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When modeling soil hydraulic properties at field scale it is desirable to approximate the variability in a given area by means of some scaling transformations which relate spatially variable local hydraulic properties to global reference characteristics. As part of a field experiment, where water and solute movement across a soil profile are being monitored on a daily basis, 70 soil cores were sampled within a banana plantation greenhouse on a 14x5 array of 2.5mx5m rectangles at 15 cm depth, to represent the field scale variability of flow related properties. Additionally, at five random locations soil cores were sampled at 4 depths. Saturated hydraulic conductivity (Ksat) and water retention characteristics were measured in these 70+20 soil cores. van Genuchten water retention curves (WRC) with optimized m (m.1-1/n) were fitted to the WR data and a general Mualem-van Genuchten model was used to predict hydraulic conductivity functions for each soil core. A scaling law, of the form .i=ai .i*, was fitted to soil hydraulic data by applying the method of Vogel et al. (1991), Water Resour. Res., 27: 2735-2741, such that the original hydraulic parameters .i were scaled down to a reference curve with parameters .i*. An analytical expression, in terms of Beta functions, for the average suction value, hc, necessary to apply the above scaling method, was obtained. This permitted implementation in a spreadsheet and fast computation of the scaling parameters for the 70 + 20 WRC. Although originally we assumed generality in the scaling law of the water content, i.e. .=a.. *, the scaling procedure showed that .=. *, suggesting that our soil behaves in a geometrically similar fashion with respect to water content, following the work of Miller and Miller (1956). Box-Cox normality plots showed that scaling factors for the suction (ah) and hydraulic conductivity (ak) were approximately log-normally distributed, as it would be expected for such a dynamic properties involving flow. By contrast static soil related properties as a. were found closely Gaussian, although a power of 3/4, was best for approaching normality. Application of four different normality tests (Anderson-Darling, Shaphiro-Wilk, Kolmogorov-Smirnov and Chi-square goodnessof- fit tests) rendered some contradictory results among them, thus suggesting that this widely extended practice is not recommended for providing a suitable probability density function for the scaling parameters, ai. Some indications for the origin of these disagreements, in terms of population size and test constraints, are pointed out. Visual inspection of normal probability plots can also lead to erroneous results. The scaling parameters a. and ak show a sinusoidal spatial variation coincident with the underlying alignment of banana plants on the field. Such anisotropic distribution is explained in terms of porosity variations due to processes promoting soil degradation as surface desiccation and soil compaction, induced by tillage and localized irrigation of banana plants. By contrast such an alignment trend is not so evident for the suction scaling factor, ah. A gradient with soil depth is observed for both ak and ah, while a. remains constant in the whole soil profile. Such a gradient in scaling parameters is interpreted in terms of macro and microporosity changes. Finally conclusions are drawn about scaling up locally estimated soil physical parameters, for water and solute modeling purposes, to field conditions where variability has an important effect.