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<p>Effective management of water resources is essential to mitigating the environmental and health impacts of wastewater discharges. This study presents a novel assessment of physico-chemical parameters in treated and untreated waters from diverse sources in Tunisia. An integrated statistical approach, combining Principal Component Analysis (PCA) and Lasso regression was applied to uncover underlying data patterns and identify the most influential parameters affecting water quality. The results revealed significant spatial variability, with parameters such as COD, BOD₅, and conductivity emerging as key indicators of pollution. In some cases, treated effluents showed unexpectedly high pollutant levels, highlighting inefficiencies in certain treatment processes. The proposed approach enhances understanding of wastewater dynamics and supports informed decision-making for sustainable water resource management.</p>

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Integrated statistical approach to physico-chemical wastewater analysis for sustainable water management in Tunisia

  • 期刊论文

  • 发表日期：

    2025年6月21日

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  • Chahnez Naccache,
  • Maha Mezghani Khemakhem

摘要

Effective management of water resources is essential to mitigating the environmental and health impacts of wastewater discharges. This study presents a novel assessment of physico-chemical parameters in treated and untreated waters from diverse sources in Tunisia. An integrated statistical approach, combining Principal Component Analysis (PCA) and Lasso regression was applied to uncover underlying data patterns and identify the most influential parameters affecting water quality. The results revealed significant spatial variability, with parameters such as COD, BOD₅, and conductivity emerging as key indicators of pollution. In some cases, treated effluents showed unexpectedly high pollutant levels, highlighting inefficiencies in certain treatment processes. The proposed approach enhances understanding of wastewater dynamics and supports informed decision-making for sustainable water resource management.