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 non-normal distribution, we used the same criterion
but using median absolute deviation (a non-parametric 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.
Birincil Dil | İngilizce |
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Bölüm | Articles |
Yazarlar | |
Yayımlanma Tarihi | 1 Ocak 2020 |
Yayımlandığı Sayı | Yıl 2020 Cilt: 9 Sayı: 1 |