Understanding water movement in the vadose zone is critical for accurate climate and crop modeling, precision agriculture, soil-atmosphere gas exchanges, and contamination mitigation. A major reason for the difficulty of performing effective hydraulic measurements is because they are scale dependent due to the inherent heterogeneity of the soil. A better understanding of the spatial variability and underlying processes responsible for this variability could lead to a more accurate modeling. The goal of this study is to investigate the scale dependencies of soil hydraulic properties. Factorial kriging analysis (FKA) is a geostatistical technique which identifies scale dependent spatial relationships and common sources of variability. FKA was applied on a number of soil properties acquired from samples collected at 4 depths ranging from 8 to 68. cm in a 20.8. ha field in the Po River delta. The farmland is characterized by the presence of paleo-channel structures and highly heterogeneous soil. Texture, bulk density, Ks (saturated hydraulic conductivity), and the van Genuchten-Mualem parameters α (inverse of air entry), n (shape parameter), θr (residual water content), and θs (saturated water content) were included in the analysis. Two nested spherical models with ranges around 105. m and 235. m plus nugget fit the experimental variograms and cross-variograms best. Regionalized correlation coefficients and regionalized PCA revealed many strong, scale dependent relationships which were not obvious from descriptive statistics, such as the effect of interaction between texture and bulk density on n and Ks, and the stronger influence of bulk density than texture on Ks. The first principal components (PCs) of the regionalized PCA explained the majority of the variability and the second PCs were rarely informative. The spatial distributions of the first PCs resembled bulk density at short scale and the paleo-channels and texture at long scale. The decoupling of bulk density and texture is likely caused by differences in soil structure. The influence of the short scale PCs is greater than the long scale PCs near the surface but becomes less important as depth increases. This suggests that depth plays an important role and should be considered more often in spatial analysis.