IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v223y2014i1p309-32810.1007-s10479-013-1455-8.html
   My bibliography  Save this article

Stochastic vs deterministic programming in water management: the value of flexibility

Author

Listed:
  • Yousaf Muhammad
  • Georg Pflug

Abstract

In the paper we develop a two stage scenario-based stochastic programming model for water management in the Indus Basin Irrigation System (IBIS). We present a comparison between the deterministic and scenario-based stochastic programming model. Our model takes stochastic inputs on hydrologic data i.e. inflow and rainfall. We divide the basin into three rainfall zones which overlap on 44 canal commands. Data on crop characteristics are taken on canal command levels. We then use ten-daily and monthly time intervals to analyze the policies. This system has two major reservoirs and a complex network of rivers, canal head works, canals, sub canals and distributaries. All the decisions on hydrologic aspects are governed by irrigation and agricultural development policies. Storage levels are maintained within the minimum and maximum bounds for every time interval according to a power generation policy. The objective function is to maximize the expected revenue from crops production. We discuss the flexibility of two stochastic optimization models with varying time horizon. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Yousaf Muhammad & Georg Pflug, 2014. "Stochastic vs deterministic programming in water management: the value of flexibility," Annals of Operations Research, Springer, vol. 223(1), pages 309-328, December.
    • Handle: RePEc:spr:annopr:v:223:y:2014:i:1:p:309-328:10.1007/s10479-013-1455-8
    DOI: 10.1007/s10479-013-1455-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-013-1455-8
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-013-1455-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rao, N. H. & Sarma, P. B. S. & Chander, Subhash, 1992. "Real-time adaptive irrigation scheduling under a limited water supply," Agricultural Water Management, Elsevier, vol. 20(4), pages 267-279, February.
    2. Ullah, M. K., 2001. "Spatial distribution of reference and potential evapotranspiration across the Indus Basin Irrigation Systems," IWMI Working Papers H029426, International Water Management Institute.
    3. Oscar R. Burt & M. S. Stauber, 1971. "Economic Analysis of Irrigation in Subhumid Climate," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 53(1), pages 33-46.
    4. N. Umamahesh & P. Sreenivasulu, 1997. "Technical Communication: Two-Phase Stochastic Dynamic Programming Model for Optimal Operation of Irrigation Reservoir," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 11(5), pages 395-406, October.
    5. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
    6. Ronald Hochreiter & Georg Pflug, 2007. "Financial scenario generation for stochastic multi-stage decision processes as facility location problems," Annals of Operations Research, Springer, vol. 152(1), pages 257-272, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Reza Roozbahani & Babak Abbasi & Sergei Schreider & Zahra Hosseinifard, 2020. "A basin-wide approach for water allocation and dams location-allocation," Annals of Operations Research, Springer, vol. 287(1), pages 323-349, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. J. F. F. Almeida & S. V. Conceição & L. R. Pinto & B. R. P. Oliveira & L. F. Rodrigues, 2022. "Optimal sales and operations planning for integrated steel industries," Annals of Operations Research, Springer, vol. 315(2), pages 773-790, August.
    2. D. Kuhn, 2009. "Convergent Bounds for Stochastic Programs with Expected Value Constraints," Journal of Optimization Theory and Applications, Springer, vol. 141(3), pages 597-618, June.
    3. Arie M. C. A. Koster & Michael Poss, 2018. "Special issue on: robust combinatorial optimization," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 6(3), pages 207-209, September.
    4. Rashed Khanjani-Shiraz & Ali Babapour-Azar & Zohreh Hosseini-Noudeh & Panos M. Pardalos, 2022. "Distributionally robust maximum probability shortest path problem," Journal of Combinatorial Optimization, Springer, vol. 43(1), pages 140-167, January.
    5. Walid Ben-Ameur & Adam Ouorou & Guanglei Wang & Mateusz Żotkiewicz, 2018. "Multipolar robust optimization," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 6(4), pages 395-434, December.
    6. Ketabchi, Saeed & Behboodi-Kahoo, Malihe, 2015. "Augmented Lagrangian method within L-shaped method for stochastic linear programs," Applied Mathematics and Computation, Elsevier, vol. 266(C), pages 12-20.
    7. Wang, Chengshan & Song, Guanyu & Li, Peng & Ji, Haoran & Zhao, Jinli & Wu, Jianzhong, 2017. "Optimal siting and sizing of soft open points in active electrical distribution networks," Applied Energy, Elsevier, vol. 189(C), pages 301-309.
    8. Adi Ben-Israel & Aharon Ben-Tal, 1997. "Duality and equilibrium prices in economics of uncertainty," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 46(1), pages 51-85, February.
    9. Garoian, Lee & Conner, J. Richard & Scifres, C.J., 1987. "A Discrete Stochastic Programming Model To Estimate Optimal Burning Schedules On Rangeland," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 19(2), pages 1-8, December.
    10. Zhou, Feng & Huang, Gordon H. & Chen, Guo-Xian & Guo, Huai-Cheng, 2009. "Enhanced-interval linear programming," European Journal of Operational Research, Elsevier, vol. 199(2), pages 323-333, December.
    11. Bastian, Nathaniel D. & Lunday, Brian J. & Fisher, Christopher B. & Hall, Andrew O., 2020. "Models and methods for workforce planning under uncertainty: Optimizing U.S. Army cyber branch readiness and manning," Omega, Elsevier, vol. 92(C).
    12. Kanudia, Amit & Loulou, Richard, 1998. "Robust responses to climate change via stochastic MARKAL: The case of Quebec," European Journal of Operational Research, Elsevier, vol. 106(1), pages 15-30, April.
    13. Walter J. Gutjahr & Alois Pichler, 2016. "Stochastic multi-objective optimization: a survey on non-scalarizing methods," Annals of Operations Research, Springer, vol. 236(2), pages 475-499, January.
    14. repec:dgr:rugsom:03a14 is not listed on IDEAS
    15. John Bistline & John Weyant, 2013. "Electric sector investments under technological and policy-related uncertainties: a stochastic programming approach," Climatic Change, Springer, vol. 121(2), pages 143-160, November.
    16. N. Umamahesh & P. Sreenivasulu, 1997. "Technical Communication: Two-Phase Stochastic Dynamic Programming Model for Optimal Operation of Irrigation Reservoir," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 11(5), pages 395-406, October.
    17. Bhuvnesh Sharma & M. Ramkumar & Nachiappan Subramanian & Bharat Malhotra, 2019. "Dynamic temporary blood facility location-allocation during and post-disaster periods," Annals of Operations Research, Springer, vol. 283(1), pages 705-736, December.
    18. Maji, Chandi Charan, 1975. "Intertemporal allocation of irrigation water in the Mayurakshi Project (India): an application of deterministic and chance-constrained linear programming," ISU General Staff Papers 197501010800006381, Iowa State University, Department of Economics.
    19. Simons, G.W.H. & Bastiaanssen, W.G.M. & Cheema, M.J.M. & Ahmad, B. & Immerzeel, W.W., 2020. "A novel method to quantify consumed fractions and non-consumptive use of irrigation water: Application to the Indus Basin Irrigation System of Pakistan," Agricultural Water Management, Elsevier, vol. 236(C).
    20. Ankur Kulkarni & Uday Shanbhag, 2012. "Recourse-based stochastic nonlinear programming: properties and Benders-SQP algorithms," Computational Optimization and Applications, Springer, vol. 51(1), pages 77-123, January.
    21. Andrea Beltratti & Andrea Consiglio & Stavros Zenios, 1999. "Scenario modeling for the management ofinternational bond portfolios," Annals of Operations Research, Springer, vol. 85(0), pages 227-247, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:223:y:2014:i:1:p:309-328:10.1007/s10479-013-1455-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.