A comparative analysis on groundwater vulnerability models-fuzzy DRASTIC and fuzzy DRASTIC-L

Area of Science:

• Environmental Science
• Hydrology
• Geology

Background:

• Groundwater vulnerability assessment is crucial for sustainable water resource management.
• Conventional methods like DRASTIC may not fully capture complex influencing factors.
• Integrating advanced techniques like fuzzy logic can improve assessment accuracy.

Purpose of the Study:

• To develop and compare fuzzy logic-based groundwater vulnerability assessment models.
• To evaluate the impact of land use and land cover on groundwater vulnerability.
• To identify the most effective model for groundwater vulnerability mapping in Thoothukudi District.

Main Methods:

• A hierarchical fuzzy inference system was developed using MATLAB.
• The fuzzy DRASTIC model was adapted, incorporating land use and land cover as an additional parameter (fuzzy DRASTIC-L).
• Groundwater vulnerability maps were generated and validated using nitrate concentration data and Receiver Operating Curve (ROC) analysis.

Main Results:

• The fuzzy DRASTIC-L model achieved a higher Area Under the Curve (AUC) of 0.90 compared to fuzzy DRASTIC's 0.83.
• Groundwater vulnerability maps were delineated into five classes: very high, high, moderate, low, and very low.
• The fuzzy DRASTIC-L model demonstrated superior performance in predicting groundwater vulnerability.

Conclusions:

• The fuzzy DRASTIC-L model, incorporating land use and land cover, is a more effective tool for groundwater vulnerability assessment.
• The study highlights the importance of land use data in refining vulnerability assessments.
• The findings provide valuable insights for groundwater resource management in the study area.