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| Titel |
Describing soil surface microrelief by crossover length and fractal dimension |
| VerfasserIn |
E. Vidal Vázquez, J. G. V. Miranda, A. Paz González |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 14, no. 3 ; Nr. 14, no. 3 (2007-05-30), S.223-235 |
| Datensatznummer |
250012196
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| Publikation (Nr.) |
 copernicus.org/npg-14-223-2007.pdf |
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| Zusammenfassung |
| Accurate description of soil surface topography is essential because
different tillage tools produce different soil surface roughness conditions,
which in turn affects many processes across the soil surface boundary.
Advantages of fractal analysis in soil microrelief assessment have been
recognised but the use of fractal indices in practice remains challenging.
There is also little information on how soil surface roughness decays under
natural rainfall conditions. The objectives of this work were to investigate
the decay of initial surface roughness induced by natural rainfall under
different soil tillage systems and to compare the performances of a
classical statistical index and fractal microrelief indices. Field
experiments were performed on an Oxisol at Campinas, São Paulo State
(Brazil). Six tillage treatments, namely, disc harrow, disc plow, chisel
plow, disc harrow + disc level, disc plow + disc level and chisel plow +
disc level were tested. Measurements were made four times, firstly just
after tillage and subsequently with increasing amounts of natural rainfall.
Duplicated measurements were taken per treatment and date, yielding a total
of 48 experimental surfaces. The sampling scheme was a square grid with 25×25 mm
point spacing and the plot size was 1350×1350 mm, so that each data
set consisted of 3025 individual elevation points. Statistical and fractal
indices were calculated both for oriented and random roughness conditions,
i.e. after height reading have been corrected for slope and for slope and
tillage tool marks. The main drawback of the standard statistical index
random roughness, RR, lies in its no spatial nature. The fractal approach
requires two indices, fractal dimension, D, which describes how roughness
changes with scale, and crossover length, l, specifying the variance of
surface microrelief at a reference scale. Fractal parameters D and l, were
estimated by two independent self-affine models, semivariogram (SMV) and
local root mean square (RMS). Both algorithms, SMV and RMS, gave equivalent
results for D and l indices, irrespective of trend removal procedure, even if
some bias was present which is in accordance with previous work. Treatments
with two tillage operations had the greatest D values, irrespective of
evolution stage under rainfall and trend removal procedure. Primary tillage
had the greatest initial values of RR and l. Differences in D values between
treatments with primary tillage and those with two successive tillage
operations were significant for oriented but not for random conditions. The
statistical index RR and the fractal indices l and D decreased with
increasing cumulative rainfall following different patterns. The l and D
decay from initial value was very sharp after the first 24.4 mm cumulative
rainfall. For five out of six tillage treatments a significant relationship
between D and l was found for the random microrelief conditions allowing a
covariance analysis. It was concluded that using RR or l together with D best
allow joint description of vertical and horizontal soil roughness
variations. |
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