Prediction of clay content from water vapour sorption isotherms considering hysteresis and soil organic matter content

Arthur, Emmanuel; Tuller, Markus; Møldrup, Per; Jensen, Dan Karup; Jonge, Lis Wollesen de

doi:10.1111/ejss.12191

Cited by 46 publications

(61 citation statements)

References 29 publications

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“…The slightly better prediction accuracy of the MCM compared to the CM is due to the difference in the matric potential at “zero water content” (ψ 0 ), while CM uses −10 6.8 cm H 2 O, MCM uses −10 6.9 cm H 2 O (see section 2 for details). This trend of slightly better predictions for the MCM compared to CM was also observed by Arthur et al () for over 200 soils. This suggests that, although recent studies ( Lu and Khorshidi , ) point out that ψ 0 depends on clay mineralogy, −10 6.9 cm H 2 O may represent a more accurate average value for modelling purposes.…”

Section: Resultssupporting

confidence: 83%

“…Comparison of the clay content prediction accuracy of the (a) AM, Arthur et al (), (b) CM, Chen et al (), and (c) MCM, the modified Chen et al () models. RMSE, root mean squared error; ME, mean error (bias); MAE, mean absolute error.…”

Section: Resultsmentioning

confidence: 99%

“…The relatively higher accuracy of the AM compared to CM and MCM can be attributed to the consideration of hysteresis in the model. Soil water sorption hysteresis exists in the RH range from 3 to 93% ( Arthur et al, ; Prunty and Bell , ) and disregarding hysteresis in clay content prediction models could introduce prediction errors as large as 12% in fine‐textured soils ( Arthur et al, ). The slightly better prediction accuracy of the MCM compared to the CM is due to the difference in the matric potential at “zero water content” (ψ 0 ), while CM uses −10 6.8 cm H 2 O, MCM uses −10 6.9 cm H 2 O (see section 2 for details).…”

Section: Resultsmentioning

confidence: 99%

“…where A is the regression coefficient at a given RH value, and θ m is the gravimetric water content (%) at the given RH. The soils were equilibrated at an RH of 28% by adsorption and to compute A , we used the following equation from Arthur et al ():

true A = 26.84 - 0.743 x + 0.011 x^{2} - 5.93 \times 10^{- 5} x^{3},

…”

Section: Methodsmentioning

confidence: 99%

“…A slightly modified version of CM is the Modified Chen Model (MCM) which utilizes −10 6.9 cm H 2 O as the ψ at zero water content rather than −10 6.8 cm H 2 O ( Arthur et al, ). The MCM is given as:

true CL normal% = \frac{7.55 \times θ_{m}}{6.9 - normallog false(- Ψ false)} + 1.57 .

…”

Section: Methodsmentioning

confidence: 99%

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Validation of water sorption‐based clay prediction models for calcareous soils

Arthur

Razzaghi

Moosavi

2017

J. Plant Nutr. Soil Sci.

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Soil particle size distribution (PSD), particularly the active clay fraction, mediates soil engineering, agronomic and environmental functions. The tedious and costly nature of traditional methods of determining PSD prompted the development of water sorption‐based models for determining the clay fraction. The applicability of such models to semi‐arid soils with significant amounts of calcium carbonate and/or gypsum is unknown. The objective of this study was to validate three water sorption‐based clay prediction models for 30 calcareous soils from Iran and identify the effect of CaCO3 on prediction accuracy. The soils had clay content ranging from 9 to 61% and CaCO3 from 24 to 97%. The three water sorption models considered showed a reasonably fair prediction of the clay content from water sorption at 28% relative humidity (RMSE and ME values ranging from 10.6 to 12.1 and −8.1 to −4.2, respectively). The model that considers hysteresis had better prediction accuracy than the other two that do not. Moreover, the prediction errors of all three models arose from under‐prediction of the clay content. The amount of hygroscopic water scaled by clay content decreased with increasing CaCO3 content. The low organic carbon content of the soils and the low fraction of low‐activity clay minerals like kaolinite suggested that the clay content under‐predictions were due to large CaCO3 contents. Thus, for such water‐sorption based models to work accurately for calcareous soils, a correction factor that considers the reduction of water content due to large CaCO3 content should be included.

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Section: Resultssupporting

confidence: 83%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

true A = 26.84 - 0.743 x + 0.011 x^{2} - 5.93 \times 10^{- 5} x^{3},

…”

Section: Methodsmentioning

confidence: 99%

true CL normal% = \frac{7.55 \times θ_{m}}{6.9 - normallog false(- Ψ false)} + 1.57 .

…”

Section: Methodsmentioning

confidence: 99%

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Validation of water sorption‐based clay prediction models for calcareous soils

Arthur

Razzaghi

Moosavi

2017

J. Plant Nutr. Soil Sci.

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Evaluation of theoretical and empirical water vapor sorption isotherm models for soils

Arthur

Tuller

Møldrup

et al. 2016

Water Resources Research

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The mathematical characterization of water vapor sorption isotherms of soils is crucial for modeling processes such as volatilization of pesticides and diffusive and convective water vapor transport. Although numerous physically based and empirical models were previously proposed to describe sorption isotherms of building materials, food, and other industrial products, knowledge about the applicability of these functions for soils is noticeably lacking. We present an evaluation of nine models for characterizing adsorption/desorption isotherms for a water activity range from 0.03 to 0.93 based on measured data of 207 soils with widely varying textures, organic carbon contents, and clay mineralogy. In addition, the potential applicability of the models for prediction of sorption isotherms from known clay content was investigated. While in general, all investigated models described measured adsorption and desorption isotherms reasonably well, distinct differences were observed between physical and empirical models and due to the different degrees of freedom of the model equations. There were also considerable differences in model performance for adsorption and desorption data. While regression analysis relating model parameters and clay content and subsequent model application for prediction of measured isotherms showed promise for the majority of investigated soils, for soils with distinct kaolinitic and smectitic clay mineralogy predicted isotherms did not closely match the measurements.

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A complete soil hydraulic model accounting for capillary and adsorptive water retention, capillary and film conductivity, and hysteresis

Rudiyanto¹,

Sakai

Genuchten

et al. 2015

Water Resources Research

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A soil hydraulic model that considers capillary hysteretic and adsorptive water retention as well as capillary and film conductivity covering the complete soil moisture range is presented. The model was obtained by incorporating the capillary hysteresis model of Parker and Lenhard into the hydraulic model of Peters‐Durner‐Iden (PDI) as formulated for the van Genuchten (VG) retention equation. The formulation includes the following processes: capillary hysteresis accounting for air entrapment, closed scanning curves, nonhysteretic sorption of water retention onto mineral surfaces, a hysteretic function for the capillary conductivity, a nonhysteretic function for the film conductivity, and a nearly nonhysteretic function of the conductivity as a function of water content (θ) for the entire range of water contents. The proposed model only requires two additional parameters to describe hysteresis. The model was found to accurately describe observed hysteretic water retention and conductivity data for a dune sand. Using a range of published data sets, relationships could be established between the capillary water retention and film conductivity parameters. Including vapor conductivity improved conductivity descriptions in the very dry range. The resulting model allows predictions of the hydraulic conductivity from saturation until complete dryness using water retention parameters.

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Prediction of clay content from water vapour sorption isotherms considering hysteresis and soil organic matter content

Cited by 46 publications

References 29 publications

Validation of water sorption‐based clay prediction models for calcareous soils

Validation of water sorption‐based clay prediction models for calcareous soils

Evaluation of theoretical and empirical water vapor sorption isotherm models for soils

A complete soil hydraulic model accounting for capillary and adsorptive water retention, capillary and film conductivity, and hysteresis

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