Abstract
In a multi-reservoir system, a single reservoir’s activity might have an impact on the other reservoirs within the system. Therefore, the reservoir must be managed as a single entity to ensure long-term water conservation. However, the integrated operation of a multi-reservoir system becomes more difficult when there is less rainfall in a basin. For this reason, the existing operating policy must be evaluated to ensure integrated functioning. Metaheuristic-based algorithms such as genetic algorithms (GA) are employed in this study to find the optimal solution, and optimization efficiency can be improved by avoiding local optimal solutions. It aims to develop a steady-state optimum operating policy using a genetic algorithm that can satisfy long-term demand and measure the performance along with a deterministic simulation-optimization model (S-O Model) in terms of reliability, resilience, vulnerability, and sustainability indices of the existing multi-reservoir system, namely, Ravishankar Sagar reservoir, Dudhawa, and Murrum Silli in Chhattisgarh, India. In addition, the overall performance of the existing reservoir is improved based on reliability by 35.66%, resilience by 40.54%, sustainability by 36.70%, and vulnerability reduced by 54.09%, respectively, compared to actual water release. Apart from that, the GA model release satisfactorily meets the needs of demand, and no deficit conditions have occurred during the entire study period, excluding the years 1989–1990, 2001–2002, and 2002–2003, respectively.
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The authors would like to extend their admiration and respect to NIT, Raipur, Chhattisgarh.
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Verma, S., Prasad, A.D., Verma, M.K. (2023). Optimizing Multi-reservoir Systems with the Aid of Genetic Algorithm: Mahanadi Reservoir Project Complex, Chhattisgarh. In: Boonpook, W., Lin, Z., Meksangsouy, P., Wetchayont, P. (eds) Applied Geography and Geoinformatics for Sustainable Development. Springer Geography. Springer, Cham. https://doi.org/10.1007/978-3-031-16217-6_3
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