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Optimizing Reservoir Operation Policy Using Chance Constraint Nonlinear Programming for Koga Irrigation Dam, Ethiopia

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  • Kassahun Birhanu
  • Tena Alamirew
  • Megersa Olumana Dinka
  • Semu Ayalew
  • Dagnachew Aklog

Abstract

One of typical problems in water resources system modeling is derivation of optimal operating policy for reservoir to ensure water is used more efficiently. This paper introduces optimization analysis to determine monthly reservoir operating policies for five scenarios of predetermined cropping patterns for Koga irrigation scheme, Ethiopia. The objective function of the model was set to minimize the sum of squared deviation (SSD) from the desired targeted supply. Reservoir operation under different water availability and thresholds of irrigation demands has been analyzed by running a chance constraint nonlinear programming model based on uncertain inflow data. The model was optimized using Microsoft Excel Solver. The lowest SSD and vulnerability, and the highest volumetric reliability were gained at irrigation deficit thresholds of 20 % under scenario I, 30 % under scenario II, III and V, and at 40 % under scenario IV when compensation release is permitted for downstream environment. These thresholds of deficits could be reduced by 10 % for all scenarios if compensation release is not permitted. In conclusion the reservoir water is not sufficient enough to meet 100 % irrigation demand for design command areas of 7,000 ha. The developed model could be used for real time reservoir operation decision making for similar reservoir irrigation systems. In this specific case study system, attempt should be made to evaluate the technical performance of the scheme and introduce a regulated deficit irrigation application. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Kassahun Birhanu & Tena Alamirew & Megersa Olumana Dinka & Semu Ayalew & Dagnachew Aklog, 2014. "Optimizing Reservoir Operation Policy Using Chance Constraint Nonlinear Programming for Koga Irrigation Dam, Ethiopia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(14), pages 4957-4970, November.
    • Handle: RePEc:spr:waterr:v:28:y:2014:i:14:p:4957-4970
    DOI: 10.1007/s11269-014-0770-4
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    References listed on IDEAS

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    1. V. Jothiprakash & Ganesan Shanthi, 2006. "Single Reservoir Operating Policies Using Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(6), pages 917-929, December.
    2. 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.
    3. Hajilal, M. S. & Rao, N. H. & Sarma, P. B. S., 1998. "Real time operation of reservoir based canal irrigation systems," Agricultural Water Management, Elsevier, vol. 38(2), pages 103-122, December.
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    Cited by:

    1. Gi Joo Kim & Young-Oh Kim, 2021. "How Does the Coupling of Real-World Policies with Optimization Models Expand the Practicality of Solutions in Reservoir Operation Problems?," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(10), pages 3121-3137, August.
    2. Qiao-feng Tan & Guo-hua Fang & Xin Wen & Xiao-hui Lei & Xu Wang & Chao Wang & Yi Ji, 2020. "Bayesian Stochastic Dynamic Programming for Hydropower Generation Operation Based on Copula Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(5), pages 1589-1607, March.
    3. Mahdi Sedighkia & Asghar Abdoli, 2023. "Design of optimal environmental flow regime at downstream of multireservoir systems by a coupled SWAT-reservoir operation optimization method," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(1), pages 834-854, January.
    4. Aida Tayebiyan & Thamer Ahmed Mohammed Ali & Abdul Halim Ghazali & M. A. Malek, 2016. "Optimization of Exclusive Release Policies for Hydropower Reservoir Operation by Using Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1203-1216, February.
    5. Gi Joo Kim & Seung Beom Seo & Young-Oh Kim, 2022. "Adaptive Reservoir Management by Reforming the Zone-based Hedging Rules against Multi-year Droughts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(10), pages 3575-3590, August.
    6. Muhammad Usman Rashid & Abid Latif & Muhammad Azmat, 2018. "Optimizing Irrigation Deficit of Multipurpose Cascade Reservoirs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1675-1687, March.
    7. Zhiyu Yan & Shengli Liao & Chuntian Cheng & Josué Medellín-Azuara & Benxi Liu, 2021. "Lagrangian Relaxation Based on Improved Proximal Bundle Method for Short-Term Hydrothermal Scheduling," Sustainability, MDPI, vol. 13(9), pages 1-20, April.
    8. Khadim, Fahad Khan & Dokou, Zoi & Bagtzoglou, Amvrossios C. & Yang, Meijian & Lijalem, Girmachew Addisu & Anagnostou, Emmanouil, 2021. "A numerical framework to advance agricultural water management under hydrological stress conditions in a data scarce environment," Agricultural Water Management, Elsevier, vol. 254(C).

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