Abstract
Groundwater vulnerability assessment using the fuzzy logic technique is attempted in this study. A hierarchical fuzzy inference system is created to serve the selected objective. The parameters considered in this study are similar to the seven parameters used in conventional DRASTIC methods; however, the effect of land use and land cover is studied by including it as an additional parameter in a model. A hierarchy is created by comparing two input parameters, say (D and R), and the output of the same is paired as an input with the third parameter (A) and so on using the fuzzy toolbox in MATLAB. Thus, the final output of fuzzy inference systems six and seven (FI6 and FI7) is defuzzified and mapped using ArcGIS to obtain the groundwater vulnerability zones by fuzzy DRASTIC and fuzzy DRASTIC-L. Each map is grouped into five vulnerability classes: very high, high, moderate, low, and very low. Further, the results were validated using the observed nitrate concentration from 51 groundwater sampling points. The receiver operating curve (ROC) technique is adopted to determine the best suitable model for the selected study. From this, area under the curve is estimated and found to be 0.83 for fuzzy DRASTIC and 0.90 for fuzzy DRASTIC-L; the study concludes that fuzzy DRASTIC-L has a better value of AUC suits best for assessing the groundwater vulnerability in Thoothukudi District.
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The data used in this research are available by the corresponding author upon reasonable request.
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Acknowledgements
The authors would like to thank the United States Geological Survey (USGS) for providing the SRTM DEM, which can be found on their website at https://earthexplorer.usgs.gov/. We would also like to thank the Regional Meteorological Centre of the India Meteorological Department (IMD) for providing the rainfall data supplied by website at http://imdchennai.gov.in/, the Geological Survey of India for providing data on the geology of the study area from their website at https://www.gsi.gov.in, the Central Groundwater Board (CGWB) for providing the well point data, and the National Bureau of Soil Survey for providing the soil data.
Finally, the authors would like to extend sincere thanks to the unknown reviewers for their time and valuable inputs.
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Thiyagarajan Saranya: writing—drafting the original manuscript, software, methodology, data curation, analyzing the results. Subbarayan Saravanan: conceptualization, supervision, reviewing, and editing the article.
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Saranya, T., Saravanan, S. A comparative analysis on groundwater vulnerability models—fuzzy DRASTIC and fuzzy DRASTIC-L. Environ Sci Pollut Res 29, 86005–86019 (2022). https://doi.org/10.1007/s11356-021-16195-1
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DOI: https://doi.org/10.1007/s11356-021-16195-1