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Development of an Improved Pollution Source Identification Model Using Numerical and ANN Based Simulation-Optimization Model

Author

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  • Triptimoni Borah

    (Department of Civil Eng., Assam Engineering College)

  • Rajib Kumar Bhattacharjya

    (Indian Institute of Technology Guwahati)

Abstract

The identification of unknown pollution sources is an important and challenging task for the engineers working on pollution management of a groundwater aquifer. The locations and transient magnitude of unknown contaminant sources can be identified using inverse optimization technique. In this approach, the absolute difference between the simulated and the observed contaminant concentration at the observation locations of the aquifer is minimized by using an optimization algorithm. The simulated concentrations is calculated using the aquifer simulation model. As such, there is a need to incorporate the aquifer simulation model with the optimization model. Thus the performance of the model is highly related to the aquifer simulation model. The incorporation of the sophisticated numerical simulation model will give better performance, but the model will be computationally expensive. On the other hand, the model will be computationally less expensive if an approximate simulation model is used in place of the numerical simulation model. However, in this case, the predictive performance of the model will decline. For achieving efficiency in both computational time as well as in predicting the performance, this study presents a new genetic algorithms based simulation-optimization method incorporating both the numerical and the approximate simulation models. The efficiency and field applicability of the model is demonstrated using illustrative study areas. The performance evaluation of the model shows that the proposed model has the potential for real-world field applications.

Suggested Citation

  • Triptimoni Borah & Rajib Kumar Bhattacharjya, 2016. "Development of an Improved Pollution Source Identification Model Using Numerical and ANN Based Simulation-Optimization Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5163-5176, November.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:14:d:10.1007_s11269-016-1476-6
    DOI: 10.1007/s11269-016-1476-6
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    References listed on IDEAS

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    1. Ching-Wen Chen & Chih-Chiang Wei & Hung-Jen Liu & Nien-Sheng Hsu, 2014. "Application of Neural Networks and Optimization Model in Conjunctive Use of Surface Water and Groundwater," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 2813-2832, August.
    2. Rajib Bhattacharjya & Bithin Datta, 2005. "Optimal Management of Coastal Aquifers Using Linked Simulation Optimization Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 19(3), pages 295-320, June.
    3. Manish Jha & Bithin Datta, 2014. "Linked Simulation-Optimization based Dedicated Monitoring Network Design for Unknown Pollutant Source Identification using Dynamic Time Warping Distance," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 4161-4182, September.
    4. Bithin Datta & Om Prakash & Sean Campbell & Gerry Escalada, 2013. "Efficient Identification of Unknown Groundwater Pollution Sources Using Linked Simulation-Optimization Incorporating Monitoring Location Impact Factor and Frequency Factor," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(14), pages 4959-4976, November.
    5. Raj Singh & Bithin Datta, 2007. "Artificial neural network modeling for identification of unknown pollution sources in groundwater with partially missing concentration observation data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(3), pages 557-572, March.
    6. Shishir Gaur & Sudheer Ch & Didier Graillot & B. Chahar & D. Kumar, 2013. "Application of Artificial Neural Networks and Particle Swarm Optimization for the Management of Groundwater Resources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(3), pages 927-941, February.
    7. Pooran Mahar & Bithin Datta, 2000. "Identification of Pollution Sources in Transient Groundwater Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 14(3), pages 209-227, June.
    8. Slim Zekri & Chefi Triki & Ali Al-Maktoumi & Mohammad Bazargan-Lari, 2015. "An Optimization-Simulation Approach for Groundwater Abstraction under Recharge Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3681-3695, August.
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