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

Abstract

The general objective of this study was to evaluate the stability of patterns of apparent 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 m  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 to 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.