Fractal Singularity–Based Multiobjective Monitoring Networks for Reactive Species Contaminant Source Characterization
Publication: Journal of Water Resources Planning and Management
Volume 144, Issue 6
Abstract
The first step in effective design of contaminated aquifer site remediation is the accurate characterization of contaminant sources, which requires a large amount of concentration measurement data. However, in real-world scenarios contamination monitoring wells are generally arbitrary in location, monitoring data are sparse in time and space, and there are various uncertainties in predicting the transport process. It is a very challenging problem to optimally design effective monitoring networks intended for accurate unknown contaminant source characterization, with multiple potential source locations. In this study, the local singularity mapping technique is utilized to obtain potential monitoring well locations, which are used as input to the optimal network design model. This set of potential monitoring locations is utilized for selecting the subset of the optimal monitoring locations. This method of selecting the set of potential locations can improve the efficiency of the designed monitoring network for source characterization. The proposed methodology utilizes a multiobjective optimization algorithm for solving a two-objective optimal monitoring network design model. The optimization model is linked to a numerical simulation model simulating flow and transport processes in the aquifer. While constraining the maximum number of permissible monitoring locations, the designed optimal monitoring network improves the accuracy of unknown contaminant source characterization. The designed monitoring network can decrease the degree of nonuniqueness in the measured set of possible aquifer responses to geochemical stresses. The potential application of the developed methodology is demonstrated by evaluating the performance for an illustrative contaminated mine site aquifer. These performance evaluation results show the improved efficiency in source characterization when concentration measurements from the designed monitoring network are utilized.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The authors are grateful for very constructive comments by the reviewers. The comments by Reviewer #1 in particular helped identify an important error overlooked in the original manuscript.
References
Afzal, P., Fadakar, A. Y., Khakzad, A., Moarefvand, P., and Rashidnejad, O. N. (2011). “Delineation of mineralization zones in porphyry Cu deposits by fractal concentration-volume modeling.” J. Geochem. Explor., 108(3), 220–232.
Chandalavada, S., Datta, B., and Naidu, R. (2011a). “Optimisation approach for pollution source identification in groundwater: An overview.” Int. Environ. Waste Manage., 8(1–2), 40–61.
Chandalavada, S., Datta, B., and Naidu, R. (2011b). “Uncertainty based optimal monitoring network design for chlorinated hydrocarbon contaminated site.” Environ. Monitor. Assess., 173(1–4), 929–940.
Chen, G., Cheng, Q., Zuo, R., Liu, T., and Xi, A. Y. (2015). “Identifying gravity anomalies caused by granitic intrusions in Nanling mineral district, China: A multifractal perspective.” Geophys. Prospect., 63(1), 256–270.
Cheng, Q. (2007). “Mapping singularities with stream sediment geochemical data for prediction of undiscovered mineral deposits in Gejiu, Yunnan Province, China.” Ore Geol. Rev., 32(1–2), 314–324.
Cheng, Q. (2008). “A combined power-law and exponential model for streamflow recessions.” J. Hydrol., 352(1), 157–167.
Cheng, Q., Agterberg, F. P., and Ballantyne, S. B. (1994). “The separation of geochemical anomalies from background by fractal methods.” J. Geochem. Explor., 51(2), 109–130.
Cheng, Q., Xu, Y., and Grunsky, E. (1999). “Integrated spatial and spectral analysis for geochemical anomaly separation.” Proc., 5th Annual Conf. of the Int. Association for Mathematical Geology, S. J. Lippard and R. Sinding–Larsen, eds., Trondheim, Norway, 87–92.
Cheng, Q., Xu, Y., and Grunsky, E. (2000). “Integrated spatial and spectrum method for geochemical anomaly separation.” Nat. Resour. Res., 9(1), 43–52.
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., 399–400.
Datta, B., Amirabdollahian, M., Zuo, R., and Prakash, O. (2016a). “Groundwater contamination plume delineation using local singularity mapping technique.” Int. J. GEOMATE, 11(25), 2435–2441.
Datta, B., Chakrabarty, D., and Dhar, A. (2009). “Optimal dynamic monitoring network design and identification of unknown groundwater pollution sources.” Water Resour. Manage., 23(10), 2031–2049.
Datta, B., Durand, F., Laforge, S., Prakash, O., Esfahani, H. K., Chandalavada, S., and Naidu, R. (2016b). “Preliminary hydrogeologic modeling and optimal monitoring network design for a contaminated abandoned mine site area: Application of a developed monitoring network design software.” J. Water Resour. Prot., 8(1), 46–64.
Datta, B., and Kourakos, G. (2015). “Preface: Optimization for groundwater characterization and management.” Hydrogeol. J., 23(6), 1043–1049.
Datta, B., and Peralta, R. C. (1986). “Interactive computer graphics-based multiobjective decision-making for regional groundwater management.” Agric. Water Manage., 11(2), 91–116.
Datta, B., Petit, C., Palliser, M., Esfahani, H. K., and Prakash, O. (2017). “Linking a simulated annealing based optimization model with PHT3D simulation model for simulation of chemically reactive transport process and optimal characterization of unknown contaminant sources in a former mine site in Australia.” J. Water Resour. Prot., 9(05), 432–454.
Datta, B., Prakash, O., Campbell, S., and Escalada, G. (2013). “Efficient identification of unknown groundwater pollution sources using linked simulation-optimization incorporating monitoring location impact factor and frequency factor.” Water Resour. Manage., 27(14), 4959–4976.
Datta, B., Prakash, O., and Sreekanth, J. (2014). “Application of genetic programming models incorporated in optimization models for contaminated groundwater systems management.” EVOLVE: A bridge between probability, set oriented numerics, and evolutionary computation V. Advances in intelligent systems and computing, Vol. 8, A.-A. Tantar, et al., eds., Springer, New York, 183–199.
Dhar, A., and Datta, B. (2007). “Multi-objective design of dynamic monitoring networks for detection of groundwater pollution.” J. Water Resour. Plann. Manage., 329–338.
Dhar, A., and Datta, B. (2010). “Logic-based design of groundwater monitoring network for redundancy reduction.” J. Water Resour. Plann. Manage., 88–94.
Esfahani, K. H., and Datta, B. (2015a). “Use of genetic programming based surrogate models to simulate complex geochemical transport processes in contaminated mine sites.” Handbook of genetic programming application. A. H. Gandomi, A. H. Alavi, and C. Ryan, eds., Springer International Publishing, Basel, Switzerland, 359–379.
Esfahani, K. H., and Datta, B. (2015b). “Simulation of reactive geochemical transport processes in contaminated aquifers using surrogate models.” Int. J. GEOMATE, 8(15), 1190–1196.
Esfahani, K. H., and Datta, B. (2016). “Linked optimal reactive contaminant source characterization in contaminated mine sites: A case study.” J. Water Resour. Plann. Manage., 04016061.
Fethi, B. J., Loaiciga, A. H., and Marino, A. M. (1994). “Multivariate geostatistical design of groundwater monitoring networks.” J. Water Resour. Plann. Manage., 505–522.
Ingber, L. (1993). Adaptive simulated annealing (ASA), global optimization C-code, Caltech Alumni Association, Pasadena, CA.
Jha, M. K., and Datta, B. (2011). “Simulated annealing based simulation-optimization approach for identification of unknown contaminant sources in groundwater aquifers.” Desalin. Water Treat., 32(1–3), 79–85.
Ketabchi, H., and Ataie-Ashtiani, B. (2015). “Review: Coastal groundwater optimization—Advances, challenges, and practical solutions.” Hydrogeol. J., 23(6), 1129–1154.
Kollat, J. B., Reed, P. M., and Maxwell, R. M. (2011). “Many-objective groundwater monitoring network design using bias-aware ensemble Kalman filtering, evolutionary optimization, and visual analytics.” Water Resour. Res., 47(2), W02529.
Koza, J. R. (1994). “Genetic programming as a means for programming computers by natural-selection.” Stat. Comput., 4(2), 26.
Loaiciga, H. A. (1989). “An optimization approach for groundwater quality monitoring network design.” Water Resour. Res., 25(8), 1771–1782.
Loaiciga, H. A., Charbeneau, R. J., Everett, L. G., Fogg, G. E., Hobbs, B. F., and Rouhani, S. (1992). “Review of ground-water quality monitoring network design.” J. Hydraul. Eng., 11–37.
Loaiciga, H. A., and Hudak, P. F. (1993). “An optimization method for network design in multilayered groundwater flow systems.” Water Resour. Res., 29(8), 2835–2845.
Luoa, Q., Wub, J., Yangb, Y., Qian, J., and Wu, J. (2016). “Multi-objective optimization of long-term groundwater monitoring network design using a probabilistic Pareto genetic algorithm under uncertainty.” J. Hydrol., 534, 352–363.
Mahar, P. S., and Datta, B. (2001). “Optimal identification of ground-water pollution sources and parameter estimation.” J. Water Resour. Plann. Manage., 20–29.
Mandelbrot, B. (1967). “How long is the coast of Britain.” Science, 156(3775), 636–638.
Mandelbrot, B. (1972). “Possible refinement of the lognormal hypothesis concerning the distribution of energy dissipation in intermittent turbulence.” Statistical models and turbulence, Springer, Berlin, 333–351.
Mandelbrot, B. (1974). “Intermittent turbulence in self-similar cascades: Divergence of high moments and dimension of the carrier.” J. Fluid Mech., 62(2), 331–358.
Prakash, O., and Datta, B. (2013). “Sequential optimal monitoring network design and iterative spatial estimation of pollutant concentration for identification of unknown groundwater pollution source locations.” Environ. Monitor. Assess., 185(7), 5611–5626.
Prakash, O., and Datta, B. (2014a). “Characterization of groundwater pollution sources with unknown release time history.” J. Water Resour. Prot., 6(4), 337–350.
Prakash, O., and Datta, B. (2014b). “Encapsulating the role of solution response space roughness on global optimal solution: Application in identification of unknown groundwater pollution sources.” Open J. Optim., 3(03), 26–41.
Prakash, O., and Datta, B. (2014c). “Multi-objective monitoring network design for efficient identification of unknown groundwater pollution sources incorporating genetic programming based monitoring.” J. Hydrol. Eng., 04014025.
Prakash, O., and Datta, B. (2014d). “Optimal monitoring network design for efficient identification of unknown groundwater pollution sources.” Int. J. GEOMATE, 6(11), 785–790.
Prakash, O., and Datta, B. (2015a). “Efficient identification of unknown pollutant source characteristics in groundwater aquifers by integrating sequential optimal monitoring network design and source identification: An application.” Hydrogeol. J., 23(6), 1089–1107.
Prakash, O., and Datta, B. (2015b). “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.
Reed, P. M., and Kollat, J. B. (2013). “Visual analytics clarify the scalability and effectiveness of massively parallel many-objective optimization: A groundwater monitoring design example.” Adv. Water Resour., 56, 1–13.
Reed, P. M., and Minsker, B. S. (2004). “Striking the balance: Long-term groundwater monitoring design for conflicting objective.” J. Water Resour. Plann. Manage., 140–149.
Sadeghi, B., Madani, N., and Carranza, E. J. M. (2015). “Combination of geostatistical simulation and fractal modeling for mineral resource classification.” J. Geochem. Explor., 149, 59–73.
Sreekanth, J., and Datta, B. (2012). “Genetic programming: Efficient modelling tool in hydrology and groundwater management.” Genetic programming—New approaches and successful applications, D. S. V. Soto, ed., InTech, London, 225–238.
Sun, J. (2004). “A three-dimensional model of fluid flow, thermal transport, and hydrogeochemical transport through variably saturated conditions.” M.S. thesis., Univ. of Central Florida, Orlando, FL.
Turcotte, D. L. (2002). “Fractals in petrology.” Lithos, 65(3), 261–271.
Wu, J., Zheng, C., and Chien, C. C. (2005). “Cost-effective sampling network design for contaminant plume monitoring under general hydrogeological conditions.” J. Contam. Hydrol., 77(1–2), 41–65.
Yeh, G. T., Cheng, J. R., and Lin, H. C. (2000). Computational subsurface hydrology reactions, transport, and fate of chemicals and microbes, Kluwer Academic Publishers, New York.
Yeh, G. T., Sun, J., Jardine, P. M., Burgos, W. D., Fang, Y., Li, M. H., and Siegel, M. D. (2004). “HYDROGEOCHEM 5.0: A three-dimensional model of coupled fluid flow, thermal transport, and HYDROGEOCHEMical transport through variably saturated conditions—Version 5.0.” Oak Ridge National Laboratory, Oak Ridge, TN, 37831–6302.
Yeh, M. S., Lin, Y. P., and Chang, L. C. (2006). “Designing an optimal multivariate geostatistical groundwater quality monitoring network using factorial Kriging and genetic algorithm.” J. Environ. Geol., 50(1), 101–121.
Yeh, W. W.-G. (2015). “Review: Optimization methods for groundwater modeling and management.” Hydrogeol. J., 23(6), 1051–1065.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 144 • Issue 6 • June 2018
Copyright
©2018 American Society of Civil Engineers.
History
Received: Sep 25, 2016
Accepted: Aug 1, 2017
Published online: Mar 27, 2018
Published in print: Jun 1, 2018
Discussion open until: Aug 27, 2018
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.