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Process Mining Approach of a New Water Quality Index for Long-Term Assessment under Uncertainty Using Consensus-Based Fuzzy Decision Support System

Author

Listed:
  • Mohammad Ali Baghapour

    (Shiraz University of Medical Sciences)

  • Mohammad Reza Shooshtarian

    (Larestan University of Medical Sciences
    Larestan University of Medical Sciences)

  • Mahdi Zarghami

    (University of Tabriz
    University of Tabriz)

Abstract

One of the biggest challenges in water quality monitoring is how to optimize big Data gathered from a wide range of resources. This paper presented a new software-based pathway of process mining approach for extending a flexible WQI (Water Quality Index) that would deal with uncertainties derived from missing data occurrence in short- and long-term assessments. The methodology is based on integration of four multi-criteria group decision-making models coupled with fuzzy simulation including AHP (Analytical Hierarchy Process), fuzzy OWA (Ordered Weighting Average), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and fuzzy TOPSIS that were used for data mining and group consensus evaluation.. Examining the methodology on groundwater resources being supplied for drinking in Shiraz, Iran showed high integrity, accuracy, and proximity-to-real interpretation of water quality. This was the first study where decision-making risks such as Decision Makers’ risk-prone or risk-aversion attitudes (optimistic degree), DMs’ power, and consensus degree of each water quality parameter have been considered in WQI research. The proposed index offered a flexible choice in defining the intended project duration, stakeholders’ judgments, types of water use and water resource, standards, as well as type and number of water quality parameters. Thus, beside sustaining the unity in structure, this methodology could be suggested as a potentially WQI for other regions. The presented methodology would help more efficient monitoring of water resources for drinking purpose with respect to water quality.

Suggested Citation

  • Mohammad Ali Baghapour & Mohammad Reza Shooshtarian & Mahdi Zarghami, 2020. "Process Mining Approach of a New Water Quality Index for Long-Term Assessment under Uncertainty Using Consensus-Based Fuzzy Decision Support System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(3), pages 1155-1172, February.
    • Handle: RePEc:spr:waterr:v:34:y:2020:i:3:d:10.1007_s11269-020-02489-5
    DOI: 10.1007/s11269-020-02489-5
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    References listed on IDEAS

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    1. Ivana I. Mladenović-Ranisavljević & Lj. Takić & Đ. Nikolić, 2018. "Water Quality Assessment Based on Combined Multi-Criteria Decision-Making Method with Index Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(7), pages 2261-2276, May.
    2. Margaret W. Gitau & Jingqiu Chen & Zhao Ma, 2016. "Water Quality Indices as Tools for Decision Making and Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(8), pages 2591-2610, June.
    3. Tapas K. Biswas & Luke M. Mosley, 2019. "From Mountain Ranges to Sweeping Plains, in Droughts and Flooding Rains; River Murray Water Quality over the Last Four Decades," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(3), pages 1087-1101, February.
    4. Andre Lermontov & Lidia Yokoyama & Mihail Lermontov & Maria Augusta Soares Machado, 2011. "A Fuzzy Water Quality Index for Watershed Quality Analysis and Management," Chapters, in: Elzbieta Broniewicz (ed.), Environmental Management in Practice, IntechOpen.
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    Cited by:

    1. S. Vijay & K. Kamaraj, 2021. "Prediction of Water Quality Index in Drinking Water Distribution System Using Activation Functions Based Ann," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(2), pages 535-553, January.
    2. Georgios K. Koulinas & Alexandros S. Xanthopoulos & Konstantinos A. Sidas & Dimitrios E. Koulouriotis, 2021. "Risks Ranking in a Desalination Plant Construction Project with a Hybrid AHP, Risk Matrix, and Simulation-Based Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(10), pages 3221-3233, August.
    3. Zoran Štirbanović & Vojka Gardić & Dragiša Stanujkić & Radmila Marković & Jovica Sokolović & Zoran Stevanović, 2021. "Comparative MCDM Analysis for AMD Treatment Method Selection," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(11), pages 3737-3753, September.
    4. Yongxiang Zhang & Ruitao Jia & Jin Wu & Huaqing Wang & Zhuoran Luo, 2021. "Evaluation of Groundwater Using an Integrated Approach of Entropy Weight and Stochastic Simulation: A Case Study in East Region of Beijing," IJERPH, MDPI, vol. 18(14), pages 1-18, July.
    5. Yalcin, Ahmet Selcuk & Kilic, Huseyin Selcuk & Delen, Dursun, 2022. "The use of multi-criteria decision-making methods in business analytics: A comprehensive literature review," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    6. Mojtaba Kadkhodazadeh & Saeed Farzin, 2021. "A Novel LSSVM Model Integrated with GBO Algorithm to Assessment of Water Quality Parameters," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(12), pages 3939-3968, September.

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