Measured Water Retention Data Research Articles

Hydraulic Property Estimation of Green Roof Substrates from Soil Moisture Time Series

The adoption of green roofs is an effective practice for mitigating environmental issues in urban areas caused by extreme weather conditions. However, certain design aspects of green roofs, such as the characterization of the physical properties of their substrates, need a better understanding. This study proposes a simple method for estimating two hydraulic properties of green roof substrates based on the evolution of moisture during drying periods, or drydowns, where evaporative processes dominate: the weighted-mean diffusivity and the saturated hydraulic conductivity. Soil moisture was monitored using 12 in situ sensors from 2015 to 2020 in a study involving six different green roof plots composed of various mixtures of demolition-recycled aggregates and organic substrates. A universal parameterization for determining water diffusivity in soils was applied to estimate the weighted-mean hydraulic diffusivity. As a by-product, the saturated hydraulic conductivity was estimated from the evaluated diffusivity and the measured water retention data. The median values obtained for and range from 14.5 to 29.9 cm2d−1 and from 22 to 361 cmd−1, respectively. These values fall within the ranges reported by other research groups using direct measurement methods and supports the validity of Brutsaert’s model for green roof substrates. Furthermore, an increase in and a decrease in were observed as the percentage of recycled aggregates in the substrates increased, which could be considered for design purposes.

HYPROP-FIT to Model Rock Water Retention Curves Estimated by Different Methods

The water retention curve, which relates the matric potential, ψ, to the water content, θ, is essential to describe the flow processes in the unsaturated zone and provides useful information for environmental and engineering applications. There are few studies devoted to measuring the rock water retention curves due to the rock’s tightness, which makes it more technically difficult to use specific methods. In this study, we tested four different methods to measure water retention curves of two lithotypes of carbonate porous rocks with the aim to find the most effective to be applied to rock samples. Suction table, evaporation, Quasi-Steady Centrifuge, and WP4-T dewpoint potentiameter methods have been applied. The Quasi-Steady Centrifuge method proved to be the only one capable of determining water retention curves in the entire water content range and capturing the bimodality of the tested media with respect to the other methods. The measured water retention data were fitted with HYPROP-FIT software that allows us to accurately describe the WRCs and obtain critical parameters for the numerical simulation of flow and transport through the vadose zone, which plays a key role in various environmental issues.

Studying Unimodal, Bimodal, PDI and Bimodal-PDI Variants of Multiple Soil Water Retention Models: I. Direct Model Fit Using the Extended Evaporation and Dewpoint Methods

This study focuses on the reliable parametrization of the full Soil Water Retention Curve (SWRC) from saturation to oven-dryness using high resolution but limited range measured water retention data by the Hydraulic Property Analyzer (HYPROP) system. We studied the performance of five unimodal water retention models including the Brooks and Corey model (BC model), the Fredlund and Xing model (FX model), the Kosugi model (K model), the van Genuchten constrained model with four free parameters (VG model), and the van Genuchten unconstrained model with five free parameters (VGm model). In addition, eleven alternative expressions including Peters–Durner–Iden (PDI), bimodal, and bimodal-PDI variants of the original models were evaluated. We used a data set consisting of 94 soil samples from Turkey and the United States with high-resolution measured data (a total of 9264 measured water retention data pairs) mainly via the HYPROP system and supplemented for some samples with measured dry-end data using the WP4C instrument. Among unimodal expressions, the FX and the K models with the Mean Absolute Error (MAE) values equal to 0.005 cm3 cm−3 and 0.015 cm3 cm−3 have the highest and the lowest accuracy, respectively. Overall, the alternative variants provided a better fit than the unimodal expressions. The unimodal models, except for the FX model, fail to provide reliable dry-end estimations using HYPROP data (average MAE: 0.041 cm3 cm−3, average r: 0.52). Our results suggested that only models that account for the zero water content at the oven dryness and properly shift from the middle range to dry-end (i.e., the FX model and PDI variants) can adequately represent the full SWRC using typical data obtained via the HYPROP system.

Measurement and estimation of the soil water retention curve using the evaporation method and the pseudo continuous pedotransfer function

HYPROP (Hydraulic Property Analyzer) system works based on the simplified evaporation method, which determines soil hydraulic properties in the laboratory. This system simultaneously monitors the changes in weight of soil samples as well as the soil matric potential at two depths throughout a drying process governed by evaporation from the soil surface. In this study, we examined the performance of the pseudo continuous pedotranfer function (PC-PTF) to estimate the soil water retention curve (SWRC) using high resolution data measured by HYPROP system. The dataset consisted of 7963 measured water retention data points obtained from 81 Turkish soil samples from which 60%, 20% and 20% were randomly selected for training, cross-validation and test subsets, respectively. The best PC-PTF developed in this study with a mean absolute error of 0.023 m3 m−3 (a root mean square error of 0.033 m3 m−3) and a correlation coefficient of 0.96 showed promising performance considering the typical performance range (RMSE = 0.034–0.085 m3 m−3) for parametric PTFs estimating SWRC. The best PC-PTF used soil textural information, soil bulk density, the percentage of stable aggregates, soil organic matter content and the initial water content as the input attributes. PTFs developed in this study also ranked high among previously developed PC-PTFs (with RMSE ranging from 0.027 to 0.056 m3 m−3) using sparse datasets collected via the traditional equilibrium approach (i.e. sandbox apparatus /pressure plates extractor). We, therefore, recommend further application of the PC-PTF approach for development of PTFs using high resolution data obtained by HYPROP system.

Predicting the Campbell Soil Water Retention Function: Comparing Visible–Near‐Infrared Spectroscopy with Classical Pedotransfer Function

Core Ideas The Campbell model was anchored at a soil water content of −1000 cm H2O matric potential. The two model parameters were predicted using either soil fines or vis–NIR spectroscopy. Both methods accurately predicted the soil water retention curve. The soil water retention curve (SWRC) is essential for the modeling of water flow and chemical transport in the vadose zone. The Campbell function and its b (pore‐size distribution index) parameter fitted to measured data is a simple method to quantify retention under relatively moist conditions. Measuring soil water retention is time consuming, and a method to accurately predict the Campbell relation from either typically available soil parameters such as bulk density, clay‐size fraction, and organic matter content (soil fines) or from visible–near‐infrared (vis–NIR) spectroscopy may provide a fast and inexpensive alternative. However, the traditional Campbell model has a reference point at saturated water content, and this soil‐structure‐dependent water content will typically be poorly related to basic texture properties and thus be poorly predicted from vis–NIR spectra. In this study, we anchor the Campbell model at the water content at −1000 cm H2O matric potential [log(1000)= pF 3]. Agricultural soil samples with a wide textural range from across Denmark were used. Soil water retention was measured at a number of matric potentials between pF 1 and 3. The soil water content at pF 3 and Campbell b were both well predicted using either a soil‐fines‐based pedotransfer function or vis–NIR spectroscopy. The resulting Campbell function anchored at pF 3 compared closely to measured water retention data for a majority of soils. The ability of the two methods to also predict field average SWRC was evaluated for three fields. Field average, predicted SWRC compared well with field average measured data, with vis–NIR overall performing better.

Predicting water permeability and relative gas permeability of unsaturated cement-based material from hydraulic diffusivity

In this paper, unsaturated water permeability and relative gas permeability of cement-based materials are predicted indirectly. First, the theoretical relationship between water permeability and hydraulic diffusivity is thoroughly analyzed, which leads to a new restriction on capacity function, the first derivative of water retention curve (WRC) model. To comply with this restriction, a new WRC model is then proposed, based on which unsaturated water permeability can be easily estimated from hydraulic diffusivity. Furthermore, the relative gas permeability is evaluated from relative water permeability through their relationship. The proposed WRC model is validated with measured water retention data of various cement-based materials. Moreover, predicted relative gas permeability agrees with reported testing results very well. Additionally, the influence of fitting parameters of the WRC model and shape parameter, which determines the shape of hydraulic diffusivity, is investigated. It is found that they have rather limited effects on relative water and gas permeability.

Direct determination of the Brooks–Corey hydraulic functions by fitting an extended power function to the outflow method data

Summary A method is developed for the direct determination of the parameters characterizing the Brooks and Corey closed-form hydraulic functions (water retention curve and hydraulic conductivity function) using data obtained only from one-step outflow experiments. Simple algebraic equations are derived to calculate directly the Brooks and Corey model parameters. The only parameters involved in these equations are empirical parameters obtained by a simple curve-fitting procedure applied to the experimental outflow data for a simple three-parameter power form equation. In addition, the method requires the value of the water content obtained at the pressure head of −150 m. The suggested method is verified numerically by simulating a one-step outflow experiment of a hypothetical soil. The proposed method was also verified from one-step outflow experimental data. The predicted soil water retention curve is compared favorably with measured water retention data. The coefficient of determination R2 is greater than 0.87 in all cases examined.

EVALUATION OF THE ARYA-PARIS MODEL FOR ESTIMATING WATER RETENTION CHARACTERISTICS OF LIGNITIC MINE SOILS

Mine soil materials may be viewed as man-made systems that consist of spatially disordered soil and sediment components, which are in an initial stage of soil development. A question is whether methods and approaches developed for natural soils may also be used for such artificially created soil materials. The applicability of the Arya and Paris pedotransfer function to obtain hydraulic properties from the particle size distribution and bulk density was tested for lignitic mine soil material of the Lusatian Lignite Mining District in eastern Germany. The scaling factor α in this model was evaluated by (i) fitting of the water retention curves estimated with the Arya-Paris model (APM) to measured water retention data and (ii) interpretation of α as a fractal dimension of the pore channels and derivation of this fractal dimension from the fractal dimension of the particle size distribution. The two tested fractal approaches resulted in relatively inaccurate predictions of the water content. The use of a single fitted α value for each depth yielded α values between 1.05 and 1.47. Because of the inability of the APM to account for residual water contents in this sandy soil material, a correction was applied. The cumulative mass fraction fractal method did not improve the estimation in comparison with the retention curves calculated with a constant α value of 1.38. The closest fits with the data were obtained by using a variable α value that depended on the particle size. The accuracy of the predictions of the APM in the higher suction range could be improved (lower mean deviations and root mean square deviations of water content) by using a linear water content-dependent correction factor. Better estimates of water retention in the relatively dry range may be significant for simulation of water budgets of mine spoil sites in the Lusatian Mining District.

Hydraulic and transport properties of the plant–soil system estimated by inverse modelling

SummaryModelling soil water flow and solute transport under field conditions requires the knowledge of many parameters that are difficult to determine directly. Values determined on small isolated samples in the laboratory are often not representative of field situations. We investigated the applicability of inverse modelling to a soil–plant system in lysimeter experiments. We also tested whether parameters obtained from one experiment could be applied to another with the same soil. In a lysimeter planted with young trees, we first did a multistep drainage experiment and then a long‐term bromide tracer experiment with atmospheric boundary conditions at the soil surface. To estimate the unsaturated hydraulic properties, we linked the inverse program SUFI (Sequential Uncertainty FItting) to the flow and transport model HYDRUS5. A comparison of several scenarios showed that the resulting values of parameters depended strongly on the data used for calibration and the formulation of the objective function. The results suggested that inverse modelling could be used to identify important processes. Inversely obtained parameters gave better predictions for a second experiment when more variables were considered in the objective function and when the range of hydraulic conditions was wider. Furthermore, with retention curves directly fitted to measured water retention data we achieved acceptable results. Despite some limitations, the inverse approach was found to be a sound and useful procedure for estimating parameters of a complex system involving water uptake by roots, solute transport and unsaturated flow.

ESTIMATING WATER RETENTION CHARACTERISTIC FROM SOIL PARTICLE-SIZE DISTRIBUTION USING A NON-SIMILAR MEDIA CONCEPT

Soil water retention characteristic is an important property of soil. Indirect estimation of this property using easily measurable soil properties remains the research focus of many soil scientists. In this study, a general approach was proposed to derive soil water retention characteristic from soil particle-size distribution and bulk density using a non-similar media concept. Effectiveness of the developed model was tested against measured water retention data of 130 sieved soils with textures ranging from sand to heavy clay. The values of the root mean square error (RMSE) between estimated and experimental pressure heads ranged from 0.4340 to 0.7287 Log cm H2O for all 11 soil textual classes tested in this study. In addition, the new model was compared with the Arya-Paris model, and the results showed that the proposed approach could reduce the overall estimation deviation significantly. The comparison in terms of RMSE values indicated that for 61% of the soils, estimations by the new model were better than those by the best one of the three approaches of the Arya-Paris model, and for about 10% of the soils, the results using the two models were similar. Evidently, the proposed model employs a simple calculation procedure and applies well to soils of all textures except sandy soils.

New geometry factors for hydraulic property-based soil solution electrical conductivity models

Improved methods are needed to intensively measure ionic solutes in soils. The concentration Ci of ionic solutes in soils is directly proportional to soil solution electrical conductivity σw. Time domain reflectometry (TDR) measures both soil water content θ and bulk soil electrical conductivity σa using the same probes. However, physical/conceptual models are required along with TDR measurements in order to use TDR for in situ estimates of Ci. We discuss a modeling approach [Mualem and Friedman, 1991] based on assumed analogy between tortuosity of electrical and hydraulic flow paths in variably saturated soils. We review the model approach, then derive a general expression for a pore geometry factor FG considering flow of electrical current through randomly distributed capillary soil pores. Two FG are derived based on two conceptual considerations of tortuous capillary length. Four water retention models (WRM) are used to describe soil hydraulic properties in the FG. When fitted to the same measured water retention data, the four WRMs provided substantially different magnitudes for FG. The model was then compared in terms of σw estimates using the two new FG in combination with field-measured θ and σa. One of the new FG produced smaller estimated σw than did that proposed in the original model. This is desirable based on our own and several other published comparisons that indicated the original model may overestimate σw in comparison with independent measurements.

Influence of three‐parameter conversion methods between van Genuchten and Brooks‐Corey Functions on soil hydraulic properties and water‐balance predictions

The Brooks‐Corey functions are commonly used in hydrologic models, with parameters obtained by fitting the functions directly to measured soil water retention data or by conversion methods from the van Genuchten functions which are continuous across the domain of matric suctions. Problems in fitting the BC functions directly to the retention data motivated use of the conversion methods. However, differences in converted parameters could significantly influence model predictions. We compared the direct fitting method and the conversion methods of Lenhard et al., Morel‐Seytoux et al., and van Genuchten using measured water retention data during drainage and determined the influence of these methods on hydrological predictions when the converted parameters were used in the root zone water quality model. The conversion methods had significant influence on predictions of water retention, hydraulic conductivity, runoff, and evapotranspiration, with the observed level of significance (p ≤ 0.006) much lower than the test level of significance (α = 0.05). The method of Morel‐Seytoux et al. inadequately described measured water retention data (p=0.027), whereas the other two methods adequately described the data at relatively high suctions (p ≥ 0.687), deviations occurred around the air‐entry suction. The method of Lenhard et al. best reproduced the characteristics of the Brooks‐Corey functions (p ≥ 0.31) and could be used to obtain the Brooks‐Corey parameters simply and reproducibly.