عنوان مقاله [English]
In this research, deriving optimal reservoir operation in selective withdrawal scheme considering quality and quantity aspects has been studied. Surrogate based simulation-optimization approach (SBSOA) has been applied to improve downstream water supply and enhance reservoir outflow water quality. CE-QUAL-W2 as the hydrodynamic and water quality simulation model in the river-reservoir system and multi-objective particle swarm optimization (MOPSO) algorithm as an efficient tool have been applied in simulation-optimization (SO) approach. To overcome the computational burdens of multiple calls of CE-QUAL-W2, as a numerical high fidelity model, various surrogate models have been developed to simulate reservoir outflow water quality parameters (DO, NO3, PO4, BOD, and Fe). The developed surrogate models and mass balance model have been coupled with MOPSO algorithm in SBSOA. In this study, the water quality objective function is defined as water quality index (WQI), which integrates various water quality parameters, DO, NO3, PO4, BOD, and Fe. The proposed approach has been applied in Ilam river-reservoir system to derive optimal reservoir operating strategies in the selective withdrawal scheme. The results show suitable efficiency and accuracy of the developed surrogate models in approximation of various water quality parameters compared with CE-QUAL-W2 simulation results (the approximation error of DO, NO3, PO4, Fe, and BOD have been respectively 3%, 1%, 2%, 2%, 3%). The studies indicate enhancing reservoir outflow water quality is consistent with downstream water supply satisfaction. It means, the increasing of reservoir outflow rate leads to the reservoir detention time decreasing, pollutant settling rate reductions, and chemical/biological reaction attenuation.
Amirkhani, M., Bozorg-Haddad, O., Fallah-Mehdipour, E. & Loáiciga, H. A. 2016. Multiobjective reservoir operation for water quality optimization. Journal of Irrigation and Drainage Engineering, 142(12), 04016065. doi:10.1061/(ASCE) IR.1943-4774.0001105.
Castelletti, A., Yajima, H., Giuliani, M., Soncini-Sessa, R. & Weber, E. 2013. Planning the optimal operation of a multioutlet water reservoir with water quality and quantity targets. Journal of Water Resources Planning and Management, 140(4), 496-510.
Celeste, A. B. & Billib, M. 2009. Evaluation of stochastic reservoir operation optimization models. Journal of Advances in Water Resources, 32(9), 1429-1443.
Chung, S.-W. & Gu, R. R. 2009. Prediction of the fate and transport processes of Atrazine in a reservoir. Journal of Environmental Management, 44(1), 46-61.
Cole, T. M. & Wells, S. A. 2006. CE-QUAL-W2: A two-dimensional, laterally averaged, hydrodynamic and water quality model, version 3.5, Instruction Report EL-06-1, US Army Engineering and Resarch Development Center, Vicksburg, MS.
Javaheri, S. & Saadatpour, M. 2017. Deriving hydropower reservoir operation rules in selective withdrawal framework considering quality and quantity objectives; simulation-optimization approach based on meta-modelling. Journal of Iran Water Resources Research, 13(3), 128-142. (In Persion)
Karamouz, M., Moridi, A. & Fayazi, H. 2008. Dealing with conflict over water quality and quantity allocation: a case study. Journal of Scientia Iranica, 15(1), 34-49.
Kerachian, R. & Karamouz, M. 2007. A stochastic conflict resolution model for water quality management in reservoir–river systems. Journal of Advances in Water Resources, 30(4), 866-882.
Kumar, D. & Reddy, M. 2007. Multipurpose reservoir operation using particle swarm optimization. Journal of Water Resources Planning and Management, 133(3), 192-201.
Ma, S., Kassinos, S. C., Fatta Kassinos, D. & Akylas, E. 2008. Effects of selective water withdrawal schemes on thermal stratification in Kouris Dam in Cyprus. Journal of Lakes & Reservoirs: Research and Management, 13(1), 51-61.
Meraji, S. H., Afshar, M. H. & Afshar, A. 2005. Reservoir operation by particle swarm optimization algorithm. Proceedings of the 7th International Conference of Civil Engineering (Icce7th), Tehran, Iran, 2005, 8-10.
MGCE. 2011. Long-Term Drinking Water Supply of Ilam City, (Mahab Ghodss Consulting Engineers), Tehran, Iran. (In Persian)
Narasimhan, B., Srinivasan, R., Bednarz, S., Ernst, M. & Allen, P. 2010. A comprehensive modeling approach for reservoir water quality assessment and management due to point and nonpoint source pollution. Journal of Transactions of the ASABE, 53(5), 1605-1617.
Ostadrahimi, L., Mariño, M. A. & Afshar, A. 2012. Multi-reservoir operation rules: multi-swarm PSO-based optimization approach. Journal of Water Resources Management, 26(2), 407-427.
Saadatpour, M. 2012. Deriving optimal reservoir operational strategy considering quality and quantity objective. PhD Thesis, Dept. of Civil Eng. Iran University of Science and Technology, Tehran, Iran. (In Persian)
Saadatpour, M. & Afshar, A. 2013. Multi objective simulation-optimization approach in pollution spill response management model in reservoirs. Water Resources Management, 27(6), 1851-1865.
Saadatpour, M., Afshar, A. & Edinger, J. E. 2017. Meta-model assisted 2d hydrodynamic and thermal simulation model (CE-QUAL-W2) in deriving optimal reservoir operational strategy in selective withdrawal scheme. Water Resources Management, 31(9), 2729-2744.
Soleimani, S., Bozorg-Haddad, O., Saadatpour, M. & Loáiciga, H. A. 2016. Optimal selective withdrawal rules using a coupled data mining model and genetic algorithm. Journal of Water Resources Planning and Management, 142(12), 04016064. Doi: 10.1061/(ASCE) WR.1943-5452.0000717.
Suen, J.-P. & Wang, R.-H. 2010. Optimal reservoir operation considering downstream water quality and environmental flow needs. World Environmental and Water Resources, Challenges of Change, Providence, Rhode Island, United States, 2592-2601.
Swamee, P. K. & Tyagi, A. 2000. Describing water quality with aggregate index. Journal of Environmental Engineering, 126(5), 451-455.
Vapnik, V. N. 1999. An overview of statistical learning theory. Journal of IEEE Transactions on Neural Networks, 10(5), 988-999.