from previous works to determine the feasibility of models employing a van Genuchten-Mualem based framework to predict K and σb – expressions for diffusivity D are also provided. We then develop analytical expressions relating K and σb using these models. It is then shown that K = K(σb) and σb = σb(K) may be determined when either parameter is fully described. Lastly, we propose a simplified model and discuss the roles of pore-size distribution, saturation, pore connectivity and tortuosity in characterizing the relationship between K and σb.

Analysis of soil hydraulic and thermal properties for land surface modeling over the Tibetan Plateau

Abstract. Soil information (e.g., soil texture and porosity) from existing soil datasets over the Tibetan Plateau (TP) is claimed to be inadequate and even inaccurate for determining soil hydraulic properties (SHP) and soil thermal properties (STP), hampering the understanding of the land surface process over TP. As the soil varies across three dominant climate zones (i.e., arid, semi-arid and subhumid) over the TP, the associated SHP and STP are expected to vary correspondingly. To obtain an explicit insight into the soil hydrothermal properties over the TP, in situ and laboratory measurements of over 30 soil property profiles were obtained across the climate zones. Results show that porosity and SHP and STP differ across the climate zones and strongly depend on soil texture. In particular, it is proposed that gravel impact on porosity and SHP and STP are both considered in the arid zone and in deep layers of the semi-arid zone. Parameterization schemes for porosity, SHP and STP are investigated and compared with measurements taken. To determine the SHP, including soil water retention curves (SWRCs) and hydraulic conductivities, the pedotransfer functions (PTFs) developed by Cosby et al. (1984) (for the Clapp–Hornberger model) and the continuous PTFs given by Wösten et al. (1999) (for the Van Genuchten–Mualem model) are recommended. The STP parameterization scheme proposed by Farouki (1981) based on the model of De Vries (1963) performed better across the TP than other schemes. Using the parameterization schemes mentioned above, the uncertainties of five existing regional and global soil datasets and their derived SHP and STP over the TP are quantified through comparison with in situ and laboratory measurements. The measured soil physical properties dataset is available at https://data.4tu.nl/repository/uuid:c712717c-6ac0-47ff-9d58-97f88082ddc0.

Hydrological Behavior of Peat- and Coir-Based Substrates and Their Effect on Begonia Growth

The physical–hydraulic properties of eight substrate mixtures based on sphagnum peat and coir were determined and their effect on the growth of Begonia xelatior was studied. The particle size distribution, water retention curve, saturated hydraulic conductivity, and pore size distribution of the substrates were determined. All substrates exhibited high total porosity, satisfactory water retention capacity, and high saturated hydraulic conductivity. Increasing the percentage of perlite in the mixtures contributed to the reduction of water retention capacity and the increase of large pores. Unsaturated hydraulic conductivity estimated by the Mualem–van Genuchten model showed a sharp decrease within a range of water pressure heads (0 to −50 cm) observed between two successive irrigations. To assess aeration and water retention capacity, total porosity; airspace; and easily, and nonavailable water, as well as the bulk density of the substrates, were determined and concomitantly compared with the “ideal substrates” determined by De Boodt and Verdonck. The comparative results showed that substrate porosity alone is not efficient to create ideal plant growth conditions, but dynamic parameters are also needed. Plants grown in a substrate classified as “nonideal” showed significantly greater growth than the plants grown in most of the other substrates studied.

A Comprehensive Model for Single Ring Infiltration I: Initial Water Content and Soil Hydraulic Properties

Core Ideas New single ring infiltration model accounts for a wide range of experimental conditions. Soil capillarity as function of initial water content was explored. Model closely matched HYDRUS‐3D simulations for thirty infiltration scenarios. Model was tested with both Brooks and Corey and van Genuchten–Mualem hydraulic parameters. Brooks and Corey parameters gave more consistent predictions for cumulative infiltration. Single ring infiltration tests are commonly used to understand soil hydraulic properties. While a number of models have been developed to describe three‐dimensional infiltration from single ring sources, these expressions are often restricted to cases where the soil is initially dry and the source pressure head is negligible. These conditions may restrict the use of these expressions in real field settings. In this study we modified a set of infiltration models to explicitly account for variations in soil hydraulic properties, initial conditions, and experimental setups. The resultant expressions allowed us to explore how soil capillary length (a measure of the capillary force acting through the wetted zone) and three‐dimensional wetting profiles vary under different initial matric heads. Specifically, as initial matric head increases, infiltration becomes increasingly one‐dimensional due to a decrease of the soil capillary force. However, for most realistic situations (i.e., moderately wet to very dry initial conditions) the model can be simplified by assuming a constant capillary length. The resulting expressions compared well with numerical results from HYDRUS‐3D for five different soils, including both dry and wet initial conditions, two ring insertion depths, and two ponding depths. Overall, the model provides further insight on the variations in soil capillarity (as sorptivity) and infiltration across a range of soil types and initial conditions, and can be used to describe single ring infiltration under nearly every scenario.

A New Soil Moisture Downscaling Approach for SMAP, SMOS, and ASCAT by Predicting Sub-Grid Variability

Several studies currently strive to improve the spatial resolution of coarse scale high temporal resolution global soil moisture products of SMOS, SMAP, and ASCAT. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. We use this information for the prediction of the sub-grid soil moisture variability for each SMOS, SMAP, and ASCAT grid cell. The approach is based on a method that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean, available at https://doi.org/10.1594/PANGAEA.878889. The resulting data set helps identify adequate regions to validate coarse scale soil moisture products by providing a measure of representativeness of small-scale measurements for the coarse grid cell. Moreover, it contains important information for downscaling coarse soil moisture observations of the SMOS, SMAP, and ASCAT missions. In this study, we present a simple application of the estimated sub-grid soil moisture heterogeneity scaling down SMAP soil moisture to 1 km resolution. Validation results in the TERENO and REMEDHUS soil moisture monitoring networks in Germany and Spain, respectively, indicate a similar or slightly improved accuracy for downscaled and original SMAP soil moisture in the time domain for the year 2016, but with a much higher spatial resolution.

How Well Does Noah-MP Simulate the Regional Mean and Spatial Variability of Topsoil Water Content in Two Agricultural Landscapes in Southwest Germany?

Abstract The spatial variability of topsoil water content (SWC) is often expressed through the relationship between its spatial mean 〈θ〉 and standard deviation σθ. The present study tests the concept that a reasonably performing land surface model (LSM) should be able to produce σθ–〈θ〉 data pairs that fall into a polygon, spanned by the cloud of observed data and two anchor points: σθ at the permanent wilting point σθ–〈θwp〉 and σθ at saturation σθ–〈θs〉. A state-of-the-art LSM, Noah-MP, was driven by atmospheric forcing data obtained from eddy covariance field measurements in two regions of southwestern Germany, Kraichgau (KR) and Swabian Alb (SA). KR is characterized with deep loess soils, whereas the soils in SA are shallow, clayey, and stony. The simulations series were compared with SWC data from soil moisture networks operating in the two study regions. The results demonstrate that Noah-MP matches temporal 〈θ〉 dynamics fairly well in KR, but performs poorly in SA. The best match is achieved with the van Genuchten–Mualem representation of soil hydraulic functions and site-specific rainfall, soil texture, green vegetation fraction (GVF) and leaf area index (LAI) input data. Nevertheless, most of the simulated σθ–〈θ〉 pairs are located outside the envelope of measurements and below the lower bound, which shows that the model smooths spatial SWC variability. This can be mainly attributed to missing topography and terrain information and inadequate representation of spatial variability of soil texture and hydraulic parameters, as well as the model assumption of a uniform root distribution.

Saturated and unsaturated salt transport in peat from a constructed fen

Abstract. The underlying processes governing solute transport in peat from an experimentally constructed fen peatland were analyzed by performing saturated and unsaturated solute breakthrough experiments using Na+ and Cl− as reactive and non-reactive solutes, respectively. We tested the performance of three solute transport models, including the classical equilibrium convection–dispersion equation (CDE), a chemical non-equilibrium one-site adsorption model (OSA) and a model to account for physical non-equilibrium, the mobile–immobile (MIM) phases. The selection was motivated by the fact that the applicability of the MIM in peat soils finds a wide consensus. However, results from inverse modeling and a robust statistical evaluation of this peat provide evidence that the measured breakthrough of the conservative tracer, Cl−, could be simulated well using the CDE. Furthermore, the very high Damköhler number (which approaches infinity) suggests instantaneous equilibration between the mobile and immobile phases underscoring the redundancy of the MIM approach for this particular peat. Scanning electron microscope images of the peat show the typical multi-pore size distribution structures have been homogenized sufficiently by decomposition, such that physical non-equilibrium solute transport no longer governs the transport process. This result is corroborated by the fact the soil hydraulic properties were adequately described using a unimodal van Genuchten–Mualem model between saturation and a pressure head of ∼-1000 cm of water. Hence, MIM was not the most suitable choice, and the long tailing of the Na+ breakthrough curve was caused by chemical non-equilibrium. Successful description was possible using the OSA model. To test our results for the unsaturated case, we conducted an unsaturated steady-state evaporation experiment to drive Na+ and Cl− transport. Using the parameterized transport models from the saturated experiments, we could numerically simulate the unsaturated transport using Hydrus-1-D. The simulation showed a good prediction of observed values, confirming the suitability of the parameters for use in a slightly unsaturated transport simulation. The findings improve the understanding of solute redistribution in the constructed fen and imply that MIM should not be automatically assumed for solute transport in peat but rather should be evidence based.

Evaluation of hydrodynamic characteristics of porous media from one-step outflow experiments using RETC code

Abstract The ability of simulation models to accurately predict water flow and solute transport in unsaturated soils usually depends on the accuracy of the parametric models used to describe the water retention curve θ(h) and unsaturated hydraulic conductivity Κ(θ). Experiments were conducted to determine θ(h) and Κ(θ) relationships of six different porous media. θ(h) relationships were determined using Haines-type assembly or Richards' pressure cell chambers, depending on the soil type. K(θ) relationships were determined using the one-step outflow method. RETC code was used to analyze hydraulic properties. Experimental data were compared with those predicted by the Mualem-van Genuchten model using RETC for two prediction scenarios with three fitting parameters a, n, θr. The first scenario uses as input data the experimental θ(h) and saturated hydraulic conductivity (Ks) measurements and the second, the experimental θ(h), K(θ) and Ks measurements for two types of conductivity regression analysis. Concerning the second scenario, the Mualem model parameter p as an additional fitting parameter was also examined. Analysis of the results showed that the best method for predicting both the θ(h) and K(θ) relationships is to use simultaneously the experimental θ(h), K(θ) and Ks data with four fitting parameters a, n, θr, p.

Operational validation of HYDRUS (2D/3D) for capillary barriers using data of a 10-m tipping trough

Abstract Capillary barriers are an interesting alternative component for cover systems of landfills and contaminated sites. Provided they are sufficiently validated, soil hydrological models could be fast and powerful tools for the dimensioning of capillary barriers. Outflow rates measured in a 10 m long tipping trough for one material combination and two slopes from stationary periods were compared to simulation results of HYDRUS (2D/3D), Version 2.05. The measured outflow rates show a typical pattern with slope-dependent threshold values indicating the efficiency of the capillary barrier. This flow pattern could not be reproduced with HYDRUS (2D/3D) that for different input setups produced smooth patterns without thresholds. The input setup was varied for different soil hydraulic models (van Genuchten-Mualem vs. Brooks-Corey), homogeneous and heterogeneous transport domains (no scaling vs. stochastically distributed scaling factors considering the Miller-Miller similitude), different HYDRUS versions (standard vs. alternative; i.e., with material properties assigned either to finite element nodes or finite elements, respectively), and different lower boundary conditions (seepage face vs. free drainage). Differences between measured and simulated outflow patterns could be caused by the measurements, the application of the model, or by the model itself. The van Genuchten-Mualem model may not be suitable to describe the soil hydrological relationships of these particular materials. The reason for the mismatch, however, could not be identified yet.