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<p>This study presents the first Analytic Hierarchy Process–Geographic Information System (AHP–GIS) integration based liquefaction susceptibility assessment framework for Varanasi, India. The Analytic Hierarchy Process (AHP) with multi-parametric geospatial modelling was used to evaluate earthquake-induced liquefaction risks through systematic integration of geo-datasets. Six crucial parameters, Peak Ground Acceleration (PGA), groundwater depth, surface elevation, shear wave velocity (Vs), soil type, and Standard Penetration Test (SPT-N) values were systematically analysed for subsurface depths 3&#xa0;m, 6&#xa0;m, 9&#xa0;m, and 12&#xa0;m. The developed AHP–GIS integration model identified soil type as the most influential factor (normalized weight: 0.3794) with high internal consistency (CR = 0.0109), demonstrating robust criterion weighting while elevation weighted to least. Spatial analysis categorized the study area into five liquefaction susceptibility classes from Very Low to Very High, revealing that 32.20% study area belongs to moderate susceptibility at 3&#xa0;m depth, while 7.52% area fell into the very high-risk category, indicating significant liquefaction vulnerability in shallow subsurface zones. With increasing depth, the High susceptibility zone decreases from 27.18% at 3&#xa0;m to 18.02% at 12&#xa0;m, while Very Low zones expand from 12.74 to 25.89%, reflecting increasing effective overburden stress. Non-monotonic behaviour in the Very High zone (7.52–9.07%) is attributed to localised deep alluvial pockets in the southern BHU–Susuwahi corridor. This integrated AHP–GIS methodology for liquefaction assessment would provide a scientifically robust, spatially explicit decision-support framework for urban planners and policymakers.</p>

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Liquefaction susceptibility mapping of ancient city Varanasi, India

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月26日

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  • Anurag Tiwari,
  • J. L. Gautam,
  • G. P. Singh

摘要

This study presents the first Analytic Hierarchy Process–Geographic Information System (AHP–GIS) integration based liquefaction susceptibility assessment framework for Varanasi, India. The Analytic Hierarchy Process (AHP) with multi-parametric geospatial modelling was used to evaluate earthquake-induced liquefaction risks through systematic integration of geo-datasets. Six crucial parameters, Peak Ground Acceleration (PGA), groundwater depth, surface elevation, shear wave velocity (Vs), soil type, and Standard Penetration Test (SPT-N) values were systematically analysed for subsurface depths 3 m, 6 m, 9 m, and 12 m. The developed AHP–GIS integration model identified soil type as the most influential factor (normalized weight: 0.3794) with high internal consistency (CR = 0.0109), demonstrating robust criterion weighting while elevation weighted to least. Spatial analysis categorized the study area into five liquefaction susceptibility classes from Very Low to Very High, revealing that 32.20% study area belongs to moderate susceptibility at 3 m depth, while 7.52% area fell into the very high-risk category, indicating significant liquefaction vulnerability in shallow subsurface zones. With increasing depth, the High susceptibility zone decreases from 27.18% at 3 m to 18.02% at 12 m, while Very Low zones expand from 12.74 to 25.89%, reflecting increasing effective overburden stress. Non-monotonic behaviour in the Very High zone (7.52–9.07%) is attributed to localised deep alluvial pockets in the southern BHU–Susuwahi corridor. This integrated AHP–GIS methodology for liquefaction assessment would provide a scientifically robust, spatially explicit decision-support framework for urban planners and policymakers.