PL EN
Identification of Groundwater Quality by Statistical Methods and a Mathematical Method in the Khemisset–Tiflet Region
 
Więcej
Ukryj
1
Organic Chemistry, Catalysis and Environment, Department of Chemistry, Faculty of Science, Ibn Tofail University, Kenitra, Morocco
2
Laboratory of Animal and Plant Production and Agro-industry, Department of Biology, Faculty of Science, Ibn Tofail University, Kenitra, Morocco
3
Engineering Laboratory of Organometallic, Molecular Materials and Environment (LIMOME), Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco
4
Research Laboratory in Applied and Marine Geosciences, Geotechnics and Geohazards, Faculty of Sciences of Tetouan, Abdelmalek Essaadi University, Avenue Khenifra, Tétouan 93000, Maroko
5
Centre Oriental des Sciences et Techniques de l'Eau, Oujda, Marocco
AUTOR DO KORESPONDENCJI
Elassassi Zahra   

Organic Chemistry, Catalysis and Environment, Department of Chemistry, Faculty of Science, Ibn-Tofail University, Kenitra, Morocco
 
Ecol. Eng. Environ. Technol. 2022; 4:115–124
 
SŁOWA KLUCZOWE
DZIEDZINY
STRESZCZENIE
Groundwater is one of the most important natural resources that is overexploited and extensively polluted by human activity. Furthermore, drinking this dirty water might have major consequences for human health. Before using groundwater, it is consequently required to conduct a precise and regular assessment of its quality. Furthermore, for five monitoring stations in the Khemisset-Tiflet region, cluster analysis (CA), principal component analysis (PCA), and a fuzzy logic technique were utilized to analyze water quality. The CA classified the sample sites into three categories. The PCA identified temporal characteristics of water quality status. Group I include stations characterized by high temperature and low DO, COD, and BOD5 values. Group II includes stations characterized by high values of pH and low concentrations of NO3-, Cl-, SO42- and turbidity. Group III includes stations characterized by high concentrations of NO3-, Cl-, SO42- and turbidity and low concentrations of pH. In addition, fuzzy logic to reveal more information about groundwater quality. In effect, water quality in spring and winter was the best; the parameters responsible for the deterioration of water quality are NO3-, Cl-, SO42- and turbidity.