Application of stochastic optimization algorithm for waste load allocation in the Nakdong River basin, Korea

Model based decision support systems are increasingly used for the purpose of water resources management. In the aspect of water quality management, deterministic water quality simulation will involve various uncertainties that may yield unrealistic results. To overcome such limitations, this study proposed an optimization algorithm incorporating the stochastic approach focusing on efficient waste load allocation. Based on Monte Carlo Simulation (MCS) uncertainty analysis method, the performance of the chance constrained linear optimization programming was validated to describe the nonlinear behavior in the river system. Applicability of the proposed optimization scheme has been tested and evaluated for the Nakdong River basin in Korea where multiple pollutant sources and a large amount of water intake facilities coexist. The proposed optimization algorithm is useful to estimate the amount of waste loads that should be removed to meet the target regulatory water quality standard considering uncertainties involved in the deterministic water quality simulation.

[1]  Keith Beven,et al.  A manifesto for the equifinality thesis , 2006 .

[2]  Shinichiro Ohgaki,et al.  Chance Constrained Model for River Water Quality Management , 1987 .

[3]  Charles S. Sawyer,et al.  Mixed-Integer Chance-Constrained Models for Ground-Water Remediation , 1998 .

[4]  Yeou-Koung Tung,et al.  Multiple-objective waste load allocation , 1989 .

[5]  Bithin Datta,et al.  Chance-Constrained Optimal Monitoring Network Design for Pollutants in Ground Water , 1996 .

[6]  Garret N. Vanderplaats,et al.  Numerical Optimization Techniques for Engineering Design: With Applications , 1984 .

[7]  M. Hanif Chaudhry,et al.  Open-Channel Flow , 2007 .

[8]  R. Daren Harmel,et al.  Consideration of measurement uncertainty in the evaluation of goodness-of-fit in hydrologic and water quality modeling , 2007 .

[9]  Ralph A. Wurbs,et al.  Water Resources Engineering , 2001 .

[10]  L. Mays,et al.  Hydrosystems engineering and management , 1991 .

[11]  F. Pappenberger,et al.  Ignorance is bliss: Or seven reasons not to use uncertainty analysis , 2006 .

[12]  Miguel A. Medina,et al.  CHANCE CONSTRAINED MODEL FOR STORM-WATER SYSTEM DESIGN AND REHABILITATION , 1997 .

[13]  J. J. Moré,et al.  Quasi-Newton Methods, Motivation and Theory , 1974 .

[14]  Garret N. Vanderplaats,et al.  Numerical optimization techniques for engineering design , 1999 .

[15]  Yeou-Koung Tung,et al.  Stochastic waste load allocation , 1990 .

[16]  Deg-Hyo Bae,et al.  STOCHASTIC WATER QUALITY ANALYSIS USING RELIABILITY METHOD1 , 2001 .

[17]  Yeou-Koung Tung,et al.  Multiple-objective stochastic waste-load allocation , 1992 .

[18]  D. Kavetski,et al.  Confronting Input Uncertainty in Environmental Modelling , 2013 .