Approximation and spatial regionalization of rainfall erosivity based on sparse data in a mountainous catchment of the Yangtze River in Central China

@article{SchnbrodtStitt2013ApproximationAS,
  title={Approximation and spatial regionalization of rainfall erosivity based on sparse data in a mountainous catchment of the Yangtze River in Central China},
  author={Sarah Sch{\"o}nbrodt-Stitt and Anna Maria Gezina Bosch and Thorsten Behrens and Heike Hartmann and Xuezheng Shi and Thomas Scholten},
  journal={Environmental Science and Pollution Research},
  year={2013},
  volume={20},
  pages={6917-6933}
}
In densely populated countries like China, clean water is one of the most challenging issues of prospective politics and environmental planning. Water pollution and eutrophication by excessive input of nitrogen and phosphorous from nonpoint sources is mostly linked to soil erosion from agricultural land. In order to prevent such water pollution by diffuse matter fluxes, knowledge about the extent of soil loss and the spatial distribution of hot spots of soil erosion is essential. In remote… CONTINUE READING

Figures, Tables, and Topics from this paper.

Citations

Publications citing this paper.
SHOWING 1-10 OF 15 CITATIONS

Spatiotemporal variations in rainfall erosivity during the period of 1960–2011 in Guangdong Province, southern China

  • Theoretical and Applied Climatology
  • 2015
VIEW 4 EXCERPTS
CITES BACKGROUND
HIGHLY INFLUENCED

No-tillage effects on N and P exports across a rice-planted watershed

  • Environmental Science and Pollution Research
  • 2016
VIEW 1 EXCERPT
CITES BACKGROUND

References

Publications referenced by this paper.
SHOWING 1-10 OF 95 REFERENCES

Soil erosion risk management in Italy

JM Van der Knijff, RJA Jones, L Montanarella
  • European Commission, European Soil Bureau,
  • 1999
VIEW 10 EXCERPTS
HIGHLY INFLUENTIAL

RECS: A program to calculate the R-factor for the USLE/RUSLE using BOM/ AWS Pluviograph data

B Yu, CJ Rosewell
  • ENS Working Paper No. 8/98,
  • 1998
VIEW 20 EXCERPTS
HIGHLY INFLUENTIAL

Estimating Single Storm Erosion Index

Vincenzo Bagarello, F. D’Asaro
  • 1994
VIEW 17 EXCERPTS
HIGHLY INFLUENTIAL