• myGriffith
    • Staff portal
    • Contact Us⌄
      • Future student enquiries 1800 677 728
      • Current student enquiries 1800 154 055
      • International enquiries +61 7 3735 6425
      • General enquiries 07 3735 7111
      • Online enquiries
      • Staff phonebook
    View Item 
    •   Home
    • Griffith Research Online
    • Journal articles
    • View Item
    • Home
    • Griffith Research Online
    • Journal articles
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

  • All of Griffith Research Online
    • Communities & Collections
    • Authors
    • By Issue Date
    • Titles
  • This Collection
    • Authors
    • By Issue Date
    • Titles
  • Statistics

  • Most Popular Items
  • Statistics by Country
  • Most Popular Authors
  • Support

  • Contact us
  • FAQs
  • Admin login

  • Login
  • Validation of Rainfall Erosivity Estimators for Mainland China

    Thumbnail
    View/Open
    YuPUB1574.pdf (551.9Kb)
    File version
    Version of Record (VoR)
    Author(s)
    Zhu, Z
    Yu, B
    Griffith University Author(s)
    Yu, Bofu
    Year published
    2015
    Metadata
    Show full item record
    Abstract
    Methods are needed to estimate R-factor values and their seasonal distribution from daily rainfall totals in regions with little or no sub-daily rainfall intensity data. This study used calculated R-factor values for a 29-year period (1956-1984) for 22 locations in mainland China to evaluate two estimators of rainfall erosivity for large-scale application of the Universal Soil Loss Equation (USLE) or the Revised USLE (RUSLE), one for an R-factor estimated from mean annual precipitation and another for event erosivity from daily rainfall. This study shows that as a first approximation, the mean annual precipitation is ...
    View more >
    Methods are needed to estimate R-factor values and their seasonal distribution from daily rainfall totals in regions with little or no sub-daily rainfall intensity data. This study used calculated R-factor values for a 29-year period (1956-1984) for 22 locations in mainland China to evaluate two estimators of rainfall erosivity for large-scale application of the Universal Soil Loss Equation (USLE) or the Revised USLE (RUSLE), one for an R-factor estimated from mean annual precipitation and another for event erosivity from daily rainfall. This study shows that as a first approximation, the mean annual precipitation is non-linearly related to the R-factor, and that the relationship can be used to predict the R-factor for mainland China locations (Nash-Sutcliffe model efficiency Ec = 0.88, RMSE = 28% of the mean). The nonlinear relationship for China is quite similar to those reported in other studies for Australia and the U.S. The study also shows that a daily rainfall erosivity model using average parameter values previously applied for Australia can satisfactorily estimate the seasonal variation in rainfall erosivity in addition to the R-factor for the mainland China locations (Ec = 0.90, RMSE = 25% of the mean). Once calibrated, model estimates of the R-factor and its monthly distribution from daily rainfall for the mainland China locations improved noticeably (Ec = 0.99, RMSE < 10% of the mean). The daily rainfall erosivity model and a gridded daily precipitation dataset (the China Gridded Daily Precipitation Product) with a 0.25° (~25 km) resolution were then used to produce a concurrent daily rainfall erosivity map for the mainland China locations (Ec = 0.96, RMSE = ~23% of the mean) for a 5-year period from April 2008 to March 2013. This study shows that: (1) mean annual precipitation can be used to estimate the R-factor for mainland China, Australia, and the U.S.; and (2) a calibrated daily rainfall erosivity model performed well in estimating the seasonal and interannual variations in rainfall erosivity, in addition to the R-factor, for large-scale erosion monitoring and assessments in China.
    View less >
    Journal Title
    Transactions of the ASABE
    Volume
    58
    Issue
    1
    DOI
    https://doi.org/10.13031/trans.58.10451
    Copyright Statement
    © 2015 American Society of Agricultural and Biological Engineers. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
    Subject
    Agriculture, Land and Farm Management not elsewhere classified
    Agricultural and Veterinary Sciences
    Engineering
    Publication URI
    http://hdl.handle.net/10072/141151
    Collection
    • Journal articles

    Footer

    Disclaimer

    • Privacy policy
    • Copyright matters
    • CRICOS Provider - 00233E

    Tagline

    • Gold Coast
    • Logan
    • Brisbane - Queensland, Australia
    First Peoples of Australia
    • Aboriginal
    • Torres Strait Islander