"Integrating AHP and geospatial data analysis for mapping groundwater potential in tropical coastal villages of Thiruvananthapuram, Southern India"

In response to the constraints imposed by limited surface water access, coastal communities increasingly understand the requirement to investigate and manage groundwater resources. This study an in-depth investigation of the groundwater potential zones, uncovering the interaction between these commu...

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Veröffentlicht in:Journal of coastal conservation 2025-02, Vol.29 (1), p.1, Article 1
Hauptverfasser: Pitchaimani, Stephen, J, Jerin Joe R., S, Richard Abishek, K, Aswin S, M, Seeththa Sankar Narayanan
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Sprache:eng
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Zusammenfassung:In response to the constraints imposed by limited surface water access, coastal communities increasingly understand the requirement to investigate and manage groundwater resources. This study an in-depth investigation of the groundwater potential zones, uncovering the interaction between these communities and the confined aquifers beneath the coastal soil. The integration of Remote sensing and Geographic Information System (GIS) has proved revolutionary in this quest. Leveraging remote sensing, we have analyzed the coastal landscape evaluating groundwater potential. Nine thematic maps, viz drainage density, lineament density, geology, geomorphology, land use/land cover, rainfall, slope, elevation, and NDVI, were methodically constructed. Weight for each map were allocated based on an exhaustive literature review and expert judgements. Employing the Analytical Hierarchy Process (AHP), a pairwise comparison matrix was developed, determining the final weights. Notably, drainage density scored highest, followed by geomorphology, while the slope map obtained the least ranking. AHP systematically examines the elements influencing groundwater potential, enabling prioritizing and mapping for optimal resource utilization. The weighted overlay evaluation, done in the ArcGIS environment, incorporated estimated weights, producing a full output map categorizing areas as very high, high, medium, low, and very low groundwater potential. Consistency of the weights was validated with a consistency ratio of 0.006. Subsequently, the final output map underwent validation using the Area Under the Curve (AUC) analysis, validating the excellent accuracy (0.909) of the prediction. The present research emphasizes the intricate relationship between coastal communities and groundwater reservoirs. It also showcases a rigorous methodology integrating advanced technologies and systematic decision-making to delineate and prioritize groundwater potential zones.
ISSN:1400-0350
1874-7841
DOI:10.1007/s11852-024-01084-9