Observed variations in the ground electrical conductivity (σb*) measurements obtained with EMI instruments depend on several soil proxies that influence crop growth and development such as salinity (σe), contents of water (θw), clay (wc) and organic matter (wom) and bulk density (ρb). However, the relative contributions of all these to σb* are unknown. This knowledge is needed to improve the planning and interpretation of σb* data for precision agriculture applications. Recently, a semi-empirical model has been developed to relate σb* measurements taken with an EM38 device to σe, θw, wc, wom and ρb and also soil temperature (t). In this work this model was subjected to a global sensitivity analysis (GSA) based on the soil data obtained during two surveys carried out, one in summer and the other in autumn, in an ample irrigated area in SE Spain. On the basis of the multiple linear regression meta-models developed for the σb* measurements, these were found to linearly respond to the soil properties (R2 between 0.92 and 0.96) and thus, the GSA could be based on their standardised regression coefficients. According to these, the soil characteristics explain the following percentages of variance in σb* (PV): 30–34 (σe), 8–20 (θw), 32–47 (wc), 0.6–2.6 (wom), 5.7–7.5 (ρb) and 0.3–0.4 (t) with changes from the summer to the autumn season of − 4, − 12 and + 15 in the PV explained by the most influential properties, respectively, σe, θw and wc. The results of the GSA will help the planning and interpretation of σb* measurements for improving crop management.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
The data associated to this article is stored in the public repository Mendeley Data (https://data.mendeley.com/): Visconti, Fernando; de Paz, José Miguel (2020), “Soil and electromagnetic induction surveys in the Vega Baja del Segura and Baix Vinalopó in 2006 and 2010”, Mendeley Data, V1, https://doi.org/10.17632/rh729nhdz3.1. They will be made openly available from 20th October 2020 on.
No specific code was developed in this research.
Abdu, H., Robinson, D. A., Seyfried, M., & Jones, S. B. (2008). Geophysical imaging of watershed subsurface patterns and prediction of soil texture and water holding capacity. Water Resources Research, 44, W00D18.
Borchers, B., Uram, T., & Hendrickx, J. M. H. (1997). Tikhonov regularization of electrical conductivity depth profiles in field soils. Soil Science Society of America Journal, 61, 1004–1009.
Brejda, J. J., Moorman, T. B., Smith, J. L., Karlen, D. L., Allan, D. L., & Dao, T. H. (2000). Distribution and variability of surface soil properties at a regional scale. Soil Science Society of America Journal, 64(3), 974–982.
Brevik, E. C., & Fenton, T. E. (2002). Influence of soil water content, clay, temperature, and carbonate minerals on electrical conductivity readings taken with an EM-38. Soil Survey Horizons Spring, 43, 9–13.
Brevik, E. C., Fenton, T. E., & Lazari, A. (2006). Soil electrical conductivity as a function of soil water content and implications for soil mapping. Precision Agriculture, 7, 393–404.
Bulmer, M. G. (1979). Principles of statistics. New York, USA: Dover Publications Inc.
Callegary, J. B., Ferré, T. P. A., & Groom, R. W. (2007). Vertical spatial sensitivity and exploration depth of low-induction-number electromagnetic-induction instruments. Vadose Zone Journal, 6(1), 158–167.
Chao, Y.-C.E., Zhao, Y., Kupper, L. L., & Nylander-French, L. A. (2008). Quantifying the relative importance of predictors in multiple linear regression analyses for public health studies. Journal of Occupational and Environmental Hygiene, 5(8), 519–529.
Corwin, D. L., & Lesch, S. M. (2003). Application of soil electrical conductivity to precision agriculture: Theory, principles, and guidelines. Agronomy Journal, 95(3), 455–471.
Corwin, D. L., & Lesch, S. M. (2005). Apparent soil electrical conductivity measurements in agriculture. Computers and Electronics in Agriculture, 46, 11–43.
Corwin, D. L., & Rhoades, J. D. (1990). Establishing soil electrical conductivity-depth relations from electromagnetic induction measurements. Communications in Soil Science and Plant Analysis, 21(11–12), 861–901.
Dakak, H., Huang, J., Zouahri, A., Douaik, A., & Triantafilis, J. (2017). Mapping soil salinity in 3-dimensions using an EM38 and EM4Soil inversion modelling at the reconnaissance scale in central Morocco. Soil Use and Management, 33(4), 553–567.
De Benedetto, D., Castrignanò, A., Rinaldi, M., Ruggieri, S., Santoro, F., Figorito, B., et al. (2013). An approach for delineating homogeneous zones by using multi-sensor data. Geoderma, 199, 117–127.
Díaz, L., & Herrero, J. (1992). Salinity estimates in irrigated soils using electromagnetic induction. Soil Science, 154(2), 151–157.
Doolittle, J., Petersen, M., & Wheeler, T. (2001). Comparison of two electromagnetic induction tools in salinity appraisals. Journal of Soil and Water Conservation, 56(3), 257–262.
García-Tomillo, A., Mirás-Avalos, J. M., Dafonte-Dafonte, J., & Paz-González, A. (2017). Estimating soil organic matter using interpolation methods with a electromagnetic induction sensor and topographic parameters: A case study in a humid region. Precision Agriculture, 18(5), 882–897.
Gee, G. W., & Or, D. (2002). Particle-size analysis. In G. Campbell, R. Horton, W. A. Jury, D. R. Nielsen, H. M. van Es, P. J. Wierenga, J. H. Dane, & G. C. Topp (Eds.), Methods of soil analysis. Part 4. Physical methods (pp. 255–294). Madison, WI, USA: SSSA, ASA.
Gunst, R. F. (1983). Regression analysis with multicollinear predictor variables: Definition, detection and effects. Communications in Statistics—Theory and Methods, 12, 2217–2260.
Hedley, C. B., Yule, I. J., Eastwood, C. R., Shepherd, T. G., & Arnold, G. (2004). Rapid identification of soil textural and management zones using electromagnetic induction sensing of soils. Australian Journal of Soil Research, 42(4), 389–400.
Heil, K., & Schmidhalter, U. (2017). The application of EM38: Determination of soil parameters, selection of soil sampling points and use in agriculture and archaeology. Sensors, 17(11), 2540 (1–44).
Hendrickx, J. M. H., Borchers, B., Corwin, D. L., Lesch, S. M., Hilgendorf, C., & Schlue, J. (2002). Inversion of soil conductivity profiles from electromagnetic induction measurements theory and experimental verification. Soil Science Society of America Journal, 66, 673–685.
Huang, J., Ramamoorthy, P., McBratney, A., & Bramley, H. (2018). Soil water extraction monitored per plot across a field experiment using repeated electromagnetic induction surveys. Soil Systems, 2(11), 1–17.
IUSS Working Group WRB. (2006). World reference base for soil resources 2006 (2nd ed.). World Soil Resources Reports No. 103. Rome, Italy: FAO.
Jung, W. K., Kitchen, N. R., Sudduth, K. A., Kremer, R. J., & Motavalli, P. P. (2005). Relationship of apparent soil electrical conductivity to claypan soil properties. Soil Science Society of America Journal, 69, 883–892.
Kachanoski, R. G., Gregorich, E. G., & Van Wesenbeeck, I. J. (1988). Estimating spatial variations of soil water content using noncontacting electromagnetic inductive methods. Canadian Journal of Soil Science, 68(4), 715–722.
Kelleners, T. J., & Verma, A. K. (2010). Measured and modeled dielectric properties of soils at 50 megahertz. Soil Science Society of America Journal, 74(3), 744–752.
Kraha, A., Turner, H., Nimon, K., Zientek, L. R., & Henson, R. K. (2012). Interpreting multiple regression in the face of multicollinearity. Frontiers in Psychology, 3, 1–10.
Lardo, E., Arous, A., Palese, A. M., Nuzzo, V., & Celano, G. (2016). Electromagnetic induction: A support tool for the evaluation of soil CO2 emissions and soil organic carbon content in olive orchards under semi-arid conditions. Geoderma, 264, 188–194.
Lesch, S. M., Herrero, J., & Rhoades, J. (1998). Monitoring for temporal changes in soil salinity using electromagnetic induction techniques. Soil Science Society of America Journal, 62, 232–242.
Lesch, S.M., Rhoades, J.D., & Corwin, D.L. (2000). The ESAP-95 version 2.01R User Manual and Tutorial Guide. Research Report No. 146. Riverside, CA, USA: USDA-ARS, George E. Brown, Jr., Salinity Laboratory.
Lesch, S. M., Rhoades, J. D., Lund, L. J., & Corwin, D. L. (1992). Mapping soil salinity using calibrated electromagnetic measurements. Soil Science Society of America Journal, 56(2), 540–548.
Lesch, S. M., Strauss, D. J., & Rhoades, J. D. (1995). Spatial prediction of soil salinity using electromagnetic induction techniques 1. Statistical prediction models: A comparison of multiple linear regression and cokriging. Water Resources Research, 31(2), 373–386.
McKenzie, R. C., Chomistek, W., & Clark, N. F. (1989). Conversion of electromagnetic inductance readings to saturated paste extract values in soils for different temperature, texture, and moisture conditions. Canadian Journal of Soil Science, 69(1), 25–32.
McNeill, J.D. (1980). Electromagnetic terrain conductivity measurement at low induction numbers. Technical Note TN-6. Ontario, Canada: Geonics Pty Ltd.
McNeill, J.D. (1992). Rapid, accurate mapping of soil salinity by electromagnetic ground conductivity meters. In: Advances in measurement of soil physical properties: Bringing theory into practice, Special Publication, 30 (pp. 209–229). Madison, WI, USA: Soil Science Society of America.
Nelson, D. W., & Sommers, L. E. (1996). Total carbon, organic carbon and organic matter. In D. L. Sparks, A. L. Page, P. A. Helmke, R. H. Loeppert, P. N. Soltanpour, M. A. Tabatabai, C. T. Johnston, & M. E. Sumner (Eds.), Methods of soil analysis. Part 3—Chemical methods (pp. 961–1010). Madison, WI, USA: SSSA, ASA.
Ortiz, R., García, A. F., Sánchez, A., Marín, P., Delgado, M. J., Hernández, J., et al. (2008). Riesgos de Salinización y Alcalinización de la Red de Riegos del Bajo Segura (Salinization and alkalinization hazards in the irrigation network from the lower Segura). Murcia, Spain: Fundación Instituto Euromediterráneo del Agua.
Rallo, G., Provenzano, G., Castellini, M., & Sirera, A. P. (2018). Application of EMI and FDR sensors to assess the fraction of transpirable soil water over an olive grove. Water, 10(2), 168.
Reedy, R. C., & Scanlon, B. R. (2003). Soil water content monitoring using electromagnetic induction. Journal of Geotechnical and Geoenvironmental Engineering, 129(11), 1028–1039.
Rhoades, J. D. (1996). Salinity: electrical conductivity and total dissolved solids. In D. L. Sparks, A. L. Page, P. A. Helmke, R. H. Loeppert, P. N. Soltanpour, M. A. Tabatabai, C. T. Johnston, & M. E. Sumner (Eds.), Methods of soil analysis. Part 3—Chemical methods (pp. 417–435). SSSA, ASA.
Rhoades, J. D., Chanduvi, F., & Lesch, S. (1999). Soil salinity assessment: Methods and interpretations of electrical conductivity measurements. FAO Irrigation and Drainage Paper 57. Rome, Italy: FAO.
Rhoades, J. D., Raats, P. A. C., & Prather, R. J. (1976). Effects of liquid-phase electrical-conductivity, water-content, and surface conductivity on bulk soil electrical-conductivity. Soil Science Society of America Journal, 40(5), 651–655.
Richards, L. A., Allison, L. E., Bernstein, L., Bower, C. A., Brown, J. W., Fireman, M., et al. (1954). Diagnosis and improvement of saline and alkali soils. Washington, DC, USA: United States Department of Agriculture.
Saey, T., Van Meirvenne, M., Vermeersch, H., Ameloot, N., & Cockx, L. (2009). A pedotransfer function to evaluate the soil profile textural heterogeneity using proximally sensed apparent electrical conductivity. Geoderma, 150(3–4), 389–395.
Saltelli, A., Tarantola, S., Campolongo, F., & Ratto, M. (2004). Sensitivity analysis in practice: A guide to assessing scientific models. London, UK: Wiley.
Sheets, K. R., & Hendrickx, J. M. H. (1995). Noninvasive soil water content measurement using electromagnetic induction. Water Resources Research, 31(10), 2401–2409.
Slavich, P. G. (1990). Determining ECa-depth profiles from electromagnetic induction measurements. Australian Journal of Soil Research, 28, 443–452.
Slavich, P. G., & Petterson, G. H. (1990). Estimating average rootzone salinity from electromagnetic induction (Em-38) measurements. Australian Journal of Soil Research, 28(3), 453–463.
Sudduth, K. A., Drummond, S. T., & Kitchen, N. R. (2001). Accuracy issues in electromagnetic induction sensing of soil electrical conductivity for precision agriculture. Computers and Electronics in Agriculture, 31(3), 239–264.
Sudduth, K. A., Kitchen, N. R., Wiebold, W. J., Batchelor, W. D., Bollero, G. A., Bullock, D. G., et al. (2005). Relating apparent electrical conductivity to soil properties across the north-central USA. Computers and Electronics in Agriculture, 46(1–3 SPEC. ISS.), 263–283.
Taghizadeh-Mehrjardi, R., Minasny, B., Sarmadianc, F., & Malone, B. P. (2014). Digital mapping of soil salinity in Ardakan region, central Iran. Geoderma, 213, 15–28.
Triantafilis, J., Huckel, A. I., & Odeh, I. O. A. (2001). Comparison of statistical prediction methods for estimating field-scale clay content using different combinations of ancillary variables. Soil Science, 166(6), 415–427.
Triantafilis, J., Laslett, G. M., & McBratney, A. B. (2000). Calibrating an electromagnetic induction instrument to measure salinity in soil under irrigated cotton. Soil Science Society of America Journal, 64, 1000–1017.
Visconti, F. (2009). Elaboración de un Modelo Predictivo de la Acumulación de Sales en Suelos Agrícolas de Regadío bajo Clima Mediterráneo: Aplicación a la Vega Baja del Segura y Bajo Vinalopó (Alicante) (Making of a predictive model for the salt buildup in irrigated agricultural soils under Mediterranean Climate: Application to the «Vega Baja del Segura y Bajo Vinalopó (Alicante)»). Ph.D. Thesis. València, Spain: Universitat de València EG.
Visconti, F., & de Paz, J. M. (2018). Cómo conocer la salinidad del suelo mediante medidas de conductividad eléctrica (How to know the soil salinity by means of electrical conductivity measurements). Levante Agrícola: Revista Internacional de Cítricos, 441, 98–103.
Visconti, F., & de Paz, J. M. (2021). A semi-empirical model to predict the EM38 electromagnetic induction measurements of soils from basic ground properties. European Journal of Soil Science, 72(2), 720–738. https://doi.org/10.1111/ejss.13044.
Weller, U., Zipprich, M., Sommer, M., Zu Castell, W., & Wehrhan, M. (2007). Mapping clay content across boundaries at the landscape scale with electromagnetic induction. Soil Science Society of America Journal, 71(6), 1740–1747.
West, E. S. (1952). A study of the annual soil temperature wave. Australian Journal of Chemistry, 5(2), 303–314.
Yao, R., & Yang, J. (2010). Quantitative evaluation of soil salinity and its spatial distribution using electromagnetic induction method. Agricultural Water Management, 97(12), 1961–1970.
Zhu, Q., Lin, H., & Doolittle, J. (2010). Repeated electromagnetic induction surveys for determining subsurface hydrologic dynamics in an agricultural landscape. Soil Science Society of America Journal, 74(5), 1750–1762.
We would like to thank the anonymous reviewers and the Editor-in-Chief for their constructing comments.
The first survey of this project was carried out within Project GV 0461/2006, funded by the Generalitat Valenciana, and the second one within Projects CGL2009-14592-C02-01 and CGL2009-14592-C02-02 funded by the Ministerio de Ciencia e Innovación from the Government of Spain and additionally within project Val i+d APOSTD/2010/029 (F. Visconti), funded by the Generalitat Valenciana.
Conflict of interest
The authors declare that they have no conflict of interest.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Visconti, F., de Paz, J.M. Sensitivity of soil electromagnetic induction measurements to salinity, water content, clay, organic matter and bulk density. Precision Agric 22, 1559–1577 (2021). https://doi.org/10.1007/s11119-021-09798-8
- Sensitivity analysis
- Electromagnetic induction
- Water content
- Organic matter