Journal of Mountain Science

, Volume 10, Issue 6, pp 1008–1017 | Cite as

Characteristics of rainfall erosivity based on tropical rainfall measuring mission data in Tibet, China

  • Jian-rong FanEmail author
  • Yang Chen
  • Dong Yan
  • Fen-fen Guo


Rainfall erosivity in Tibet from 2000 to 2010 was estimated based on simplified erosion prediction model using daily rainfall data derived from the Tropical Rainfall Measurement Misssion (TRMM) 3B42 rainfall measurement algorithm. Semimonthly erosive rainfall and rainfall erosivity were validated using weather station data. The spatial distribution of annual rainfall erosivity as well as its seasonal and annual variation in Tibet was also examined. Results showed that TRMM 3B42 data could serve as an alternative data source to estimate rainfall erosivity in the area where only data from sparsely distributed weather stations are available. The spatial distribution of rainfall erosivity in Tibet generally resembles the distribution of multi-year average of annual rainfall. Annual rainfall erosivity in Tibet decreased from the southeast to the northwest. The concentration degree of rainfall erosivity shows an increasing trend from the southeast to the northwest. High rainfall erosivity accompanies low rainfall erosivity concentration degree and vice versa. Rainfall erosivity increased in the middle and western Tibet and decreased in the southeastern Tibet during the 11 years of this study.


Rainfall erosivity TRMM 3B42 data Tibet Temporal distribution Spatial distribution 


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Copyright information

© Science Press, Institute of Mountain Hazards and Environment, CAS and Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jian-rong Fan
    • 1
    • 2
    Email author
  • Yang Chen
    • 2
    • 3
  • Dong Yan
    • 4
  • Fen-fen Guo
    • 2
    • 3
  1. 1.Key Laboratory of Mountain Hazards and Earth Surface ProcessesChinese Academy of SciencesChengduChina
  2. 2.Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengduChina
  3. 3.University of the Chinese Academy of SciencesBeijingChina
  4. 4.Department of Geography and Environmental SustainabilityUniversity of OklahomaNormanUSA

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