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Implementation and evaluation of different techniques to modify DRASTIC method for groundwater vulnerability assessment: a case study from Bouficha aquifer, Tunisia

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Abstract

Groundwater vulnerability assessment has nowadays evolved into an essential tool towards proper groundwater protection and management, while the DRASTIC method is included among the most widely applied vulnerability assessment methods. However, the high uncertainty of the DRASTIC method mainly associated with the subjectivity in assigning parameters ratings and weights has driven many researchers to apply various methods for improving its efficiency. In this context, in the present study, different techniques were implemented with the aim of modifying the DRASTIC framework and thus enhancing its performance for groundwater vulnerability assessment in the Bouficha aquifer, Tunisia. In a first stage, the land use type (L) was incorporated as an additional parameter in the typical DRASTIC framework, thus taking into consideration the impact of anthropogenic activities on groundwater vulnerability. Subsequently, the rating and weighting systems of the developed DRASTIC-L framework were modified through the application of statistical methods (DRASTIC-L-SA) and genetic algorithms (GA) (DRASTIC-L-GA) in an attempt to investigate and compare both linear and nonlinear modifications. To evaluate the various vulnerability frameworks, correlation between vulnerability values and nitrate concentrations, expressed as Spearman’s rank correlation coefficient (ρ) and Correlation Index (CI), was examined. The results revealed that the DRASTIC-L-GA framework developed by applying a fully GA-based optimization procedure provided the highest values in terms of the performance metrics used, making it the most suitable for the study area. In addition, the aquifer under study was found to be less vulnerable to pollution when employing the typical DRASTIC framework instead of the modified ones, leading to the conclusion that the former substantially underestimates pollution potential in the study area.

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Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Funding

This research was conducted in the context of MEDSAL Project (www.medsal.eu), which is part of PRIMA Programme supported by the European Union’s Horizon 2020 Research and Innovation Programme and funded by the national funding agency of MHESR (grant number 2018-12). Moreover, partial funding for this research was provided through the Operational Programme “Coastal Environment Observatory and Risk Management (AEGIS +)” in the context of the project “Coastal Environment Observatory and Crisis Management in Island Regions (AEGIS +)” (MIS-5033021), implemented by the Special Account for Research Funds of the University of the Aegean. The junior researcher Madiha Arfaoui conducted some of this research while on an Erasmus+ traineeship at the University of the Aegean.

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Authors and Affiliations

  1. Department of Marine Sciences, University of the Aegean, 81100, Mytilene, Greece

    Ilias Siarkos & Ourania Tzoraki

  2. Faculty of Sciences of Tunis, Laboratory of Sedimentary Basins and Petroleum Geology (SBPG), LR18 ES07, 2092, Tunis, Tunisia

    Madiha Arfaoui, Mounira Zammouri & Fadoua Hamzaoui-Azaza

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  1. Ilias Siarkos
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  2. Madiha Arfaoui
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  3. Ourania Tzoraki
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  4. Mounira Zammouri
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  5. Fadoua Hamzaoui-Azaza
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Contributions

Ilias Siarkos was responsible for lead, conceptualization, methodology, software, formal analysis, visualization and writing - original draft. Madiha Arfaoui was responsible for methodology, investigation, visualization and writing - original draft. Ourania Tzoraki was responsible for methodology, supervision and writing - review & editing. Mounira Zammouri and Fadoua Hamzaoui-Azaza were responsible for supervision and writing - review & editing.

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Highlights

• DRASTIC framework was modified through various techniques to improve its performance.

• Land use factor (L) was incorporated as an additional parameter (DRASTIC-L).

• Ratings and weights of the developed DRASTIC-L framework were optimized.

• Statistical analysis and genetic algorithms were used for optimization.

• Nonlinear optimization through genetic algorithms provided the best results.

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Siarkos, I., Arfaoui, M., Tzoraki, O. et al. Implementation and evaluation of different techniques to modify DRASTIC method for groundwater vulnerability assessment: a case study from Bouficha aquifer, Tunisia. Environ Sci Pollut Res 30, 89459–89478 (2023). https://doi.org/10.1007/s11356-023-28625-3

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