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| Titel |
A multifractal approach to characterize cumulative rainfall and tillage effects on soil surface micro-topography and to predict depression storage |
| VerfasserIn |
E. Vidal Vázquez, J. G. V. Miranda, J. Paz-Ferreiro |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 7, no. 10 ; Nr. 7, no. 10 (2010-10-01), S.2989-3004 |
| Datensatznummer |
250005002
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| Publikation (Nr.) |
 copernicus.org/bg-7-2989-2010.pdf |
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| Zusammenfassung |
| Most of the indices currently employed for assessing soil
surface micro-topography, such as random roughness (RR), are merely
descriptors of its vertical component. Recently, multifractal analysis
provided a new insight for describing the spatial configuration of soil
surface roughness. The main objective of this study was to test the ability
of multifractal parameters to assess in field conditions the decay of
initial surface roughness induced by natural rainfall under different soil
tillage systems. In addition, we evaluated the potential of the joint use of
multifractal indices plus RR to improve predictions of water storage in
depressions of the soil surface (MDS). Field experiments were performed on
an Oxisol at Campinas, São Paulo State (Brazil). Six tillage treatments,
namely, disc harrow, disc plough, chisel plough, disc harrow + disc level,
disc plough + disc level and chisel plough + disc level were tested. In each
treatment soil surface micro-topography was measured four times, with
increasing amounts of natural rainfall, using a pin meter. The sampling
scheme was a square grid with 25 × 25 mm point spacing and the plot size was
1350 × 1350 mm (≈1.8 m2), so that each data set consisted of
3025 individual elevation points. Duplicated measurements were taken per
treatment and date, yielding a total of 48 experimental data sets. MDS was
estimated from grid elevation data with a depression-filling algorithm.
Multifractal analysis was performed for experimental data sets as well as
for oriented and random surface conditions obtained from the former by
removing slope and slope plus tillage marks, respectively. All the
investigated microplots exhibited multifractal behaviour, irrespective of
surface condition, but the degree of multifractality showed wide differences
between them. Multifractal parameters provided valuable information for
characterizing the spatial features of soil micro-topography as they were
able to discriminate data sets with similar values for the vertical
component of roughness. Conversely, both, rough and smooth soil surfaces,
with high and low roughness values, respectively, can display similar levels
of spectral complexity. Although in most of the studied cases trend removal
produces increasing homogeneity in the spatial configuration of height
readings, spectral complexity of individual data sets may increase or
decrease, when slope or slope plus tillage tool marks are filtered.
Increased cumulative rainfall had significant effects on various parameters
from the generalized dimension, Dq, and singularity spectrum,
f(α). Overall, micro-topography decay by rainfall was reflected on a shift of
the singularity spectra, f(α) from the left side
(q>>0) to the right side (q<<0) and also on a shift of the generalized
dimension spectra from the right side (q>>0) to the left side
(q<<0). The use of an exponential model of vertical roughness indices,
RR, and multifractal parameters accounting for the spatial configuration
such as D1 or D5 improved estimation of water stored in surface
depressions. |
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