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dc.contributor.authorYu, Bofuen_US
dc.date.accessioned2017-04-04T15:50:09Z
dc.date.available2017-04-04T15:50:09Z
dc.date.issued2002en_US
dc.date.modified2009-09-08T08:01:32Z
dc.identifier.issn00012351en_US
dc.identifier.doihttp://asae.frymulti.com/abstract.asp?aid=9952en_AU
dc.identifier.urihttp://hdl.handle.net/10072/6721
dc.description.abstractCLIGEN is a stochastic weather generator that produces continuous daily variables to drive process-based runoff and erosion prediction models such as WEPP. To test CLIGEN's ability to generate precipitation-related variables, which are particularly important to runoff and erosion prediction, algorithms were developed to compute the R-factor, its monthly distribution, and 10-year storm erosion index (EI) needed to apply the Revised Universal Soil Loss Equation (RUSLE). Measured R-factor and 10-year storm EI for 76 sites in the U.S. were used for calibration, and 89 additional sites were used for validation. It was found that the generated R-factor using CLIGEN is highly correlated with the measured R-factor for the calibration sites (r2 = 0.96), although the generated R-factor is systematically larger than the measured R-factor. The predicted R-factor for validation sites has a model efficiency (Ec) of 0.92 and a root mean squared error of around 600 MJ mm ha-1 h-1 year-1, or 24% of the average R-factor for the 89 sites. In addition, CLIGEN-generated precipitation data can also be used to predict 10-year storm EI (Ec = 0.75) and monthly distribution of rainfall erosivity for a wide range of climate environments (average discrepancy = 2.6%). This represents considerable improvement over existing methods to estimate R-factor and 10-year storm EI for locations with only monthly precipitation data, although the systematic over-estimation of the R-factor using CLIGEN-generated climate data suggests possible inadequacies in the assumed storm patterns in CLIGEN and WEPP.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.format.extent1626875 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherASAEen_US
dc.publisher.placeSt Joseph, USAen_US
dc.publisher.urihttp://www.asabe.org/pubs/trans.htmlen_AU
dc.relation.ispartofpagefrom993en_US
dc.relation.ispartofpageto1001en_US
dc.relation.ispartofissue4en_AU
dc.relation.ispartofjournalTransactions of the ASAEen_US
dc.relation.ispartofvolume45en_US
dc.subject.fieldofresearchcode260599en_US
dc.titleUsing CLIGEN to generate RUSLE climate inputsen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.facultyGriffith Sciences, Griffith School of Engineeringen_US
gro.rights.copyrightCopyright 2002 American Society of Agricultural and Biological Engineers (ASABE). The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the journal link for access to the definitive, published version.en_AU
gro.date.issued2002
gro.hasfulltextFull Text


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