A semi‐empirical model to predict the EM38 electromagnetic induction measurements of soils from basic ground properties

Abstract

Electromagnetic induction (EMI) measurements (σb*) are widely used for the survey of several soil attributes, among which basic properties such as salinity (σe), water content (θw), clay (wc), organic matter (wom) and bulk density (ρb) stand out. In usual practice, purely empirical models relating one of these properties to σb* are calibrated at selected sites. However, this calibration is site and time specific and has to be repeated time and again. In order to understand where the variability of the EMI empirical models comes from, it is necessary to know how the different soil properties contribute to them and, with this aim, a more physically based relationship between σb* and, at least, σe, θw, wc, wom and ρb was developed in this work, additionally including soil temperature (t). It was calibrated and cross‐validated with the data from one survey carried out in a wide agricultural irrigation area in SE Spain, taking σb* measurements with the Geonics EM38 in the horizontal and vertical dipole modes and at various heights over the ground. Then, it was externally validated with the data from a second survey carried out 4 years later in the same area but in a different season. In the calibration, R2 and root mean square error (RMSE) were 0.84 and 0.18 dS m−1 (41%), respectively, for the vertical dipole orientation and 0.90 and 0.11 dS m−1 (39%) for the horizontal one. In the external validation, R2 and RMSE were 0.80 and 0.24 dS m−1 (44%), respectively, for the vertical dipole orientation and 0.90 and 0.13 dS m−1 (38%) for the horizontal one. Therefore, because the performance of the model barely worsened as time passed by, it can be considered to represent the underlying physical process and, therefore, to increase our understanding of how the soil EMI signals are generated, with potential benefits for the planning and comparability of EMI soil measurements, specifically with the EM38, among different areas.Highlights A semi‐empirical model was developed to predict soil EMI measurements from basic ground properties. Salinity, water content, clay, organic matter, bulk density and temperature were used as predictors. The model was able to explain between 80 and 90% of the variance in EMI measurements in the validation. This model helps us understand how the basic soil properties contribute to the EMI measurements.

Optimization of Vineyard Water Management: Challenges, Strategies, and Perspectives

“…In vineyards, these measurements have been correlated with vine stem water potential and berry composition [245]. This limitation comes from the fact that these measurements are usually related to soil properties through purely empirical correlations, which are site-specific and vary over time [244,246]. In a recent study, a semiempirical model represented the underlying physical process that affects electromagnetic induction signals and provided the basis for planning and comparing these measurements among different areas [246].…”

“…This limitation comes from the fact that these measurements are usually related to soil properties through purely empirical correlations, which are site-specific and vary over time [244,246]. In a recent study, a semiempirical model represented the underlying physical process that affects electromagnetic induction signals and provided the basis for planning and comparing these measurements among different areas [246]. However, the use of these sensors in vineyard management is nowadays limited to the delineation of site-specific management zones [10,247,248], which can be useful for precise and optimal irrigation scheduling.…”

Time-Lapse Electromagnetic Conductivity Imaging for Soil Salinity Monitoring in Salt-Affected Agricultural Regions

“…One method for quickly and reliably assessing soil salinity across different locations is through electromagnetic induction (EMI) [7][8][9][10][11][12][13][14]. Electromagnetic instruments measure the apparent electrical conductivity of soil (EC a ; mS m −1 ), which is often strongly correlated with the electrical conductivity of saturated soil paste extract (EC e ) [14].…”

Model-Based Correction of Temperature-Dependent Measurement Errors in Frequency Domain Electromagnetic Induction (FDEMI) Systems

“…Electromagnetic induction (EMI) measurements allow a fast non-contact measurement of the soil apparent electrical conductivity (ECa), which is directly related to the bulk soil electrical conductivity and thus to soil properties such as clay content, salinity and water content. EMI measurements have been used for soil mapping in precision agriculture in a wide range of studies [ 1 , 2 , 3 , 4 ]. For instance, Cameron et al [ 5 ], Visconti and Miguel de Paz [ 6 ] and Corwin and Rhoades [ 7 ] found that EMI allowed the fast mapping of the soil to obtain a clear delineation of field-scale salinity profiles.…”