Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Advertisement

Springer Nature Link
Log in

Optimal Reservoir Operation for Flood Control Using Folded Dynamic Programming

  • Published:
Water Resources Management Aims and scope Submit manuscript

Abstract

Folded Dynamic Programming (FDP) is adopted for developing optimal reservoir operation policies for flood control. It is applied to a case study of Hirakud Reservoir in Mahanadi basin, India with the objective of deriving optimal policy for flood control. The river flows down to Naraj, the head of delta where a major city is located and finally joins the Bay of Bengal. As Hirakud reservoir is on the upstream side of delta area in the basin, it plays an important role in alleviating the severity of the flood for this area. Data of 68 floods such as peaks of inflow hydrograph, peak of outflow from reservoir during each flood, peak of flow hydrograph at Naraj and d/s catchment contribution are utilized. The combinations of 51, 54, 57 thousand cumecs as peak inflow into reservoir and 25.5, 20, 14 thousand cumecs respectively as peak d/s catchment contribution form the critical combinations for flood situation. It is observed that the combination of 57 thousand cumecs of inflow into reservoir and 14 thousand cumecs for d/s catchment contribution is the most critical among the critical combinations of flow series. The method proposed can be extended to similar situations for deriving reservoir operating policies for flood control.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Ahmad S, Simonovic SP (2006) An intelligent decision support system for management of floods. Water Resour Manag 20:391–410

    Article  Google Scholar 

  • Al-Humoud JM, Esen II (2006) Approximate methods for the estimation of Muskingum flood routing parameters. Water Resour Manag 20:979–990

    Article  Google Scholar 

  • Baliarsingh F (2000) Long-term and short-term optimal reservoir operation for flood control. Doctoral thesis, Indian Institute of Technology, Kharagpur, India

  • Bellman R (1957) Dynamic programming. Princeton University Press, Princeton

    Google Scholar 

  • Bras RL, Buchanan R, Curry KC (1983) Real time adaptive closed loop control of reservoirs with the high Aswan dam as a case study. Water Resour Res 19:33–52

    Article  Google Scholar 

  • Dewan AM, Islam MM, Kumamoto T, Nishigaki M (2007) Evaluating flood hazard for land-use planning in greater Dhaka of Bangladesh using remote sensing and GIS techniques. Water Resour Manag 21:1601–1612

    Article  Google Scholar 

  • Ermolieva TY, Sergienko IV (2008) Catastrophe risk management for sustainable development of regions under risks of natural disasters. Cybern Syst Anal 44:405–417

    Article  Google Scholar 

  • Hall WA (1964) Optimum design of a multipurpose reservoir. J Hydraul Div ASCE 90:141–149

    Google Scholar 

  • Hall WA, Buras N (1961) The dynamic programming approach to water resources development. J Geophys Res 66:517–520

    Article  Google Scholar 

  • Hall WA, Butcher WS, Esogbue A (1968) Optimization of the operation of a multiple-purpose reservoir by dynamic programming. Water Resour Res 4:471–477

    Article  Google Scholar 

  • Hall WA, Harboe R, Yeh WWG, Askew AJ (1969) Optimum firm power output from a two reservoir system by incremental dynamic programming. Contribution 130. Water Resources Center, University of California, Los Angeles

    Google Scholar 

  • Heidari M, Chow VT, Kokotovic PV, Meredith DD (1971) Discrete differential dynamic programming approach to water resources systems optimization. Water Resour Res 7:273–282

    Article  Google Scholar 

  • Jacobson D, Mayne D (1970) Differential dynamic programming. Elsevier, New York

    Google Scholar 

  • Jamieson DG, Wilkinson JC (1972) River Dee research program, 3. A short-term control strategy for multipurpose reservoir systems. Water Resour Res 8:911–920

    Article  Google Scholar 

  • Karamouz M, Abesi O, Moridi A, Ahmadi A (2009) Development of optimization schemes for floodplain management: a case study. Water Resour Manag 23:1743–1761

    Article  Google Scholar 

  • Kelman J, Damazio JM, Marien JL, Costa JPD (1989) The determination of flood control volumes in a multireservoir system. Water Resour Res 25:337–344

    Article  Google Scholar 

  • Labadie JW (2004) Optimal operation of multireservoir systems: state-of-the-art review. J Water Resour Plan Manage ASCE 130:93–111

    Article  Google Scholar 

  • Larson R (1968) State increment dynamic programming. Elsevier, New York

    Google Scholar 

  • Liu P, Guo S, Xiong L, Li W, Zhang H (2006) Deriving reservoir refill operating rules by using the proposed DPNS model. Water Resour Manag 20:337–357

    Article  Google Scholar 

  • Machado SM, Ahmad S (2007) Flood hazard assessment of Atrato River in Colombia. Water Resour Manag 21:591–609

    Article  Google Scholar 

  • Marien JL, Damázio JM, Costa FS (1994) Building flood control rule curves for multipurpose multireservoir systems using controllability conditions. Water Resour Res 30(4):1135–1144

    Article  Google Scholar 

  • Mays LW, Tung YK (1992) Hydrosystems engineering and management. McGraw-Hill, Singapore

    Google Scholar 

  • Murray DM, Yakowitz SJ (1979) Constrained differential dynamic programming and its application to multireservoir control. Water Resour Res 15:1017–1027

    Article  Google Scholar 

  • Nagesh Kumar D, Baliarsingh F (2003) Folded dynamic programming for optimal operation of multireservoir system. Water Resour Manag 17:337–353

    Article  Google Scholar 

  • Nagesh Kumar D, Janga Reddy M (2007) Multipurpose reservoir operation using particle swarm optimization. J Water Resour Plan Manage ASCE 133:192–201

    Article  Google Scholar 

  • Ozden M (1984) A binary state DP algorithm for operation problems of multireservoir systems. Water Resour Res 20:9–14

    Article  Google Scholar 

  • Patri S (1993) Data on flood control operation of Hirakud dam. Irrigation Department, Government of Orissa, India

    Google Scholar 

  • Perera BJC, Codner GP (1998) Computational improvement for stochastic dynamic programming models of urban water supply reservoirs. J Am Water Resour Assoc 34:267–278

    Article  Google Scholar 

  • Prasad AS, Umamahesh NV, Viswanath GK (2006) Optimal irrigation planning under water scarcity. J Irrig Drain Eng ASCE 132:228–237

    Article  Google Scholar 

  • Rama Mehta, Jain SK (2009) Optimal operation of a multi-purpose reservoir using neuro-fuzzy technique. Water Resour Manag 23:509–529

    Article  Google Scholar 

  • Reddy MJ, Nagesh Kumar D (2006) Optimal reservoir operation using multi-objective evolutionary algorithm. Water Resour Manag 20:861–878

    Article  Google Scholar 

  • Saghafian B, Farazjoo H, Bozorgy B, Yazdandoost F (2008) Flood intensification due to changes in land use. Water Resour Manag 22:1051–1067

    Article  Google Scholar 

  • Simonovic SP (1992) Reservoir systems analysis: closing gap between theory and practice. J Water Resour Plan Manage ASCE 118:262–280

    Article  Google Scholar 

  • Subramanya K (1994) Engineering hydrology. McGraw-Hill, New Delhi, India

    Google Scholar 

  • Teixeira ADS, Marino MA (2002) Coupled reservoir operation-irrigation scheduling by dynamic programming. J Irrig Drain Eng ASCE 128:63–73

    Article  Google Scholar 

  • Turgeon A (1981) Optimal short-term hydro scheduling from the principle of progressive optimality. Water Resour Res 17:481–486

    Article  Google Scholar 

  • Wei CC, Hsu NS (2008) Multireservoir flood-control optimization with neural-based linear channel level routing under tidal effects. Water Resour Manag 22:1625–1647

    Article  Google Scholar 

  • Yakowitz S (1982) Dynamic programming applications in water resources. Water Resour Res 18:673–696

    Article  Google Scholar 

  • Yazicigil H, Houck MH, Toebes GH (1983) Daily operation of a multipurpose reservoir system. Water Resour Res 19:1–13

    Article  Google Scholar 

  • Yeh WWG (1985) Reservoir management and operations models: a state-of-the-art review. Water Resour Res 21:1797–1818

    Article  Google Scholar 

  • Yeh CH, Labadie JW (1997) Multiobjective watershed-level planning of storm-water detention systems. J Water Resour Plan Manage ASCE 123:336–343

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Civil Engineering, Indian Institute of Science, Bangalore, India

    D. Nagesh Kumar

  2. Department of Civil Engineering, CET, Bhubaneswar, India

    Falguni Baliarsingh

  3. Department of Civil Engineering, Birla Institute of Technology and Science–Pilani, Hyderabad Campus, Hyderabad, India

    K. Srinivasa Raju

Authors
  1. D. Nagesh Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Falguni Baliarsingh
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. K. Srinivasa Raju
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to D. Nagesh Kumar.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nagesh Kumar, D., Baliarsingh, F. & Srinivasa Raju, K. Optimal Reservoir Operation for Flood Control Using Folded Dynamic Programming. Water Resour Manage 24, 1045–1064 (2010). https://doi.org/10.1007/s11269-009-9485-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11269-009-9485-3

Keywords

Search

Navigation