Optimal Characterization of Unknown Multispecies Reactive Contamination Sources in an Aquifer
This article has a reply.
VIEW THE REPLYPublication: Journal of Hydrologic Engineering
Volume 26, Issue 11
Abstract
Groundwater contamination source characterization is the prerequisite for the rehabilitation and remediation of contaminated aquifers. This study demonstrates the computational feasibility and application of an efficient linked simulation-optimization based methodology for optimal characterization of multicomponent reactive contamination sources in a complex contaminated aquifer. The computational encumbrance of the complex reactive transport simulation is ameliorated using sufficiently accurate multioutput support vector regression (MSVR)–trained surrogate models as embedded constraints within the simulation-optimization framework. Three different metaheuristic optimization algorithms, i.e., genetic algorithm (GA), particle swarm optimization (PSO), and generalized simulated annealing (GSA), were used, and their comparative performances were evaluated for a contaminated aquifer resembling a filed-scale contaminated mine site located in Northern Territory, Australia. The performance evaluation result based on an actual contaminated aquifer site along with synthetic concentration measurements indicated that the performance of the GSA-based source identification model is superior compared to PSO and GA. The reliability and robustness of the GSA model were further investigated for erroneous concentration measurement scenarios. The preliminary findings demonstrated the computational efficiency and accuracy of the proposed MSVR surrogate model–assisted optimization for simultaneous identification of multicomponent reactive sources at complex geochemically contaminated field-scale aquifers.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors greatly appreciate James Cook University and the Australian Government Research Training Program Scholarship for providing financial support to the first author.
References
Amirabdollahian, M., and B. Datta. 2013. “Identification of contaminant source characteristics and monitoring network design in groundwater aquifers: An overview.” J. Environ. Prot. 4 (5A): 26–41. https://doi.org/10.4236/jep.2013.45A004.
Anderson, M. P., W. W. Woessner, and R. J. Hunt. 2015. Applied groundwater modeling: Simulation of flow and advective transport. San Diego: Academic Press.
Aral, M. M., and J. Guan. 1996. “Genetic algorithms in search of groundwater pollution sources.” In Advances in groundwater pollution control and remediation, 347–369. New York: Springer.
Aral, M. M., J. Guan, and M. L. Masila. 2001. “Identification of contaminant source location and release history in aquifers.” J. Hydrol. Eng. 6 (3): 225–234. https://doi.org/10.1061/(ASCE)1084-0699(2001)6:3(225).
Asher, M. J., B. F. Croke, A. J. Jakeman, and L. J. Peeters. 2015. “A review of surrogate models and their application to groundwater modeling.” Water Resour. Res. 51 (8): 5957–5973. https://doi.org/10.1002/2015WR016967.
Atmadja, J., and A. C. Bagtzoglou. 2001. “State of the art report on mathematical methods for groundwater pollution source identification.” Environ. Forensics 2 (3): 205–214. https://doi.org/10.1006/enfo.2001.0055.
Ayvaz, M. T. 2010. “A linked simulation–optimization model for solving the unknown groundwater pollution source identification problems.” J. Contam. Hydrol. 117 (1–4): 46–59. https://doi.org/10.1016/j.jconhyd.2010.06.004.
Best, R. 2005. Browns oxide project groundwater assessment. Batchelor, NT. Hawthorn East, VIC, Australia: Enesar Consultants.
Blowes, D., C. Ptacek, J. Jambor, C. Weisener, D. Paktunc, W. Gould, and D. Johnson. 2003. “The geochemistry of acid mine drainage.” Environ. Geochem. 9: 149–204. https://doi.org/10.1016/B0-08-043751-6/09137-4.
Curtis, G. P., J. A. Davis, and D. L. Naftz. 2006. “Simulation of reactive transport of uranium (VI) in groundwater with variable chemical conditions.” Water Resour. Res. 42 (4). 1–15. https://doi.org/10.1029/2005WR003979.
Datta, B. 2002. “Discussion of ‘Identification of contaminant source location and release history in aquifers’ by Mustafa M. Aral, Jiabao Guan, and Morris L. Maslia.” J. Hydrol. Eng. 7 (5): 399–400. https://doi.org/10.1061/(ASCE)1084-0699(2002)7:5(399).
Dhar, A., and B. Datta. 2010. “Logic-based design of groundwater monitoring network for redundancy reduction.” J. Water Resour. Plan. Manage. 136 (1): 88–94. https://doi.org/10.1061/(ASCE)0733-9496(2010)136:1(88).
Esfahani, H. K., and B. Datta. 2016. “Linked optimal reactive contaminant source characterization in contaminated mine sites: Case study.” J. Water Resour. Plan. Manage. 142 (12): 04016061. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000707.
Ferreira, L. B., F. F. da Cunha, R. A. de Oliveira, and E. I. Fernandes Filho. 2019. “Estimation of reference evapotranspiration in Brazil with limited meteorological data using ANN and SVM–A new approach.” J. Hydrol. 572 (May): 556–570. https://doi.org/10.1016/j.jhydrol.2019.03.028.
Gorelick, S. M., B. Evans, and I. Remson. 1983. “Identifying sources of groundwater pollution: An optimization approach.” Water Resour. Res. 19 (3): 779–790. https://doi.org/10.1029/WR019i003p00779.
Gurarslan, G., and H. Karahan. 2015. “Solving inverse problems of groundwater-pollution-source identification using a differential evolution algorithm.” Hydrogeol. J. 23 (6): 1109–1119. https://doi.org/10.1007/s10040-015-1256-z.
Hayford, M., and B. Datta. 2018. “Geochemical reactive modeling of flow and transport process at a mine site in Northern Territory, Australia.” Int. J. Geomate 15 (51): 9–15. https://doi.org/10.21660/2018.51.7260.
Huang, F., J. Huang, S.-H. Jiang, and C. Zhou. 2017. “Prediction of groundwater levels using evidence of chaos and support vector machine.” J. Hydroinf. 19 (4): 586–606. https://doi.org/10.2166/hydro.2017.102.
Jha, M., and B. Datta. 2013. “Three-dimensional groundwater contamination source identification using adaptive simulated annealing.” J. Hydrol. Eng. 18 (3): 307–317. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000624.
Jha, M. K., and B. Datta. 2011. “Simulated annealing based simulation-optimization approach for identification of unknown contaminant sources in groundwater aquifers.” Desalin. Water Treat. 32 (1–3): 79–85. https://doi.org/10.5004/dwt.2011.2681.
Johnson, D. B., and K. B. Hallberg. 2005. “Acid mine drainage remediation options: A review.” Sci. Total Environ. 338 (1–2): 3–14. https://doi.org/10.1016/j.scitotenv.2004.09.002.
Jones, D. R. 2019. Geochemical characterisation-waste rock solute source terms stage 2 and main pit tailings. Berrimah, NT: Northern Territory Department of Primary Industry and Resources.
Lal, A., and B. Datta. 2018. “Development and implementation of support vector machine regression surrogate models for predicting groundwater pumping-induced saltwater intrusion into coastal aquifers.” Water Resour. Manage. 32 (7): 2405–2419. https://doi.org/10.1007/s11269-018-1936-2.
Lal, A., and B. Datta. 2019. “Multi-objective groundwater management strategy under uncertainties for sustainable control of saltwater intrusion: Solution for an island country in the South Pacific.” J. Environ. Manage. 234 (Mar): 115–130. https://doi.org/10.1016/j.jenvman.2018.12.054.
Luo, J., and W. Lu. 2014. “A mixed-integer non-linear programming with surrogate model for optimal remediation design of NAPLs contaminated aquifer.” Int. J. Environ. Pollut. 54 (1): 1–16. https://doi.org/10.1504/IJEP.2014.064047.
Mahar, P. S., and B. Datta. 1997. “Optimal monitoring network and ground-water–pollution source identification.” J. Water Resour. Plan. Manage. 123 (4): 199–207. https://doi.org/10.1061/(ASCE)0733-9496(1997)123:4(199).
Mahar, P. S., and B. Datta. 2000. “Identification of pollution sources in transient groundwater systems.” Water Resour. Manage. 14 (3): 209–227. https://doi.org/10.1023/A:1026527901213.
Mahar, P. S., and B. Datta. 2001. “Optimal identification of ground-water pollution sources and parameter estimation.” J. Water Resour. Plan. Manage. 127 (1): 20–29. https://doi.org/10.1061/(ASCE)0733-9496(2001)127:1(20).
Mahinthakumar, G., and M. Sayeed. 2005. “Hybrid genetic algorithm—Local search methods for solving groundwater source identification inverse problems.” J. Water Resour. Plan. Manage. 131 (1): 45–57. https://doi.org/10.1061/(ASCE)0733-9496(2005)131:1(45).
Maier, H. R., et al. 2014. “Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions.” Environ. Model. Software 62 (Dec): 271–299. https://doi.org/10.1016/j.envsoft.2014.09.013.
McCready, A., E. Stumpfl, J. Lally, M. Ahmad, and R. Gee. 2004. “Polymetallic mineralization at the browns deposit, Rum Jungle mineral field, Northern Territory, Australia.” Econ. Geol. 99 (2): 257–277. https://doi.org/10.2113/gsecongeo.99.2.257.
McKay, M. D., R. J. Beckman, and W. J. Conover. 2000. “A comparison of three methods for selecting values of input variables in the analysis of output from a computer code.” Technometrics 42 (1): 55–61. https://doi.org/10.1080/00401706.2000.10485979.
Mirghani, B. Y., K. G. Mahinthakumar, M. E. Tryby, R. S. Ranjithan, and E. M. Zecham. 2009. “A parallel evolutionary strategy based simulation–optimization approach for solving groundwater source identification problems.” Water Resour. Res. 32 (9): 1373–1385. https://doi.org/10.1016/j.advwatres.2009.06.001.
Mirghani, B. Y., E. M. Zechman, R. S. Ranjithan, and G. Mahinthakumar. 2012. “Enhanced simulation-optimization approach using surrogate modeling for solving inverse problems.” Environ. Forensics 13 (4): 348–363. https://doi.org/10.1080/15275922.2012.702333.
Moriasi, D. N., J. G. Arnold, M. W. Van Liew, R. L. Bingner, R. D. Harmel, and T. L. Veith. 2007. “Model evaluation guidelines for systematic quantification of accuracy in watershed simulations.” Trans. ASABE 50 (3): 885–900. https://doi.org/10.13031/2013.23153.
Mudd, G. M., and J. Patterson. 2008. “The Rum Jungle U-Cu project: A critical evaluation of environmental monitoring and rehabilitation success.” In Uranium, mining and hydrogeology, 295–306. Cham, Switzerland: Springer.
Neupane, R., and B. Datta. 2020. “Groundwater flow and multi-component reactive transport simulation of acid mine drainage at a former mine site.” Int. J. Geomate 19 (76): 188–196. https://doi.org/10.21660/2020.76.48092.
Niswonger, R. G., S. Panday, and M. Ibaraki. 2011. “MODFLOW-NWT, a Newton formulation for MODFLOW-2005.” US Geol. Surv. Tech. Methods 6 (A37): 44.
Parkhurst, D. L., and C. Appelo. 1999. “User’s guide to PHREEQC (version 2): A computer program for speciation, batch-reaction, one-dimensional transport, and inverse geochemical calculations.” Water-Resour. Invest. Rep. 99 (4259): 312.
Prakash, O., and B. Datta. 2014a. “Characterization of groundwater pollution sources with unknown release time history.” J. Water Resour. Prot. 6 (4): 337–350. https://doi.org/10.4236/jwarp.2014.64036.
Prakash, O., and B. Datta. 2014b. “Multiobjective monitoring network design for efficient identification of unknown groundwater pollution sources incorporating genetic programming–based monitoring.” J. Hydrol. Eng. 19 (11): 04014025. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000952.
Prakash, O., and B. Datta. 2015. “Optimal characterization of pollutant sources in contaminated aquifers by integrating sequential-monitoring-network design and source identification: Methodology and an application in Australia.” Hydrogeol. J. 23 (6): 1089–1107. https://doi.org/10.1007/s10040-015-1292-8.
Prommer, H., and V. Post. 2010. “A reactive multicomponent model for saturated porous media, Version 2.0, user’s manual.” Accessed August 1, 2010. http://gmsdocs.aquaveo.com/PHT3D_manual_v210.pdf.
Razavi, S., B. A. Tolson, and D. H. Burn. 2012. “Review of surrogate modeling in water resources.” Water Resour. Res. 48 (7): W07401. https://doi.org/10.1029/2011WR011527.
Refsgaard, J. C., S. Christensen, T. O. Sonnenborg, D. Seifert, A. L. Højberg, and L. Troldborg. 2012. “Review of strategies for handling geological uncertainty in groundwater flow and transport modeling.” Adv. Water Resour. 36 (Feb): 36–50. https://doi.org/10.1016/j.advwatres.2011.04.006.
Regis, R. G., and C. A. Shoemaker. 2007. “A stochastic radial basis function method for the global optimization of expensive functions.” INFORMS J. Comput. 19 (4): 497–509. https://doi.org/10.1287/ijoc.1060.0182.
RGC (Robertson Geo Consultants). 2016. Groundwater flow and transport model for current condition. Rum Jungle, NT: RGC.
Ritter, A., and R. Muñoz-Carpena. 2013. “Performance evaluation of hydrological models: Statistical significance for reducing subjectivity in goodness-of-fit assessments.” J. Hydrol. 480 (Feb): 33–45. https://doi.org/10.1016/j.jhydrol.2012.12.004.
Roy, D. K., and B. Datta. 2017. “A surrogate based multi-objective management model to control saltwater intrusion in multi-layered coastal aquifer systems.” Civ. Eng. Environ. Syst. 34 (3–4): 238–263. https://doi.org/10.1080/10286608.2018.1431777.
Singh, R. M., and B. Datta. 2004. “Groundwater pollution source identification and simultaneous parameter estimation using pattern matching by artificial neural network.” Environ. Forensics 5 (3): 143–153. https://doi.org/10.1080/15275920490495873.
Singh, R. M., and B. Datta. 2006. “Identification of groundwater pollution sources using GA-based linked simulation optimization model.” J. Hydrol. Eng. 11 (2): 101–109. https://doi.org/10.1061/(ASCE)1084-0699(2006)11:2(101).
Singh, R. M., B. Datta, and A. Jain. 2004. “Identification of unknown groundwater pollution sources using artificial neural networks.” J. Water Resour. Plan. Manage. 130 (6): 506–514. https://doi.org/10.1061/(ASCE)0733-9496(2004)130:6(506).
Sreekanth, J., and B. Datta. 2011. “Coupled simulation-optimization model for coastal aquifer management using genetic programming-based ensemble surrogate models and multiple-realization optimization.” Water Resour. Res. 47 (4): W04516. https://doi.org/10.1029/2010WR009683.
Sun, A. Y., S. L. Painter, and G. W. Wittmeyer. 2006. “A robust approach for iterative contaminant source location and release history recovery.” J. Contam. Hydrol. 88 (3–4): 181–196. https://doi.org/10.1016/j.jconhyd.2006.06.006.
Taylor, M. P. 2007. “Distribution and storage of sediment-associated heavy metals downstream of the remediated Rum Jungle Mine on the East Branch of the Finniss River, Northern Territory, Australia.” J. Geochem. Explor. 92 (1): 55–72. https://doi.org/10.1016/j.gexplo.2006.07.005.
Unger, C., A. Lechner, V. Glenn, M. Edraki, and D. Mulligan. 2012. “Mapping and prioritising rehabilitation of abandoned mines in Australia.” In Proc., Life-of-Mine, 259–266. Reston, VA: ASCE.
Vapnik, V. 2013. The nature of statistical learning theory. New York: Springer.
Wagner, B. J., and S. M. Gorelick. 1987. “Optimal groundwater quality management under parameter uncertainty.” Water Resour. Res. 23 (7): 1162–1174. https://doi.org/10.1029/WR023i007p01162.
Xing, Z., R. Qu, Y. Zhao, Q. Fu, Y. Ji, and W. Lu. 2019. “Identifying the release history of a groundwater contaminant source based on an ensemble surrogate model.” J. Hydrol. 572 (May): 501–516. https://doi.org/10.1016/j.jhydrol.2019.03.020.
Yadav, S., and S. Shukla. 2016. “Analysis of k-fold cross-validation over hold-out validation on colossal datasets for quality classification.” In Proc., 2016 IEEE 6th Int. Conf. on Advanced Computing (IACC). New York: IEEE. https://doi.org/10.1109/IACC.2016.25.
Yeh, H. D., T. H. Chang, and Y. C. Lin. 2007. “Groundwater contaminant source identification by a hybrid heuristic approach.” Water Resour. Res. 43 (9): W09420. https://doi.org/10.1029/2005WR004731.
Yoon, H., S.-C. Jun, Y. Hyun, G.-O. Bae, and K.-K. Lee. 2011. “A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer.” J. Hydrol. 396 (1–2): 128–138. https://doi.org/10.1016/j.jhydrol.2010.11.002.
Yu, X., C. Tao, J. Sreekanth, S. Mangeon, R. Doble, P. Xin, D. Rassam, and M. Gilfedder. 2020. “Deep learning emulators for groundwater contaminant transport modelling.” J. Hydrol. 590 (Nov): 125351. https://doi.org/10.1016/j.jhydrol.2020.125351.
Zhang, J., W. Li, G. Lin, L. Zeng, and L. Wu. 2017. “Efficient evaluation of small failure probability in high-dimensional groundwater contaminant transport modeling via a two-stage Monte Carlo method.” Water Resour. Res. 53 (3): 1948–1962. https://doi.org/10.1002/2016WR019518.
Zhao, Y., W. Lu, and C. Xiao. 2016. “A Kriging surrogate model coupled in simulation–optimization approach for identifying release history of groundwater sources.” J. Contam. Hydrol. 185–186 (Feb–Mar): 51–60. https://doi.org/10.1016/j.jconhyd.2016.01.004.
Zhao, Y., R. Qu, Z. Xing, and W. Lu. 2020. “Identifying groundwater contaminant sources based on a KELM surrogate model together with four heuristic optimization algorithms.” Adv. Water Resour. 138 (Apr): 103540. https://doi.org/10.1016/j.advwatres.2020.103540.
Zheng, C., and P. P. Wang. 1999. MT3DMS: A modular three-dimensional multispecies transport model for simulation of advection, dispersion, and chemical reactions of contaminants in groundwater systems; documentation and user’s guide. Vicksburg, MS: USACE, Engineer Research and Development Center.
Information & Authors
Information
Published In
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Jan 22, 2021
Accepted: Jul 19, 2021
Published online: Sep 10, 2021
Published in print: Nov 1, 2021
Discussion open until: Feb 10, 2022
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
Cited by
- Anirban Chakraborty, Om Prakash, Identification of Clandestine Groundwater Pollution Sources in Aquifer Polluted with BTEX, Journal of Water Resources Planning and Management, 10.1061/JWRMD5.WRENG-5078, 149, 2, (2023).