Development of a relationship between hydrometric and hydrographic observations to predict reservoir capacity loss

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.