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A Multiobjective Optimisation Model for Groundwater Remediation Design at Petroleum Contaminated Sites

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  • Q. Yang
  • L. He
  • H. Lu

Abstract

This study proposes a fuzzy multi-objective model for groundwater remediation in petroleum-contaminated aquifers. The optimisation system is designed based on the PAT technology, and includes two objectives (i.e. total pumping rate and average post-remedial contaminant concentration). The relationship between pumping rates and contamination concentrations at all monitoring wells after remediation are determined by a proxy model, which integrates simulation, inference, and optimisation technologies and is composed of intercept, linear, interactive, and quadratic options. Fuzzy algorithms are used to solve the formulated multi-objective optimisation problem to find optimal solutions. The model is then applied to a petroleum-contaminated aquifer in western Canada. The trade-off and λ analyses of the results indicate that the fuzzy multi-objective model has great potential in groundwater remediation applications as it can: (1) provide reliable groundwater remediation strategies, (2) reduce computational costs in the optimization processes, and (3) balance the trade-off between remediation costs and remediation outcomes. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Q. Yang & L. He & H. Lu, 2013. "A Multiobjective Optimisation Model for Groundwater Remediation Design at Petroleum Contaminated Sites," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2411-2427, May.
    • Handle: RePEc:spr:waterr:v:27:y:2013:i:7:p:2411-2427
    DOI: 10.1007/s11269-013-0294-3
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    References listed on IDEAS

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    1. Ali Haghighi & Hossein Samani & Zeinab Samani, 2011. "GA-ILP Method for Optimization of Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(7), pages 1791-1808, May.
    2. S. Moharram & M. Gad & T. Saafan & S. Allah, 2012. "Optimal Groundwater Management Using Genetic Algorithm in El-Farafra Oasis, Western Desert, Egypt," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(4), pages 927-948, March.
    3. Prakash Kaini & Kim Artita & John Nicklow, 2012. "Optimizing Structural Best Management Practices Using SWAT and Genetic Algorithm to Improve Water Quality Goals," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(7), pages 1827-1845, May.
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    Cited by:

    1. Sina Sadeghfam & Yousef Hassanzadeh & Rahman Khatibi & Ata Allah Nadiri & Marjan Moazamnia, 2019. "Groundwater Remediation through Pump-Treat-Inject Technology Using Optimum Control by Artificial Intelligence (OCAI)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(3), pages 1123-1145, February.

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