Please use this identifier to cite or link to this item: http://117.252.14.250:8080/jspui/handle/123456789/5304
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSarkar, Archana-
dc.contributor.authorKumar, Rakesh-
dc.contributor.authorSingh, R. D.-
dc.date.accessioned2020-11-12T19:51:28Z-
dc.date.available2020-11-12T19:51:28Z-
dc.date.issued2012-
dc.identifier.urihttp://117.252.14.250:8080/jspui/handle/123456789/5304-
dc.description.abstractThe magnitude of sediments transported by rivers is a major concern for the water resources planning and management. The methods available for sediment estimation are largely empirical, with sediment rating curves being the most widely used. In this study, Artificial Neural Network (ANN) technique has been applied to model the sediment-discharge relationship of two different rivers. Daily data of sediment concentration and discharge of two rivers namely, Satluj River (Indian part and Pranhita River (a sub-basin of Godavari River in India) have been used. A comparison has been made between the results obtained using ANNs and conventional sediment rating curves. The sediment load estimations for the river obtained by ANNs have been found to be significantly superior to the corresponding classical sediment rating curve ones.en_US
dc.language.isoenen_US
dc.publisherIndian Association of Hydrologists, National Institute of Hydrology, Roorkeeen_US
dc.subjectEmerging Techniqueen_US
dc.subjectWater resources managementen_US
dc.subjectIndian Riversen_US
dc.subjectANN Techniqueen_US
dc.titleIV-3-Modeling Sediment Runoff - Case Studies from Indian Rivers using ANN Technique.en_US
dc.typeTechnical Reporten_US
Appears in Collections:Proceedings of the National Symposium on Water Resources Management in Changing Environment (WARMICE-2012), 8-9 February 2012

Files in This Item:
File Description SizeFormat 
IV-3-Modeling Sediment Runoff - Case Studies from Indian Rivers using ANN Technique..pdf2.18 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.