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Summary Collecting and interpreting permeability data in karst systems is considered complicated due to three distinct properties of these systems. First, the distribution of high permeability features may be one-dimensional features difficult to detect with wells, or may be so high in the wells the upper measurement limit is encountered during aquifer testing. Secondly, turbulent flow may make the application of continuum hydraulic principles difficult. Finally, permeability in these systems commonly increases with the scale of measurement. The aquifer for Sete Lagoas, Brazil, was used to evaluate a permeability combination methodology testing the permeability structure across a range of spatial scales in order to develop a quantitative model of hydraulically active features consistent across all scales of measurement, from matrix properties to regional-scale flow. The aquifer in this study has some wells without measurable drawdown during pumping due to high permeability. Data indicated an increase in permeability from the small- to the well-scale and a decrease from the well- to regional-scale due to the localized development of a karst bedding plane dissolution in one structurally controlled region of the aquifer. The matrix permeability in the region is very low and the secondary porosity is mostly filled by secondary precipitation of calcite. Based on measurement technique, the permeability data vary over many orders of magnitude, while the physical size of permeable features of the aquifer are consistent across the scales of data collection. The geometry provides a quantitative understanding of the scale effects of permeability measurements.

Soil water tension was measured 22 times through a 50 day period, in a transect with 48 sets of tensiometers at five depths. General variability and temporal stability of this property as well as the spatio-temporal dependence of its variability were evaluated. The whole data set was divided into subsets according to location and time of measurement. The variability of soil water tension could be explained by a temporal trend (macro variation) and a random-like micro-variation. The tension values increased similarly for all locations along the measured period, and exhibited strong temporal stability, which was higher at the top layers. It was possible to identify and model spatio-temporal dependence of the variability. The spatial variograms for the sub-sets presented higher uncertainties, but were very similar to each other. Temporal dependence was clearly identified for transformed data, although larger differences were found between sub-sets. Very good agreement was found between the actual and the estimated data using the product–sum model for the spatio-temporal dependence. The procedure seems suitable for combining the spatial and temporal scales to expand the description of the variability dependence of soil hydraulic properties.