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Efficient Identification of Unknown Groundwater Pollution Sources Using Linked Simulation-Optimization Incorporating Monitoring Location Impact Factor and Frequency Factor

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  • Bithin Datta
  • Om Prakash
  • Sean Campbell
  • Gerry Escalada

Abstract

This study aims to improve the accuracy of groundwater pollution source identification using concentration measurements from a heuristically designed optimal monitoring network. The designed network is constrained by the maximum number of permissible monitoring locations. The designed monitoring network improves the results of source identification by choosing monitoring locations that reduces the possibility of missing a pollution source, at the same time decreasing the degree of non uniqueness in the set of possible aquifer responses to subjected geo-chemical stresses. The proposed methodology combines the capability of Genetic Programming (GP), and linked simulation-optimization for recreating the flux history of the unknown conservative pollutant sources with limited number of spatiotemporal pollution concentration measurements. The GP models are trained using large number of simulated realizations of the pollutant plumes for varying input flux scenarios. A selected subset of GP models are used to compute the impact factor and frequency factor of pollutant source fluxes, at candidate monitoring locations, which in turn is used to find the best monitoring locations. The potential application of the developed methodology is demonstrated by evaluating its performance for an illustrative study area. These performance evaluation results show the efficiency in source identification when concentration measurements from the designed monitoring network are utilized. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:27:y:2013:i:14:p:4959-4976
    DOI: 10.1007/s11269-013-0451-8
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    References listed on IDEAS

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    1. Goffe William L., 1996. "SIMANN: A Global Optimization Algorithm using Simulated Annealing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 1(3), pages 1-9, October.
    2. Sreenivasulu Chadalavada & Bithin Datta, 2008. "Dynamic Optimal Monitoring Network Design for Transient Transport of Pollutants in Groundwater Aquifers," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(6), pages 651-670, June.
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    Cited by:

    1. 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.
    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. 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.

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