Document Type : Research Paper

Authors

1 Department of Water Engineering, Faculty of Agriculture, University of Agricultural Sciences & Natural Resources, Gorgan, Iran.

2 Department of Water Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran.

Abstract

Optimizing the crop cultivation pattern, in order to reduce water consumption, in arid and semi-arid regions such as Iran, due to water scarcity and food intake, is an essential solution for food intakes needs. Optimizing the crop cultivation pattern, in order to reduce water consumption, in arid and semi-arid regions such as Iran, due to water scarcity and food intake, is an essential solution for food intakes needs. In this study, new methods based on the election algorithms (EA) and gray wolf optimizer (GWO) algorithms were used to determine the optimal cultivation pattern in Moghan plain during the statistical years of 2007-2016. The objective function in the agricultural sector was based on each product and its yield, net from each product and the cultivar. Then, maximization of the objective function was performed using GWO and EA algorithm. The results of using GWO algorithm in determining the optimal crop pattern in Moghan plain showed that using economic policies such as changing the cultivar pattern, we can obtain a better result compared to EA algorithm in the agricultural sector. In general, the results of GWO algorithm showed that in the Moghan plain with 0.9, 140 billion rials, that is, about 42 % will have economic growth. In sum, the results showed that GWO algorithm with high values of statistical criteria (R2=0.96, RMSE=0.022 and NSE=0.75) has a higher efficiency in optimizing the crop cultivation pattern of Moghan plain, which can be applied to the correct planning for other cultivation areas to be employed.

Keywords

Alabdulkader A.M., Al-Amoud A.I., Awad F.S., Optimization of the cropping pattern in Saudi Arabia using a mathematical programming sector model, Agricultural Economics/Zemedelska Ekonomika 12 (2012) 58-69.
Alizadeh A., Majidi N., Ghorbani M., Mohammadian F., Cultivation pattern optimization to balance groundwater resource (case study: Mashhad-Chenaran plain), Iranian Journal of Irrigation and Drainage 1 (2012) 55-68.
Amantaray S., Rath A., Sahu A., Swain P., Derivation of optimal cropping pattern in sambalpur distributary using genetic algorithm, International Journal of Soft Computing and Artificial Intelligence 5 (2017) 1-6.
Asadi A., Keramatzade A., Eshraghi F., Determination of optimal crop cultivation pattern (Case study: Gorgan city), 4th International Congress on Advanced Research in Management, Accounting and Economics Studies, 28 May, Hall of Conferences of Cultures, Shiraz, Iran, (2017).
Barikani A., Ahmadian M., Khalilian S., Optimal operation of groundwater resources in agriculture sector (Case study: agriculture subsection of Qazvin plain), Journal of Agricultural Economic and Development 25 (2012) 253-262.
Borhani Darian A.R., and Farahmandfar Z., Calibration of rainfall-runoff models using MBO algorithm, Iranian of Irrigation and Water Engineering 1 (2011) 60-71.
Daniel T., and Larose C.D., Discovering knowledge in data: an introduction to data mining, Jhon Wiley & Sons Inc, 240 pages; (2004).
Dutta S., Sahoo B., Mishra R., Acharya S., Fuzzy stochastic genetic algorithm forobtaining optimum crops pattern and water balance in a farm, Water Resource Management 30 (2016) 4097–4123.
Emami H., and Derakhshan F., Election algorithm: A new socio-politically inspired strategy, AI Communications 28 (2015) 591–603.
Ghahraman B., and Sepaskhah A.R., Optimal allocation of water from a single purpose reservoir to an irrigation project with pre-determined multiple cropping patterns, Irrigation Science 21 (2002) 127–137.
Gorgani J., Determining the risk-based crop cultivation pattern with agricultural water management using a combination of agricultural pattern, MSc. Thesis of Economic, Mgamotad Department, Ferdosi Mashhad University (2014).
Gopi A., Land allocation strategies through genetic algorithm approach–a case study, Global Journal of Research in Engineering 11 (2011) 6-14.
Khanjari Sadati S., Speelman M., Sabouhi M., Gitizadeh M., Ghahraman B., Optimal irrigation water allocation using a genetic algorithm under various weather conditions, Water 6 (2014) 3068-3084.
Khasheie-Siuki A., Ghahreman B., Khochekzadeh M., Determine optimal crop cultivation pattern to prevent groundwater level, Iranian Journal of Water Research 8 (2014) 137-146.
Majidi N., Alizadeh A., Ghorbani M., Determining the optimum cropping pattern in same direction with water resources management of Mashhad-CHenaran plain, Journal of Water and Soil 25 (2011) 776-785.
Mech L.D., Alpha status, dominance, and division of labor in wolf packs, Canadian Journal of Zoology 77 1999) 1196-1203.
Mirjalili S., Mirjalili S.M., Lewis A., Grey wolf optimizer, Advances in Engineering Software 69 (2014) 46-61.
Mirzaie S., Zakerinia M., Sharifan H., Shahabifar M., The determination of optimal crop pattern operation with max-mim ant system method (MMAS) (Case study: Golestan dam irrigation and drainage network), Iranian Journal of Irrigation and Drainage 9 (2015) 66-74.
Mirzaie S., Zakerinia M., Shahabifar M., Sharifan H., Determining optimum cropping pattern using genetic algorithm (Case study: Golestan dam irrigation and drainage network, Journal of Irrigation Sciences and Engineering (JISE) 40 (2017) 181-190.