Abstract
Accuracy of reservoir capacity loss estimation on daily timescale is dependent on the certainty of sediment load prediction, density estimate and capacity observed by consecutive hydrographic surveys. Data-scarce and uncertain data conditions restrict the development of a relationship between hydrographic surveys and hydrometric observations. The present study has been carried for Ukai Reservoir, India. A novel sediment rating curve fitting approach by optimization technique has been proposed in order to accurately predict sediment load from low-frequency sampled discharge and sediment concentration observations. The study demonstrates the validation of the bulk density estimate using statistical hypothesis testing and identifies the correctness of the hydrographic survey results. Application of the developed hydrometric and hydrographic relationship indicated that about 50% of the capacity loss of a year might occur during a single extreme event. The proposed approach can serve as a decision support system to monitor and manage sedimentation for the reservoir having uncertain data conditions.
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Acknowledgements
We thank Gregory L. Morris, P.E., Ph.D. for the motivation and assistance he provided in taking up this research and R. N. Sankhua, Ph.D., Director, Basin Planning, Ministry of WR, India, for comments on an earlier version of the manuscript, although any errors are our own and should not tarnish the reputations of these esteemed persons. We are grateful to the CWC, India, for collecting and archiving the hydrometric dataset. We would like to thank Ukai Dam authority for the reservoir water budget and hydrographic survey data. We are also immensely grateful to the reviewers for their insights.
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Jabbar, Y.C., Yadav, S.M. Development of a relationship between hydrometric and hydrographic observations to predict reservoir capacity loss. Acta Geophys. 67, 1451–1469 (2019). https://doi.org/10.1007/s11600-019-00323-0
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DOI: https://doi.org/10.1007/s11600-019-00323-0