Advance of Optimization Methods for Identifing Groundwater Pollution Source Porperties

Abstract:

China has to confront the groundwater resources crisis and the deterioration of groundwater environment. Reinforcing the studies on groundwater pollution source identification (GPSI) could be an important support to contamination removing, groundwater protecting, drinking water security, and development of society and economy. Exploring the new theory and method on GPSI could push the studies on ill-posed problems, and improve the techniques of contamination remediation. GPSI has been studied for thirty years, and a brief review is given to conclude the characteristics of GPSI problems. The mathematical simulation method can be classified into four types: optimization method, analytical and regression method, direct method, and stochastic method. A specific review of optimization approaches is given in this paper. The configuration, simulation procedures, common optimization algorithms used by the optimization methods are discussed in detail. Both non-heuristic and heuristic algorithm can be used to solve the PSI problem. The heuristic algorithm is more suitable for complex numerical and field cases, but it is time-consuming. The non-heuristic algorithm, especially the algorithm combined with analytical method, is time-economical, but is not suitable for complicated numerical and field tests. Further researches may focus on more complex GPSI problems, expressing physical chemistry and biological process, improving efficiency and model uncertainty of GPSI modeling.

• Periodical: Applied Mechanics and Materials (Volumes 178-181)
• Pages: 603-608
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.178-181.603
• Online since: May 2012
• Authors: Yu Qiao Long, Wei Li, Ju Huang
• Keywords: Ground Water, Optimization Approach, Pollution, Source Identification

References

[1] Y. Q. Xue and Y. K. Zhang, Twofold significance of ground water pollution prevention in China's water pollution control, Acta Scientiae Circumstantiae, vol. 29 (2009), pp.474-481. (in Chinese)

[2] J. J .Jiang, Groundwater polltion and prevention of China,Environmental Protection, vol. 38 (2007), pp.16-17.(in Chinese)

[3] Y. Sun, S. L. Painter and G. W. Wittmeyer, A constrained robust least squares approach for contaminant source release history identification, Water Rescources Research, vol. 42, W04414, doi: 10.1029/2005WR004312, 2006.

DOI: 10.1029/2005wr004312

[4] P. S. Mahar and B. Datta, Optimal monitoring network and ground-water pollution source identification, Journal of Water Resources Planning and Management, vol. 123 (1997), pp.199-207.

DOI: 10.1061/(asce)0733-9496(1997)123:4(199)

[5] C. Bagtzoglou, D. E. Dougherty and A. F. B. Tompson, Application of particle methods to reliable identification of groundwater pollution sources, Water Resources Management, vol. 6 (1992), pp.15-23.

DOI: 10.1007/bf00872184

[6] E. Milnes and P. Perrochet, Simultaneous identification of a single pollution point-source location and contamination time under known flow field conditions, Advances in Water Resources, vol. 30 (2007), pp.2439-2446.

DOI: 10.1016/j.advwatres.2007.05.013

[7] J. Wagner, Simultaneous parameter estimation and contaminant source characterization for coupled groundwater flow and contaminant transport modeling, Journal of Hydrology, vol. 135 (1992), pp.275-303.

DOI: 10.1016/0022-1694(92)90092-a

[8] T. H. Skaggs and Z. J. Kabala, Recovering the release history of a groundwater contaminant, Water Resources Research, vol. 30 (1994), pp.71-79.

DOI: 10.1029/93wr02656

[9] L. Mansuy, R. P. Philip and J. Allen, Source identification of oil spills based on the isotopic composition of individual components in weathered oil samples, Environmental Science and Technology, vol. 31 (1997), pp.3417-3425.

DOI: 10.1021/es970068n

[10] P. Rachdawong and E. Christensen, Determination of PCB sources by a principal component method with non-negative constraints, Environmental Science and Technology, vol. 31 (1997), pp.2686-2691.

DOI: 10.1021/es970107v

[11] J. Atmadja and A. C. Bagtzoglou, State of the Art Report on Mathematical Methods for Groundwater Pollution Source Identification, Environmental Forensics, vol. 2 (2001), pp.205-214.

DOI: 10.1006/enfo.2001.0055

[12] Liu and W. P. Ball, Application of inverse methods to contaminant source identification from aquitard diffusion profiles at Dover AFB, Delaware, Water Resources Research, vol. 35 (1999), pp.1975-1985.

DOI: 10.1029/1999wr900092

[13] C. Bagtzoglou and J. Atmadja, Marching-jury backward beam equation and quasi-reversibility methods for hydrologic inversion: application to contaminant plume spatial distribution recovery, Water Resources Research, vol. 39 (2003), pp.10-14.

DOI: 10.1029/2001wr001021

[14] Y. Mirghani, K. G. Mahinthakumar, M. E. Tryby, R. S. Ranjithan, and E. M. Zechman, A parallel evolutionary strategy based simulation–optimization approach for solving groundwater source identification problems, Advances in Water Resources, vol. 32 (2009), pp.1373-1385.

DOI: 10.1016/j.advwatres.2009.06.001

[15] M. T. Ayvaz, A linked simulation–optimization model for solving the unknown groundwater pollution source identification problems, Journal of Contaminant Hydrology, vol. 117 (2010), pp.46-59.

DOI: 10.1016/j.jconhyd.2010.06.004

[16] S. N. Bashi-Azghadi, R. Kerachian, M. R. Bazargan-Lari, and K. Solouki, Characterizing and unknown pollution source in groundwater resources systems using PSVM and PNN, Expert Systems with Applications, vol. 37 (2010), pp.7154-7161.

DOI: 10.1016/j.eswa.2010.04.019

[17] S. M. Gorelick, B. Evans and I. Ramson, Identifying sources of groundwater pollution: an optimization approach, Water Resources Research, vol. 19 (1983), pp.779-790.

DOI: 10.1029/wr019i003p00779

[18] P. S. Mahar and B. Datta, Optimal identification of ground-water pollution sources and parameter estimation, Journal of Water Resources Planning and Management, vol. 127 (2001), pp.20-29.

DOI: 10.1061/(asce)0733-9496(2001)127:1(20)

[19] H. R. Ghafouri and B. S. Darabi, Optimal Identification of Ground-Water Pollution Sources, International Journal of Civil Engineering, vol. 5 (2007), pp.144-154.

[20] M. M. Aral, J. Guan and M. L. Maslia, Identification of contaminant source location and release history in aquifers, Journal of Hydrological Engineering, vol. 6 (2001), pp.225-234.

DOI: 10.1061/(asce)1084-0699(2001)6:3(225)

[21] X. P. Fan and G. S. Li, An improved genetic algorithm for groundwater pollution, chinese Journal of Computational Physics, vol. 24 (2007), pp.187-191.(in Chinese)

[22] H. D. Yeh, T. H. Chang and Y. C. Liang, Groundwater contaminant source identification by a hybrid heuristic approach, Water Resources Research, vol. 43, doi:10.1029/2005WR004731, 2007.

DOI: 10.1029/2005wr004731

[23] T. V. Bharat, P. V. Sivapullaiah and M. M. Allam, Swarm Intelligence Based Inverse Model for Characterization of Groundwater Contaminant Source, Electronic Journal of Geotechnical Engineering, vol. 14 (2009), pp.1-14.

[24] V. V. Vesselinov and D. R. Harp, Contaminant source identification using adaptive hybrid optimization of inverse groundwater transport model, Water Resources Research, (2010) (under review).

[25] R. M. Singh, B. Datta and A. Jain, Identification of unknown groundwater pollution sources using artificial neural networks, Journal of Water Resources Planning and Management, vol. 130 (2004), pp.506-514.

DOI: 10.1061/(asce)0733-9496(2004)130:6(506)