dc.contributor.author |
Sarkar, Archana |
|
dc.contributor.author |
Kumar, Rakesh |
|
dc.contributor.author |
Singh, R. D. |
|
dc.date.accessioned |
2020-11-12T19:51:28Z |
|
dc.date.available |
2020-11-12T19:51:28Z |
|
dc.date.issued |
2012 |
|
dc.identifier.uri |
http://117.252.14.250:8080/jspui/handle/123456789/5304 |
|
dc.description.abstract |
The 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.iso |
en |
en_US |
dc.publisher |
Indian Association of Hydrologists, National Institute of Hydrology, Roorkee |
en_US |
dc.subject |
Emerging Technique |
en_US |
dc.subject |
Water resources management |
en_US |
dc.subject |
Indian Rivers |
en_US |
dc.subject |
ANN Technique |
en_US |
dc.title |
IV-3-Modeling Sediment Runoff - Case Studies from Indian Rivers using ANN Technique. |
en_US |
dc.type |
Technical Report |
en_US |