GIS-Based Assessment of Groundwater Vulnerability in Bapatla District, Andhra Pradesh, India Using the SINTACS Model
Sreerama Naik S R, T K Prasad, Jayapal G
Asian Journal of Geographical Research · pp. 150–165 · Published 24 Oct 2025
10.9734/ajgr/2025/v8i4325Abstract
The necessity of groundwater in semi-arid regions like Bapatla District, Andhra Pradesh emerges from its role in supporting agricultural activities, together with industrial operations and household needs. The continuing viability of the ecosystem faces serious threats from increasing pollution linked to human activities. The evaluation of groundwater vulnerability plays a critical role in managing resources effectively while preventing pollution. This research employs the SINTACS model, which functions as a GIS overlay and index method to evaluate inherent groundwater vulnerability by analysing seven hydrogeological factors: Slope (S) Infiltration (I) Net recharge (N) Soil media (T), Aquifer media (A) Hydraulic conductivity (C) and Saturation zone depth (S). Bapatla District's intricate hydrogeological features, comprising coastal aquifers alongside deltaic plains and hard rock formations, render it susceptible to contamination from agricultural, industrial, and urban sources. The SINTACS model adjusted for specific local conditions integrates spatial data obtained from multiple sources, including the Geological Survey of India (GSI) Water Resources Information System (WRIS) and remote sensing (DEM). The evaluation assigns scores and weights to each parameter based on its influence on contaminant transport, which results in a composite vulnerability index. The groundwater vulnerability map produced for the district designates areas into low moderate, high and very high vulnerability zones, which enables specific conservation actions. This study pinpoints zones requiring immediate surveillance and protective measures to support sustainable land-use planning, together with groundwater management. Policymakers in Bapatla District can secure long-term water resources through the GIS-based SINTACS method, which provides an economically viable and scalable solution.
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