https://doi.org/10.4081/jae.2023.1542
On evaluating the hypothesis of shape similarity between soil particle-size distribution and water retention function
Published: 26 October 2023
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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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Two pedotransfer functions (PTFs) are available in the literature enabling the soil water retention function (WRF) to be estimated from knowledge of the soil particle-size distribution (PSD), oven-dry soil bulk density (rb), and saturated soil water content (qs): i) the Arya and Heitman model (PTF-AH), and ii) the Mohammadi and Vanclooster model (PTF-MV). These physicoempirical PTFs rely on the hypothesis of shape similarity between PSD and WRF, and do not require the calibration of the input parameters. In the first stage, twenty-seven PSD models were evaluated using 4,128 soil samples collected in Campania (southern Italy). These models were ranked according to the root mean square residuals (RMSR), corrected Akaike information criterion (AICc), and adjusted coefficient of determination (R2adj). In the second stage, three subsets of PSD and WRF data (DS-1, DS-2, and DS-3), comprising 282 soil samples, were used to evaluate the two PTFs using the best three PSD models selected in the first stage. The hypothesis of shape similarity was assumed as acceptable only when the RMSR value was lower than the field standard deviation of the WRFs (s*), which is viewed as a tolerance threshold and computed from the physically based scaling approach proposed by Kosugi and Hopmans (1998). In the first study area (DS- 1), characterized by a fairly uniform, loamy textured volcanic soil, the PTF-AH outperformed the PTF-MV and both PTFs provided reasonable performance within the acceptance threshold (i.e., RMSR < s*). In the other two heterogeneous field sites (DS-2 and DS-3, characterized by soil textural classes that span from clay and clay-loam to loam and even sandy-loam soils), the PTF-MV (with 3% to 6% RMSR surpassing s*) outperformed the PTF-AH (with 8% to 30% RMSR surpassing s*) and the majority of RMSR values were larger than those obtained in the original studies. The mean relative error (MRE) revealed that the PTF-MV systematically underestimates the measured WRFs, whereas the PTF-AH provided negative MRE values indicating an overall overestimation. The outcomes of our study provide a critical evaluation when using calibration-free PTFs to predict WRFs over large areas
Allocca, C., A. Castrignanò, P. Nasta, N. Romano, 2023. Regional-scale assessment of soil functions and resilience indicators: Accounting for change of support to estimate primary soil properties and their uncertainty. Geoderma 431, 116339,
DOI: https://doi.org/10.1016/j.geoderma.2023.116339
Amanabadi S, Vazirinia M, Vereecken H, Asefpour Vakilian K, Mohammadi MH. 2019. Learning-based pedotransfer functions of water retention curve with particle size distribution data. Eurasian Soil Science. 52 (12): 1555–1571.
DOI: https://doi.org/10.1134/S106422931930001X
Andersson S. 1990. Markfysikaliska undersökningar i odlad jord,XXVI. Om mineraljordens och mullens rumsutfyllande egenskaper. En teoretisk studie. (In Swedish). Swedish University of agricultural sciences, Uppsala, p. 70.
Antinoro C, Bagarello V, Ferro V, Giordano G, Iovino M. 2014. A simplified approach to estimate water retention for Sicilian soils by the Arya–Paris model. Geoderma 213: 226–234
DOI: https://doi.org/10.1016/j.geoderma.2013.08.004
Arya LM, Paris JF. 1981. A physico-empirical model to predict the soil moisture characteristic from particle-size distribution and bulk density data. Soil Sci. Soc. Am. J., 45, 1023-1030.
DOI: https://doi.org/10.2136/sssaj1981.03615995004500060004x
Arya LM, Heitman JL. 2015. A non-empirical method for computing pore radii and soil water characteristics from particle-size distribution. Soil Sci. Soc. Am. J. 79:1537–1544
DOI: https://doi.org/10.2136/sssaj2015.04.0145
Arya LM, Bowman DC, Thapa BB, Kassel DK. 2008. Scaling soil water characteristics of golf course and athletic field sands from particle-size distribution. Soil Sci. Soc. Am. J., 72, 25-32.
DOI: https://doi.org/10.2136/sssaj2006.0232
Arya LM, Leij FJ, van Genuchten Mth, Shouse P. 1999. Scaling parameter to predict the soil water characteristic from particle-size distribution data. Soil Sci. Soc. Am. J., 63, 510-519.
DOI: https://doi.org/10.2136/sssaj1999.03615995006300030013x
Arya LM, Heitman JL. 2018. Response to “Comment on ‘A Non-Empirical Method for Computing Pore Radii and Soil Water Characteristics from Particle Size Distribution’ by Arya and Heitman (2015)” Soil Sci. Soc. Am. J. 82:1595–1596.
DOI: https://doi.org/10.2136/sssaj2018.01.0063r
Ayoubi S, Karami M. 2019. Pedotransfer functions for predicting heavy metals in natural soils using magnetic measures and soil properties. Journal of Geochemical Exploration, 197: 212–219.
DOI: https://doi.org/10.1016/j.gexplo.2018.12.006
Bah AR, Kravchuk O, Kirchhof G. 2009. Fitting performance of particle-size distribution models on data derived by conventional and laser diffraction techniques. Soil Sci. Soc. Am. J., 73, 1101-1107.
DOI: https://doi.org/10.2136/sssaj2007.0433
Bayat H, Rastgo M, Zadeh MM, Vereecken H. 2015. Particle size distribution models, their characteristics and fitting capability. J. Hydrol. 529: 872–889.
DOI: https://doi.org/10.1016/j.jhydrol.2015.08.067
Bayat H, Rastgou M, Nemes A, Mansourizadeh M, Zamani P. 2017. Mathematical models for soil particle-size distribution and their overall and fraction-wise fitting to measurements. European Journal of Soil Science. 68, 345–364.
DOI: https://doi.org/10.1111/ejss.12423
Bird N, Perrier E, Rieu M. 2000. The water retention function for a model of soil structure with pore and solid fractal distributions. European Journal of Soil Science. 51, 55–63.
DOI: https://doi.org/10.1046/j.1365-2389.2000.00278.x
Bittelli M, Flury M. 2009. Errors in water retention curves determined with pressure plates. Soil Sci. Soc. Am. J. 73:1453–1460 doi:10.2136/sssaj2008.0082.Bouyoucos GJ. 1951. A recalibration of the hydrometer method for making mechanical analysis of soils. Agron. J. 43: 434 – 438.
DOI: https://doi.org/10.2136/sssaj2008.0082
Bouyoucos GJ. 1951. A recalibration of the hydrometer method for making mechanical analysis of soils. Agron. J. 43: 434 – 438.
DOI: https://doi.org/10.2134/agronj1951.00021962004300090005x
Buchan GD. 1989. Applicability of the simple lognormal model to particle-size distribution in soils. Soil Science. 147: 155–161.
DOI: https://doi.org/10.1097/00010694-198903000-00001
Buchan GD, Grewal K, Robson A. 1993. Improved models of particle-size distribution: an illustration of model comparison techniques. Soil Science Society of America Journal. 57: 901–908.
DOI: https://doi.org/10.2136/sssaj1993.03615995005700040004x
Campos-Guereta I, Dawson A, Thom N. 2021. An alternative continuous form of Arya and Paris model to predict the soil water retention curve of a soil. Adv. Water Res. 154: 103968.
DOI: https://doi.org/10.1016/j.advwatres.2021.103968
Chan TP, Govindaraju RS. 2004. Estimating soil water retention curve from particle-size distribution data based on polydisperse sphere systems. Vadose Zone J. 3: 1443-1454.
DOI: https://doi.org/10.2113/3.4.1443
Chang CC, Cheng DH, Qiao XY. 2019. Improving estimation of pore size distribution to predict the soil water retention curve from its particle size distribution. Geoderma 340: 206 – 212.
DOI: https://doi.org/10.1016/j.geoderma.2019.01.011
Cheshmberah F, Zolfaghari A.A., Taghizadeh-Mehrjardi R, Scholten T. 2022. Evaluation of mathematical models for predicting particle size distribution using digital soil mapping in semiarid agricultural lands. Geocarto International. 37: 1-23.
DOI: https://doi.org/10.1080/10106049.2022.2076911
Ciollaro G, Romano N. 1995. Spatial variability of the hydraulic properties of a volcanic soil. Geoderma 65:263-282.
DOI: https://doi.org/10.1016/0016-7061(94)00050-K
Cornelis WM, Ronsyn J, Van Meirvenne M, Hartmann R. 2001. Evaluation of pedotransfer functions for predicting the soil moisture retention curve. Soil Sci. Soc. Am. J. 65:638–648.
DOI: https://doi.org/10.2136/sssaj2001.653638x
Day PR. 1965. Particle fractionation and particle-size analysis, in Methods of Soil Analysis, edited by C. A. Black, pp. 545–567, American Society of Agronomy Inc., Madison, Wis.
DOI: https://doi.org/10.2134/agronmonogr9.1.c43
Elfaki JT, Gafer MA, Sulieman MM, Ali ME. 2016. Hydrometer method against pipette method for estimating soil particle size distribution in some soil types selected from Central Sudan. Int. J. Eng. Res. Adv. Tech. 2 (2): 25 – 41.
Esmaeelad L, Siavashi F, Seyedmohammadi J, Shabanpour M. 2016. The best mathematical models describing particle size distribution of soils. Model. Earth Syst. Environ. 2:166,
DOI: https://doi.org/10.1007/s40808-016-0220-9
Fredlund MD, Fredlund D, Wilson GW. 2000. An equation to represent grain-size distribution. Canadian Geotechnical Journal. 37: 817–827.
DOI: https://doi.org/10.1139/t00-015
Gee GW, Bauder JW. 1986. Particle-size analysis. In: Klute, A. (Ed.), Methods of Soil Analysis. Part 1., 2nd ed. Agron. Monogr. 9. ASA and SSSA, Madison, WI, pp. 383 – 411.
DOI: https://doi.org/10.2136/sssabookser5.1.2ed.c15
Gee GW, Or, D. 2002. Particle-size analysis. In: Dane, J.H., Topp, G.C. (Eds.), Methods of Soil Analysis: Part 4 — Physical Methods. SSSA Book Series 5, Madison, USA, pp. 255-293.
DOI: https://doi.org/10.2136/sssabookser5.4.c12
Haghverdi A, Öztürk HS, Durner W. 2020. Studying unimodal, bimodal, PDI and bimodal-PDI variants of multiple soil water retention models: II. Evaluation of parametric pedotransfer functions against direct fits. Water. 12:896.
DOI: https://doi.org/10.3390/w12030896
Harris C. 1968. The application of size distribution equations to multi-event comminution processes. Transactions of the Institution of Mining Metallurgy, London, 241, 343–358.
Hassan SBM, Dragonetti G, Comegna A, Sengouga A, Lamaddalena N, Coppola A. 2022. A bimodal extension of the ARYA & PARIS approach for predicting hydraulic properties of structured soils. J. Hydrol., 610: 127980.
DOI: https://doi.org/10.1016/j.jhydrol.2022.127980
Haverkamp R, Parlange J-Y. 1986. Predicting the water-retention curve from particle-size distribution: 1. Sandy soils without organic matter. Soil Science. 142: 325–339.
DOI: https://doi.org/10.1097/00010694-198612000-00001
Haverkamp R, Reggiani P, Nimmo JR. 2002. Property-Transfer Models. p. 759–782. In J.H. Dane and G.C. Topp (ed.) Methods of soil analysis. Part 4. SSSA Book Series No. 5. SSSA, Madison, WI.
DOI: https://doi.org/10.2136/sssabookser5.4.c28
Hwang SI. 2004. Effect of texture on the performance of soil particle-size distribution models. Geoderma. 123: 363–371.
DOI: https://doi.org/10.1016/j.geoderma.2004.03.003
Hwang SI, Lee KP, Lee DS, Powers SE. 2002. Models for estimating soil particle-size distributions. Soil Science Society of America Journal. 66: 1143–1150.
DOI: https://doi.org/10.2136/sssaj2002.1143
Hwang SI, Choi SI. 2006. Use of a lognormal distribution model for estimating soil water retention curves from particle-size distribution data. J. Hydrol. 323: 325-334.
DOI: https://doi.org/10.1016/j.jhydrol.2005.09.005
Jaky J. 1944. Soil Mechanics. Egyetemi Nyomda, Budapest (in Hungarian).
Kettler TA, Doran JW, Gilbert TL. 2001. Simplified method for soil particle-size determination to accompany soil-quality analyses. Soil Sci. Soc. Am. J. 65 (3): 849 – 852.
DOI: https://doi.org/10.2136/sssaj2001.653849x
Kolev B, Rousseva S, Dimitrov D. 1996. Derivation of soil water capacity parameters from standard soil texture information for Bulgarian soils. Ecological Modelling. 84: 315–319.
DOI: https://doi.org/10.1016/0304-3800(95)00134-4
Kosugi K. 1996. Log-Normal distribution model for unsaturated soil hydraulic properties. Water Resour. Res. 32: 2697-2703.
DOI: https://doi.org/10.1029/96WR01776
Lassabatere L, Angulo-Jaramillo R, Soria Ugalde J, Cuenca R, Braud I, Haverkamp R. 2006. Beerkan estimation of soil transfer parameters through infiltration experiments – BEST. Soil Science Society of America Journal. 70: 521–532.
DOI: https://doi.org/10.2136/sssaj2005.0026
Lee T-K, Ro H-M. 2014. Estimating soil water retention function from its particle-size distribution. Geosciences Journal. 18, (2): 219 – 230.
DOI: https://doi.org/10.1007/s12303-014-0017-7
Li X, Li JH, Zhang LM. 2014. Predicting bimodal soil–water characteristic curves and permeability functions using physically based parameters. Computers and Geotechnics. 57: 85–96.
DOI: https://doi.org/10.1016/j.compgeo.2014.01.004
Li D, Gao G, Shao M, Fu B. 2016. Predicting available water of soil from particle-size distribution and bulk density in an oasis-desert transect in northwestern China. J. Hydrol. 538: 539–550.
DOI: https://doi.org/10.1016/j.jhydrol.2016.04.046
Mandelbrot BB. 1983. The Fractal Geometry of Nature. Macmillan, Freeman, San Francisco, CA.
DOI: https://doi.org/10.1119/1.13295
Mebius LJ. 1960. A rapid method for the determination of organic carbon in soil. Anal. Chim. Acta. 22: 120–124.
DOI: https://doi.org/10.1016/S0003-2670(00)88254-9
Meskini-Vishkaee F, Mohammadi MH, 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: 4053–4063.
DOI: https://doi.org/10.5194/hess-18-4053-2014
Meskini-Vishkaee F, Davatgar N. 2018. Evaluation of different predictor models for detailed soil particle-size distribution. Pedosphere. 28(1): 157–164.
DOI: https://doi.org/10.1016/S1002-0160(17)60422-3
Millan H, Gonzalez-Posada M, Aguilar M, Domınguez J, Cespedes L. 2003. On the fractal scaling of soil data. Particle-size distributions. Geoderma. 117: 117–128.
DOI: https://doi.org/10.1016/S0016-7061(03)00138-1
Mohammadi MH, Meskini-Vishkaee F. 2013. Predicting soil moisture characteristic curves from continuous particle-size distribution data. Pedosphere 23 (1): 70–80.
DOI: https://doi.org/10.1016/S1002-0160(12)60081-2
Mohammadi MH. 2018. Comment on “A Non-Empirical Method for Computing Pore Radii and Soil Water Characteristics from Particle Size Distribution by Arya and Heitman (2015).” Soil Sci. Soc. Am. J. 82.
DOI: https://doi.org/10.2136/sssaj2018.01.0063
Mohammadi MH, Vanclooster M. 2011. Predicting the soil moisture characteristic curve from particle size distribution with a simple conceptual model. Vadose Zone J. 10: 594–602.
DOI: https://doi.org/10.2136/vzj2010.0080
Nasta P, Kamai T, Chirico GB, Hopmans JW, Romano N. 2009. Scaling soil water retention functions using particle-size distribution. J. Hydrol. 374: 223-234.
DOI: https://doi.org/10.1016/j.jhydrol.2009.06.007
Nasta P, Romano N, Assouline S, Vrugt JA, Hopmans JW. 2013. Prediction of spatially-variable unsaturated hydraulic conductivity using scaled particle-size distribution functions. Water Resources Research 49.
DOI: https://doi.org/10.1002/wrcr.20255
Nasta P, Palladino M, Sica B, Pizzolante A, Trifuoggi M, Toscanesi M, Giarra A, D’Auria J, Nicodemo F, Mazzitelli C, Lazzaro U, Di Fiore P, Romano N. 2020. Evaluating pedotransfer functions for predicting soil bulk density using hierarchical mapping information in Campania, Italy. Geoderma Reg. 21.
DOI: https://doi.org/10.1016/j.geodrs.2020.e00267
Nasta P, Szabó B, Romano N. 2021. Evaluation of Pedotransfer Functions for predicting soil hydraulic properties: A voyage from regional to field scales across Europe. Journal of Hydrology: Regional Studies 37.
DOI: https://doi.org/10.1016/j.ejrh.2021.100903
Nemes A, Wösten J, Lilly A, Oude Voshaar J. 1999. Evaluation of different procedures to interpolate particle-size distributions to achieve compatibility within soil databases. Geoderma. 90: 187–202.
DOI: https://doi.org/10.1016/S0016-7061(99)00014-2
Nesbitt A, Breytenbach W. 2006. A particle size distribution model for manufactured particulate solids of narrow and intermediate size ranges. Powder Technology. 164: 117–123.
DOI: https://doi.org/10.1016/j.powtec.2006.03.015
Nimmo JR, Herkelrath WN, Laguna Luna AM. 2007. Physically based estimation of soil water retention from textural data: General framework, new models, and streamlined existing models. Vadose Zone J. 6: 766–773.
DOI: https://doi.org/10.2136/vzj2007.0019
Palladino M, Romano N, Pasolli E, Nasta P. 2022. Developing pedotransfer functions for predicting soil bulk density in Campania Region. Geoderma. 412: 115726.
DOI: https://doi.org/10.1016/j.geoderma.2022.115726
Pasikatan M, Steele J, Milliken G, Spillman C, Haque E. 1999. Particle size distribution and sieving characteristics of first-break ground wheat. American Society of Agricultural Engineers. 319: 1–11.
Perrier E, Bird N. 2002. Modelling soil fragmentation: the pore solid fractal approach. Soil and Tillage Research. 64: 91–99.
DOI: https://doi.org/10.1016/S0167-1987(01)00247-1
Romano N, Santini A. 1999. Determining soil hydraulic functions from evaporation experiments by a parameter estimation approach: Experimental verifications and numerical studies. Water Resources Research. 35: 3343-3359.
DOI: https://doi.org/10.1029/1999WR900155
Romano N, Nasta P. 2016. How effective is bimodal soil hydraulic characterization? Functional evaluations for predictions of soil water balance. European Journal of Soil Science. 67: 523-535.
DOI: https://doi.org/10.1111/ejss.12354
Romano N, Hopmans JW, Dane JH. 2002. Water retention and storage: Suction table. In “Methods of Soil Analysis, Part 4, Physical Methods” (J.H. Dane and G.C. Topp, eds.), pp. 692-698, SSSA Book Series N.5, Madison, WI, USA.
Romano N, Nasta P, Severino G, Hopmans JW. 2011. Using bimodal log-normal functions to describe the hydraulic properties of soils. Soil Science Society of America Journal. 75: 468-480.
DOI: https://doi.org/10.2136/sssaj2010.0084
Romano N, Nasta P, Bogena HR, De Vita P, Stellato L, Vereecken H. 2018. Monitoring hydrological processes for land and water resources management in a Mediterranean ecosystem: the Alento River catchment observatory. Vadose Zone Journal. 17:180042.
DOI: https://doi.org/10.2136/vzj2018.03.0042
Rosin P, Rammler E. 1933. The laws governing the fineness of powdered coal. Journal of the Institute of Fuel. 7: 29–36.
Russel JC, Engle EB. 1928. The organic matter content and color of soils in the central grassland states. In: Proceedings and Papers of the First International Congress of Soil Science (R.B. Deemer, ed.), June 13-22, 1927, Washington, DC, USA.
Shang L, Li D. 2019. Comparison of different approaches for estimating soil water characteristic curves from saturation to oven dryness. J. Hydrol. 577: 123971.
DOI: https://doi.org/10.1016/j.jhydrol.2019.123971
Schuhmann JR. 1940. Principles of comminution, I-size distribution and surface calculations. Mining Technology. 4: l–11.
Stokes GG. 1850. On the effect of the internal friction of fluids on the motion of pendulums. Trans. Cambridge Philos. Soc. 9: 8 – 106.
Tóth B, Weynants M, Nemes A, Makó A, Bilas G, Tóth G. 2015. New generation of hydraulic pedotransfer functions for Europe. Eur. J. Soil Sci. 66(1): 226–238.
DOI: https://doi.org/10.1111/ejss.12192
Tuller M, Or D. 2001. Hydraulic conductivity of variably saturated porous media: film and corner flow in angular pore space. Water Resour. Res. 37 (5): 1257–1276.
DOI: https://doi.org/10.1029/2000WR900328
van Genuchten MTh. 1980. A closed form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44: 892-898.
DOI: https://doi.org/10.2136/sssaj1980.03615995004400050002x
Van Looy K, Bouma J, Herbst M, Koestel J, Minasny B, Mishra U et al. 2017. Pedotransfer functions in Earth system science: Challenges and perspectives. Rev. Geophys. 55: 1199 – 1256.
DOI: https://doi.org/10.1002/2017RG000581
Vaz CMP, Ferreira EJ, Posadas AD. 2020. Evaluation of models for fitting soil particle-size distribution using UNSODA and a Brazilian dataset. Geoderma Regional. 21: e00273.
DOI: https://doi.org/10.1016/j.geodrs.2020.e00273
Vipulanandan C, Ozgurel, HG. 2009. Simplified relationships for particle-size distribution and permeation groutability limits for soils. Journal of Geotechnical & Geoenvironmental Engineering. 135: 1190–1197.
DOI: https://doi.org/10.1061/(ASCE)GT.1943-5606.0000064
Weibull W. 1951. A statistical distribution function of wide applicability. Journal of Applied Mechanics. 18: 293–297.
DOI: https://doi.org/10.1115/1.4010337
Wösten JHM, Pachepsky Y, Rawls WJ. 2001. Pedotransfer functions: bridging the gap between available basic soil data and missing soil hydraulic characteristics. Journal of Hydrology. 251: 123–150.
DOI: https://doi.org/10.1016/S0022-1694(01)00464-4
Zhang Y, Weihermüller L, Toth B, Noman M, Vereecken H. 2022. Analyzing dual porosity in soil hydraulic properties using soil databases for pedotransfer function development. Vadose Zone Journal. 21: e20227.
DOI: https://doi.org/10.1002/vzj2.20227
Zhuang J, Jin Y, Miyazaki T. 2001. Estimating water retention characteristic from soil particle-size distribution using a non-similar media concept. Soil Science. 166: 308–321.
DOI: https://doi.org/10.1097/00010694-200105000-00002
Zobeck TM, Gill TE, Popham TW. 1999. A two-parameter Weibull function to describe airborne dust particle size distributions. Earth Surface Processes & Landforms. 24: 943–955.
DOI: https://doi.org/10.1002/(SICI)1096-9837(199909)24:10<943::AID-ESP30>3.0.CO;2-9
You T, Li S, Guo Y, Wang C, Liu X, Zhao J, Wang D. 2022. A superior soil – water characteristic curve for correcting the Arya-Paris model based on particle size distribution. J. Hydrol., 613: 128393.
DOI: https://doi.org/10.1016/j.jhydrol.2022.128393
How to Cite
Lazzaro, U. (2023) “On evaluating the hypothesis of shape similarity between soil particle-size distribution and water retention function”, Journal of Agricultural Engineering, 54(4). doi: 10.4081/jae.2023.1542.
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