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<p>Groundwater scarcity represents a growing concern in semi-arid regions, necessitating efficient evaluation methods to support sustainable management. This study focuses on assessing groundwater potential in the Takelsa coastal basin, Tunisia, using an integrated geospatial approach. Geographic Information Systems and remote sensing techniques were combined with two decision-making frameworks: the Multi-Influencing Factor method and the Analytic Hierarchy Process. Ten thematic factors influencing groundwater occurrence were considered, with lithology, elevation, and slope identified as the most influential, contributing approximately 60% of the total weight. The model’s consistency was confirmed through a consistency ratio of 0.045 and a consistency index of 0.067. Resulting maps classified the basin into four groundwater recharge potential zones. Areas with very good or good recharge potential covered 52.5% of the basin according to the Analytic Hierarchy Process, and 68.9% according to the Multi-Influencing Factor method. Validation using existing well locations confirmed the reliability of the approach. The findings provide decision-makers with a practical tool for identifying priority zones for groundwater development, optimizing well placement, and supporting sustainable water infrastructure planning. The methodology also offers a transferable framework for other data-scarce or climate-sensitive regions facing similar groundwater management challenges.</p>

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Integrated geospatial approach for assessing groundwater potential in the Takelsa Coastal Basin, Tunisia

  • 期刊论文

  • 发表日期：

    2025年9月17日

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  • B. Farhat,
  • R. Mejdoud El Fehri,
  • M. Laouissi,
  • R. Chrigui,
  • N. Rebai,
  • A. Ben Mammou

摘要

Groundwater scarcity represents a growing concern in semi-arid regions, necessitating efficient evaluation methods to support sustainable management. This study focuses on assessing groundwater potential in the Takelsa coastal basin, Tunisia, using an integrated geospatial approach. Geographic Information Systems and remote sensing techniques were combined with two decision-making frameworks: the Multi-Influencing Factor method and the Analytic Hierarchy Process. Ten thematic factors influencing groundwater occurrence were considered, with lithology, elevation, and slope identified as the most influential, contributing approximately 60% of the total weight. The model’s consistency was confirmed through a consistency ratio of 0.045 and a consistency index of 0.067. Resulting maps classified the basin into four groundwater recharge potential zones. Areas with very good or good recharge potential covered 52.5% of the basin according to the Analytic Hierarchy Process, and 68.9% according to the Multi-Influencing Factor method. Validation using existing well locations confirmed the reliability of the approach. The findings provide decision-makers with a practical tool for identifying priority zones for groundwater development, optimizing well placement, and supporting sustainable water infrastructure planning. The methodology also offers a transferable framework for other data-scarce or climate-sensitive regions facing similar groundwater management challenges.