Topsoil texture maps based on calibration of soil electrical conductivity with soil datasets varying in size

Michał Konrad Stępień, Dariusz Gozdowski, Elżbieta Bodecka, Joanna Groszyk, Jan Rozbicki, Stanisław Samborski


The purpose of the study was to verify the possibility of creation of reliable soil texture class (STC) maps of a topsoil based on a linear calibration of shallow (0-30cm) soil electrical conductivity (ECsh) with small datasets of soil samples with laboratory determined STC . ECsh values were calibrated against four datasets of soil samples. The smallest datasets (5-6 soil samples per field) were selected: 1) in an arbitrary way; or 2) based on the quartiles of ECsh values. A dataset of an intermediate size (11-17 points) and a full dataset of all ST data available (33-38 points) were also tested. For one field, the calibration with ECsh quartiles produced STC maps with greater agreement with field's status than the complete dataset of laboratory results. Although, the root mean square errors and mean absolute errors were greater for quartiles than for the other datasets. The ECsh values depended on the content of fine soil (<2 mm) fractions to a depth of 90 cm, so ECsh measurements are efficient in mapping the topsoil texture of fields with relatively uniform texture in subsoil. The datasets, which produced lower values of errors did not always permit to prepare more accurate STC maps.



electrical conductivity; soil texture; calibration; linear regression; topsoil

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Coates G.F., Hulse C.A., 1985. A comparison of four methods of size analysis of fine-grained sediments. New Zealand Journal of Geology and Geophysics 28(2): 369-380.

Ferro V., Mirabile S., 2009. Comparing particle size distribution analysis by sedimentation and laser diffraction method. Journal of Agricultural Engineering 2: 35-43.

IUSS Working Group WRB, 2014. World reference base for soil resources 2014. World Soil Resources Reports No. 106. FAO, Rome. 182pp.

Florinsky I. V., 2012. Digital terrain analysis in soil science and geology. Elsevier.

Heil, K., Schmidhalter, U., 2012. Characterization of soil texture variability using the apparent soil electrical conductivity at a highly variable site. Computers and Geosciences 39 98-110.

Jary, Z., Kida, J., Śnihur, M., 2002. Loess and loess-derived sediments in south-western Poland (in Polish). Czasopismo Geograficzne 73(1-2): 63-100.

Kuhn J., Brenning A., Wehrhan M., Koszinski S., Sommer M., 2009. Interpretation of electrical conductivity patterns by soil properties and geological maps for precision agriculture. Precision Agriculture 10: 490-507.

Kweon G., Lund, E., Maxton C., 2012. The ultimate soil survey in one pass: soil texture, organic matter, pH, elevation, slope, and curvature. Proceedings of the 11th ICPA 2012. Indianapolis IN: 1-13.

Landrum C., Castrignano A., Mueler T., Zourarakis D., Zhu J., Benedetto de D., 2015. An approach for delineating homogenous within-field zones using proximal sensing and multivariate geostatistics. Agricultural Water Management 147: 144-153.

Machado P.L.O.A., Bernardi A.A.C.C., Valencia L.I.O., Molin J.P., Gimenez L.M., Silva C.A., Andrade de A.G., Madari B.E., Meirelles M.S.P., 2006. Electrical conductivity mapping in relation to clay of a Ferralsol under no tillage system (In Portuguese). Pesquisa Agropecuária Brasileira, 41(6): 1023-1031.

Mzuku M., Khosla R., Reich R., Inman D., Smith F. and MacDonald L., 2005. Spatial variability of measured soil properties across site-specific management zones. Soil Science of America Journal 69: 1572–1579.

Orzechowski M., Smólczyński S., Długosz J., Poźniak P., 2014. Measurements of texture of soils formed from glaciolimnic sediments by areometric method, pipette method and laser diffraction method. Soil Science Annual 65(2): 72-79.

Pondel H., Terelak H., Terelak T. and Wilkos S., 1979. Chemical properties of Polish arable soils (in Polish). Pamiętnik Puławski 71 Suppl. 190pp.

Quantum GIS Development Team (2013). QGIS 2.0 Geographic Information System. Open Source Geospatial Foundation Project.

Ruckamp D., Schick J., Haneklaus S., Schnug E., 2013. Algorithms for variable-rate application of manure. Knowledge Report. access: 21.04.2017.

Serrano J., Shahidian S., Marques da Silva J., 2014. Spatial and temporal patterns of apparent electrical conductivity: Dualem vs. Veris sensors for monitoring soil properties. Sensors 14: 10024-10041.

Sudduth K.A., Kitchen N.R., Wiebold W.J., Bachelor W.D., Bollero G.A., Bullock D.G., Clay D.E., Palm H.L., Pierce F.J., Schuler R.T., Thelen K.D., 2005. Relating apparent electrical conductivity to soil properties across the north-central USA. Computers and Electronics in Agriculture 46: 263-283.

Webster R., Oliver M.A., 1992. Sample adequately to estimate variograms of soil properties. Journal of Soil Science 25: 121-134.

Data publikacji: 2018-01-15 09:23:54
Data złożenia artykułu: 2017-04-28 21:20:06


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