IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v30y2016i14d10.1007_s11269-016-1476-6.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-016-1476-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11269-016-1476-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tiku T. Tanyimboh, 2017. "Informational Entropy: a Failure Tolerance and Reliability Surrogate for Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3189-3204, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. L. Guneshwor & T. I. Eldho & A. Vinod Kumar, 2018. "Identification of Groundwater Contamination Sources Using Meshfree RPCM Simulation and Particle Swarm Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(4), pages 1517-1538, March.
    2. 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.
    3. Partha Majumder & T. I. Eldho, 2016. "A New Groundwater Management Model by Coupling Analytic Element Method and Reverse Particle Tracking with Cat Swarm Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(6), pages 1953-1972, April.
    4. Bithin Datta & Dibakar Chakrabarty & Anirban Dhar, 2009. "Optimal Dynamic Monitoring Network Design and Identification of Unknown Groundwater Pollution Sources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(10), pages 2031-2049, August.
    5. Divya Srivastava & Raj Singh, 2015. "Groundwater System Modeling for Simultaneous Identification of Pollution Sources and Parameters with Uncertainty Characterization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(13), pages 4607-4627, October.
    6. Madan K. Jha & Richard C. Peralta & Sasmita Sahoo, 2020. "Simulation-Optimization for Conjunctive Water Resources Management and Optimal Crop Planning in Kushabhadra-Bhargavi River Delta of Eastern India," IJERPH, MDPI, vol. 17(10), pages 1-20, May.
    7. Paresh Shirsath & Anil Singh, 2010. "A Comparative Study of Daily Pan Evaporation Estimation Using ANN, Regression and Climate Based Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(8), pages 1571-1581, June.
    8. 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.
    9. Ioannis Trichakis & Ioannis Nikolos & G. Karatzas, 2011. "Artificial Neural Network (ANN) Based Modeling for Karstic Groundwater Level Simulation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(4), pages 1143-1152, March.
    10. Fateme Heydari & Bahram Saghafian & Majid Delavar, 2016. "Coupled Quantity-Quality Simulation-Optimization Model for Conjunctive Surface-Groundwater Use," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4381-4397, September.
    11. Om Prakash Vats & Bhrigumani Sharma & Juergen Stamm & Rajib Kumar Bhattacharjya, 2020. "Groundwater Circulation Well for Controlling Saltwater Intrusion in Coastal aquifers: Numerical study with Experimental Validation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(11), pages 3551-3563, September.
    12. Seyed Naghibi & Hamid Pourghasemi, 2015. "A Comparative Assessment Between Three Machine Learning Models and Their Performance Comparison by Bivariate and Multivariate Statistical Methods in Groundwater Potential Mapping," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5217-5236, November.
    13. Zekri, S., 2018. "Optimizing aquifer recharge and recovery using seasonal surplus desalinated water," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 276946, International Association of Agricultural Economists.
    14. Hamid Kardan Moghaddam & Saman Javadi & Timothy O. Randhir & Neda Kavehkar, 2022. "A Multi-Indicator, Non-Cooperative Game Model to Resolve Conflicts for Aquifer Restoration," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5521-5543, November.
    15. Gokmen Tayfur, 2017. "Modern Optimization Methods in Water Resources Planning, Engineering and Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3205-3233, August.
    16. Yu, Xiayang & Sreekanth, J. & Cui, Tao & Pickett, Trevor & Xin, Pei, 2021. "Adaptative DNN emulator-enabled multi-objective optimization to manage aquifer−sea flux interactions in a regional coastal aquifer," Agricultural Water Management, Elsevier, vol. 245(C).
    17. Youssef, Ayman & El-Telbany, Mohammed & Zekry, Abdelhalim, 2017. "The role of artificial intelligence in photo-voltaic systems design and control: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 72-79.
    18. Kusum Pandey & Shiv Kumar & Anurag Malik & Alban Kuriqi, 2020. "Artificial Neural Network Optimized with a Genetic Algorithm for Seasonal Groundwater Table Depth Prediction in Uttar Pradesh, India," Sustainability, MDPI, vol. 12(21), pages 1-24, October.
    19. Mojtaba Shourian & S. M. Javad Davoudi, 2017. "Optimum Pumping Well Placement and Capacity Design for a Groundwater Lowering System in Urban Areas with the Minimum Cost Objective," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(13), pages 4207-4225, October.
    20. Chefi Triki & Slim Zekri & Ali Al-Maktoumi & Mahsa Fallahnia, 2017. "An Artificial Intelligence Approach for the Stochastic Management of Coastal Aquifers," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(15), pages 4925-4939, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:30:y:2016:i:14:d:10.1007_s11269-016-1476-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.