An in-situ methodology to separate the contribution of soil water content and salinity to EMI-based soil electrical conductivity

Abstract

Salt accumulation in the root zone limits agricultural productivity and can eventually lead to land abandonment. Therefore, monitoring the spatial distribution of soil water content and solution salinity is crucial for effective land and irrigation management. However, assessing soil water content and salinity at the field scale is often challenging due to the heterogeneity of soil properties. Electromagnetic induction (EMI) offers a fast, non-invasive, in situ geophysical method to map spatial variability in soil. EMI instruments measure the apparent soil electrical conductivity (ECa), which reflects the integrated contribution of the bulk electrical conductivity (b) of different soil layers. By inverting the measured ECa, it is possible to obtain the distribution of the b along the soil profile, which provides indirect information on soil salinity. However, in saline soils, b is influenced by both water content () and soil solution electrical conductivity (w) (the salinity), making it difficult to independently quantify these two variables through a single, straightforward procedure. The objective of this study is to separate the respective contributions of  and w to b, as obtained from the EMI inversion. To achieve this, ECa was measured using a CMD-MiniExplorer instrument in two maize plots irrigated with saline and non-saline water, respectively, in an agricultural field in southern Italy. The dataset was then inverted in order to obtain the b distribution. By employing a site-specific calibrated Rhoades linear model and assuming pedological homogeneity between the two plots, the spatial distribution of  and w in the saline plot was successfully estimated. To validate the results, independent measurements of soil water content by Time Domain Reflectometry (TDR) and direct measurement of soil solution electrical conductivity, w, were performed. The proposed procedure enables the estimation of  and w with high accuracy along the soil profile, except in the soil surface, where EMI reliability is limited. These findings demonstrate that the integration of EMI with a site-specific –b–w model is a reliable and efficient in-situ approach for mapping soil salinity and water content at field scale, offering valuable insights for optimizing agricultural irrigation management in systems using saline water.