Predicting saturated hydraulic conductivity from air permeability: Application in stochastic water infiltration modeling

Abstract

Several relationships exist for predicting unsaturated hydraulic conductivity K (ψ) from saturated hydraulic conductivity K s and the soil‐water retention curve. These relationships are convenient for modeling of field scale system sensitivity to spatial variability in K (ψ) . It is, however, faster and simpler to measure air permeability k a at ψ = −100 cm H 2 O, than K s . This study explores the existence of a general prediction relationship between k a , measured at −100 cm H 2 O, and K s . Comparative analyses between k a ‐ K s relationships for nine Danish and Norwegian soils, six different soil treatments, and three horizons validated the establishment of a soil type, soil treatment, and depth/horizon independent log‐log linear k a ‐ K s relationship. The general k a ‐ K s relationship is based on data from a total of 1614 undisturbed, 100‐cm 3 core samples and displays general prediction accuracy better than ±0.7 orders of magnitude. The accuracy and usefulness of the general relationship was evaluated through stochastic analyses of field scale infiltration and ponding during a rainstorm event. These analyses showed possible prediction bias associated with the general k a ‐ K s relationship, but also revealed that sampling uncertainty associated with estimation of field scale variability in K s from a limited number of samples could easily be larger than the possible prediction bias.