Improving the field estimation of saturated hydraulic conductivity in soil survey

Abstract

Prediction of the movement and storage of water in soil is central to quantitative land evaluation. However, spatial and temporal predictions have not been provided by most Australian soil surveys. The saturated hydraulic conductivity (K_s) is an essential parameter for description of water movement in soil and its estimation has been considered too difficult for logistic and technical reasons. The K_s cannot be measured everywhere and relationships with readily observed morphological variables have to be established. However, conventional morphology by itself is a poor predictor of K_s. We have developed a more functional set of morphological descriptors better suited to the prediction of K_s. The descriptors can be applied at several levels of detail.

Measurements of functional morphology and K_s were made on 99 horizons from 36 sites across south-eastern Australia. Useful predictions of K_s were possible using field texture, grade of structure, areal porosity, bulk density, dispersion index, and horizon type. A simple visual estimate of areal porosity was satisfactory, although a more quantitative system of measurement provided only slightly better predictions. Regression trees gave more plausible predictive models than standard multiple regressions because they provided a realistic portrayal of the non-additive and conditional nature of the relationships between morphology and K_s.

The results are encouraging and indicate that coarse-level prediction of K_s is possible in routine soil survey. Direct measurement of K_s does not appear to be generally feasible because of the high cost, dynamic nature of K_s, and substantial short-range variation in the field. Prediction is further constrained by the limited returns from more sophisticated morphological predictors. The degree to which this limits practical land evaluation is yet to be demonstrated.