Abstract
Damage caused by entered pollution in reservoirs can affect a water resource system in two ways: (1) Damages that are caused due to consumption of polluted water and (2) damages that are caused due to insufficient water allocation. Those damages conflict with each other. Thus, the crisis should be managed in a way that the least damage occurs in the water resource system. This paper investigates crisis management due to the sudden entrance of a 30 m3 methyl tert-butyl ether (MTBE) load to the Karaj dam in Iran, which supplies municipal water to the cities of Tehran and Karaj. To simulate MTBE advection, dispersion, and vaporization, the latter process is added to the CE-QUAL-W2 model. After that, the multi-objective NSGAII-ALANN algorithm, which is a combination of the NSGAII optimization method along with a multi layer perceptron (MLP), which is one of the most widely used artificial neural network (ANN) structures, is employed to extract the best set of decisions in which the two aforementioned damages are minimized. By assigning a specific importance to each objective function, after extracting the optimal solutions, it is possible to choose one of the solutions with the least damage. Four scenarios of entering pollution to the Karaj reservoir the first day of each season are considered, resulting in a Pareto set of operation policies for each scenario. Results of the proposed methodology indicate that if the pollution enters the reservoir in summer, by using one of the optimal policies extracted from the Pareto set of the 2nd Scenario, by a 36 % reduction in meeting the demand, allocated pollution decreases to about 60 %. In other seasons, there is a significant decrease in allocated pollution with a smaller reduction in the met demand.
Similar content being viewed by others
References
Afshar A, Shafii M, Bozorg Haddad O (2011) Optimizing multi-reservoir operation rules: an improved HBMO approach. J Hydroinf 13(1):121–139
Aly AH, Peralta PC (1999) Optimal design of aquifer cleanup systems under uncertainty using a neural network and a genetic algorithm. Water Resour Res 35(8):2523–2532
Belayneh MZ, Bhallamudi SM (2012) Optimization model for management of water quality in a tidal river using upstream releases. J Water Resour Protect 4:149–162
Bender DA, Asher WE, Zogorsk JS (2003) A deterministic model to estimate volatile organic compound concentrations in lakes and reservoirs. U.S. Geological Survey, Open-file report, Reston, pp 03–212
Bozorg Haddad O, Mariño MA (2007) Dynamic penalty function as a strategy in solving water resources combinatorial optimization problems with honey-bee optimization (HBMO) algorithm. J Hydroinf 9(3):233–250
Bozorg Haddad O, Adams BJ, Mariño MA (2008a) Optimum rehabilitation strategy of water distribution systems using the HBMO algorithm. J Water Supply Res Technol AQUA 57(5):327–350
Bozorg Haddad O, Afshar A, Mariño MA (2008b) Design-operation of multi-hydropower reservoirs: HBMO approach. Water Resour Manag 22(12):1709–1722
Bozorg Haddad O, Afshar A, Mariño MA (2008c) Honey-bee mating optimization (HBMO) algorithm in deriving optimal operation rules for reservoirs. J Hydroinf 10(3):257–264
Bozorg Haddad O, Afshar A, Mariño MA (2009) Optimization of non-convex water resource problems by honey-bee mating optimization (HBMO) algorithm. Eng Comput (Swansea Wales) 26(3):267–280
Bozorg Haddad O, Afshar A, Mariño MA (2011a) Multireservoir optimisation in discrete and continuous domains. Proc Inst Civ Eng Water Manag 164(2):57–72
Bozorg Haddad O, Moradi-Jalal M, Mariño MA (2011b) Design-operation optimisation of run-of-river power plants. Proc Inst Civ Eng Water Manag 164(9):463–475
Castelletti A, Pianosi F, Soncini-Sessa R, Antenucci JP (2010) A multi-objective response surface approach for improved water quality planning in lakes and reservoirs. Water Resour Res 46(6). doi:10.1029/2009WR008389
Chaves P, Tsukatani T, Kojiri T (2004) Operation of storage reservoir for water quality by using optimization and artificial intelligence techniques. Math Comput Simul 67(4):419–432
Chen L, McPhee J, Yeh W (2007) A diversified multiobjective GA for optimization reservoir rule curves. Adv Water Resour 30(1):51–66
Cole MT, Wells AS (2006) CE-QUAL-W2: A two-dimensional, laterally averaged, hydrodynamic and water quality model, Version 3.5. U.S. Army Corps of Engineers, Washington DC
Dandy G, Crawley P (1992) Optimum operation of multiple reservoir system inducing salinity effect. Water Resour Res 28(4):979–990
Deb K, Partap A, Agarwal S, Meyarivan T (2002) Fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197
Dhar A, Datta B (2006) Chance constrained water quality management model for reservoir systems. ISH J Hydraul Eng 12(3):39–48
Dhar A, Datta B (2008) Optimal operation of reservoirs for downstream water quality control using linked simulation optimization. Hydrol Process 22(6):842–853
Fallah-Mehdipour E, Bozorg Haddad O, Beygi S, Mariño MA (2011) Effect of utility function curvature of Young’s bargaining method on the design of WDNs. Water Resour Manag 25(9):2197–2218
Fallah-Mehdipour E, Bozorg Haddad O, Mariño MA (2012) Extraction of multi-crop planning rules in a reservoir system: application of evolutionary algorithms. J Irrig Drain Eng 139(6):490–498
Fontane D, Labadie JW, Loftis B (1981) Optimal control of reservoir discharge quality through selective withdrawal. Water Resour Res 17(6):1594–1604
Ghajarnia N, Bozorg Haddad O, Mariño MA (2011) Performance of a novel hybrid algorithm in the design of water networks. Proc Inst Civ Eng Water Manag 164(4):173–191
Hakimi-Asiabar M, Ghodsypour H, Kerachian R (2010) Deriving operation policies for multiobjective reservoir systems: application of self-learning genetic algorithm. Appl Soft Comput 10(4):1151–1163
Han J, Moraga C (1995) The influence of the sigmoid function parameters on the speed of backpropagation learning. In: From natural to artificial neural computation. Springer, Berlin, pp 195–201
Hayes DF, Labadie JW, Sanders TG, Brown JK (1998) Enhancing water quality in hydropower system operation. Water Resour Res 34(3):471–483
Heald PC, Schladow SG, Reuter JE, Allen BC (2005) Modeling MTBE and BTEX in lakes and reservoirs used for recreational boating. Environ Sci Technol 39(4):1111–1118
Hyduk W, Laudie H (1974) Prediction of diffusion coefficients for nonelectrolytes in dilute aqueous solutions. Am Inst Chem Eng 20(3):611–615
Johnson VM, Rogers LL (2000) Accuracy of neural network approximators in simulation optimization. J Water Resour Plan Manag 126(2):48–56
Karamouz M, Zahraie B, Kerachian R (2003) Development of a master plan for water pollution control using MCDM techniques: a case study. Water Int 28(4):478–490
Kerachian R, Karamouz M (2006) Optimal reservoir operation considering the water quality issue: A deterministic and stochastic conflict resolution approach. Water Resour Res 42(12):1–17
Kerachian R, Karamouz M (2007) A stochastic conflict resolution model for water quality management on reservoir systems. Adv Water Resour 30(4):866–882
Lence BJ, Takyi AK (1992) Data requirement for seasonal discharge program: an application of a regionalized sensitivity analysis. Water Resour Res 28(7):1781–1789
Lewis WK, Whitman WG (1924) Principles of gas absorption. Ind Eng Chem 16(12):1215–1220
Loftis B, Labadie JW, Fontane DG (1985) Optimal operation of a system of lakes for quality and quantity. Specialty Conference of Computer Applications in Water Resources, New York, pp 693–702
Moradi-Jalal M, Bozorg Haddad O, Karney BW, Mariño MA (2007) Reservoir operation in assigning optimal multi-crop irrigation areas. Agric Water Manag 90(1–2):149–159
Nash JF (1950) Equilibrium points in n-person games. Proc Natl Acad Sci 36(1):48–49
Neeklakantan TR, Pundarikanthan NV (2000) Neural network-based simulation-optimization model for reservoir operation. J Water Resour Plan Manag 126(2):57–64
Noory H, Liaghat AM, Parsinejad M, Bozorg Haddad O (2012) Optimizing irrigation water allocation and multicrop planning using discrete PSO algorithm. J Irrig Drain Eng 138(5):437–444
Rasoulzadeh-Gharibdousti S, Bozorg Haddad O, Mariño MA (2011) Optimal design and operation of pumping stations using NLP-GA. Proc Inst Civ Eng Water Manag 164(4):163–171
Rathbun RE (2000) Transport, behavior and fate of volatile organic compounds in stream. Environ Sci Technol 30(2):129–295
Sabbaghpour S, Naghashzadehgan M, Javaherdeh K, Bozorg Haddad O (2012) HBMO algorithm for calibrating water distribution network of Langarud city. Water Sci Technol 65(9):1564–1569
Shirangi E, Kerachian R, Shafai Bejestan M (2008) A simplified model for reservoir operation considering the water quality issues: application of the young conflict resolution theory. Environ Monit Assess 146(1–3):77–89
Shokri A, Haddad OB, Mariño MA (2013) Algorithm for increasing the speed of evolutionary optimization and its accuracy in multi-objective problems. Water Resour Manag 27(7):2231–2249
Solomatine DP, Torres A (1996) Neural network approximation of a hydrodynamic model in optimizing reservoir operation. Proceedings of the Second International Conference on Hydroinformatics, Zurich, Switzerland
Soltanjalili M, Bozorg Haddad O, Mariño MA (2010) Effect of breakage level one in design of water distribution networks. Water Resour Manag 25(1):311–337
Soltanjalili M, Bozorg Haddad O, Seifollahi-Aghmiuni S, Mariño MA (2013) Water distribution network simulation by optimization approaches. Water Sci Technol Water Supply 13(4):1063–1079
Young HP (1993) An evolutionary model of bargaining. J Econ Theory 59(1):145–168
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Shokri, A., Bozorg Haddad, O. & Mariño, M.A. Multi-Objective Quantity–Quality Reservoir Operation in Sudden Pollution. Water Resour Manage 28, 567–586 (2014). https://doi.org/10.1007/s11269-013-0504-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-013-0504-z