Optimal Unknown Pollution Source Characterization in a Contaminated Groundwater Aquifer—Evaluation of a Developed Dedicated Software Tool

Abstract

Precise identification of the pollutant source characteristics is the first step for designing an effective groundwater contamination remediation strategy. In this study a linked simulation-optimization based methodology is utilized for identification of unknown groundwater pollution sources in a real life contaminated aquifer in New South Wales, Australia where the source locations and source flux release history are the explicit unknown variables. The methodology is applied utilizing an in house software package GWSID developed at James Cook University for optimal determination of the unknown source characteristics. The methodology incorporates linked simulation optimization approach and utilizes simulated Algorithm as an evolutionary optimization algorithm. The performance evaluation results show practical utility of the methodology and of the associated developed computers software in identifying the unknown source characteristics.

Share and Cite:

Datta, B. , Prakash, O. , Cassou, P. and Valetaud, M. (2014) Optimal Unknown Pollution Source Characterization in a Contaminated Groundwater Aquifer—Evaluation of a Developed Dedicated Software Tool. Journal of Geoscience and Environment Protection, 2, 41-51. doi: 10.4236/gep.2014.25007.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Ababou, R., Bagtzoglou, A. C., & Mallet, A. (2010). Anti-Diffusion and Source Identification with the RAW Scheme: A Particle-Based Censored Random Walk. Environmental Fluid Mechanics, 10, 41-76 http://dx.doi.org/10.1007/s10652-009-9153-4 [Google Scholar] [CrossRef]
[2] Aral, M. M., Guan, J., & Maslia, M. L. (2001). Identification of Con-taminant Source Location and Release History in Aquifers. Journal of Hydrologic Engineering, 6, 225-234. http://dx.doi.org/10.1061/(ASCE)1084-0699(2001)6:3(225) [Google Scholar] [CrossRef]
[3] Atmadja, J., & Bagtzoglou, A. C. (2001). State of the Art Report on Mathematical Methods to Reliable of Groundwater Pollution Source Identification. Environmental Forensics, 2, 205-214. http://dx.doi.org/10.1006/enfo.2001.0055 [Google Scholar] [CrossRef]
[4] Ayvaz, T. M. (2010). A Linked Simulation-Optimization Model for Solving the Unknown Groundwater Pollution Source Identification Problems. Journal of Contaminant Hydrology, 117, 46-59. http://dx.doi.org/10.1016/j.jconhyd.2010.06.004 [Google Scholar] [CrossRef] [PubMed]
[5] Bagtzoglou, A. C. (2003). On the Non-Locality of Reversed Time Particle Tracking Methods. Environmental Forensics, 4, 215-225. http://dx.doi.org/10.1080/713848511 [Google Scholar] [CrossRef]
[6] Chadalavada, S., Datta, B., & Naidu, R. (2011). Optimisation Approach for Pollution Source Identification in Groundwater: An Overview. International Journal of Environment and Waste Manage-ment, 8, 40-61. http://dx.doi.org/10.1504/IJEWM.2011.040964 [Google Scholar] [CrossRef]
[7] Datta, B., Arachchige, R. R, Prakash, O., Amirabdollihan, M., Chadalavada, S., & Naidu, R. (2013a). Integrated Software for Characterizing Groundwater Pollution Sources in a polluted aquifer CARE-GWSID—Software User Manual, James Cook University and CRC-CARE.
[8] Datta, B., Beegle, J. E., Kavvas, M. L., & Orlob, G. T. (1989). Development of an Expert-System Embedding Pattern-Recognition Techniques for Pollution Source Identification. Technical Report: PB-90-185927/XAB, OSTI ID: 6855981. Davis, CA: Dept. of Civil Engineering, California Univ.
[9] Datta, B., Chakrabarty, D., & Dhar, A. (2009a). Optimal Dynamic Monitoring Network Design and Identification of Unknown Groundwater Pollution Sources. Water Resour. Manage., Springer, 23, 2031-2049.
[10] Datta, B., Chakrabarty, D., & Dhar, A. (2009b). Simultaneous Identification of Unknown Groundwater Pollution Sources and Estimation of Aquifer Parameters. J. Hydrol., 376, 48-57.
[11] Datta, B., Chakrabarty, D., & Dhar, A. (2011). Identification of Unknown Groundwater Pollution Sources Using Classical Optimization with Linked Simulation. Journal of Hydro-Environment Research, 5, 25-36. http://dx.doi.org/10.1016/j.jher.2010.08.004 [Google Scholar] [CrossRef]
[12] Datta, B., Prakash, O., Campbell, S., & Escalada, G., (2013b). Efficient Identification of Unknown Groundwater Pollution Sources Using Linked Simulation-Optimization Incorporating Monitoring Location Impact Factor and Frequency Factor. Water Resources Management, 27, 4959-4976. http://dx.doi.org/10.1007/s11269-013-0451-8 [Google Scholar] [CrossRef]
[13] Domenico, P. A., & Schwartz, F. W. (1998). Physical and Chemical Hydrogeology (2nd ed.). New York: John Wiley & Sons, Inc.
[14] Goffe, W. L. (1996). SIMANN: A Global Optimization Algorithm Using Simulated Annealing, Studied in Nonlinear Dynamics and Econometrics. Berkeley Electronic Press.
[15] Gorelick, S. M., Evans, B., & Ramson, I. (1983). Identifying Sources of Groundwater Pollution: An Optimization Approach. Water Resources Research, 19, 779-790. http://dx.doi.org/10.1029/WR019i003p00779 [Google Scholar] [CrossRef]
[16] Harbaugh, A. W., Banta, E. R., Hill, M. C., & McDonald, M. G. (2000). MODFLOW-2000, the U.S. Geological Survey modular Ground-Water Model. U.S. Geological Survey Open-File Report. 00-92, 121 p.
[17] Jha, M. K., & Datta, B. (2011). Simulated Annealing Based Simulation-Optimization Approach for Identification of Unknown Contaminant Sources in Groundwater Aquifers. Desalination and Water Treatment, 32, 79-85. http://dx.doi.org/10.5004/dwt.2011.2681 [Google Scholar] [CrossRef]
[18] Jha, M. K., & Datta, B. (2012). Linked Simulation-Optimization Based Methodologies for Unknown Groundwater Pollutant Source Identification in Managed and Unmanaged Contaminated Sites. Chapter 4, PhD Thesis, James Cook University.
[19] Kirkpatrick, S., Gelatt, D. C., & Vecchi, P. M. (1983). Optimization by Simulated Annealing. Science, 220, 671-680. http://dx.doi.org/10.1126/science.220.4598.671 [Google Scholar] [CrossRef] [PubMed]
[20] Mahar, P. S., & Datta, B. (1997). Optimal Monitoring Network and Ground-Water Pollution Source Identification. Journal of Water Resources Planning and Management, 123, 199-207. http://dx.doi.org/10.1061/(ASCE)0733-9496(1997)123:4(199) [Google Scholar] [CrossRef]
[21] Mahar, P. S., & Datta, B. (2000). Identification of Pollution Sources in Transient Groundwater System. Water Resources Management, 14, 209-227. http://dx.doi.org/10.1023/A:1026527901213 [Google Scholar] [CrossRef]
[22] Mahar, P. S., & Datta, B. (2001). Optimal Identification of Ground-Water Pollution Sources and Parameter Estimation. Journal of Water Resources Planning and Management, 127, 20-29. http://dx.doi.org/10.1061/(ASCE)0733-9496(2001)127:1(20) [Google Scholar] [CrossRef]
[23] Marsden, J. (2011). Report for Strengthening Basin Communities—Planning Study Business Case—Enhancing Dubbo’s Irrigation System. Dubbo City Council.
[24] Metropolis, N., Rosenbluth, A., Rosenbluth, M., Teller, A., & Teller, E. (1953). Equation of State Calculations by Fast Computing Machines. The Journal of Chemical Physics, 21, 1087-1092. http://dx.doi.org/10.1063/1.1699114 [Google Scholar] [CrossRef]
[25] Prakash, O., & Datta, B. (2012). Sequential Optimal Monitoring Network Design and Iterative Spatial Estimation of Pollutant Concentration for Identification of Unknown Groundwater Pollution Source Locations. Environmental Monitoring and Assessment, 185, 5611-5626. http://dx.doi.org/10.1007/s10661-012-2971-8 [Google Scholar] [CrossRef] [PubMed]
[26] Prakash, O., & Datta, B. (2014a). Optimal Monitoring Network Design for Efficient Identification of Unknown Groundwater Pollution Sources. Int. J. of GEOMATE, 6, 785-790.
[27] Prakash, O., & Datta, B. (2014b). Characterization of Groundwater Pollution Sources with Unknown Release Time History. Journal of Water Resource and Protection, 6, 337-350. http://dx.doi.org/10.4236/jwarp.2014.64036 [Google Scholar] [CrossRef]
[28] Prakash, O., & Datta, B. (2014b). Optimal Monitoring Network Design and Identification of Unknown Pollutant Sources in Polluted Aquifers. Chapter 6, PhD Thesis, James Cook University.
[29] Prakash, O., & Datta, B., (2013). A Multi-Objective Monitoring Network Design for Efficient Identification of Unknown Groundwater Pollution Sources Incorporating Genetic Programming Based Monitoring. Journal of Hydrologic Engineering, 19, 04014025. http://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0000952 [Google Scholar] [CrossRef]
[30] Puech, V. (2010). Upper Macquarie Groundwater Model. Technical Report VW04680, Office of Water, NSW Government and National Water Commission, Australia.
[31] Rushton, K. R., & Redshaw, S. C. (1979). Seepage and Groundwater Flow. New York: Wiley.
[32] Sidauruk, P., Cheng, A. H.-D., & Ouazar, D. (1997). Groundwater Contaminant Source and Transport Parameter Identification by Correlation Coefficient Optimization. Groundwater, 36, 208-214. http://dx.doi.org/10.1111/j.1745-6584.1998.tb01085.x [Google Scholar] [CrossRef]
[33] Singh, R. M., & Datta, B. (2004). Groundwater Pollution Source Identification and Simultaneous Parameter Estimation Using Pattern Matching by Artificial Neural Network. En-vironmental Forensics, 5, 143-159. http://dx.doi.org/10.1080/15275920490495873 [Google Scholar] [CrossRef]
[34] Singh, R. M., & Datta, B. (2006). Identification of Groundwater Pol-lution Sources Using GA-Based Linked Simulation Optimization Model. Journal of Hydrologic Engineering, 11, 101-109. http://dx.doi.org/10.1061/(ASCE)1084-0699(2006)11:2(101) [Google Scholar] [CrossRef]
[35] Singh, R. M., & Datta, B. (2007). Artificial Neural Network Modeling for Identification of Unknown Pollution Sources in Groundwater with Partially Missing Concentration Observation Data. Water Resources Management, 21, 557-572. http://dx.doi.org/10.1007/s11269-006-9029-z [Google Scholar] [CrossRef]
[36] Singh, R. M., Datta, B., & Jain, A. (2004). Identification of Unknown Groundwater Pollution Sources Using Artificial Neural Networks. J. Water Resour. Plan. Manage., 130, 506-514. http://dx.doi.org/10.1061/(ASCE)0733-9496(2004)130:6(506) [Google Scholar] [CrossRef]
[37] Sun, A. Y., Painter, S. L., & Wittmeyer, G. W. (2006). A Robust Approach for Contaminant Source Location and Release History Recovery. J. Contam. Hydrol., 88, 29-44.
[38] Wagner, B. J. (1992). Simultaneous Parameter Estimation and Contaminant Source Characterization for Coupled Groundwater Flow and Contaminant Transport Modeling. Journal of Hydrology, 135, 275-303. http://dx.doi.org/10.1016/0022-1694(92)90092-A [Google Scholar] [CrossRef]
[39] Woodbury, A. D., Sudicky, E., Ulrych, T. J., & Ludwig, R. (1998). Three-Dimensional Plume Source Reconstruction Using Minimum Relative Entropy Inversion. Journal of Contaminant Hydrology, 32, 131-158. http://dx.doi.org/10.1016/S0169-7722(97)00088-0 [Google Scholar] [CrossRef]
[40] Yeh, W. W.-G. (1986). Review of Parameter Identification Procedure in Groundwater Hydrology: The Inverse Problem. Water Resour. Res., 22, 95-108. http://dx.doi.org/10.1029/WR022i002p00095 [Google Scholar] [CrossRef]
[41] Zheng, C., & Wang, P. P. (1999). MT3DMS, A Modular Three-Dimensional Multi-Species Transport Model for Simulation of Advection, Dispersion and Chemical Reactions of Contaminants in Groundwater Systems. Vicksburg, MS: U.S. Army Engineer Research and Development Center Contract Report SERDP-99-1, 202 p.

Copyright © 2026 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.