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PROCEEDINGS OF HYDRAULIC ENGINEERING
Article . 2001 . Peer-reviewed
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Application of RUSLE Model on Global Soil Erosion Estimate

Authors: Thai Nam PHAM; Dawen YANG; Shinjiro KANAE; Taikan OKI; Katumi MUSIAKE;

Application of RUSLE Model on Global Soil Erosion Estimate

Abstract

Soil erosion is one of the most serious environmental problems commonly in over the world, which is caused by both natural and human factors. It is possible to investigate the global issue on soil erosion with the development of global data sets. This research estimated global soil erosion by the RUSLE model with use of a comprehensive global data set. The accuracy of the estimate mostly depends on the available information related to the study area. Present available finest data was used in this study. As the desired objective of estimating soil erosion by water at global scale, the application of RUSLE has shown its positive applicability on large-scale estimates. The study has shown a global view of water soil erosion potential with 0.5-degree grid resolution. Regional validations and examinations have been carried out by different ways. The global mean of annual soil erosion by water was estimated as 1100 ton/ km2, which agrees with several results obtained in different regions.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
26
Top 10%
Top 10%
Average
bronze