Comparative Analysis of Saturated Hydraulic Conductivity (K _sat) Derived from Image Analysis of Soil Thin Sections, Pedotransfer Functions, and Field-Measured Methods

Abstract

Saturated hydraulic conductivity (K _sat) is an important soil parameter that governs water movement through horizons, pedons, and soil landscapes. K _sat is infamous for its spatial and temporal variability, which contributes to the difficulty and considerable expense in measuring or otherwise quantifying it. Consequently, predictive methods such as pedotransfer functions (PTFs) that use physical soil properties, such as texture and bulk density, have been developed to derive K _sat values. Soil texture and structure are key factors influencing K _sat because of their direct relationship to pore size distribution. Quantitatively defining the combined effects of texture and structure on pore size distribution in a PTF is a difficult task. The objectives of this research were to: (i) estimate K _sat based on pore characteristics derived from soil thin sections via image analysis; and (ii) compare the resultant values with field-measured K _sat and with K _sat estimated by a PTF using soil texture and bulk density parameters. We digitally scanned 39 thin sections from 11 pedons of soils derived from loess over till and/or over weathered sandstone. Soil voids were classified based on their size and shape. K _sat was measured in the field using a Compact Constant-head Permeameter (Amoozemeter) and estimated using a Rosetta PTF. Simple and multiple linear regression (MLR) analyses were used to relate pore indexes and soil physical properties with measured and estimated K _sat. The mean measured K _sat was 0.74 cm h⁻¹, whereas the PTF-estimated K _sat from Rosetta and MLR were 0.36 cm h⁻¹ and 0.49 cm h⁻¹, respectively. The addition of pore characteristics into the model improved K _sat predictions compared to predictions using Rosetta alone. The estimated K _sat based on the model with added pore characteristics was better correlated with field-measured K _sat (r = 0.82) than that based on Rosetta (r = 0.62). The addition of pore characteristics can improve K _sat predictions. However, thin section void analysis from additional parent materials is needed.