TECHNICAL PAPERS
May 21, 2010

Modeling the Time Variation of Reservoir Trap Efficiency

Publication: Journal of Hydrologic Engineering
Volume 15, Issue 12

Abstract

All reservoirs are subjected to sediment inflow and deposition to a certain extent resulting in reduction of their capacity. Trap efficiency (Te) , a most important parameter for reservoir sedimentation studies, is being estimated using conventional empirical methods till today. A limited research has been carried out on estimating the variation of Te with time. In the present study, an attempt has been made to incorporate the age of the reservoir to estimate the Te . This study investigates the suitability of conventional empirical approaches along with soft computing data-driven techniques to estimate the reservoir Te . The incorporation of reservoir age, in empirical model, has resulted in a better Te estimation. Further, to estimate Te at different time steps, soft computing approaches such as artificial neural networks (ANNs) and genetic programming (GP) have been attempted. Based on correlation analysis, it was found that ANN model (4–4-1) resulted better than conventional empirical methods but inferior to GP. The results show that the GP model is parsimonious and understandable and is well suited to estimate Te of a large reservoir.

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Acknowledgments

The writers would like to thank BBMB for providing data to carry out this work. They gratefully acknowledge the anonymous reviewers and editors for their valuable comments and suggestions.

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Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 15Issue 12December 2010
Pages: 1001 - 1015

History

Received: Aug 27, 2008
Accepted: Apr 30, 2010
Published online: May 21, 2010
Published in print: Dec 2010

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Authors

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Vaibhav Garg, S.M.ASCE [email protected]
Research Scholar, Dept. of Civil Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400 076, Maharashtra, India. E-mail: [email protected]
V. Jothiprakash [email protected]
Associate Professor, Dept. of Civil Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400 076, Maharashtra, India (corresponding author). E-mail: [email protected]

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