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Artificial neural network modeling for identification of unknown pollution sources in groundwater with partially missing concentration observation data

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  • Raj Singh
  • Bithin Datta

Abstract

Groundwater pollution sources are characterized by spatially and temporally varying source locations, injection rates, and duration of activity. Concentration measurement data at specified observation locations are generally utilized to identify these sources characteristics. Identification of unknown groundwater pollution sources in terms of these source characteristics becomes more difficult in the absence of complete breakthrough curves of concentration history at all the time steps. If concentration observations are missing over a length of time after an unknown source has become active, it is even more difficult to correctly identify the unknown sources. An artificial neural network (ANN) based methodology is developed to identify these source characteristics for such a missing data scenario, when concentration measurement data over an initial length of time is not available. The source characteristics and the corresponding concentration measurements at time steps for which it is not missing, constitute a pattern for training the ANN. A groundwater flow and transport numerical simulation model is utilized to generate the necessary patterns for training the ANN. Performance evaluation results show that the back-propagation based ANN model is essentially capable of extracting hidden relationship between patterns of available concentration measurement values, and the corresponding sources characteristics, resulting in identification of unknown groundwater pollution sources. The performance of the methodology is also evaluated for different levels of noise (or measurement errors) in concentration measurement data at available time steps. Copyright Springer Science+Business Media, Inc. 2007

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:21:y:2007:i:3:p:557-572
    DOI: 10.1007/s11269-006-9029-z
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. 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.
    2. 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.
    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 & 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. 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.
    6. Dan Yin & Longcang Shu & Xunhong Chen & Zhenlong Wang & Mokhatar Mohammed, 2011. "Assessment of Sustainable Yield of Karst Water in Huaibei, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(1), pages 287-300, January.
    7. 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.

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