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Optimal Groundwater Remediation Under Uncertainty Using Multi-objective Optimization

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  • Aristotelis Mantoglou
  • George Kourakos

Abstract

A methodology is developed for optimal remediation of groundwater aquifers under hydraulic conductivity uncertainty. A multi-objective management method based on a pump-and-treat remediation technology, is proposed. The pumping rates and well locations are the decision variables and two objectives are chosen: minimization of contaminated groundwater in the aquifer and minimization of remediation cost. A Monte Carlo simulation method is used to cope with hydraulic conductivity uncertainty. A number of equally probable realizations of hydraulic conductivity are created and a Pareto front is obtained using a modified multi-objective Genetic Algorithm. A penalty function is utilized to maintain the algebraic sum of pumping and recharging rates equal to zero. Since Monte Carlo simulations are CPU time consuming, a method is proposed to identify the few significant realizations which have an effect on the optimal solution (critical realizations). A Pareto front with an assigned probability is derived, so that the decision maker can make decisions with specified reliability. In a case study with 100 realizations, only 11 realizations were found critical and need be considered. The remaining 89 realizations consistently obtain low ranks for all designs considered and do not affect decisions at 95% reliability level. Thus these realizations need not be considered which implies a 89% savings in computer time. The designs obtained using the critical realizations, retain a similar reliability for new realizations not considered in the design process. Copyright Springer Science+Business Media, Inc. 2007

Suggested Citation

  • Aristotelis Mantoglou & George Kourakos, 2007. "Optimal Groundwater Remediation Under Uncertainty Using Multi-objective Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(5), pages 835-847, May.
    • Handle: RePEc:spr:waterr:v:21:y:2007:i:5:p:835-847
    DOI: 10.1007/s11269-006-9109-0
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    Citations

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    Cited by:

    1. Hossein Rezaei & Omid Bozorg-Haddad & Hugo A. Loáiciga, 2020. "Reliability-Based Multi-Objective Optimization of Groundwater Remediation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(10), pages 3079-3097, August.
    2. Xiaoyi Liu & Jonghyun Lee & Peter Kitanidis & Jack Parker & Ungtae Kim, 2012. "Value of Information as a Context-Specific Measure of Uncertainty in Groundwater Remediation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(6), pages 1513-1535, April.
    3. Claudio Alimonti & Mara Lombardi & Monica Cardarilli & Elena Soldo, 2017. "Reliability Analysis Applied on Land Subsidence Effects of Groundwater Remediation: Probabilistic vs. Deterministic Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(6), pages 1745-1758, April.
    4. L. Raso & S. V. Weijs & M. Werner, 2018. "Balancing Costs and Benefits in Selecting New Information: Efficient Monitoring Using Deterministic Hydro-economic Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(1), pages 339-357, January.
    5. Bungon Kumphon, 2013. "Genetic Algorithms for Multi-objective Optimization: Application to a Multi-reservoir System in the Chi River Basin, Thailand," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(12), pages 4369-4378, September.
    6. Claudio Alimonti & Mara Lombardi, 2015. "Reliability Analysis for Preliminary Forecasts of Hydrogeological Unit Productivity," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3771-3785, August.
    7. Domenico Baú, 2012. "Planning of Groundwater Supply Systems Subject to Uncertainty Using Stochastic Flow Reduced Models and Multi-Objective Evolutionary Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(9), pages 2513-2536, July.
    8. P. Sidiropoulos & N. Mylopoulos & A. Loukas, 2015. "Stochastic Simulation and Management of an Over-Exploited Aquifer Using an Integrated Modeling System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(3), pages 929-943, February.
    9. Zeinab Takbiri & Abbas Afshar, 2012. "Multi-Objective Optimization of Fusegates System under Hydrologic Uncertainties," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(8), pages 2323-2345, June.
    10. Gift Dumedah, 2012. "Formulation of the Evolutionary-Based Data Assimilation, and its Implementation in Hydrological Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(13), pages 3853-3870, October.
    11. Li He & Feng Shao & Lixia Ren, 2021. "Sustainability appraisal of desired contaminated groundwater remediation strategies: an information-entropy-based stochastic multi-criteria preference model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(2), pages 1759-1779, February.

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