Pedotransfer functions (PTFs) have gained recognition in recent years as an approach to translate simple soil characteristics found in soil surveys into more complicated model input parameters. However, existing pedotransfer functions have not yet incorporated critical soil structural information. This study showed that soil hydraulic properties could be estimated from morphological features determined in situ (including texture, initial moisture state, pedality, macroporosity, and root density) through a morphology quantification system. Comparison between the class and continuous PTFs developed in this study indicated that the use of quantified morphological properties yielded predictive power similar to that of physical properties in estimating hydraulic conductivity at zero potential; water flow rates in macro‐, meso‐, and micropores; and a soil structure and texture parameter αmacro The results confirmed that soil structure was crucial in characterizing hydraulic behavior in macropore flow region; whereas texture had major impact on those hydraulic properties controlled by micropores. Depending on the flow domain to be included, estimation of hydraulic properties required the use of different combinations of morphometric indices or physical properties. The PTFs established may be used as starting points for estimating model input parameters.

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Utilization of existing soil survey databases for characterizing water flow and solute transport in field soils has practical value. However, the lack of a proper means for quantifying soil morphology limits the incorporation of soil structural information into models. In this study, we examined basic relationships between five major soil morphological features (texture, initial moisture, pedality, macroporosity, and root density) and steady infiltration rates for 96 soil horizons of varying structure. Based on these relationships, a point scale system was developed as an approach to quantify soil morphology. Descriptive morphological classes were first rated with respect to their potential impacts on soil water flow rate. Points that provided the best correlation with the measured steady infiltration rates were then obtained for each morphological class through a computer optimization program. The optimal points assigned to each morphological feature were divided by the maximum value to yield a morphometric index of 0 to 1. Such an approach permitted the determination of interrelationships among different morphological features that would otherwise be difficult with qualitative descriptors. The proposed morphology quantification system also has potential in facilitating pedotransfer studies of estimating water flow and chemical transport parameters from soil survey databases including structural descriptors.

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