DSpace Repository

07-Estimation of Sediment-Discharge of Jwalamukhi Site Using Artificial Neural Network.

Show simple item record

dc.contributor.author Pinki
dc.contributor.author Under the Guidance of Mehta, Rama
dc.date.accessioned 2025-07-23T11:08:08Z
dc.date.available 2025-07-23T11:08:08Z
dc.date.issued 2015
dc.identifier.uri http://117.252.14.250:8080/jspui/handle/123456789/7652
dc.description.abstract Sediment-discharge measurements usually are available on a discrete or periodic basis. However, estimates of sediment transport often are needed for unmeasured periods, such as when daily or annual sediment-discharge values are sought, or when estimates of transport rates for unmeasured or hypothetical flows are required. Selected methods for estimating suspended-sediment, bedload, bed- material-load, and total-load discharges have been presented in some detail elsewhere in this volume. The purposes of this contribution are to present some limitations and potential pitfalls associated with obtaining and using the requisite data and equations to estimate sediment discharges and to provide guidance for Selecting appropriate estimating equations. Records of sediment discharge are derived from data collected with sufficient frequency to obtain reliable estimates for the computational interval and period. Most sediment discharge records are computed at daily or annual intervals based on periodically collected data, although some partial records represent discrete or seasonal intervals such as those for flood periods. The method used to calculate sediment discharge records is dependent on the types and frequency of available data. Records for suspended-sediment discharge computed by methods described by Porterfield (1972) are most prevalent, in part because measurement protocols and computational techniques are well established and because suspended sediment composes the bulk of sediment discharges for many rivers. Discharge records for bed load, total load, or in some cases bed-material load plus wash load are less common. en_US
dc.language.iso en en_US
dc.publisher National Institute of Hydrology en_US
dc.subject Jwalamukhi en_US
dc.subject Artificial Neural Network (ANN) en_US
dc.title 07-Estimation of Sediment-Discharge of Jwalamukhi Site Using Artificial Neural Network. en_US
dc.type Technical Report en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account