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| Titel |
Improving the global applicability of the RUSLE model – adjustment of the topographical and rainfall erosivity factors |
| VerfasserIn |
V. Naipal, C. Reick, J. Pongratz, K. Oost |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 8, no. 9 ; Nr. 8, no. 9 (2015-09-15), S.2893-2913 |
| Datensatznummer |
250116559
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| Publikation (Nr.) |
 copernicus.org/gmd-8-2893-2015.pdf |
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| Zusammenfassung |
Large uncertainties exist in estimated rates and the extent of soil erosion
by surface runoff on a global scale. This limits our understanding of the
global impact that soil erosion might have on agriculture and climate. The
Revised Universal Soil Loss Equation (RUSLE) model is, due to its simple
structure and empirical basis, a frequently used tool in estimating average
annual soil erosion rates at regional to global scales. However, large
spatial-scale applications often rely on coarse data input, which is not
compatible with the local scale on which the model is parameterized. Our
study aims at providing the first steps in improving the global
applicability of the RUSLE model in order to derive more accurate global
soil erosion rates.
We adjusted the topographical and rainfall erosivity factors of the RUSLE
model and compared the resulting erosion rates to extensive empirical
databases from the USA and Europe. By scaling the slope according to the
fractal method to adjust the topographical factor, we managed to improve the
topographical detail in a coarse resolution global digital elevation model.
Applying the linear multiple regression method to adjust rainfall erosivity
for various climate zones resulted in values that compared well to high
resolution erosivity data for different regions. However, this method needs
to be extended to tropical climates, for which erosivity is biased due to
the lack of high resolution erosivity data.
After applying the adjusted and the unadjusted versions of the RUSLE model
on a global scale we find that the adjusted version shows a global higher
mean erosion rate and more variability in the erosion rates. Comparison to
empirical data sets of the USA and Europe shows that the adjusted RUSLE model
is able to decrease the very high erosion rates in hilly regions that are
observed in the unadjusted RUSLE model results. Although there are still
some regional differences with the empirical databases, the results indicate
that the methods used here seem to be a promising tool in improving the
applicability of the RUSLE model at coarse resolution on a global scale. |
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