Skip to main content
Log in

Multi objective simulation–optimization operation of dam reservoir in low water regions based on hedging principles

  • Research Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

The high level of reliability of water resources is always an advantage for consumers, but in arid and semi-arid regions where the inflow to the reservoir is faced with severe fluctuations, it makes sense to decrease the percentage of reliability of the system and allocate less water to consumption zones to prevent critical conditions such as emptying of the reservoir. In this research, the employed operation model is based on the simulation–optimization combination by considering the objectives of minimizing the violation of the allowed capacity of the reservoir and maximizing the percentage of supplying the demands. The optimal hedging variables are specified by linking the WEAP (Water Evaluation and Planning System) to the MOPSO multi-objective optimization algorithm. According to the available data, the duration of the simulation and optimization period in the model is 360 months. After 1000 iterations, the optimal reservoir volume values are obtained at the hedging level and hedging coefficient in different months. Finally, the model results are compared with the results obtained from the standard operation policy (SOP). The results show that the proposed model is able to manage the allocation to needs in the dry months and prevent the reservoir from emptying. Also, by storing a part of the flow in the reservoir in watery months and consuming it in low water months, it increases the supply of needs by 20 to 35% and reduces the failure rate in dry months.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Data availability

The total data and materials are available for applicants if needed.

References

  • Azari A, Hamzeh S, Naderi S (2018) Multi-objective optimization of the reservoir system operation by using the hedging policy. Water Resour Manage 32(6):2061–2078. https://doi.org/10.1007/s11269-018-1917-5

    Article  Google Scholar 

  • Bayesteh M, Azari A (2021) Stochastic optimization of reservoir operation by applying hedging Rules. J Water Resour Plann Manag 147(2):04020099. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001312

    Article  Google Scholar 

  • Daraeikhah M, Meraji SH, Afshar MH (2009) Application of particle swarm optimization to optimal design of cascade stilling basins. Scientia Iranica 16(1):50–57

    Google Scholar 

  • Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Trans Evol Comput Indian 6(2):182–197

    Article  Google Scholar 

  • Draper AJ, Lund JR (2004) Optimal hedging and carry over storage value. Water Resour Plann Manage ASCE 130(1):83–87

    Article  Google Scholar 

  • Felfelani F, JalaliMovahed A, Zarghami M (2013) Simulating hedging rules for effective reservoir operation by using system dynamics: a case study of Dez Reservoir, Iran. Lake Reserv Manage 29(2):126–140

    Article  Google Scholar 

  • Goorani Z, Shabanlou S (2021) Multi-objective optimization of quantitative-qualitative operation of water resources systems with approach of supplying environmental demands of Shadegan Wetland. J Environ Manage 292(6):112769. https://doi.org/10.1016/j.jenvman.2021.112769

    Article  Google Scholar 

  • Izquierdo J, Montalvo I, Pérez R, Fuertes VS (2008) Design optimization of wastewater collection networks by PSO. Comput Math Appl 56(3):777–784

    Article  Google Scholar 

  • Jalilian A, Heydari M, Azari A, Shabanlou S (2022) Extracting optimal rule curve of dam reservoir base on stochastic inflow. Water Resour Manage 36(6):1763–1782. https://doi.org/10.1007/s11269-022-03087-3

    Article  Google Scholar 

  • Li X, Zhao Y, Shi C, Sha J, Wang ZL, Wang Y (2015) Application of Water Evaluation and Planning (WEAP) model for water resources management strategy estimation in coastal Binhai New Area, China. Ocean Coast Manag 106:97–109

    Article  Google Scholar 

  • Loucks DP, Van Beek E (2017) Water resource systems planning and management: An introduction to methods, models, and applications. Springer, p 624

  • Moghaddam A, Afsharnia M, Peirovi Minaee R (2020) Preparing the optimal emergency response protocols by MOPSO for a real-world water distribution network. Environ Sci Pollut Res 27(2):30625–30637. https://doi.org/10.1007/s11356-020-08892-0

    Article  Google Scholar 

  • Mousavi SJ, Anzab NR, Asl-Rousta B, Kim JH (2017) Multi-objective optimization-simulation for reliability-based inter-basin water allocation. Water Resour Manage 31(9):1–20. https://doi.org/10.1007/s11269-017-1678-6

    Article  Google Scholar 

  • Nagesh Kumar D, Janga Reddy M (2007) Multipurpose reservoir operation using particle swarm optimization. J Water Resour Plann Manag 133(3):192–201

    Article  Google Scholar 

  • Neelakantan TR, Pundarikanthan NV (1999) Hedging rule optimization for water supply reservoirs system. Water Resour Manage 13(6):409–426

    Article  Google Scholar 

  • Neelakantan TR, Sasireka K (2015) Review of hedging rules applied to reservoir operation. Int J Eng Technol 7(5):1571–1580

    Google Scholar 

  • Rafiee Anzab N, Mousavi SJ, Rousta BA, Kim JH (2016) Simulation optimization for optimal sizing of water transfer systems. In: Harmony Search Algorithm. Springer, Berlin, Heidelberg, pp 365–375

    Chapter  Google Scholar 

  • Reddy MJ, Kumar DN (2007) Optimal reservoir operation for irrigation of multiple crops using elitist-mutated particle swarm optimization. Hydrol Sci J 52(4):686–701

    Article  Google Scholar 

  • Rezaei F, Safavi HR, Zekri M (2017) A hybrid fuzzy-based multi-objective PSO algorithm for conjunctive water use and optimal multi-crop pattern planning. Water Resour Manage 31:1139–1155. https://doi.org/10.1007/s11269-016-1567-4

    Article  Google Scholar 

  • Rezaei F, Safavi HR (2020) f-MOPSO/Div: an improved extreme-point-based multi-objective PSO algorithm applied to a socio-economic-environmental conjunctive water use problem. Environ Monit Assess 192(12):1–27

    Article  Google Scholar 

  • Sen GD, Sharma J, Goyal GR, Singh AK (2017) A multi-objective PSO (MOPSO) algorithm for optimal active power dispatch with pollution control. Math Model Eng Probl 4(3):113–119. https://doi.org/10.18280/mmep.040301

    Article  Google Scholar 

  • Shih JS, ReVelle C (1994) Water-supply operations during drought:continuous hedging rule. Water Resour Plann Manage ASCE 120(5):613–629

    Article  Google Scholar 

  • Taghian M, Rosbjerg D, Haghighi A, Madsen H (2014) Optimization of conventional rule curves coupled with hedging rules for reservoir operation. Water Resour Plann Manag 140(5):693–698

    Article  Google Scholar 

  • Tennant DL (1976) Instream flow regimens for fish, wildlife, recreation and related environmental resources. Fisheries 1(4):6–10. https://doi.org/10.1577/1548-8446(1976)001%3c0006:IFRFFW%3e2.0.CO;2

    Article  Google Scholar 

  • Xilin Z, Yuejin T, Zhiwei Y (2019) Resource allocation optimization of equipment development task based on MOPSO algorithm. J Syst Eng Electron 30(6):1132–1143

    Article  Google Scholar 

  • Vasan A (2013) Optimal reservoir operation for irrigation planning using the swarm intelligence algorithm. Metaheuristics in Water Geotechnical and Transport Engineering, pp 147–165

    Google Scholar 

  • Zeinali M, Azari A, Heidari MM (2020a) Multi-objective optimization for water resource management in low flow areas based on a coupled surface water-groundwater model. J Water Resour Plann Manag 146(5):04020020

    Article  Google Scholar 

  • Zeinali M, Azari A, Heidari MM (2020b) Simulating unsaturated zone of soil for estimating the recharge rate and flow exchange between a river and an aquifer. Water Resour Manage 34(1):425–443

    Article  Google Scholar 

  • Zhang J, Wu Z, Cheng CT, Zhang SQ (2011) Improved particle swarm optimization algorithm for multi-reservoir system operation. Water Sci Eng 4(1):61–74

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Sedighe Mansouri, Hossein Fathian, Alireza Nikbakht Shahbazi, Mehdi Asadi Lourm, and Ali Asareh. The first draft of the manuscript was written by Hossein Fathian and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Hossein Fathian.

Ethics declarations

Ethics approval

The authors approve principles of ethical and professional conduct.

Consent to participate

The authors consent to participate in the preparation of this article.

Consent to publish

The authors consent to publish this article in journal of Environmental Science and Pollution Research.

Competing interests

The authors declare no competing interests.

Additional information

Responsible Editor: Marcus Schulz

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mansouri, S., Fathian, H., Nikbakht Shahbazi, A. et al. Multi objective simulation–optimization operation of dam reservoir in low water regions based on hedging principles. Environ Sci Pollut Res 30, 41581–41590 (2023). https://doi.org/10.1007/s11356-022-25089-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-022-25089-9

Keywords

Navigation