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Reservoir Operation Modelling with Fuzzy Logic

Author

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  • D. Panigrahi
  • P. Mujumdar

Abstract

In this article, a fuzzy rule based model is developed for the operation of a single purpose reservoir. The model operates on an 'if – then' principle, where the 'if' is a vector of fuzzy premises and the 'then' is a vector of fuzzy consequences. The steps involved in the development of the model include, construction of membership functions for the inflow, storage, demand and the release, formulation of fuzzyrules, implication and defuzzification. The methodology is illustrated through the case study of the Malaprabha irrigation reservoir in Karnataka, India. Reservoir storage, inflow, and demands are used as premises and the release as the consequence.Simulated reservoir operation with a steady state policy provides the knowledge base necessary for the formulation of the Fuzzy rules. Copyright Kluwer Academic Publishers 2000

Suggested Citation

  • 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.
  • Handle: RePEc:spr:waterr:v:14:y:2000:i:2:p:89-109
    DOI: 10.1023/A:1008170632582
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    Citations

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    Cited by:

    1. Bhabagrahi Sahoo & Anil Lohani & Rohit Sahu, 2006. "Fuzzy Multiobjective and Linear Programming Based Management Models for Optimal Land-Water-Crop System Planning," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(6), pages 931-948, December.
    2. Mahsa Amirabdollahian & Morteza Mokhtari, 2015. "Optimal Design of Pumped Water Distribution Networks with Storage Under Uncertain Hydraulic Constraints," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2637-2653, June.
    3. D. Han & I. Cluckie & D. Karbassioun & J. Lawry & B. Krauskopf, 2002. "River Flow Modelling Using Fuzzy Decision Trees," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 16(6), pages 431-445, December.
    4. Wei Yang & Zhifeng Yang, 2013. "Development of a Long-term, Ecologically Oriented Dam Release Plan for the Lake Baiyangdian Sub-basin, Northern China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(2), pages 485-506, January.
    5. D. Regulwar & Jyotiba Gurav, 2012. "Sustainable Irrigation Planning with Imprecise Parameters under Fuzzy Environment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(13), pages 3871-3892, October.
    6. Deepti Rani & Maria Moreira, 2010. "Simulation–Optimization Modeling: A Survey and Potential Application in Reservoir Systems Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(6), pages 1107-1138, April.
    7. Jenq-Tzong Shiau & Yen-Ning Hung & Huei-Er Sie, 2018. "Effects of Hedging Factors and Fuzziness on Shortage Characteristics During Droughts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1913-1929, March.
    8. 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.
    9. Gokmen Tayfur & Luca Brocca, 2015. "Fuzzy Logic for Rainfall-Runoff Modelling Considering Soil Moisture," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3519-3533, August.
    10. Ijaz Ahmad & Fan Zhang & Junguo Liu & Muhammad Naveed Anjum & Muhammad Zaman & Muhammad Tayyab & Muhammad Waseem & Hafiz Umar Farid, 2018. "A linear bi-level multi-objective program for optimal allocation of water resources," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-25, February.
    11. 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.
    12. 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.

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