Predicting ephemeral gully location and length using topographic index models

dc.citation.doi10.13031/trans.56.10087en_US
dc.citation.epage1440en_US
dc.citation.issue4en_US
dc.citation.jtitleTransactions of the ASABEen_US
dc.citation.spage1427en_US
dc.citation.volume56en_US
dc.contributor.authorDaggupati, Prasad
dc.contributor.authorDouglas-Mankin, Kyle R.
dc.contributor.authorSheshukov, Aleksey Y.
dc.contributor.authoreidkrdmen_US
dc.contributor.authoreidasheshen_US
dc.date.accessioned2013-12-02T20:52:55Z
dc.date.available2013-12-02T20:52:55Z
dc.date.issued2013-07-01
dc.date.published2013en_US
dc.description.abstractEphemeral gullies (EGs) are incised channels resulting from concentrated overland flow that often form in a similar location every year. These erosional features add to producers’ management efforts and costs. Locating EGs and predicting their length is crucial for estimating sediment load and planning conservation strategies. Since topography plays an important role in the formation of EGs, this study investigated the prediction of EG location and length in two agricultural areas (S1 and S2) in two different physiographic regions using four topographic index models: compound topographic index (CTI), slope area (SA), wetness topographic index (WTI), and slope area power (SAP). The impacts of digital elevation model (DEM) resolution, agricultural land use mask data source, and topographic model critical thresholds were also evaluated. Automated geospatial models were developed to locate and derive EG length. Results show that the SA model predicted EG occurrence and length better than other models tested. The SA and CTI model predictions had similar patterns in terms of locating EG trajectory; however, the CTI model had greater discontinuity along the trajectory. The method developed to derive length in this study was sensitive to discontinuity, so the performance of the CTI model was poor. Finer-resolution DEMs (2 m) predicted EG location and lengths better than coarser-resolution DEMs (10 m or greater). Use of actual field-level reconnaissance data instead of NASS data for agricultural land use masking decreased false negative classification by 16% or more for all models. Detailed calibration of the SA model yielded different optimal thresholds for the two study regions: T[subscript SA] = 30 for S1 and T[subscript SA] = 50 for S2. Topographic index models were found to be useful in locating EGs and estimating expected lengths, but site-specific calibration of the topographic index model threshold was required, which might limit the general utility of these methods.en_US
dc.identifier.urihttp://hdl.handle.net/2097/16943
dc.language.isoen_USen_US
dc.relation.urihttp://doi.org/10.13031/trans.56.10087en_US
dc.rightsThis Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).en_US
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectEphemeral gullyen_US
dc.subjectModelingen_US
dc.subjectSedimenten_US
dc.subjectTopographyen_US
dc.titlePredicting ephemeral gully location and length using topographic index modelsen_US
dc.typeArticle (publisher version)en_US

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