Determining saturated hydraulic conductivity of medium land soils under different cropping systems in semi-arid red and lateritic region.

Abstract

To predict the saturated hydraulic conductivity of the semi-arid red and lateritic medium soils of West Bengal, India, different statistical procedures such as correlation matrix, multiple regression equations and principal component analysis were employed on the measured dataset for different soil variables. The correlation and regression functions suggested sand fraction as the key indicator in regulating the saturated hydraulic conductivity of the soils. While the PCA and minimum data set (MSD) techniques showed that the first component could explain maximum variance of the saturated hydraulic conductivity than the second and third component. The soil porosity, cation exchange capacity and clay fraction in combination were identified as the best predictors which could contribute maximum variability of the saturated hydraulic conductivity. This unorthodox technique may provide an alternative way of estimating the saturated hydraulic conductivity indirectly from the easily measured basic soil properties.