Open Access Open Access  Restricted Access Subscription or Fee Access

Reservoir Trap Efficiency Using Artificial Neural Networks

Vaibhav Garg, V. Jothiprakash


The developmental activities, undergoing within the vicinity of reservoir watershed, result in discharge of large volumes of sediment into the reservoir, which in turn affects biodiversity of the reservoir and reservoir useful life period. These necessitate the reservoir sedimentation studies. The volume of sediment deposited or trapped in a reservoir can easily be quantified by the simple knowledge of its trap efficiency (Te), which is been estimated by various conventional empirical approaches till date. In the present study empirical methods proposed by Brown and Brune have been modified and adopted to estimate Te of Pong Reservoir (Beas Dam) on the Beas River in Kangra district of Himachal Pradesh, India. The major contribution of the study is incorporation of reservoir age in an empirical equation. It is found that the present study estimation of the Te is much better than any other conventional methods. Further, an attempt has been made to estimate ‘Te’ using Artificial Neural Networks (ANN). The study shows that ANN can successfully be applied to estimate not only the trend but also the magnitude of the Te better than the conventional models.


Age of the reservoir, Brown method, Brune method, Gill method, Reservoir Sedimentation, Trap efficiency, Artificial Neural Networks.

Full Text:


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information. Also: DOI is paid service which provided by a third party. We never mentioned that we go for this for our any journal. However, journal have no objection if author go directly for this paid DOI service.