A fixed-mix stochastic fractional programming method for optimizing agricultural irrigation and hydropower generation in Central Asia Academic Article uri icon

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abstract

  • In this study, a fixed-mix stochastic fractional programming (FSFP) method is developed for balancing the water-allocation conflict between upstream hydropower generation and downstream agricultural irrigation. FSFP has advantages in dealing with ratio-objective problem under uncertainty, reflecting the dynamic and stochastic characteristics over a long-term planning context, as well as analyzing interrelationships between system efficiency and violation risk of water-allocation target. Then, FSFP is firstly applied to Tuyamuyun reservoir in the lower reach of Amu Darya River basin (Central Asia), where multiple scenarios based on different hydropower-generation targets and inflow levels are examined for identifying the complex relationship between hydropower generation and crop irrigation. Major findings and managerial insights can be summarized as: (i) with the reduction of reservoir inflow, water allocation for downstream agricultural irrigation would decrease by 30.4% once the minimum demand is satisfied, and hydropower generation should be higher priority for pursuing higher marginal benefit; (ii) with the shrinking water supply and rising hydropower-generation target, cotton planting should be firstly restrained due to its high water demand and grape planting is encouraged; (iii) under extreme water scarcity (i.e., low and very-low inflow levels), low-level hydropower generation target (i.e., α = 0.45) is desired for meeting the food requirement in the study basin; (iv) for alleviating the water shortage during dry seasons, it is recommended that water storage should be conducted in autumn and winter, and water release for crop irrigation should be implemented during spring and summer. These findings can help managers identify sustainable water-allocation schemes for agricultural irrigation and hydropower generation against water shortage, environmental destruction and energy insecurity in arid regions.

publication date

  • June 2022