Optimal Management of a Freshwater Lens in a Small Island Using Surrogate Models and Evolutionary Algorithms
Publication: Journal of Hydrologic Engineering
Volume 19, Issue 2
Abstract
This paper examines a linked simulation-optimization procedure based on the combined application of an artificial neural network (ANN) and genetic algorithm (GA) with the aim of developing an efficient model for the multiobjective management of groundwater lenses in small islands. The simulation-optimization methodology is applied to a real aquifer in Kish Island of the Persian Gulf to determine the optimal groundwater-extraction while protecting the freshwater lens from seawater intrusion. The initial simulations are based on the application of SUTRA, a variable-density groundwater numerical model. The numerical model parameters are calibrated through automated parameter estimation. To make the optimization process computationally feasible, the numerical model is subsequently replaced by a trained ANN model as an approximate simulator. Even with a moderate number of input data sets based on the numerical simulations, the ANN metamodel can be efficiently trained. The ANN model is subsequently linked with GA to identify the nondominated or Pareto-optimal solutions. To provide flexibility in the implementation of the management plan, the model is built upon optimizing extraction from a number of zones instead of point-well locations. Two issues are of particular interest to the research reported in this paper are: (1) how the general idea of minimizing seawater intrusion can be effectively represented by objective functions within the framework of the simulation-optimization paradigm, and (2) the implications of applying the methodology to a real-world small-island groundwater lens. Four different models have been compared within the framework of multiobjective optimization, including (1) minimization of maximum salinity at observation wells, (2) minimization of the root mean square (RMS) change in concentrations over the planning period, (3) minimization of the arithmetic mean, and (4) minimization of the trimmed arithmetic mean of concentration in the observation wells. The latter model can provide a more effective framework to incorporate the general objective of minimizing seawater intrusion. This paper shows that integration of the latest innovative tools can provide the ability to solve complex real-world optimization problems in an effective way.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The research reported in this paper was supported under grant number 17/419295 by the Iran Kish Free-Zone Organization. The writers are grateful for the constructive comments of the editor and two anonymous reviewers, which helped improve the final paper.
References
Ataie-Ashtiani, B., and Ketabchi, H. (2011). “Elitist continuous ant colony optimization algorithm for optimal management of coastal aquifers.” Water Resour. Manage., 25(1), 165–190.
Ataie-Ashtiani, B., Rajabi, M. M., and Ketabchi, H. (2013a). “Inverse modelling for freshwater lens in small islands: Kish Island, Persian Gulf.” Hydrol. Process., 27(19), 2759–2773.
Ataie-Ashtiani, B., Werner, A. D., Simmons, C. T., Morgan, L. K., and Lu, C. (2013b). “How important is the impact of land-surface inundation on seawater intrusion caused by sea-level rise?.” Hydrogeology J., 21(7), 1673–1677.
Ataie-Ashtiani, B., Volker, R. E., and Lockington, D. A. (1999). “Tidal effects on sea water intrusion in unconfined aquifers.” J. Hydrol., 216(1), 17–31.
Banerjee, P., Singh, V. S., Chatttopadhyay, K., Chandra, P. C., and Singh, B. (2011). “Artificial neural network model as a potential alternative for groundwater salinity forecasting.” J. Hydrol., 398(3), 212–220.
Bhattacharjya, R. K., and Datta, B. (2005). “Optimal management of coastal aquifers using linked simulation optimization approach.” Water Resour. Manage., 19(3), 295–320.
Bhattacharjya, R. K., and Datta, B. (2009). “ANN-GA-based model for multiple objective management of coastal aquifers.” J. Water Resour. Plann. Manage., 314–322.
Bhattacharjya, R. K., Datta, B., and Satish, M. (2007). “Artificial neural networks approximation of density dependent seawater intrusion process in coastal aquifers.” J. Hydrol. Eng., 273–282.
Cheng, A., Halhal, D., Naji, A., and Ouazar, D. (2000). “Pumping optimization in seawater-intruded coastal aquifers.” Water Resour. Res., 36(8), 2155–2166.
Das, A., and Datta, B. (2000). “Optimization based solution of density dependent seawater intrusion in coastal aquifers.” J. Hydrol. Eng., 82–89.
Dhar, A., and Datta, B. (2009a). “Seawater intrusion management of coastal aquifers. I: Linked simulation-optimization.” J. Hydrol. Eng., 1263–1272.
Dhar, A., and Datta, B. (2009b). “Seawater intrusion management of coastal aquifers. II: Operation uncertainty and monitoring.” J. Hydrol. Eng., 1273–1282.
Doherty, J. (2005). PEST: Model independent parameter estimation, 5th Ed., Watermark Numerical Computing, Brisbane, Australia.
Drees and Sommer. (2004). Kish Island integrated management plan–Kish Island, Iran Kish Free-Zone Organization, Kish Island, Iran.
Emch, P. G., and Yeh, W. W. G. (1998). “Management model for conjunctive use of coastal surface water and ground water.” J Water Resour. Plann. Manage., 129–139.
Falkland, A. (1991). Hydrology and water resources of small islands: A practical guide, United Nations Educational, Scientific, and Cultural Organization, Paris.
Finney, B., Samsuhadi, A., and Willis, R. (1992). “Quasi-three-dimensional optimization of Jakarta Basin.” J. Water Resour. Plann. Manage., 18–31.
Gümrah, F., Öz, B., Güler, B., and Evin, S. (2000). “The application of artificial neural networks for the prediction of water quality of polluted aquifer.” J. Water Air Soil Pollut., 119(1–4), 275–294.
Kentel, E., and Aral, M. M. (2007). “Fuzzy multiobjective decision-making approach for roundwater resources management.” J. Hydrol. Eng., 206–217.
Ketabchi, H., Mahmoodzadeh, D., Ataie-Ashtiani, B., Werner, A. D., and Simmons, C. T. (2013). “Sea-level rise impact on fresh groundwater lenses in two-layer small islands.” Hydrol. Process..
Kish Free-Zone Organization (KFZO). (2006). “Annual report. Kish Island.” Kish Island, Iran.
Kollat, J. B., and Reed, P. M. (2006). “Comparing state-of-the-art evolutionary multi-objective algorithms for long-term groundwater monitoring design.” Adv. Water Resour., 29(6), 792–807.
Kourakos, G., and Mantoglou, A. (2009). “Pumping optimization of coastal aquifers based on evolutionary algorithms and surrogate modular neural network models.” Adv. Water Resour., 32(4), 507–521.
Kourakos, G., and Mantoglou, A. (2011). “Simulation and multi-objective management of coastal aquifers in semi-arid regions.” Water Resour. Manage., 25(4), 1063–1074.
Lallahem, S., Mania, J., Hani, A., and Najjar, Y. (2005). “On the use of neural networks to evaluate groundwater levels in fractured media.” J. Hydrol., 307(1), 92–111.
Lloyd, J. W. (1986). “A review of aridity and groundwater.” Hydrol. Process., 1(1), 63–78.
Maier, H. R., and Dandy, G. C. (2000). “Neural networks for the prediction and forecasting of water resources variables: A review of modeling issues and applications.” Environ. Model. Softw., 15(1), 101–124.
Manisha, P. J., Rastogi, A. K., and Mohan, B. K. (2008). “Critical review of applications of artificial neural networks in groundwater hydrology.” Proc., Int. Conf. of Int. Association for Computer Methods and Advances in Geomechanics, Balkema, Rotterdam, Netherlands, 2463–2474.
Mantoglou, A. (2003). “Pumping management of coastal aquifers with analytical models of seawater intrusion.” Water Resour. Res., 39(12), WR001891.
Mantoglou, A., Papantoniou, M., and Giannoulopoulos, P. (2004). “Management of coastal aquifers based on nonlinear optimization and evolutionary algorithms.” J. Hydrol., 297(1), 209–228.
Milnes, E., and Renard, P. (2004). “The problem of salt recycling and seawater intrusion in coastal irrigated plains: An example from the Kiti aquifer (southern Cyprus).” J. Hydrol., 288(3), 327–343.
Nicklow, J., et al. (2010). “State of the art for genetic algorithms and beyond in water resources planning and management.” J. Water Resour. Plann. Manage., 412–432.
Park, C. H., and Aral, M. M. (2004). “Multi-objective optimization of pumping rates and well placement in coastal aquifers.” J. Hydrol., 290(1), 80–99.
Park, C. H., and Aral, M. M. (2008). “Saltwater intrusion hydrodynamics in a tidal aquifer.” J. Hydrol. Eng., 863–872.
Park, S. U., Kim, J. M., Yum, B. W., and Yeh, G. T. (2012). “Three-dimensional numerical simulation of saltwater extraction schemes to mitigate seawater intrusion due to groundwater pumping in a coastal aquifer system.” J. Hydrol. Eng., 10–22.
Potter, L. D. (1992). Desert characteristics as related to waste disposal, in deserts as dumps? The disposal of hazardous materials in arid ecosystems, Univ. of New Mexico Press, Albuquerque, NM.
Qahman, K. H., Larabi, A., Quazar, D., Naji, A., Alexander, H., and Cheng, D. (2005). “Optimal and sustainable extraction of groundwater in coastal aquifers.” Stoch. Environ. Res. Risk Assess., 19(2), 99–110.
Rao, S. V. N., Sreenivasulu, V., Bhallamudi, S. M., Thandaveswara, B. S., Sudheer, K. P. (2004). “Planning groundwater development in coastal aquifers.” Hydrolog. Sci. J., 49(1), 155–170.
Rao, S. V. N., Thandaveswara, B. S., Bhallamudi, S. M., and Srinivasulu, V. (2003). “Optimal groundwater management in deltaic regions using simulated annealing and neural networks.” Water Resour. Manage., 17(6), 409–428.
Reeves, C. R., and Rowe, J. E. (2003). Genetic algorithms: Principles and perspectives–A guide to GA theory, Kluwer, New York.
Shahin, M. A., Jaksa, M. B., and Maier, H. R. (2008). “State of the art of artificial neural networks in geotechnical engineering.” Electron. J. Geotech. Eng., 8(1), 1–26.
Shamir, U., Bear, J., and Gamiliel, A. (1984). “Optimal annual operation of a coastal aquifer.” Water Resour. Res., 20(4), 435–444.
Sreekanth, J., and Datta, B. (2010). “Multi-objective management of saltwater intrusion in coastal aquifers using genetic programming and modular neural network based surrogate models.” J. Hydrol., 393(3), 245–256.
Sreekanth, J., and Datta, B. (2011). “Comparative evaluation of genetic programming and neural network as potential surrogate models for coastal aquifer management.” Water Resour. Manage., 25(13), 3201–3218.
Stone, M. (1974). “Cross-validatory choice and assessment of statistical predictions.” J. Roy. Stat. Soc. B., 36(2), 111–147.
Thornthwaite, C. (1948). “An approach toward a rational classification of climate.” Geogr. Rev., 38(1), 55–94.
Turc, L. (1955). “Le bilan d’eau des sols. Relations entre les precipitations, l’evaporation et l’ecoulemet.” Ann. Agron., 6(1), 5–131 (in French).
United Nations Conference on Environment, and Development. (1992). “Agenda 21: Chapter 17.3.” 〈http://www.un.org/esa/sustdev/documents/agenda21/english/agenda21chapter17.htm〉 (Oct. 30, 2013).
Van der Velde, M., Green, S. R., Vanclooster, M., and Clothier, B. E. (2007). “Sustainable development in small island developing states: Agricultural intensification, economic development, and freshwater resources management on the coral atoll of Tongatapu.” Ecol. Econ., 61(2), 456–468.
Voss, C. I., and Provost, A. M. (2010). “SUTRA: A model for saturated-unsaturated, variable-density groundwater flow with solute or energy transport.”, U.S. Geological Survey, Reston, VA.
Werner, A. D., et al. (2013). “Seawater intrusion processes, investigation and management: Recent advances and future challenges.” Adv. Water Resour., 51(1), 3–26.
Wheater, H. S., Mathias, S. A., and Li, X. (2010). Groundwater modeling in arid and semi arid areas, Cambridge University Press, Cambridge, U.K.
White, I., et al. (1999). Groundwater recharge in low coral islands Bonriki, South Tarawa, Kiribati–Issues, traditions and conflicts in groundwater use and management, United Nations Educational, Scientific, and Cultural Organization, Paris.
White, I., and Falkland, T. (2010). “Management of freshwater lenses on small Pacific islands.” Hydrogeol. J., 18(1), 227–246.
Yoon, H., Jun, S. C., Hyun, Y., Bae, G. O., and Lee, K. K. (2011). “A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer.” J. Hydrol., 396, 128–138.
Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 19 • Issue 2 • February 2014
Pages: 339 - 354
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Feb 10, 2012
Accepted: Feb 25, 2013
Published online: Feb 27, 2013
Discussion open until: Jul 27, 2013
Published in print: Feb 1, 2014
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.