Optimal Evaluation of Different Flow Scenarios Emphasizing Economic Productivity and Using Multi-stage Stochastic Programming

Articles in Press

Document Type : Research Paper

Authors

1 Science and Research Branch, Islamic Azad University, Tehran, Iran

2 2Department of Water Science and Engineering, Faculty of Agriculture and Environment, Arak University, Arak, Iran.

3 Associated professor, Department of water, Islamic Azad university share Quds branch, Tehran, Iran

4 5Department of Water Sciences and Engineering, Science and Research Branch, Islamic Azad University, Tehran,Iran.

Abstract

Introduction: This study investigated the optimal management and allocation of irrigation water under different flow scenarios focusing on economic water productivity (EWP) index. Purpose : In this study, the aim was to allocate and distribute water between networks and lower crops of Maroon reservoir dam. Materials and Methods: The multi-stage stochastic programming method was used to develop the optimization model under three scenarios of arid, normal and wet years in two management modes and the results were compared with the traditional management figures. For this purpose, hydrometric data was sourced from the Marun network station for the 2006–2016 periods. Findings: The results showed that the average EWP index for the three scenarios was 8% higher in the first run and 20% higher in the second run than the traditional management figures. In the first run of the model, water distribution and allocation happened among crops. Moreover, in the second run, water supply and allocation happened between networks and crops. Conclusion: Finally, the results of the second run provided a better irrigation program with a 19% increase in the total planting area and a 7% increase in objective function profit.

Keywords

Main Subjects

Irrigation Sciences and Engineering

Articles in Press, Accepted Manuscript
Available Online from 24 November 2024

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History

  • Receive Date: 31 July 2024
  • Revise Date: 19 November 2024
  • Accept Date: 24 November 2024
  • Publish Date: 24 November 2024

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