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July 15, 2026Applied SciencesOpen Access

Irrigation-Driven Groundwater Recharge and Quality Degradation in Semi-Arid Regions: Hydrochemical, GIS-Based, and Explainable Machine Learning Assessment in Central Tunisia

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Authors

RMRim MissaouiUniversity of SfaxMGMatteo GentilucciUniversità di CamerinoYHYounes HamedUniversity of Gafsa

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Overview

Randomized trial assesses groundwater quality degradation from irrigation practices in semi-arid regions, highlighting implications for sustainable management.

Key Points

  • The study aims to investigate how irrigation practices affect groundwater recharge and quality in semi-arid regions.
  • Analyzed thirty groundwater samples for physicochemical parameters and irrigation suitability indicators.
  • Employed GIS-based spatial modeling and explainable machine learning for assessment.
  • Utilized hydrochemical analysis to study groundwater salinity and nitrate contamination.
  • Groundwater salinity was high, with Electrical Conductivity (EC) ranging from 1490 to 8710 µS/cm.
  • Over 40% of groundwater samples were unsuitable for irrigation due to high salinity and sodicity.
  • Linear Regression showed excellent performance for estimating Irrigation Water Quality Index (R2 = 0.9839).

Cite This Study

Missaoui et al. (2026) studied this question.

synapsesocial.com/papers/6a5723fd88b21df875480856https://doi.org/10.3390/app16147014
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