An Interval-Parameter Waste-Load-Allocation Model for River Water Quality Management Under Uncertainty

Environmental Management - Tập 43 - Trang 999-1012 - 2009
Xiaosheng Qin1,2, Guohe Huang3, Bing Chen4, Baiyu Zhang5
1Sino-Canada Center of Energy and Environmental Research, North China Electric Power University, Beijing, China
2Center for Studies in Energy and Environment, University of Regina, Regina, Canada
3Faculty of Engineering, University of Regina, Regina, Canada
4Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s, Canada
5Department of Civil Engineering, Dalhousie University, Halifax, Canada

Tóm tắt

A simulation-based interval quadratic waste load allocation (IQWLA) model was developed for supporting river water quality management. A multi-segment simulation model was developed to generate water-quality transformation matrices and vectors under steady-state river flow conditions. The established matrices and vectors were then used to establish the water-quality constraints that were included in a water quality management model. Uncertainties associated with water quality parameters, cost functions, and environmental guidelines were described as intervals. The cost functions of wastewater treatment units were expressed in quadratic forms. A water-quality planning problem in the Changsha section of Xiangjiang River in China was used as a study case to demonstrate applicability of the proposed method. The study results demonstrated that IQWLA model could effectively communicate the interval-format uncertainties into optimization process, and generate inexact solutions that contain a spectrum of potential wastewater treatment options. Decision alternatives can be generated by adjusting different combinations of the decision variables within their solution intervals. The results are valuable for supporting local decision makers in generating cost-effective water quality management strategies.

Tài liệu tham khảo

Bouwer H (2003) Integrated water management for the 21st century: problems and solutions. Food Agriculture and Environment 1:118–127 Burn DH, McBean EA (1987) Application of nonlinear optimization to water quality. Applied Mathematical Modelling 11:438–446 Chen MJ, Huang GH (2001) A derivative algorithm for inexact quadratic program–application to environmental decision-making under uncertainty. European Journal of Operational Research 128:570–586 Cheng ST, Cheng LL (1990) Environmental systems analysis. China Higher Education Press, Beijing Dupacova J, Gaivoronski A, Kos Z, Szantai T (1991) Stochastic programming in water management: a case study and a comparison of solution techniques. European Journal of Operational Research 52:28–44 Fu GW, Cheng ST (1985) Systems planning for water pollution control. Tsinghua University Press, Beijing Fujiwara O (1988) River basin water quality management in stochastic environment. Journal of Environmental Engineering 114:864–877 Gen M, Ida K, Lee J (1997) Fuzzy nonlinear goal programming using genetic algorithm. Computers and Industrial Engineering 33:39–42 Giri BS, Karimi IA, Ray MB (2001) Modeling and Monte Carlo simulation of TCDD transport in a river. Water Research 35:1263–1279 Huang GH (1998) A hybrid inexact-stochastic water management model. European Journal of Operational Research 107:137–158 Huang GH, Chang NB (2003) The perspectives of environmental informatics and systems analysis. Journal of Environmental Informatics 191:1–6 Huang GH, Loucks DP (2000) An inexact two-stage stochastic programming model for water resources management under uncertainty. Civil Engineering and Environmental Systems 17:95–118 Huang GH, Qin XS (2008a) Environmental systems analysis under uncertainty. Civil Engineering and Environmental Systems 25:77–80 Huang GH, Qin XS (2008b) Editorial: climate change and sustainable energy development. Energy Sources, Part A – Recovery Utilization and Environmental Effects 30:1281–1285 Huang GH, Baetz BW, Patry GG (1992) An interval linear programming approach for municipal solid waste management planning under uncertainty. Civil Engineering Systems 9:319–335 Huang GH, Baetz BW, Party GG (1995) Grey quadratic programming and its application to municipal solid waste management planning under uncertainty. Engineering Optimization 23:201–223 Huang YF, Huang GH, Baetz BW, Liu L (2002) Violation analysis for solid waste management systems: an interval fuzzy programming approach. Journal of Environmental Management 65:431–446 Karmakar S, Mujumdar PP (2006) Grey fuzzy optimization model for water quality management of a river system. Advances in Water Resources 29:1088–1105 Kennedy WJ, Gentle JE (1981) Statistics: textbooks and monographs. Marcel Dekker, New York, pp 200–270 Kim KJ, Lin DKJ (1998) Dual response surface optimization: a fuzzy modeling approach. Journal of Quality Technology 30:1–10 Kothandaraman V, Ewing BB (1969) A probabilistic analysis of dissolved oxygen-biochemical oxygen demand relationship in streams. Journal of Water Pollution Control Federation 41:155–162 Lee CS, Chang SP (2005) Interactive fuzzy optimization for an economic and environmental balance in a river system. Water Research 39:221–231 Lee CS, Wen CG (1996) River assimilative capacity analysis via fuzzy linear programming. Fuzzy Sets and Systems 79:191–201 Lee CS, Wen CG (1997) Fuzzy goal programming approach for water quality management in a river basin. Fuzzy Sets and Systems 89:181–192 Li YP, Huang GH, Baetz BW (2006) Environmental management under uncertainty—an internal-parameter two-stage chance-constrained mixed integer linear programming method. Environmental Engineering Science 23:761–779 Liu Y, Guo HC, Zhang ZX, Wang LJ, Dai YL, Fan YY (2007) An optimization method based on scenario analyses for watershed management under uncertainty. Environmental Management 39(5):678–690 Liu Y, Yang PJ, Hu C, Guo HC (2008) Water quality modeling for load reduction under uncertainty: a Bayesian approach. Water Research, doi:10.1016/j.watres.2008.04.007 Loucks DP (2003) Managing America’s rivers: who’s doing it? International Journal of River Basin Management 1:21–31 Loucks DP, Stedinger JR, Haith DA (1981) Water resource systems planning and analysis. Prentice-Hall Inc., Englewood Cliffs, New Jersey Loucks DP, Kindler J, Fedra K (1985) Interactive water resources modeling and model use: an overview. Water Resources Research 21:95–102 Marr JK, Canale RP (1988) Load allocation for toxics using Monte Carlo techniques, Journal—Water Pollution Control Federation 60:659–666 Mujumdar PP, Sasikumar K (2002) A fuzzy risk approach for seasonal water quality management of a river system. Water Resources Research 38: doi:10.1029/2000WR000126 Mujumdar PP, Saxena P (2004) A stochastic dynamic programming model for stream water quality management. Sadhana 29:477–497 O’Connor DJ, Dobbins WE (1958) Mechanisms of reaeration in natural streams. Transactions of the American Society of Civil Engineering 123:641–684 Qin XS, Zeng GM (2002) Application of genetic algorithm to gray non-linear programming problems for water environment. Advances in Water Science (China) 13:32–37 Qin XS, Huang GH, Zeng GM, Chakma A, Huang YF (2007a) An interval-parameter fuzzy nonlinear optimization model for stream water quality management under uncertainty. European Journal of Operational Research 180:1331–1357 Qin XS, Huang GH, Zeng GM, Chakma A, Xi BD (2007b) A fuzzy composting process model. Journal of Air & Waste Management Association 57:535–550 Qin XS, Huang GH, Chakma A (2007c) A stepwise-inference-based optimization system for supporting remediation of petroleum-contaminated sites. Water, Air and Soil Pollution 185:349–368 Qin XS, Huang GH, Sun W, Chakma A (2008a) Optimizing remediation operations at petroleum contaminated sites through a simulation-based stochastic-MCDA approach. Energy Sources, Part A – Recovery Utilization and Environmental Effects 30:1300–1326 Qin XS, Huang GH, Li YP (2008b) Risk management of BTEX contamination in ground water – An integrtated fuzzy approach. Ground Water 46:755–767 Qin XS, Huang GH, Zeng GM, Chakma A (2008c) Simulation-based optimization of dual-phase vacuum extraction to remove nonaqueous phase liquids in subsurface. Water Resources Research 44: W04422 Rauch W, Henze M, Koncsos L, Reichert P (1998) River water quality modelling I. state of the art. In: Proceedings at the IAWQ Biennial International Conference, Vancouver, British Columbia, Canada, pp 21–26 Revelli R, Ridolfi L (2004) Stochastic dynamics of BOD in a stream with random inputs. Advances in Water Resources 27:943–952 Rinaldi S, Soncini-Sessa R, Stehfest H, Tamura H (1979) Modeling and control of river quality. McGraw-Hill, New York, London Sasikumar K, Mujumdar PP (1998) Fuzzy optimization model for water quality management of river system. Journal of Water Resources Planning and Management (ASCE) 124:79–84 SEPA (State Environmental Protection Administration) (1996) Industrial wastewater discharge standard (GB8978–1996), Beijing SEPA (State Environmental Protection Administration) (2002) Environmental quality standard for surface water (GB3838–2002), Beijing Thomann RV, Mueller JA (1987) Principles of surface water quality modeling and control. Harper & Row, New York Wu XY, Huang GH, Liu L, Li JB (2006) An interval nonlinear program for the planning of waste management systems with economies-of-scale effects—a case study for the region of Hamilton, Ontario, Canada. European Journal of Operational Research 171:349–372 Zeng GM, Lin YP, Qin XS, Huang GH, Li JB (2004) Optimum municipal wastewater treatment plan design with consideration of uncertainty. Journal of Environmental Sciences 16:126–131 Zeng GM, Qin XS, Wang W, Huang GH, Li JB, Statzner B (2003). Water environmental planning considering the influence of non-linear characteristics. Journal of Environmental Sciences 15:800–807