Investigation of the Effect of Climate Change on the Optimization of Dam reservoir operation using Dolphin Echolocation and Gravitational Search Algorithms (Case study: Lar Dam Basin)

Document Type : Research

Authors

1 Ph.D. Student, Civil Engineering Department, Roudehen Branch, Islamic Azad University, Roudehen, Iran.

2 Assistant Professor, Civil Engineering Department, Roudehen Branch, Islamic Azad University, Roudehen, Iran. Email: sarraf@riau.ac.ir

3 Assistant Professor, Civil Engineering Department, Roudehen Branch, Islamic Azad University, Roudehen, Iran

Abstract

Considering the recent human activities and the resulting climate change in optimizing the operation of the dam reservoir, the effects of climate change should be noticed. In this research, in order to extract command curves by dolphin echolocation and gravitational search algorithms, the monthly inflow of the reservoir, the reservoir storage volume, and the downstream demand of the reservoir in case of climate change were calculated .The optimal output values of the reservoir of Lar Dam (located in Larijan, Amol City) were determined by the approach of minimizing the total square of the monthly relative deficiencies in supply demand and climate change conditions based on the river flow According to the research, by using HADCM3 and scenarios RCP2.6, RCP4.5, and RCP 8.5, climate change has increased the maximum temperature by 5%, 5.2%, and 6.2%, respectively. It has increased the minimum temperature by 3.5%, 5.6%, 5.17%, and increased precipitation by 8.5%, 9.5%, and 13%, respectively. In addition, the runoff from the intermediate scenarios indicates an increase of 3.3% compared to the base period. Moreover, to examine the water allocation policies required downstream, two future and basic conditions are considered. In this study, reservoir efficiency indices in the conditions of (future) climate change and their corresponding values ​​in the base period were compared. The execution results of each of the algorithms show that the execution speed of the DE algorithm is much higher than the GSA algorithm, as well as, in the conditions of climate change, the reliability index in the dolphin echolocation and gravity search algorithms has increased.  9.73 and 12.46% Vulnerability has decreased by 21.4% and 26.51%, respectively, and reversibility has increased by 18.27% and 17.64%, respectively. The execution results of each of the algorithms show that the execution speed of the DE algorithm is much higher than the GSA algorithm. Furthermore, in the conditions of climate change, the reliability index in the dolphin echolocation and gravity search algorithms has increased 9.73 and 12.46% Vulnerability has decreased by 21.4% and 26.51%, respectively, and reversibility has increased by 18.27% and 17.64%, respectively.

Keywords

References

[1] Hashimoto, T., Stedinger, J. R., and Loucks, D. P. (1982). "Reliability, resilience, and vulnerability criteria for water resource system performance evaluation". Water Resources Research, 18(1): 14-20
https://doi.org/10.1029/WR018i001p00014
 
[2] Labadie, J. W., (2004). "Optimal operation of multireservoirs system: State-of-the-art review". Journal of Water Resources Planning and Management, 130(2): 93-111
https://doi.org/10.1061/(ASCE)0733-9496(2004)130:2(93)
 
[3] Rashedi, E,Nezamabadi, H, and Saryazdi,S, (2009), "A Gravitational Search Algorithm", Information Science, pp 2232-2248.
https://doi.org/10.1016/j.ins.2009.03.004
 
[4] Garousi-Nejad, I., Bozorg-Haddad, O., Loáiciga, H. A. and Mariño, M. A. 2016. Application of the firefly algorithm to optimal operation of reservoirs with the purpose of irrigation supply and hydropower production. Journal of Irrigation and Drainage Engineering. 142(10):04016041.
https://doi.org/10.1061/(ASCE)IR.1943-4774.0001064
 
[5] Kaveh, A. and Farhoudi, N. 2013. A new optimization method: Dolphin echolocation. Advances in Engineering Software. 59: 53-70.
https://doi.org/10.1016/j.advengsoft.2013.03.004
 
[6] Karamouz, M. and Houck, M. H. (1982). "Annual and monthly reservoir operating rules", Water Resources Research, 18 (5), 1337-1344.
https://doi.org/10.1029/WR018i005p01337
 
[7] Binaman J, Shoemaker CA. 2005. An analysis of high-flow sediment event data for evaluating model performance. Journal of Hydrological Processes, 19(3): 605-620.
https://doi.org/10.1002/hyp.5608
 
[8] Santhi , Arnold JG, Williams J, Dugas WA, Hauck L. 2001. Validation of the SWAT model on a large river basin with point and nonpoint sources. The American Water Resources Association, 37 (5): 1169-1188.
https://doi.org/10.1111/j.1752-1688.2001.tb03630.x
 
[9] Ashofteh, P. S., Bozorg Haddad, O., and Mariño, M. A., (2013b). "Scenario assessment of streamflow simulation and its transition probability in future periods under climate change", Water Resources Management, 27 (1), 255-274.
https://doi.org/10.1007/s11269-012-0182-2
 
[10] Donyaii, A., Sarraf, A.P. 2021 Management of reservoir dams in the conditions of climate change using the search optimization dolphin echolocation algorithm'. Iranian Journal of Irrigation and Drainage.
 
[11] Afkhamifar, S., Sarraf. A.P. 2020. Groundwater level prediction of Urmia plain aquifer using hybrid wavelet model - maximal learning machine and optimization with quantum particle swarm - watershed engineering and management. 12 (2 :) 364 - 351
 
[12] Hamidzadeh, J., Salehnia, K. and Basir, M. 2014 / Evolutionary optimization algorithm for dolphins' group hunting (HDA). The first national conference on technology and knowledge management with a focus on resistance economics. Torbat Heydariyeh. Iran
 
[13] Donyaii. A., Sarraf. A.P. and Ahmadi. H. 2020b. Application of a New Appproach in Optimizing the Operation of the Multi-Objective Reservoir J.Hydraul.Struct.,6(3)1-20 DOI:10.22055/jhs.2020.34556.1145
https://doi.org/10.1155/2020/8870464
 
[14] Donyaii. A., Sarraf. A.P., and H. Ahmadi. 2020. Water reservoir Multi-Objective optimal operation using Gray Wolf optimizer , Shock and Vibration , vol .2020, articleID88700464, 10 pages.
https://doi.org/10.1155/2020/8870464
 
[15] Donyaii. A., Sarraf. A.P., and Ahmadi. H. 2021. Optimization of Reservoir Dam Operation using Gray Wolf, Crow Search and Whale Algorithms Based on the Solution of the Nonlinear Programming Model. Journal of Water and Soil Science. 2021; 24(4): 159-175.
https://doi.org/10.47176/jwss.24.4.42751
 
[16] Donyaii. A., Sarraf. A.P., and Ahmadi. H. 2021. Multi-Objective Optimal Utilization Policy of Boostan Dam Reservoir Using Whale and NSGA-II Algorithms Based on Game Theory and Shannon Entropy Method. Iranian Water Researches Journal. 2021; 14(4): 99-111.
 
[17] Nakhaei. M., Mohammadi. Kh., Rezaei. H. 2014 Optimization Aquifer Harvesting Using Genetic Algorithm (Case Study Urmia Coastal Aquifer), Iranian Water Resources Research 94-97: (30) 10.
 
[18] Mansouri, R., Nasseri, F and Khorrami, M., (1999), "Effective time variation of G in a model universe with variable space dimention", Physics Letters, vol. 259, pp. 194-200.
https://doi.org/10.1016/S0375-9601(99)00449-1
Numerical Methods in Civil Engineering
Volume 7, Issue 4
June 2023
Pages 50-65

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History

  • Receive Date: 27 June 2022
  • Revise Date: 13 September 2022
  • Accept Date: 22 September 2022

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