Development of operation policy for dry season reservoirs in tropical partially gauged river basins

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Date

2024

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Taylor and Francis Ltd.

Abstract

The present investigations focus on developing an appropriate model for streamflow generation of a partially gauged basin and the operation of small storage in a tropical, seasonal river basin. The small storages created through the vented dams effectively conserve and sustain the water resources for the lean season. Hence, it is pertinent to develop streamflow models to derive streamflow series at the vented dam locations. In the present investigation, streamflow modelling was attempted using response surface and neural network models in a first of its kind. Out of them, the Response Surface Box Behnken model was found to be most efficient in generating streamflow, with Nash Sutcliff's efficiency above 0.617. Further, it is also essential to operate these small storages to maintain a sustainable, ecological flow in the river course. The operation policy for seasonal storage like vented dams is yet to be reported in the literature. The present work uses reservoir simulation and multi-objective optimisation to derive such storages operation policy through hedging operations, with modified shortage index and mean event deficit as objectives. The performance indicators evaluated the operation policy for eight vented dams of the basin. The results illustrate that vented dams indicate shortages while satisfying the respective demands. The results demonstrate that hedging improves the reservoir's performance by reducing the mean event deficit of 0.268–0.044 Mm3 before and after hedging. The frequency and intensity of shortages were also reduced through hedging for the tropical, seasonal river basins. © 2022 International Association for Hydro-Environment Engineering and Research.

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Keywords

artificial neural network, flow modeling, numerical model, performance assessment, rainfall-runoff modeling, reservoir characterization, river basin, streamflow

Citation

International Journal of River Basin Management, 2024, 22, 2, pp. 187-201

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