Role of Bimodal Particle-Size Distribution to Predict the Soil Water Retention Curve

Document Type : Research Paper

Authors

1 Assistant Professor, Department of Water Sciences and Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran.

2 PhD Graduated, Department of soil science and Engineering, College of agriculture, Tabriz University, Tabriz, Iran.

3 Professor, Department of Soil Science, College of Agricultural Sciences, University Of Tabriz, Tabriz, Iran.

4 Assistant Professor, Department of Soil Science, College of Agricultural Sciences, University Of Guilan, Rasht, Iran.

Abstract

The particle sizes distribution (PSD) has a major impact on the pore arrangement in the soil, which is the basis for many soil water retention curve (SWRC) models. Lack of some particles in PSD lead to bimodal distribution of soils. In this situation, the performance of developed SWRC models for normal soils were decreased. In this study, the accuracy of three models that estimate SWRC from PSD including Aria et al. (1999), Mohammadi and Vanclooster (MV) (2011), and modified MV, that combined with VanGenuchten (1980) model, (MV-VG) (2013) were investigated in unimodal and bimodal zone of soil textural triangle. For this purpose, 94 soil samples, with a wide range of physical properties including PSD and SWRC data, were selected from the UNSODA hydraulic properties database and their SWRC were estimated by the proposed models. Estimation accuracy was evaluated using RMSE, NSE and R2 statistics. Results showed that in unimodal soil textures including loam, silt loam and silty clay, the models have good accuracy. As well as in sand, sandy loam and loamy sand soils, because of high sand content, models accuracy not affected by bimodality. In soils associated with bimodal zone of soil textural triangle including sandy clay loam, clay loam, sandy clay and clay, SWRC prediction depended on bimodality index that proposed in this paper. The mean RMSE, NSE and R2 statistics for the three models in unimodal zone of soil textural triangle were obtained 0.044, 0.378 and 0.921 and in bimodal zone they were 0.062, -2.501 and 0.859 respectively. Also, it was found that the accuracy of the three models was different and the MV-VG model had insignificant correlation with the bimodality index and could estimate more accurately SWRC from PSD.

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References

Arya, L. M. and Paris, J. F. (1981). A physicoempirical model to predict the soil moisture characteristic from particle-size distribution and bulk density data. Soil Science Society of America Journal, .45(6), 1023–1030.
Arya, L. M., Leij, F. J., van Genuchten, M. T. and Shouse, P.J. (1999). Scaling parameter to predict the soil water characteristic from particle-size distribution data. Soil Science Society of America Journal, 63(3), 510–519.
Basile, A. and D’Urso, G. (1997). Experimental corrections of simplified methods for predicting water retention curves in clayloamy soils from particle-size determination. Soil Technology,10(3), 261–272.
Chang, C. C. and Cheng, D. H. (2018). Predicting the soil water retention curve from the particle size distribution based on a pore space geometry containing slit-shaped spaces. Hydrology and Earth System Sciences, 22(9), 4621-4632.
De Condappa, D., Galle, S.,  Dewandel, B. and Haverkamp, R. (2008). Bimodal zone of the soil textural triangle: common in tropical and subtropical regions. Soil Science Society of America Journal, 72(1), 33-40.
Fredlund, M. D., Wilson, G. W. and Fredlund, D. G. (2002). Use of the grain-size distribution for estimation of the soil–water characteristic curve. Canadian Geotechnical Journal, 39(5),1103–1117.
Gee, G. W. and Bauder, J. W. (1986). Particle-size analysis, In A. Klute (Ed.), Methods of Soil Analysis. Part 1. Physical and Mineralogical Methods, 2nd edn. American Society of Agronomy, Madison, Wisconsin, (pp. 383–411).
Ghanbarian-Alavijeh, B. and Hunt, A. (2012). Estimation of soil-water retention from particle-size distribution: fractal approaches. Soil Science, 177(5), 321-326.
Haverkamp R. and Parlance J. Y. (1986). Prediction the water retention curve from particle size distribution: 1. Sandy soils without organic matter. Soil Science, 142, 325-339.
Hwang, S. I. and Choi, S. I. (2006). Use of a lognormal distribution model for estimating soil water retention curves from particle-size distribution data. Journal of Hydrology, 323(1-4), 325-334.
Krause, P., Boyle, D.P. and Bäse, F. )2005(. Comparison of different efficiency criteria for hydrological model assessment. Advances in geosciences, 5, 89-97.
Li, D., Gao, G., Shao, M. A. and Fu, B. (2016). Predicting available water of soil from particle-size distribution and bulk density in an oasis–desert transect in northwestern China. Journal of Hydrology, 538, 539-550.
Meskini-Vishkaee, F., Mohammadi, M. H. and Vanclooster, M. (2014). Predicting the soil moisture retention curve, from soil particle size distribution and bulk density data using a packing density scaling factor. Hydrology and Earth System Sciences, 18(10), 4053-4063.
Mishra, S., Parker, J. C. and Singhal, N. (1989). Estimation of soil hydraulic properties and their uncertainty from particle size distribution data. Journal of Hydrology, 108, 1–18.
Mohammadi, M. H. and Meskini-Vishkaee, F. (2013). Predicting soil moisture characteristic curves from continuous particle-size distribution data. Pedosphere, 23(1), 70-80.
Mohammadi, M. H., & Vanclooster, M. (2011). Predicting the soil moisture characteristic curve from particle size distribution with a simple conceptual model. Vadose Zone Journal, 10(2), 594-602.
Rezaee, L., Shabanpour, M. Davatgar, N. (2011). Estimating the scaling parameter of Arya-Paris model by various methods to improve estimation of soil moisture characteristic curve. Water and Soil Science, 21(3), 103-114. (In Farsi).
Shang, L. and Li, D. (2019). Comparison of different approaches for estimating soil water characteristic curves from saturation to oven dryness. Journal of Hydrology, 577, 123971.
van Genuchten, MT. (1980). A closed form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Science Society of America Journal, 44, 892–898.
Vaz, C. M. P., de Freitas Iossi, M., de Mendonça Naime, J., Macedo, A., Reichert, J. M., Reinert, D. J. and Cooper, M. (2005). Validation of the Arya and Paris water retention model for Brazilian soils. Soil Science Society of America Journal, 69(3) 577-583.
Zhang, L. and Q. Chen. (2005). Predicting bimodal soil–water characteristic curves. Journal of Geotechnical and Geoenvironmental Engineering, 131(5), 666-670.
Zhuang, J., Jin, Y. and Miyazaki T. (2001). Estimating water retention characteristic from soil particle-size distribution using a non-similar media concept. Soil Science, 166(5), 308-321.
Iranian Journal of Soil and Water Research
Volume 51, Issue 5
August 2020
Pages 1081-1091

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