Objectives: To assess the spatial distribution of groundwater quality in the Kuzhithuraiyar Sub-Basin of Kanyakumari District, evaluate the extent of seawater intrusion and its impact on groundwater characteristics, examine the influence of urbanization and tourism on water quality deterioration, identify groundwater quality zones using suitable analytical and GIS techniques, and propose effective management strategies for sustainable utilization and continuous monitoring of groundwater resources in the region. Method: The study evaluates groundwater quality using key physico-chemical parameters, including Total Dissolved Solids (TDS), Turbidity, pH, Electrical Conductivity (EC), Alkalinity, Magnesium (Mg), Calcium (Ca), Total Hardness (TH), Chloride (Cl⁻), Sodium (Na), Potassium (K), Sulphate (SO₄²⁻), Fluoride (F⁻), and Nitrate (NO₃⁻) for the pre monsoon of 2023. Spatial analysis was carried out using Geographic Information System (GIS) techniques. The collected attribute data were integrated into the GIS environment using ArcGIS 9.1. The Inverse Distance Weighting (IDW) interpolation method was applied to generate spatial distribution maps for each parameter. These maps were then compared with standard permissible limits to assess groundwater quality variations across the Kuzhithuraiyar Sub-Basin. Findings: The study revealed significant spatial variability in groundwater quality across the study area, with severe deterioration observed in locations such as Paloor, Malavilai, Kannanoor, and Athencode. Total Dissolved Solids (566–2234 mg/L) and Total Hardness (107.396–965.034 mg/L) exceeded desirable limits in most sampling locations, indicating widespread mineralization and poor water quality. Elevated chloride concentrations (up to 671.96 mg/L) and electrical conductivity values (up to 1896.32 µS/cm) suggest the influence of seawater intrusion in coastal zones. Nitrate levels reached 70 mg/L in several samples, surpassing the permissible limit and indicating contamination from anthropogenic activities. The spatial distribution maps clearly delineated contamination hotspots, emphasizing the uneven distribution of groundwater quality and the urgent need for targeted management and remediation strategies in critically affected regions. Novelty: This study demonstrates the effective integration of GIS and IDW interpolation techniques for groundwater quality assessment in coastal regions. The generation of spatial distribution maps for multiple water quality parameters offers a comprehensive understanding of contamination patterns. The approach provides a scientific basis for identifying critical zones and supports decision-making in groundwater management. Keywords: Spatial Distribution, Groundwater Quality, Physico-Chemical Parameters, GIS, Inverse Distance Weighting (IDW)
Raj et al. (Thu,) studied this question.