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Optimal Reservoir Operation Based on Conjunctive Use of Surface Water and Groundwater Using Neuro-Fuzzy Systems

Author

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  • Hamid Safavi
  • Iman Chakraei
  • Abdolreza Kabiri-Samani
  • Mohammad Golmohammadi

Abstract

Reservoir operation cannot be carried out without due heed to surface water and groundwater resources, since neglecting either will have irreversible consequences. Optimal operation of the Zayandehrood Dam which supplies water into the Zayandehrood River basin in the central plateau of Iran is a case in point which warrants due consideration paid to both dam operation and the climate conditions in the region suffering from a history of successive droughts. The main objective of the present research is to develop operation rules for the Zayandehrood reservoir through a combined perspective of both surface and ground water resources using the fuzzy inference system, and adaptive neuro-fuzzy inference system. The objective is to determine the share of the Zayandehrood reservoir in meeting downstream water demands. For this purpose, the water shortage and the dramatic groundwater drawdown in the Zayandehrood River basin faced with in recent years have been studied in an attempt to develop operation models capable of controlling groundwater drawdown. The models indicate that not only can groundwater drawdown be controlled, but that it is also possible to establish a greater sustainability. Different operation models have been compared in terms of their operation criteria. Results show that the ANFIS model composed of optimal data enjoys a higher sustainability compared to others. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Hamid Safavi & Iman Chakraei & Abdolreza Kabiri-Samani & Mohammad Golmohammadi, 2013. "Optimal Reservoir Operation Based on Conjunctive Use of Surface Water and Groundwater Using Neuro-Fuzzy Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(12), pages 4259-4275, September.
    • Handle: RePEc:spr:waterr:v:27:y:2013:i:12:p:4259-4275
    DOI: 10.1007/s11269-013-0405-1
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    References listed on IDEAS

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    1. Hamid Safavi & Fatemeh Darzi & Miguel Mariño, 2010. "Simulation-Optimization Modeling of Conjunctive Use of Surface Water and Groundwater," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(10), pages 1965-1988, August.
    2. S. Mousavi & K. Ponnambalam & F. Karray, 2005. "Reservoir Operation Using a Dynamic Programming Fuzzy Rule–Based Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 19(5), pages 655-672, October.
    3. A. Cancelliere & G. Giuliano & A. Ancarani & G. Rossi, 2002. "A Neural Networks Approach for Deriving Irrigation Reservoir Operating Rules," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 16(1), pages 71-88, February.
    4. Rama Mehta & Sharad Jain, 2009. "Optimal Operation of a Multi-Purpose Reservoir Using Neuro-Fuzzy Technique," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(3), pages 509-529, February.
    5. P. Jairaj & S. Vedula, 2000. "Multireservoir System Optimization using Fuzzy Mathematical Programming," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 14(6), pages 457-472, December.
    6. Pan Liu & Shenglian Guo & Lihua Xiong & Wei Li & Honggang Zhang, 2006. "Deriving Reservoir Refill Operating Rules by Using the Proposed DPNS Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(3), pages 337-357, June.
    7. D. Panigrahi & P. Mujumdar, 2000. "Reservoir Operation Modelling with Fuzzy Logic," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 14(2), pages 89-109, April.
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    5. C. Dai & Y. P. Cai & W. T. Lu & H. Liu & H. C. Guo, 2016. "Conjunctive Water Use Optimization for Watershed-Lake Water Distribution System under Uncertainty: a Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4429-4449, September.
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