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Groundwater vulnerability mapping using the modified DRASTIC model: the metaheuristic algorithm approach.

Balaji L1, Saravanan R2, Saravanan K2

  • 1Centre for Water Resources, Anna University, Chennai, 600025, India. balajicwr@annauniv.edu.in.

Environmental Monitoring and Assessment
|January 3, 2021
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Summary

Optimizing the DRASTIC model using metaheuristic algorithms significantly improved groundwater vulnerability mapping accuracy. The firefly algorithm (FA) outperformed others, enhancing the correlation between groundwater vulnerability index and nitrate concentration.

Keywords:
DRASTIC modelGroundwater vulnerabilityMetaheuristic algorithmTOPSISWilcoxon test

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Area of Science:

  • Environmental Science
  • Hydrogeology
  • Computational Intelligence

Background:

  • Groundwater vulnerability assessment is crucial for sustainable resource management.
  • The DRASTIC model is widely used but often shows poor correlation with actual contaminant levels.
  • Optimizing DRASTIC's parameters can enhance its predictive accuracy.

Purpose of the Study:

  • To improve the accuracy of the DRASTIC model for groundwater vulnerability mapping.
  • To compare the performance of five metaheuristic algorithms for optimizing DRASTIC parameters.
  • To identify the best-performing algorithm for weight optimization using a ranking methodology.

Main Methods:

  • Applied the Wilcoxon test and five metaheuristic algorithms (FA, IWO, TLBO, SFLA, PSO) to optimize DRASTIC model rates and weights.
  • Utilized the TOPSIS method to rank algorithms based on computational speed and iteration count.
  • Evaluated the improvement in correlation between the groundwater vulnerability index and nitrate concentration.

Main Results:

  • All metaheuristic algorithms converged to optimal solutions, with varying efficiencies.
  • The firefly algorithm (FA) was identified as the top-performing algorithm through the TOPSIS ranking.
  • The optimized Wilcoxon-MH-DRASTIC model showed a substantial increase in the correlation coefficient (0.7247) compared to the original DRASTIC model (0.0545).

Conclusions:

  • Metaheuristic optimization significantly enhances groundwater vulnerability assessment accuracy.
  • The proposed ranking approach is effective for selecting optimal algorithms in DRASTIC weight optimization.
  • This methodology offers a robust framework for improving the sustainable management of groundwater resources.