Eurasian Journal of Soil Science

Volume 9, Issue 4, Oct 2020, Pages 306-313
DOI: 10.18393/ejss.760201
Stable URL: http://ejss.fess.org/10.18393/ejss.760201
Copyright © 2020 The authors and Federation of Eurasian Soil Science Societies



Transformation of soil texture schemes and determination of water-physical properties of soils

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Sadovski,A., Ivanova,M., 2020. Transformation of soil texture schemes and determination of water-physical properties of soils. Eurasian J Soil Sci 9(4):306-313. DOI : 10.18393/ejss.760201
Sadovski,A.,,& Ivanova,M. Transformation of soil texture schemes and determination of water-physical properties of soils Eurasian Journal of Soil Science, 9(4):306-313. DOI : 10.18393/ejss.760201
Sadovski,A.,, and ,Ivanova,M."Transformation of soil texture schemes and determination of water-physical properties of soils" Eurasian Journal of Soil Science, 9.4 (2020):306-313. DOI : 10.18393/ejss.760201
Sadovski,A.,, and ,Ivanova,M. "Transformation of soil texture schemes and determination of water-physical properties of soils" Eurasian Journal of Soil Science,9(Oct 2020):306-313 DOI : 10.18393/ejss.760201
A,Sadovski.M,Ivanova "Transformation of soil texture schemes and determination of water-physical properties of soils" Eurasian J. Soil Sci, vol.9, no.4, pp.306-313 (Oct 2020), DOI : 10.18393/ejss.760201
Sadovski,Alexander ;Ivanova,Mariya Transformation of soil texture schemes and determination of water-physical properties of soils. Eurasian Journal of Soil Science, (2020),9.4:306-313. DOI : 10.18393/ejss.760201

How to cite

Sadovski, A., Ivanova, M., 2020. Transformation of soil texture schemes and determination of water-physical properties of soils. Eurasian J. Soil Sci. 9(4): 306-313. DOI : 10.18393/ejss.760201

Author information

Alexander Sadovski , Bulgarian Science Center of the IEAS, Sofia, Bulgaria
Mariya Ivanova , Institute of Soil Science, Agrotechnologies and Plant Protection, Sofia, Bulgaria

Publication information

Article first published online : 29 Jun 2020
Manuscript Accepted : 19 Jun 2020
Manuscript Received: 28 Feb 2020
DOI: 10.18393/ejss.760201
Stable URL: http://ejss.fesss.org/10.18393/ejss.760201

Abstract

Measuring soil water-physical properties is laborious, time-consuming, and expensive. That provokes a lot of scientists to estimate them which action is troubled by the usage of different soil texture classification systems. The study proposes a rapid, reliable, and universally applicable methodology for soil textural transformations between different classification systems. The method of discrete mathematics is applied to make the conversion of particle-size classes from the Kachinsky system, which is used in Bulgaria to the International systems. Three different data sources were used to determine the water-physical properties of soils from textural data - 376 soil profiles from Bulgaria, extraction from the SoilGrids system for the Plovdiv district in Bulgaria and data from CanSIS/NSDB database. The relationship between the dependent variables field capacity (FC), wilting point (WP) and bulk density (BD), and independent variables sand, silt, and clay soil content was sought in the form of a regression equation. The applied stepwise regression procedure produces a close dependence between the soil texture and its water-physical properties.

Keywords

Bulk density, discrete mathematics, field capacity, soil texture, wilting point.

Corresponding author

References

Abdelbaki, A.M., 2018. Evaluation of pedotransfer functions for predicting soil bulk density for U.S. soils. Ain Shams Engineering Journal 9(4): 1611-1619.

Ahuja, L.R., Naney, J.W., Williams, R.D., 1985. Estimating soil water characteristics from simpler properties or limited data. Soil Science Society of America Journal 49(5), 1100-1105.

Antipov Karataev,  I.N., 1960. Soils in Bulgaria. Zemizdat, Sofia, Bulgaria. [in Bulgarian]

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.

Børgesen, C.D., Iversen, B.V., Jacobsen, O.H., Schaap, M.G., 2008. Pedotransfer functions estimating soil hydraulic properties using different soil parameters. Hydrological Processes 22(11): 1630-1639.

Dilkova R., 2014. Structure, physical properties апd aeration of Bulgarian Soils. Publish SciSet-Eco, Sofia. Bulgaria. 351p. [in Bulgarian]

Dimitrov, E., Kercheva, M., 2016. Assessment of spatial variation and mapping of soil organic carbon and hydrological indices of heterogeneous soil mechanical composition. In: Proc. 4th Nat. Conf. "Humic Substances and Their Role for Climate Change Mitigation", Filcheva, E. et al. (Eds.) Sofia. pp. 142-156. [in Bulgarian]

Dobarco, M.R., Cousin, I., Le Bas, C., Martin, M.P., 2019. Pedotransfer functions for predicting available water capacity in French soils, their applicability domain and associated uncertainty. Geoderma 336: 81-95.

FAO. 2006. Guidelines for soil description, Fourth edition. Food and Agriculture Organization of the United Nations (FAO), Rome. Italy. 97p. Available at [access date : 28.02.2020]: http://www.fao.org/3/a-a0541e.pdf

Fredlund M.D., Fredlund, D.G., Wilson. G.W., 1997. Prediction of the Soil-Water Characteristic Curve from Grain-Size Distribution and Volume-Mass Properties. 3rd Brazilian Symposium on Unsaturated Soils, April 22-25. 1997.Rio de Janeiro, Brazil.

Hengl, T., de Jesus, J.M., Heuvelink, G.B.M., Gonzalez, M.R., Kilibarda, M., Blagotić, A., Shangguan, W., Wright, M.N., Geng, X., Bauer-Marschallinger, B., Antonio Guevara, M.A., Vargas, R., MacMillan, R.A., Batjes, N.H., Leenaars, J.G.B.,  Ribeiro, E., Wheeler, I.,  Mantel, S., Kempen, B., 2017. SoilGrids250m: Global gridded soil information based on machine learning. PLoS ONE 12(2): e0169748.

Kachinsky, N.A., 1943. Methods of mechanical and microagregatic analysis of soil. Publ. House Acad. Sci. USSR, Moscow, 39 p.  [in Russian]

Kachinsky, N.A. ,1965. Soil Physics. Publ. Higher School, Moscow, 320 p. [in Russian]

Kachinski, N.A., 1956. Die mechanische Bodenanalyse und die Klassifikation der Böden nach ihrer mechanischen Zusammensetzung. Rapports au Sixiéme Congrés de la Science du Sol. Paris, B, pp.321-327.

Kolev, B., Rousseva, S., Dimitrov, D., 1996. Derivation of soil water capacity parameters from standard soil texture information for Bulgarian soils. Ecological Modelling 84(1-3): 315-319.

MacDonald, K.B., Valentine, K.W.G., 1992. CanSIS/NSDB: A general description. Centre for Land and Biological Resources Research. Research Branch, Agriculture Canada, Ottawa. CLBRR Contribution Number 92-35, 40p.

Manrique L.A., Jones, C.A., Dyke, P.T., 1991. Predicting soil water retention characteristics from soil physical and chemical properties, Communications in Soil Science and Plant Analysis 22(17-18): 1847-1860.

Minasny, B., McBratney, A.B., 2001. The Australian soil texture boomerang: a comparison of the Australian and USDA/FAO soil particle-size classification systems. Australian Journal of Soil Research 39(6): 1443-1451.

Nourbakhsh F., Afyuni, M., Abbaspour, K.C., Schulin, R., 2004. Research note: Estimation of field capacity and wilting point from basic soil physical and chemical properties, Arid Land Research and Management 19(1): 81-85.

Pachepsky, Y., Rawls, W. J., 2004. Development of Pedotransfer Functions in Soil Hydrology. Amsterdam: Elsevier, 542p.

Robinson, G.W., 1927. The grouping of fractions in the mechanical analysis. First International Congress of Soil Science. June 13-22, 1927. Washington D.C., USA.

Rodríguez-Lado, L., Rial, M., Taboada, T., Cortizas, A.M., 2015. A pedotransfer function to map soil bulk density from limited data. Procedia Environmental Sciences 27: 45 – 48.

Rosen, K.H., 2012. Discrete mathematics and its applications. McGraw-Hill Higher Education 1071p.

Rousseva, S.S., 1997. Data transformations between soil texture schemes. European Journal of Soil Science 48(4): 749-758.

Sadovski, A., 1998. Self-organizing Models of Biological and Environmental Systems. Journal of Balkan Ecology 1(2): 15-20.

Saxton, K.E., Rawls, W.J., 2006. Soil Water characteristic estimates by texture and organic matter for hydrologic solutions. Soil Science Society of America Journal 70(5): 1569–1578.

Saxton, K.E., Rawls, W.J., Romberger, J.S., Papendick, R.I., 1986. Estimating generalized soil-water characteristics from texture. Soil Science Society of America Journal 50(4): 1031-1036.

Shein, E.V., 2009. The particle-size distribution in soils: Problems of the methods of study, ınterpretation of the results, and classification. Eurasian Soil Science 42(3): 284-291.

Shein, E.V., Kukharuk, N.S., Panina, S.S., 2014. Soil water retention curve: Experimental and pedotransfer data to forecast water movement in soils. Biogeosystem Technique 1(1): 89-96.

Soil Survey Staff. 2017. Soil survey manual. United States Department of Agriculture (USDA) Agriculture Handbook No. 18. Government Printing Office, Washington, D.C., USA. 639p. Available at [access date : 28.02.2020]:  https://www.nrcs.usda.gov/wps/PA_NRCSConsumption/download?cid=nrcseprd1333016&ext=pdf

Sokolovsky, A.N., Kachinsky, N.A., 1930. Soil physics.  Second International Congress of Soil Science. July 20-31, 1930.  Leningrad-Moscow, USSR.

Teoharov, M., Popandova, Sv., Kancheva, R., Atanasova, T., Tsolova, V., Banov, M., Ivanov, P., Filcheva, E., Ilieva, R., 2009. Reference database for soils in Bulgaria. N.Poushkarov Institute of Soil Science, Sofia. Bulgaria. Publ. House "Poni". Bulgaria. 416p. [in Bulgarian]

Van Genuchten, M.T., 1980. A closed‐form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Science Society of America Journal 44(5): 892-898.

Van Genuchten, M.T., Nielsen, D.R. 1985. On describing and predicting the hydraulic properties of unsaturated soils. Annales Geophysicae 3(5): 615-628

Van Keulen, H., Wolf, J., 1986. Modeling of agricultural production: weather, soils and crops. Pudoc, Wageningen, the Netherlands. 479p.

Vereecken, H., Maes, J., Feyen, J., Darius, P., 1989. Estimating the soil moisture retention characteristic from texture, bulk density and carbon content. Soil Science 148(6): 389-403.

Abstract

Measuring soil water-physical properties is laborious, time-consuming, and expensive. That provokes a lot of scientists to estimate them which action is troubled by the usage of different soil texture classification systems. The study proposes a rapid, reliable, and universally applicable methodology for soil textural transformations between different classification systems. The method of discrete mathematics is applied to make the conversion of particle-size classes from the Kachinsky system, which is used in Bulgaria to the International systems. Three different data sources were used to determine the water-physical properties of soils from textural data - 376 soil profiles from Bulgaria, extraction from the SoilGrids system for the Plovdiv district in Bulgaria and data from CanSIS/NSDB database. The relationship between the dependent variables field capacity (FC), wilting point (WP) and bulk density (BD), and independent variables sand, silt, and clay soil content was sought in the form of a regression equation. The applied stepwise regression procedure produces a close dependence between the soil texture and its water-physical properties.

Keywords: Bulk density, discrete mathematics, field capacity, soil texture, wilting point.

References

Abdelbaki, A.M., 2018. Evaluation of pedotransfer functions for predicting soil bulk density for U.S. soils. Ain Shams Engineering Journal 9(4): 1611-1619.

Ahuja, L.R., Naney, J.W., Williams, R.D., 1985. Estimating soil water characteristics from simpler properties or limited data. Soil Science Society of America Journal 49(5), 1100-1105.

Antipov Karataev,  I.N., 1960. Soils in Bulgaria. Zemizdat, Sofia, Bulgaria. [in Bulgarian]

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.

Børgesen, C.D., Iversen, B.V., Jacobsen, O.H., Schaap, M.G., 2008. Pedotransfer functions estimating soil hydraulic properties using different soil parameters. Hydrological Processes 22(11): 1630-1639.

Dilkova R., 2014. Structure, physical properties апd aeration of Bulgarian Soils. Publish SciSet-Eco, Sofia. Bulgaria. 351p. [in Bulgarian]

Dimitrov, E., Kercheva, M., 2016. Assessment of spatial variation and mapping of soil organic carbon and hydrological indices of heterogeneous soil mechanical composition. In: Proc. 4th Nat. Conf. "Humic Substances and Their Role for Climate Change Mitigation", Filcheva, E. et al. (Eds.) Sofia. pp. 142-156. [in Bulgarian]

Dobarco, M.R., Cousin, I., Le Bas, C., Martin, M.P., 2019. Pedotransfer functions for predicting available water capacity in French soils, their applicability domain and associated uncertainty. Geoderma 336: 81-95.

FAO. 2006. Guidelines for soil description, Fourth edition. Food and Agriculture Organization of the United Nations (FAO), Rome. Italy. 97p. Available at [access date : 28.02.2020]: http://www.fao.org/3/a-a0541e.pdf

Fredlund M.D., Fredlund, D.G., Wilson. G.W., 1997. Prediction of the Soil-Water Characteristic Curve from Grain-Size Distribution and Volume-Mass Properties. 3rd Brazilian Symposium on Unsaturated Soils, April 22-25. 1997.Rio de Janeiro, Brazil.

Hengl, T., de Jesus, J.M., Heuvelink, G.B.M., Gonzalez, M.R., Kilibarda, M., Blagotić, A., Shangguan, W., Wright, M.N., Geng, X., Bauer-Marschallinger, B., Antonio Guevara, M.A., Vargas, R., MacMillan, R.A., Batjes, N.H., Leenaars, J.G.B.,  Ribeiro, E., Wheeler, I.,  Mantel, S., Kempen, B., 2017. SoilGrids250m: Global gridded soil information based on machine learning. PLoS ONE 12(2): e0169748.

Kachinsky, N.A., 1943. Methods of mechanical and microagregatic analysis of soil. Publ. House Acad. Sci. USSR, Moscow, 39 p.  [in Russian]

Kachinsky, N.A. ,1965. Soil Physics. Publ. Higher School, Moscow, 320 p. [in Russian]

Kachinski, N.A., 1956. Die mechanische Bodenanalyse und die Klassifikation der Böden nach ihrer mechanischen Zusammensetzung. Rapports au Sixiéme Congrés de la Science du Sol. Paris, B, pp.321-327.

Kolev, B., Rousseva, S., Dimitrov, D., 1996. Derivation of soil water capacity parameters from standard soil texture information for Bulgarian soils. Ecological Modelling 84(1-3): 315-319.

MacDonald, K.B., Valentine, K.W.G., 1992. CanSIS/NSDB: A general description. Centre for Land and Biological Resources Research. Research Branch, Agriculture Canada, Ottawa. CLBRR Contribution Number 92-35, 40p.

Manrique L.A., Jones, C.A., Dyke, P.T., 1991. Predicting soil water retention characteristics from soil physical and chemical properties, Communications in Soil Science and Plant Analysis 22(17-18): 1847-1860.

Minasny, B., McBratney, A.B., 2001. The Australian soil texture boomerang: a comparison of the Australian and USDA/FAO soil particle-size classification systems. Australian Journal of Soil Research 39(6): 1443-1451.

Nourbakhsh F., Afyuni, M., Abbaspour, K.C., Schulin, R., 2004. Research note: Estimation of field capacity and wilting point from basic soil physical and chemical properties, Arid Land Research and Management 19(1): 81-85.

Pachepsky, Y., Rawls, W. J., 2004. Development of Pedotransfer Functions in Soil Hydrology. Amsterdam: Elsevier, 542p.

Robinson, G.W., 1927. The grouping of fractions in the mechanical analysis. First International Congress of Soil Science. June 13-22, 1927. Washington D.C., USA.

Rodríguez-Lado, L., Rial, M., Taboada, T., Cortizas, A.M., 2015. A pedotransfer function to map soil bulk density from limited data. Procedia Environmental Sciences 27: 45 – 48.

Rosen, K.H., 2012. Discrete mathematics and its applications. McGraw-Hill Higher Education 1071p.

Rousseva, S.S., 1997. Data transformations between soil texture schemes. European Journal of Soil Science 48(4): 749-758.

Sadovski, A., 1998. Self-organizing Models of Biological and Environmental Systems. Journal of Balkan Ecology 1(2): 15-20.

Saxton, K.E., Rawls, W.J., 2006. Soil Water characteristic estimates by texture and organic matter for hydrologic solutions. Soil Science Society of America Journal 70(5): 1569–1578.

Saxton, K.E., Rawls, W.J., Romberger, J.S., Papendick, R.I., 1986. Estimating generalized soil-water characteristics from texture. Soil Science Society of America Journal 50(4): 1031-1036.

Shein, E.V., 2009. The particle-size distribution in soils: Problems of the methods of study, ınterpretation of the results, and classification. Eurasian Soil Science 42(3): 284-291.

Shein, E.V., Kukharuk, N.S., Panina, S.S., 2014. Soil water retention curve: Experimental and pedotransfer data to forecast water movement in soils. Biogeosystem Technique 1(1): 89-96.

Soil Survey Staff. 2017. Soil survey manual. United States Department of Agriculture (USDA) Agriculture Handbook No. 18. Government Printing Office, Washington, D.C., USA. 639p. Available at [access date : 28.02.2020]:  https://www.nrcs.usda.gov/wps/PA_NRCSConsumption/download?cid=nrcseprd1333016&ext=pdf

Sokolovsky, A.N., Kachinsky, N.A., 1930. Soil physics.  Second International Congress of Soil Science. July 20-31, 1930.  Leningrad-Moscow, USSR.

Teoharov, M., Popandova, Sv., Kancheva, R., Atanasova, T., Tsolova, V., Banov, M., Ivanov, P., Filcheva, E., Ilieva, R., 2009. Reference database for soils in Bulgaria. N.Poushkarov Institute of Soil Science, Sofia. Bulgaria. Publ. House "Poni". Bulgaria. 416p. [in Bulgarian]

Van Genuchten, M.T., 1980. A closed‐form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Science Society of America Journal 44(5): 892-898.

Van Genuchten, M.T., Nielsen, D.R. 1985. On describing and predicting the hydraulic properties of unsaturated soils. Annales Geophysicae 3(5): 615-628

Van Keulen, H., Wolf, J., 1986. Modeling of agricultural production: weather, soils and crops. Pudoc, Wageningen, the Netherlands. 479p.

Vereecken, H., Maes, J., Feyen, J., Darius, P., 1989. Estimating the soil moisture retention characteristic from texture, bulk density and carbon content. Soil Science 148(6): 389-403.



Eurasian Journal of Soil Science