Optimization of Crop Pattern Using Analytical Hierarchy Process and Linear Programming (Case Study: Plain Birjand)

Document Type : Research Paper

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Abstract

     It is necessary to optimize the use of water resources in arid and semi-arid of world because of limited water resources, low performance efficiency, increasing population and demand for water. Suitable cropping patterns are very effective and efficient method for use of water. Due to limited water resources in Birjand plain, this research was conducted to optimization of crop pattern in the plain. For this purpose, crop pattern in Birjand plain (A) and 8 common crop patterns were studied. The method of multi-criteria decision analytic hierarchy process and LINGO programming model used to determine the best cropping pattern. Economic and social measures used to maximize net income, employment and labor and minimizing water consumption, cost and virtual water in both model. Results showed that profit and water is factor that is more important other than to determine crop pattern. Results show that saffron, cumin, barley, wheat, summer crops, vegetables, sugar beet, forage plant and cotton are the highest priority for cultivation. AHP results showed that 8, 2 and 4 models were determined the best cropping patterns so that in these models the forage plant (21.12%), wheat (36.74%) and wheat (46.76%) had the highest cultivation area, respectively. Model 8 due to had a low coefficient of determination (R2) in LINGO so this model is inappropriate. The cultivated wheat and vegetable in models 2 and 4 increased than cropping patterns prevalent in the region. Cucurbit plants, saffron, cotton and barley in Model 2 increased compared to the current model, while Model 4 decreased. Cumin decreased in model 2 but increased in model 4. Cultivation of forage plant and sugar beet in both models reduced compared to the current crop pattern.
 

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History

  • Receive Date: 13 January 2014
  • Revise Date: 09 July 2016
  • Accept Date: 23 May 2015
  • Publish Date: 21 June 2016

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