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Optimal irrigation water allocation using a genetic algorithm under various weather conditions

(2014) WATER. 6(10). p.3068-3084
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Abstract
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.
Keywords
MULTIPLE CROPS, OPTIMAL RESERVOIR OPERATION, MANAGEMENT, MODEL, irrigation scheduling, Iran, integrated soil water balance, deficit irrigation, cropping pattern

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Citation

Please use this url to cite or link to this publication:

MLA
Sadati, Somayeh Khanjari, Stijn Speelman, Mahmood Sabouhi, et al. “Optimal Irrigation Water Allocation Using a Genetic Algorithm Under Various Weather Conditions.” WATER 6.10 (2014): 3068–3084. Print.
APA
Sadati, S. K., Speelman, S., Sabouhi, M., Gitizadeh, M., & Ghahraman, B. (2014). Optimal irrigation water allocation using a genetic algorithm under various weather conditions. WATER, 6(10), 3068–3084.
Chicago author-date
Sadati, Somayeh Khanjari, Stijn Speelman, Mahmood Sabouhi, Mohsen Gitizadeh, and Bijan Ghahraman. 2014. “Optimal Irrigation Water Allocation Using a Genetic Algorithm Under Various Weather Conditions.” Water 6 (10): 3068–3084.
Chicago author-date (all authors)
Sadati, Somayeh Khanjari, Stijn Speelman, Mahmood Sabouhi, Mohsen Gitizadeh, and Bijan Ghahraman. 2014. “Optimal Irrigation Water Allocation Using a Genetic Algorithm Under Various Weather Conditions.” Water 6 (10): 3068–3084.
Vancouver
1.
Sadati SK, Speelman S, Sabouhi M, Gitizadeh M, Ghahraman B. Optimal irrigation water allocation using a genetic algorithm under various weather conditions. WATER. 2014;6(10):3068–84.
IEEE
[1]
S. K. Sadati, S. Speelman, M. Sabouhi, M. Gitizadeh, and B. Ghahraman, “Optimal irrigation water allocation using a genetic algorithm under various weather conditions,” WATER, vol. 6, no. 10, pp. 3068–3084, 2014.
@article{5765915,
  abstract     = {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.},
  author       = {Sadati, Somayeh Khanjari and Speelman, Stijn and Sabouhi, Mahmood and Gitizadeh, Mohsen and Ghahraman, Bijan},
  issn         = {2073-4441},
  journal      = {WATER},
  keywords     = {MULTIPLE CROPS,OPTIMAL RESERVOIR OPERATION,MANAGEMENT,MODEL,irrigation scheduling,Iran,integrated soil water balance,deficit irrigation,cropping pattern},
  language     = {eng},
  number       = {10},
  pages        = {3068--3084},
  title        = {Optimal irrigation water allocation using a genetic algorithm under various weather conditions},
  url          = {http://dx.doi.org/10.3390/w6103068},
  volume       = {6},
  year         = {2014},
}

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