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<p>This study describes groundwater potential zones (GWPZs) and identifies suitable artificial recharge sites within the Rushikulya River Basin, Odisha, India, integrating geospatial technology and a multi-criteria decision-making (MCDM) framework. Analytic Hierarchy process (AHP) and fuzzy-AHP were employed to integrate ten hydrogeologically significant parameters, viz., drainage density, geomorphology, geology, lineament density, land use/land cover, precipitation, proximity to rivers, slope, soil, and topographic wetness index. The fuzzy membership was established to alleviate epistemic ambiguity and linguistic vagueness inherent in hydro-environmental systems. Delineated GWPZs were classified as high (4.47%), moderate (93.17%), and low (2.36%). Model performance was validated using 128 well locations. Additionally, 89 potential artificial recharge sites were identified and ranked based on recharge suitability. To overcome hydro-centric approaches, a novel socially sensitive hydrogeologically suitable recharge zones (SSHSRZ) was established to enhance the hydrogeological accuracy of the Fuzzy-AHP model with socio-economic (population density, poverty index, and irrigation intensity) dimensions into the decision architecture. The proposed hydro–socio–economic framework, coupled with geospatial modelling, serves as a decision-support tool for prioritising groundwater recharge interventions and promoting equitable groundwater management in semi-arid hard-rock regions by providing a scalable, adaptable, and resilience-focused approach to sustainable aquifer stewardship worldwide.</p>

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A GIS-based fuzzy-AHP framework for delineating hydrogeologically and socially sensitive recharge zones in Southern Odisha, India

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月9日

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  • Suvendu Dash,
  • Swayam Siddha

摘要

This study describes groundwater potential zones (GWPZs) and identifies suitable artificial recharge sites within the Rushikulya River Basin, Odisha, India, integrating geospatial technology and a multi-criteria decision-making (MCDM) framework. Analytic Hierarchy process (AHP) and fuzzy-AHP were employed to integrate ten hydrogeologically significant parameters, viz., drainage density, geomorphology, geology, lineament density, land use/land cover, precipitation, proximity to rivers, slope, soil, and topographic wetness index. The fuzzy membership was established to alleviate epistemic ambiguity and linguistic vagueness inherent in hydro-environmental systems. Delineated GWPZs were classified as high (4.47%), moderate (93.17%), and low (2.36%). Model performance was validated using 128 well locations. Additionally, 89 potential artificial recharge sites were identified and ranked based on recharge suitability. To overcome hydro-centric approaches, a novel socially sensitive hydrogeologically suitable recharge zones (SSHSRZ) was established to enhance the hydrogeological accuracy of the Fuzzy-AHP model with socio-economic (population density, poverty index, and irrigation intensity) dimensions into the decision architecture. The proposed hydro–socio–economic framework, coupled with geospatial modelling, serves as a decision-support tool for prioritising groundwater recharge interventions and promoting equitable groundwater management in semi-arid hard-rock regions by providing a scalable, adaptable, and resilience-focused approach to sustainable aquifer stewardship worldwide.