Journals / Tarım Bilimleri Dergisi / 2008 / Cilt: 14 - Sayı: 01

Comparison of Different Methods Used in Determination of Irrigation Reservoir Capacity

Sulama Amaçlı Hazne Kapasitesinin Belirlenmesinde Çeşitli Yöntemlerin Karşılaştırılması

Pages
1–7
Publication Date
2008-01-01
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Results showed that the dam capacity with Ripple method mass curve will be 13.1 hm3, with sequent peak algorithm will be 6.86 hm3 and with non-linear optimization will be 6.19 hm3

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Usually development of dams and irrigation-drainage projects requires high investment cost.
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Key Findings & Data:Because of financial limitations, consideration of optimization techniques for determination of reservoir capacity is clear.
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Conclusion & Impact:Results showed that the dam capacity with Ripple method mass curve will be 13.1 hm3, with sequent peak algorithm will be 6.86 hm3 and with non-linear optimization will be 6.19 hm3
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Baraj işletmesi · Ripple yöntemi · Ardışık Pik Analizi yöntemi

Abstract

Usually development of dams and irrigation-drainage projects requires high investment cost. Because of financial limitations, consideration of optimization techniques for determination of reservoir capacity is clear. Determination of reservoir capacity by classical methods such as mass curve Ripple method and sequent peak algorithm, don’t consider all effective parameters in problem. In these methods reservoir capacity may be estimated with a higher than that of optimization methods. In this research comparison between classical and modern methods for calculating one dam capacity in East Azerbaijan named Yalgiz Agac has been done. Results showed that the dam capacity with Ripple method mass curve will be 13.1 hm3, with sequent peak algorithm will be 6.86 hm3 and with non-linear optimization will be 6.19 hm3

Özet

Genel olarak sulama, su temini ve drenaj projelerinin gerçekleştirilmesi için büyük yatırımlara gerek duyulmaktadır. Finans kaynakların yetersizliğinden su temini için yapılması planlanan hazne kapasitesinin belirlenmesinde optimizasyon tekniklerini kullanmak zorunlu olmaktadır. Hazne kapasitesinin belirlemesinde; Ripple yöntemi ve Ardışık Pik Analizleri olarak tanımlanan klasik yöntemler problemin bütün etkin parametrelerini ve boyutlarını dikkate almamaktadır. Böyle durumlarda hazne kapasitesi gereğinden çok büyük olarak hesaplanabilir. Bu çalışmada, Doğu Azerbaycan”da İran’ın kuzey batısında bulunan sulama amaçlı Yalkız Ağac barajının kapasitesi; klasik ve optimizasyon yöntemleriyle belirlenmiştir. Sonuçlara göre hazne kapasitesi Ripple yöntemi ile 13.1 hm3, Ardışık Pik Analizleri yöntemi ile 6.86 hm3ve Doğrusal Olmayan Optimizasyon yöntemi ile 6.19 hm3olarak hesaplanmıştır

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Cite This Article

SATTAR, M. T., SALMASİ, F., ÖZTÜRK, F. (2008). Comparison of Different Methods Used in Determination of Irrigation Reservoir Capacity. Tarım Bilimleri Dergisi, Cilt: 14 - Sayı: 01, 1–7. https://ajindex.com/articles/178766

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References (10)

  1. Amit, K. Sinha, B. V. Rao and C. H. Bischof. 1999. Nonlinear optimization model for screening multipurpose reservoir system, Journal of water resources planning and management, 125 (4): 229-233. Anonymous, 2004. Hydrological report of Yalkız Agac Reservoir. Ashnab Consulting Engineers. Getachew, B. Peralta and Simulation/Optimization modeling for water resources management, Journal of water resources planning and management, 125 (3): 154-161. Richard. 1999.
  2. Hajilal M.S., N. H. Rao and P. B. S. Sarma. 1998. Real time operation of reservoir based canal irrigation systems, Journal of Agricultural Water Management No. 38 (2): 103-122.
  3. Hossein, M. V., Samani and A. Mottaghi. 2006. Optimization of Water Distribution Networks using Integer Linear Programming. Journal of Hydraulic Engineering, 132 (5): 501-509.
  4. Hugo, A. 2002. Reservoir designs and operation with variable lake hydrology, Journal of Water Resources Planning and Management 128 (6): 399-405.
  5. Jain, K. S., M. K. Goel and P. K. Agarwal. 1998. Reservoir operation studies of Sabramati system, India, Journal of water resources planning and management 124 (1): 31- 38. Larry, W. M. and Y. K, Tung. 1992. Hydro systems engineering and management, McGraw-Hill Inc. Loucks, D. P., J. R, Stedinger and D. A, Halth. 1981. Water resource systems planning and analysis, Prentice-Hall Inc., Englewood Cliffs, N. J. Ming-Yen Tu, Nien-Sheng Hsu and William W.-G. Yeh. 2003. Optimization of reservoir management and operation with hedging rules, Journal of Water Resources Planning and Management, 129 (2): 86-97.
  6. Montaseri, M. and A. Adeloye. 2002. Effects of integrated planning on capacity-yield-performance functions, Journal of Water Resources Planning and Management 128 (6): 456-461.
  7. Needham, J. T., D. W. Watkins, J. R. Lund and S. K. Nanda. 2000. Linear programming for flood control the Iowa and Des Moines Rivers, Journal of Water Resources Planning and Management 126 (3): 118-127.
  8. Ravikumar, V and K. Venugopal. 1998. Optimal operation of South Indian irrigation systems, Journal of water resources planning and management 124 (5): 264-271.
  9. Reis, L. F. R, F. T. Bessler, G. A. Walters and D. Savic. 2006. Water supply reservoir operation by combined genetic algorithm – linear programming (GA-LP) approach, J. of Water Resources Management 20 (2): 227-255.
  10. Srinivasan, K., S. Engrg and Nagarajukumar. 1999. Mixed- Integer programming model for reservoir performance optimization, Journal of water resources planning and management 12