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<p>Groundwater vulnerability assessment is vital for sustainable management, especially in regions with intensive agricultural and urban activities. This study evaluated groundwater susceptibility in the Pench River Basin using DRASTIC, DRASTIC-AHP, and modified DRASTIC-AHP models. Seven key hydrogeological parameters, net recharge, aquifer yield, depth to water table, soil media, slope, hydraulic conductivity, and vadose zone depth, were integrated, along with Land Use and Land Cover (LULC) in the modified model. This approach represents a novel integration of LULC and AHP within the DRASTIC framework, validated with field-based fluoride data to enhance model reliability. Vulnerability indices ranged from 43 to 182, categorizing the area into five classes: very low (17.78%), low (21.67%), moderate (24.24%), high (19.31%), and very high (17%). Central and southern regions exhibited high vulnerability due to shallow water tables (&lt; 3.56 mbgl) and high recharge rates ranged from 50 to 250&#xa0;mm/year, over 38% of the area. Urban (38%) and agricultural zones (29%) were identified as high-risk areas, while vegetation (23%) and barren land (10%) showed reduced vulnerability. Validation with 84 groundwater samples revealed fluoride concentrations (&gt; 0.63&#xa0;mg/L) moderately correlated (<i>R</i>²=0.45) with vulnerability, demonstrating the modified DRASTIC-AHP model’s superior accuracy and applicability. Findings indicate excessive fertilizer use and improper sewage disposal as major contributors to contamination, necessitating targeted interventions like regulating agricultural runoff, managing urban wastewater, and implementing artificial recharge. This study underscores the importance of integrating LULC into vulnerability assessments and highlights the practical implications of using such maps as decision-support tools for sustainable groundwater management in semi-arid regions.</p>

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Integrated groundwater vulnerability assessment in the Pench River Basin, Madhya Pradesh, Central India using DRASTIC-based models

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月8日

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  • Chandra Shekhar Dwivedi,
  • Amarjeet Kumar Mahato,
  • Arvind Chandra Pandey,
  • Sagar Kumar Swain,
  • Bikash Ranjan Parida

摘要

Groundwater vulnerability assessment is vital for sustainable management, especially in regions with intensive agricultural and urban activities. This study evaluated groundwater susceptibility in the Pench River Basin using DRASTIC, DRASTIC-AHP, and modified DRASTIC-AHP models. Seven key hydrogeological parameters, net recharge, aquifer yield, depth to water table, soil media, slope, hydraulic conductivity, and vadose zone depth, were integrated, along with Land Use and Land Cover (LULC) in the modified model. This approach represents a novel integration of LULC and AHP within the DRASTIC framework, validated with field-based fluoride data to enhance model reliability. Vulnerability indices ranged from 43 to 182, categorizing the area into five classes: very low (17.78%), low (21.67%), moderate (24.24%), high (19.31%), and very high (17%). Central and southern regions exhibited high vulnerability due to shallow water tables (< 3.56 mbgl) and high recharge rates ranged from 50 to 250 mm/year, over 38% of the area. Urban (38%) and agricultural zones (29%) were identified as high-risk areas, while vegetation (23%) and barren land (10%) showed reduced vulnerability. Validation with 84 groundwater samples revealed fluoride concentrations (> 0.63 mg/L) moderately correlated (R²=0.45) with vulnerability, demonstrating the modified DRASTIC-AHP model’s superior accuracy and applicability. Findings indicate excessive fertilizer use and improper sewage disposal as major contributors to contamination, necessitating targeted interventions like regulating agricultural runoff, managing urban wastewater, and implementing artificial recharge. This study underscores the importance of integrating LULC into vulnerability assessments and highlights the practical implications of using such maps as decision-support tools for sustainable groundwater management in semi-arid regions.