[b]Optimization Model of Hirmand River Basin Water Resources in the Agricultural Sector Using Stochastic Dynamic Programming under Uncertainty Conditions[/b]
Journal Title: International Journal of Agricultural Management and Development - Year 2016, Vol 6, Issue 2
Abstract
In this study, water management allocated to the agricultural sector’was analyzed using stochastic dynamic programming under uncertainty conditions. The technical coefficients used in the study referred to the agricultural years, 2013-2014. They were obtained through the use of simple random sampling of 250 farmers in the region for crops wheat, barley, melon, watermelon and ruby grapes under the scenarios of drought, wet, normal, and water required in the most sensitive growth stages. Production function and profit function were obtained from the yield-water-product function of crops using Eviews software. Expected net profit of the system and optimal allocation of water were also calculated based on the GAMS economic analysis software. The results revealed that 14% of the cases over the past 30 years had wet years (high), 47% of the time and that 39% had experienced drought (low) and normal (average) years. In the best case, i.e. with high current levels, respectively at, 58, 67, 54, and 48% of water requirements for these crops and, in the worst case (with low current levels), 47, 35, 49, 53 and 48% of the water requirements provided during the most sensitive growth stages. Moreover, the results showed that the cultivation of the ruby grape was the best product with the highest expected profit in normal and rainfall conditions. In general, when the expected value of net profit is positive, managers would act optimistically and they would promise the optimal level of water provided to the farmers. Conversely, when the net value is negative they would prefer to be more conservative and would promise a lesser amount of water provided to the farmers. Hence, if the promised water to the farmer is not wasted, he will choose the loss incurred from a lesser harvest.
Authors and Affiliations
Mahmoud Mohammadghasemi , Javad Shahraki, Mahmood Sabouhi Sabouni
Keywords
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