Sample dimensions effect on prediction of soil water retention curve and saturated hydraulic conductivity

•Sample dimensions effect on hydraulic properties prediction is addressed.•A novel data mining method called CPXR is introduced.•The proposed CPXR-based models are statistically evaluated.•The proposed models are compared with the multiple linear regression models.

SummarySoil water retention curve (SWRC) and saturated hydraulic conductivity (SHC) are key hydraulic properties for unsaturated zone hydrology and groundwater. Not only the SWRC and SHC measurements are time-consuming, but also their results are scale dependent. Although prediction of the SWRC and SHC from available parameters, such as textural data, organic matter, and bulk density have been under investigation for decades, up to now no research has focused on the effect of sample dimensions on the soil hydraulic properties pedotransfer functions development. The main purpose here is investigating sample internal diameter and height (or length) effects on the prediction of the soil water retention curve and the saturated hydraulic conductivity. We, therefore, develop pedotransfer functions using a novel approach called contrast pattern aided regression (CPXR) and consider the sample dimensions as input variables. Two datasets including 210 and 213 soil samples with known sample dimensions were extracted from the UNSODA database to develop and evaluate pedotransfer functions for the SWRC and SHC, respectively. The 10-fold cross-validation method is applied to evaluate the accuracy and reliability of the proposed regression-based models. Our results show that including sample dimensions, such as sample internal diameter and height (or length) could substantially improve the accuracy of the SWRC and SHC pedotransfer functions developed using the CPXR method.