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Optimum Design of a Seawater Intrusion Monitoring Scheme Based on the Image Quality Assessment Method

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  • Yue Fan

    (Key Laboratory of Groundwater Resources and Environment (Jilin University), Ministry of Education
    Jilin University
    Jilin University)

  • Wenxi Lu

    (Key Laboratory of Groundwater Resources and Environment (Jilin University), Ministry of Education
    Jilin University
    Jilin University)

  • Tiansheng Miao

    (Key Laboratory of Groundwater Resources and Environment (Jilin University), Ministry of Education
    Jilin University
    Jilin University)

  • Jiuhui Li

    (Key Laboratory of Groundwater Resources and Environment (Jilin University), Ministry of Education
    Jilin University
    Jilin University)

  • Jin Lin

    (Nanjing Hydraulic Research Institute)

Abstract

Seawater intrusion monitoring is quite different from the conventional monitoring of groundwater pollution. In this study, a new optimization method for the seawater intrusion monitoring scheme in the transitional zone was proposed. The objective of optimization was to maximize effective information monitored. The structural similarity index method (SSIM) of the image quality assessment was innovatively used to establish a mathematical expression for the effective monitored information, and an optimization model was constructed based on this. Taken the Longkou city of China as the study area, a numerical simulation model of variable density groundwater was constructed. The Monte Carlo method was used to consider the influence of the sensitivity parameters uncertainty on the monitoring scheme design. To avoid repeatedly calling of simulation models in the process of Monte Carlo experiments, a surrogate model was constructed by using the kernel extreme learning machine (KELM). Finally, the optimization model was solved by the genetic algorithm to obtain the optimal monitoring scheme. The results showed that the input-output relationship of the numerical simulation model for variable-density groundwater can be well approximated by the KELM surrogate model. The monitoring scheme optimized by the above method can well reflect the real state of seawater intrusion. This study expands the method on the scheme designs for seawater intrusion monitoring.

Suggested Citation

  • Yue Fan & Wenxi Lu & Tiansheng Miao & Jiuhui Li & Jin Lin, 2020. "Optimum Design of a Seawater Intrusion Monitoring Scheme Based on the Image Quality Assessment Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(8), pages 2485-2502, June.
    • Handle: RePEc:spr:waterr:v:34:y:2020:i:8:d:10.1007_s11269-020-02565-w
    DOI: 10.1007/s11269-020-02565-w
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. Zheng Han & Wenxi Lu & Yue Fan & Jianan Xu & Jin Lin, 2021. "Surrogate-Based Stochastic Multiobjective Optimization for Coastal Aquifer Management under Parameter Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(5), pages 1479-1497, March.
    2. Fatemeh Faal & Hamid Reza Ghafouri & Seyed Mohammad Ashrafi, 2022. "Monitoring and Predicting Saltwater Intrusion via Temporal Aquifer Vulnerability Maps and Surrogate Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(3), pages 785-801, February.

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