Development of Optimization Model for Water Allocation in Agriculture, Industry and Service sectors By Using Advanced Algorithm, GAPSO

Document Type : Research Article

Authors

M. Habibi Davijani

M.E. Banihabib

S.R. Hashemi

https://doi.org/10.22067/jsw.v0i0.28080

Abstract

Population growth has caused increase of water demand for the drinking water, industry and agriculture. This condition needs the application of effective measures for optimal water management. So, in this research, a water allocation model is proposed for agriculture, industry and service sectors. In agricultural sector, production function of each crop is determined and then, objective function is specified based on the production function, and income of crops. In the industrial sector, the water demand of the product is function of water and other material prices and so, the demand function is determined based on these factors. Due to the necessity of water for the service sector, the total water demand of this section was fully allocated. Then, using innovative learning algorithms, a combination of genetic algorithms-Collective Intelligence (GAPSO), objective function is maximized and optimal allocation of water for agriculture and industry, were determined and compared. According to the result mentioned, use pattern of deficit irrigation model, changing crop pattern, remove the acreage of some crops and use of more water resources in the industry field can be effect on increase revenues to 114 billion Rls. In sum, the income of agriculture and industry in the Iran Central Kavir basin can be up to 56 percent of revenues of the current situation using water resource allocation for different sectors. In this case, the region will witness a remarkable progress. Therefore changes in the water resources allocation of the area seem to be necessary.

Keywords

Water Resources

Agriculture and Industry

Optimization

Genetic Algorithms

Particle swarm optimization

GAPSO

20.1001.1.20084757.1392.27.4.2.7

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