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Evaluation of remote sensing techniques-based water quality monitoring for sustainable hydrological applications: an integrated FWZIC-VIKOR modelling approach

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Abstract

Evaluating remote sensing techniques (RST)-based water quality monitoring systems in hydrological applications is a complex multi-attribute decision-making (MADM) problem due to several integrated issues. These issues include the need to consider 15 evaluation criteria, the importance of these criteria in relation to their application and network infrastructure, data variation, and trade-offs and conflicts between them. Therefore, this study proposes an MADM integrated modelling approach to weight these criteria and rank the selected RSTs using the “Fuzzy Weighted with Zero Inconsistency” (FWZIC) method coupled with the “Vlse-kriterijumska Optimizcija I Kaompromisno Resenje” (VIKOR) method. First, a decision matrix was developed for the evaluation criteria and their intersection with various RSTs in different network categories. Next, the assessment criteria were weighted using FWZIC, followed by ranking the RSTs for each category using VIKOR. The findings reveal that the criteria weighting varied across categories, as assigned by specialists-based FWZIC. For example, the “data acquisition system complexity” criterion received the maximum weight (w = 0.081) for mesh-based sensing and the lowest (w = 0.057) for cellular-based sensing. Using the obtained weights and based on the ascending order of the performance score value (Q), various RSTs were benchmarked using VIKOR. This includes (n = 22) RSTs in fixed star, (n = 8) RSTs in mesh sensing, (n = 6) RSTs in cellular sensing, (n = 3) RSTs in fixed cable sensing, and (n = 2) RSTs in movable sensing. Finally, the evaluation process for the benchmarked RSTs involved systematic ranking, sensitivity analysis, and comparison analysis, which confirmed the robustness of the proposed approach across all RST categories.

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Authors and Affiliations

  1. Department of Computing and META Technology (FKMT), Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia

    A. H. Alamoodi

  2. Department of Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia (UTHM), 86400, Parit Raja, Malaysia

    Mohammed Talal

  3. Department of Operations Research and Statistics, Faculty of Organizational Sciences, University of Belgrade, Belgrade, Serbia

    Dragan Pamucar

  4. College of Engineering, Yuan Ze University, Taoyuan City, Taiwan

    Dragan Pamucar

  5. Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC, Australia

    O. S. Albahri

  6. Computer Techniques Engineering Department, Mazaya University College, Thi-Qar, Nassiriya, Iraq

    O. S. Albahri

  7. Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq

    A. S. Albahri

Authors
  1. Mohammed Talal
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  2. A. H. Alamoodi
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  3. O. S. Albahri
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  4. A. S. Albahri
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  5. Dragan Pamucar
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Correspondence to Dragan Pamucar.

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Appendix

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See Tables

Table 21 Experts assessment
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21,

Table 22 Experts assessment fuzzy numbers
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22, and

Table 23 Experts assessment ratio
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23.

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Talal, M., Alamoodi, A.H., Albahri, O.S. et al. Evaluation of remote sensing techniques-based water quality monitoring for sustainable hydrological applications: an integrated FWZIC-VIKOR modelling approach. Environ Dev Sustain (2023). https://doi.org/10.1007/s10668-023-03432-5

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