The growing significance of preserving the health of downstream river ecosystems impacted by reservoir operations has stimulated the development of effective long-term reservoir operation strategies. These strategies aim to strike a reasonable balance between meeting human water needs and maintaining environmental flows. To address this, a novel two-stage multi-objective simulation-optimization (S-O) framework has been proposed. In the first stage, optimal monthly environmental flow (E-flow) targets are determined through a multi-objective model of minimizing the modified shortage index (MSI) of irrigation at the reservoir and hydrologic alteration (HA) in the river (a conventional single-stage model). The trade-off between the MSI of existing irrigation requirements and the MSI of derived E-flow requirements is obtained in stage-2, for the E-flow targets corresponding to the possible range of HA obtained from the stage-1. Both stages share a common reservoir simulation module employing fuzzy hedging factors and fuzzified (transition) rule curves. Application of the proposed two-stage model to the monthly operation of the Bhadra reservoir in Southern India illustrates its superiority over the conventional single-stage model in achieving a better trade-off between irrigation and E-flows at the reservoir, markedly improving E-flow performance.
A novel a continuous hedging rule for the long-term operation of multi-purpose reservoirs is proposed by extending the generalized linear two-point hedging technique. A S-O model is developed for the same and employed to obtain the trade-off between the existing irrigation requirements and derived E-flow requirements from stage-1 of the two-stage S-O model illustrated for the long-term operation of the Bhadra reservoir. The results clearly demonstrate the efficiency of the proposed continuous hedging rule over the Fuzzified and discrete hedging rules in significantly enhancing the trade-off between competing reservoir uses accompanied by their superior performances. The proposed models would enable reservoir managers frame appropriate operating policies that meet downstream E-flow requirements while addressing other beneficial uses, already served by the reservoir.