Apparent electrical conductivity in dry versus wet soil conditions in a shallow soil

The general objective of this study was to evaluate the stability of patterns of apparent soil electrical conductivity (ECₐ) in dry versus wet soil conditions in a shallow soil typically used for pastures in Mediterranean conditions of the southern region of Portugal. A 6 ha experimental field of permanent bio-diverse pasture was divided into 76 squares of 28 × 28 m. The soil electrical conductivity was measured using a Dualem 1S sensor under dry conditions (June 2007) and under wet conditions during the rainy season (March 2010). Soil samples, geo-referenced with GPS, were collected in a depth range of 0–0.30 m. The soil was characterized in terms of bedrock depth, moisture content, texture, pH, organic matter content, and macronutrients (nitrogen, phosphorus, and potassium). Pasture samples, also geo-referenced with GPS, were collected to measure the pasture dry matter yield. The statistical analysis of apparent electrical conductivity between dry and wet soil conditions resulted in a linear significant correlation coefficient (R = 0.88). The results also showed a significant correlation between apparent electrical conductivity and the relative field elevation (R = −0.64 and R = −0.66), the pasture dry matter yield (R = 0.42 and R = 0.48), the bedrock depth (R = 0.40 and R = 0.27), the pH (R = 0.50 and R = 0.49), the silt (R = 0.27 and R = 0.38) and soil moisture content (R = 0.48 and R = 0.45), in dry and wet conditions, respectively. A multi-variate regression was carried out using the following soil parameters that showed significant correlation with ECₐ and that did not present multi-collinearity: pH, bedrock depth, silt and moisture content. The results showed, in dry and wet conditions, that the analysis was significant (R = 0.75 and R = 0.84, respectively). Overall, these results indicate the temporal stability of ECₐ patterns under different soil moisture contents, which is relevant with respect to the time when a field should be surveyed and is important for using the electrical conductivity sensor, as a decision support tool for management zones in precision agriculture.