Hide
Show all
Email this article Fitting soil particle-size distribution (PSD) models by PSD curve fitting software
Abstract
This paper describes a particle-size distribution (PSD) curve fitting software for analyzing the soil PSD and soil physical properties. A better characterization of soil texture can be obtained by describing the soil PSD using mathematical models. The mathematical equations of soil PSD are mainly used as a basis to estimate the soil hydraulic properties. Until now, many attempts are made to represent PSD curves using mathematical models, but selecting the best PSD model requires fitting all models to the PSD data, which would be difficult and time-consuming. So far, no specific program has been developed to fit the PSD models to the experimental data. A practical user-friendly software called "PSD Curve Fitting Software" was developed and introduced to program a simultaneous fitting of all models on soil PSD data of all samples. Some of the capabilities of this software are calculating evaluation statistics for all models and soils and their statistical properties such as average, standard deviation, minimum and maximum for all models, the amount of models’ fitting parameters and their statistical properties for all soil samples, soil water retention curve by Arya and Paris (1981) and Meskini-Vishkaee et al. (2014) methods, soil hydraulic conductivity by Arya et al. (1999) method, different textural and hydraulic properties, specific surface area, and other descriptive statistics of PSD for all soil samples. All calculated parameters are presented in an output Excel file format by the software. The software runs under Windows XP/7/8/10.
Keywords
Full Text:
PDFReferences
Arya, L.M., Leij, F.J., Shouse, P.J., van Genuchten, M.T., 1999. Relationship between the hydraulic conductivity function and the particle-size distribution. Soil Science Society of America Journal, 63(5): 1063–1070.
Arya, L.M., 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.
Bayat, H., Rastgo, M., Zadeh, M.M., Vereecken, H., 2015. Particle size distribution models, their characteristics and fitting capability. Journal of Hydrology, 529(3): 872–889.
Botula, Y.-D., Cornelis, W.M., Baert, G., Mafuka, P., Van Ranst, E., 2013. Particle size distribution models for soils of the humid tropics. Journal of Soils and Sediments, 13(4): 686–698. DOI:10.1007/s11368-012-0635-5.
Burnham, K.P., Anderson, D.R., 2003. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. Springer Science & Business Media, New York, USA.
Chau, J.F., Bagtzoglou, A.C., Willig, M.R., 2011. The effect of soil texture on richness and diversity of bacterial communities. Environmental Forensics, 12(4): 333–341.
Everitt, B.S., Skrondal, A., 2002. The Cambridge Dictionary of Statistics. Cambridge, Cambridge.
Fredlund, M.D., Fredlund, D., Wilson, G.W., 2000. An equation to represent grain-size distribution. Canadian Geotechnical Journal, 37(4): 817–827.
Gao, G.-L., Ding, G.-D., Wu, B., Zhang, Y.-Q., Qin, S.-G., Zhao, Y.-Y., Bao, Y.-F., Liu, Y.-D., Wan, L., Deng, J.-F., 2014. Fractal scaling of particle size distribution and relationships with topsoil properties affected by biological soil crusts. PLOS ONE, 9(2): e88559.
Gupta, S., Larson, W., 1979. Estimating soil water retention characteristics from particle-size distribution, organic matter percent, and bulk density. Water Resources Research, 15(6): 1633–1635. DOI: 10.1029/WR015i006p01633.
Haverkamp, R.T., Parlange, J.-Y., 1986. Predicting the water-retention curve from particle-size distribution: 1. sandy soils without organic matter. Soil Science, 142(6): 325–339.
Huang, L., Dong, B.C., Xue, W., Peng, Y.K., Zhang, M.X., Yu, F.H., 2013. Soil particle heterogeneity affects the growth of a rhizomatous wetland plant. PLOS ONE, 8(7): e69836.
MathWorks, 2018. MATLAB: the language of technical computing. Natick, Massachusetts, United States.
Meskini-Vishkaee, F., Mohammadi, M.H., 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 Earth System Sciences, 18(10): 4053–4063.
Nesbitt, A., Breytenbach, W., 2006. A particle size distribution model for manufactured particulate solids of narrow and intermediate size ranges. Powder Technology, 164(3): 117–123.
Piron, E., Latrille, E., Rene, F., 1997. Application of artificial neural networks for crossflow microfiltration modelling: “black-box” and semi-physical approaches. Computers & Chemical Engineering, 21(9): 1021–1030.
Shangguan, W., Dai, Y., García-Gutiérrez, C., Yuan, H., 2014. Particle-size distribution models for the conversion of Chinese data to FAO/USDA system. The Scientific World Journal, 2014(2014): 1–11.
Vaz, C.M.P., de Freitas Iossi, M., de Mendonça Naime, J., Macedo, A., Reichert, J.M., Reinert, D.J., 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.
Vipulanandan, C., Ozgurel, H.G., 2009. Simplifid relationships for particle-size distribution and permeation groutability limits for soils. Journal of Geotechnical and Geoenvironmental Engineering, 135(9): 1190–1197.
Weipeng, W., Jianli, L., Bingzi, Z., Jiabao, Z., Xiaopeng, L., Yifan, Y., 2015. Critical evaluation of particle size distribution models using soil data obtained with a laser diffraction method. PLOS ONE, 10(4): e0125048. DOI: 10.1371/journal.pone.0125048.
DOI: http://dx.doi.org/10.17951/pjss.2019.52.2.211
Date of publication: 2019-11-21 12:59:38
Date of submission: 2018-09-30 06:36:18
Statistics
Indicators
Refbacks
- There are currently no refbacks.
Copyright (c) 2019 Mostafa Rastgou, Hossein Bayat, MUHARRAM MANSOORIZADEH
This work is licensed under a Creative Commons Attribution 4.0 International License.