In the past, texture-based classification of soils has been used for grouping soils in variably saturated water flow and solute transport studies. Classification of soils becomes especially important for large-scale studies where the spatial and temporal variability in the hydraulic properties of soils exceeds the field sampling capabilities. Although soil-texture-based classification has been widely used, questions remain about the validity of its use from a hydraulic perspective. In this study, we attempt to answer the following questions: (1) what is the optimal number of (soil hydraulic) classes that can adequately classify the soils from a hydraulic standpoint, and (2) how does such a classification compare to the soil texture classification currently used? To investigate these questions, the commonly used κ-means clustering algorithm was integrated with the ROSETTA pedotransfer functions to predict the so-called soil hydraulic classes. The optimal soil hydraulic classifications and the associated uncertainty were estimated for numbers of soil hydraulic classes varying from 2 to 30. It was concluded that the optimal number of soil hydraulic classes is 12. The optimal soil hydraulic classes were represented in a ternary diagram called the soil hydraulic triangle. While there exist some surprising similarities in classification between the soil texture triangle and the soil hydraulic triangle for soils with high sand percentages (sand >60%), the opposite is true for soils with low sand contents. From a hydraulic standpoint, the texture-based classification does not classify soils well when there is a considerable impact of capillary forces. The soil texture and hydraulic classes were analyzed for accuracy using two databases. Compared to the soil texture classes, it was found that the soil hydraulic classes marginally improve the accuracy of classification. Even though the improvement is only marginal, it was observed that the optimality of soil texture triangle for hydraulic studies cannot be assured because of the nonuniform distribution of data across various textural possibilities in the two databases. As an extension of this research, we have also estimated the average soil hydraulic parameters for the different optimal soil hydraulic classes.
ASJC Scopus subject areas
- Water Science and Technology