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<p>Groundwater contamination is a significant concern for the environment and local populations, and reliable approaches are needed to assess aquifer vulnerability. This study investigates and compares the DRASTIC-LU and DRASTIC-LU-NO<sub>3</sub><sup>−</sup> methods applied to the Ouled Ogbane aquifer in northwestern Morocco to improve pollution risk assessment. The performance of these methods was evaluated by correlating their scores with groundwater quality parameters, including nitrate (NO₃<sup>−</sup>) concentrations, fecal coliforms (FC), organic matter (OM), and ammonium (NH₄<sup>+</sup>). The results show that DRASTIC-LU has a low correlation with nitrate concentrations (R2 = 0.10), whereas integrating nitrate concentrations into the DRASTIC-LU-NO<sub>3</sub><sup>−</sup> method significantly improves this correlation (R2 = 0.26). In addition, DRASTIC-LU-NO<sub>3</sub><sup>−</sup> demonstrated moderate correlations with other parameters, including fecal coliforms (R2 = -0.66), organic matter (R2 = 0.59), and ammonium (R2 = 0.34). These findings confirm that adding nitrates as a specific variable enhances the model’s sensitivity to contamination sources, allowing for a more accurate assessment of vulnerable areas. This approach provides a valuable tool for developing sustainable groundwater management strategies and reducing environmental risks.</p>

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Comparison of groundwater pollution vulnerability assessments via the DRASTIC-LU and DRASTIC-LU-NO3− methods in the Ouled Ogbane aquifer, Northwest Morocco

  • 期刊论文

  • 发表日期：

    2025年6月24日

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  • Morad Chahid,
  • Ismail Hilal,
  • Chaimaa Et-Takaouy,
  • Khalid En-Nagre,
  • Jamal Eddine Stitou El Messari,
  • Mohammed Reda Aoulad Mansour,
  • Mourad Aqnouy

摘要

Groundwater contamination is a significant concern for the environment and local populations, and reliable approaches are needed to assess aquifer vulnerability. This study investigates and compares the DRASTIC-LU and DRASTIC-LU-NO3− methods applied to the Ouled Ogbane aquifer in northwestern Morocco to improve pollution risk assessment. The performance of these methods was evaluated by correlating their scores with groundwater quality parameters, including nitrate (NO₃−) concentrations, fecal coliforms (FC), organic matter (OM), and ammonium (NH₄+). The results show that DRASTIC-LU has a low correlation with nitrate concentrations (R2 = 0.10), whereas integrating nitrate concentrations into the DRASTIC-LU-NO3− method significantly improves this correlation (R2 = 0.26). In addition, DRASTIC-LU-NO3− demonstrated moderate correlations with other parameters, including fecal coliforms (R2 = -0.66), organic matter (R2 = 0.59), and ammonium (R2 = 0.34). These findings confirm that adding nitrates as a specific variable enhances the model’s sensitivity to contamination sources, allowing for a more accurate assessment of vulnerable areas. This approach provides a valuable tool for developing sustainable groundwater management strategies and reducing environmental risks.