Unveiling the impact of the COVID-19 pandemic on water quality: a case study on Ain-Silan and Ain-Karma sources

ABSTRACT The water quality may change over time due to a variety of physical, chemical, and biological conditions. The objectives of this study were to use statistical methods to compare the composition of cations and anions in water before and after the COVID-19 pandemic. The statistical method (ordinary least square regression) employed to assess the relationships between water quality parameters involved calculating the coefficient of determination (R2). Two key sampling sites, Ain-Karma (urban, Khenchela city) and Ain-Silan (rural), had frequent sample collection over seven years (2015–2022). Parameters analyzed include electrical conductivity (EC), pH, sodium (Na), magnesium (Mg), calcium (Ca), ammonium (NH4), nitrate (NO3), chloride (Cl), sulfate (SO4), and nitrite (NO2). At Ain-Silan, the regression models show R² values of 0.8708 for Mg, 0.850 for SO4, and 0.7495 for NO3, highlighting their significant changes over time and importance as water quality predictors. At Ain-Karma, NO2, NH4, and Mg exhibit high R2 values of 0.8418, 0.7947, and 0.8347, respectively, underscoring their critical roles in water quality prediction. These strong correlations suggest that fluctuations in these parameters significantly influence water quality, reflecting both anthropogenic and natural processes.