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A number of riparian ecosystem functions such as reducing chemicals are associated with high soil moisture conditions. Finding easy-to-measure riparian features that indicate soil moisture regime in riparian ecosystem may of use in environmental management. In this study, we answered the following question: can streambank height, on which these riparian zones are, indicate soil moisture regime? By measuring soil matric potential (0.15–0.9 m depth) and water table depth on a weekly basis at three forested riparian zones on different bank heights (low, moderate and high) and under a similar soil type, we demonstrate that riparian zones on high-to-moderate streambank height (h ≥ 1 m) generally have lower water table compared to riparian zones on low streambanks (h ≤ 0.3 m). This difference on water table depth led to significant differences in soil matric potential as water table depth lowers. However, in order to predict soil moisture regime more accurately, streambank height must be associated with a detailed field description of local factors such as soil type which can help in explaining deviations from the expected pattern of soil moisture as shown in moderate and high. [ABSTRACT FROM AUTHOR]

There have been a number of studies dealing with soil hydraulic properties. Yet, there is a poor discussion on the number of samples necessary to represent such variables that usually vary orders of magnitude in space. In the present paper, we examine the adequate number of samples for two soil saturated hydraulic conductivity (Ksat) data sets: (1) normal distribution (a 40 year-old pasture) and (2) non-normal distribution (primary forest). To assess the adequate number of samples in each case, we used for normal distribution, an statistical criterion of standard deviation lower than 5% compared to a high sampling effort (n = 25) as an indicative of a proper representation of Ksat variability. In the case of nonnormal distribution, we used the same criterion but using median absolute deviation (a nonparametric statistics). Both data sets were available in Salemi et al. (2013) and were Ksat measured at 0.15 m soil depth for medium-textured inceptisols in São Paulo State, Brazil. For each data set, we simulated 10 'new' samplings in which we calculated mean and standard deviation from sample 1 to 25 (for normal data) and median and median absolute deviation (for non-normal data). We found that, on average, at least 17 to 22 samples had to be collected to meet the adopted criterion for normal data whereas 20 to 25 had to be collected for non-normal data. Such numbers of samples exceed those used in a number of papers. Additional examples of this method with a light modification are given to establish number of samples in new study areas as well as to estimate number of samples when comparing two (or more) land-uses. Simple and practical procedures like those presented here could estimate the number of samples that adequately represents soil hydraulic properties variability. [ABSTRACT FROM AUTHOR]

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