Operation Policies through Dynamic Programming and Genetic Algorithms, for a Reservoir with Irrigation and Water Supply Uses

In this study, operation policies were obtained for a reservoir in Michoacán, Mexico, used for irrigation and domestic water supplies. The main purpose of these policies is to optimize the uses of the water, an increasingly scarce resource everywhere. Two optimization methodologies were used; stocha...

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Bibliographic Details
Published in:Water resources management 2021-03, Vol.35 (5), p.1573-1586
Main Authors: Mendoza Ramírez, Rosalva, Arganis Juárez, Maritza Liliana, Domínguez Mora, Ramón, Padilla Morales, Luis Daniel, Fuentes Mariles, Óscar Arturo, Mendoza Reséndiz, Alejandro, Carrizosa Elizondo, Eliseo, Carmona Paredes, Rafael Bernardo
Format: Article
Language:English
Subjects:
Algorithms
Atmospheric Sciences
Civil Engineering
Domestic water
Dynamic programming
Earth and Environmental Science
Earth Sciences
Environment
Genetic algorithms
Geotechnical Engineering & Applied Earth Sciences
Hydrogeology
Hydrology/Water Resources
Inflow
Irrigation
Irrigation water
Methods
Optimization
Policies
Reservoir operation
Stochasticity
Water inflow
Water supply
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Summary:In this study, operation policies were obtained for a reservoir in Michoacán, Mexico, used for irrigation and domestic water supplies. The main purpose of these policies is to optimize the uses of the water, an increasingly scarce resource everywhere. Two optimization methodologies were used; stochastic dynamic programming, that provides release decisions for each stage, and genetic algorithms coupled with a reservoir operation simulation program, to achieve annual release curves. The operation of the reservoir was evaluated using historical inflow records. Monthly requirements for crop cycles, as well as the volumes of spills and deficits were examined. Both methodologies gave inverse relationships between deficits and spilled volumes. While both methodologies proved efficient in achieving the objectives, the results of the stochastic dynamic programming showed a better performance for this system.
ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-021-02802-w