Premium
A semi‐empirical model to predict the EM38 electromagnetic induction measurements of soils from basic ground properties
Author(s) -
Visconti Fernando,
De Paz José Miguel
Publication year - 2021
Publication title -
european journal of soil science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.244
H-Index - 111
eISSN - 1365-2389
pISSN - 1351-0754
DOI - 10.1111/ejss.13044
Subject(s) - calibration , soil science , soil water , environmental science , mean squared error , empirical modelling , irrigation , soil salinity , mathematics , statistics , agronomy , computer science , biology , programming language
Electromagnetic induction (EMI) measurements ( σ b *) are widely used for the survey of several soil attributes, among which basic properties such as salinity ( σ e ), water content ( θ w ), clay ( w c ), organic matter ( w om ) and bulk density ( ρ b ) stand out. In usual practice, purely empirical models relating one of these properties to σ b * 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 σ b * and, at least, σ e , θ w , w c , w om and ρ b 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 σ b * 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, R 2 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, R 2 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.