Estimation of Saturated Hydraulic Conductivity of Soils From Particle Size Distribution and Bulk Density Data

Since laboratory and field measurement of soil hydraulic properties is time consuming and subject to large error, numerous models have been proposed to predict soil hydraulic properties from easily measurable soil properties such as particle size distribution, bulk density, effective porosity and carbon content. In this study a multiple linear regression model was developed to predict the saturated hydraulic conductivity of soils from their particle size distribution and bulk density data. Published data from 350 soil core samples of varying soils from different sources were used to develop the model. Stepwise regression selected the best model for prediction of soil hydraulic conductivity (R2 = 0.68, P < 0.0001) from the independent parameters of silt, clay, and bulk density. Additional field measured data were collected to test and validate the model using several statistical evaluation procedures. Based on the statistical evaluation criteria, the model performed fairly well and gave a satisfactory validation versus the field measured data.