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dc.contributor.authorZhu, Z
dc.contributor.authorYu, B
dc.date.accessioned2017-08-18T02:06:17Z
dc.date.available2017-08-18T02:06:17Z
dc.date.issued2015
dc.identifier.issn2151-0032
dc.identifier.doi10.13031/trans.58.10451
dc.identifier.urihttp://hdl.handle.net/10072/141151
dc.description.abstractMethods 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.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherAmerican Society of Agricultural and Biological Engineers
dc.relation.ispartofpagefrom61
dc.relation.ispartofpageto71
dc.relation.ispartofissue1
dc.relation.ispartofjournalTransactions of the ASABE
dc.relation.ispartofvolume58
dc.subject.fieldofresearchAgriculture, Land and Farm Management not elsewhere classified
dc.subject.fieldofresearchAgricultural and Veterinary Sciences
dc.subject.fieldofresearchEngineering
dc.subject.fieldofresearchcode070199
dc.subject.fieldofresearchcode07
dc.subject.fieldofresearchcode09
dc.titleValidation of Rainfall Erosivity Estimators for Mainland China
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
dc.description.versionVersion of Record (VoR)
gro.rights.copyright© 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.
gro.hasfulltextFull Text
gro.griffith.authorYu, Bofu


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