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Open AccessArticle

Optimal Irrigation Water Allocation Using a Genetic Algorithm under Various Weather Conditions

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Department of Agricultural Economics, Zabul University, Zabul 98615-538, Iran
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Department of Agricultural Economics, Gent University, Gent 9000, Belgium
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Department of Electronics and Electrical Engineering, Shiraz University of Technology, Shiraz 71555-313, Iran
4
Irrigation Department, Ferdowsi University, Mashhad 91779-48974, Iran
*
Author to whom correspondence should be addressed.
Water 2014, 6(10), 3068-3084; https://doi.org/10.3390/w6103068
Received: 30 August 2013 / Revised: 19 September 2014 / Accepted: 22 September 2014 / Published: 14 October 2014
Growing water scarcity, due to growing populations and varying natural conditions, puts pressure on irrigation systems, which often are the main consumptive water users. Therefore, water resources management to improve the allocation of limited water supplies is essential. In this study, a non-linear programming optimization model with an integrated soil/water balance is developed to determine the optimal reservoir release policies and the optimal cropping pattern around Doroudzan Dam in the South-West of Iran. The proposed model was solved using a genetic algorithm (GA). Four weather conditions were identified by combining the probability levels of rainfall, evapotranspiration and inflow. Moreover, two irrigation strategies, full irrigation and deficit irrigation were modeled under each weather condition. The results indicate that for all weather conditions the total farm income and the total cropped area under deficit irrigation were larger than those under full irrigation. In addition, our results show that when the weather conditions and the availability of water changes the optimal area under corn and sugar beet decreases sharply. In contrast, the change in area cropped with wheat is small. It is concluded that the optimization approach has been successfully applied to Doroudzan Dam region. Thus, decision makers and water authorities can use it as an effective tool for such large and complex irrigation planning problems. View Full-Text
Keywords: cropping pattern; deficit irrigation; integrated soil water balance; Iran; irrigation scheduling cropping pattern; deficit irrigation; integrated soil water balance; Iran; irrigation scheduling
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Sadati, S.K.; Speelman, S.; Sabouhi, M.; Gitizadeh, M.; Ghahraman, B. Optimal Irrigation Water Allocation Using a Genetic Algorithm under Various Weather Conditions. Water 2014, 6, 3068-3084.

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