• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology

Article

Indian Journal of Science and Technology

Year: 2018, Volume: 11, Issue: 32, Pages: 1-14

Original Article

Water Quality Assessment of a Coastal Canal within a Protected Zone in Algeria using Principal Component Analysis

Abstract

Objectives/Methods: The effects of human and agricultural activities on waters of Messida canal link up Tonga Lake (RAMSAR site) with the Mediterranean Sea were assessed by determining the fluctuations of indicator of fecal pollution and physico-chemical parameters. The distribution of bacterial pathogens was also monitored. Findings: Most of hydrological parameters show large fluctuations between sampling sites and seasons (P<0.05). In spring and summer, chlorophyll-a, orthophosphate, BOD5 values were abundant compared to winter values. The nitrate and nitrite concentrations exceeded the guideline for protection of aquatic life. Ammonium, pH, suspended matter, total dissolved matter content does not exceed existing norms. All water samples also had detectable concentrations of five indicators and total viable and active bacteria (TVBC) with log mean ± standard deviation densities of 6.02 ± 0.4 total coliforms (TC), 5.8 ± 0.4 fecal coliforms (FC), 5.7 ± 0.4 Escherichia coli (EC), 4.6 ± 0.2 fecal streptococci (FS), 2.5 ± 1.4 sulfito-reducing bacteria (RS), and 6.8 ± 0.3 TVBC per 100 ml. The results of the statistical analysis (PCA) showed that the presence of fecal indicator is strongly influenced by the oxygen, DBO5 and PO4 and to a lesser extent by salinity, T° and pH. A total of 40 species of potential pathogens bacteria were isolated: the most common strains isolated from all samples were Aeromonas hydrophila (70%). Application: These results demonstrated that the water quality in this region is critical and support a need for better land management practices to protect water quality and aquatic life. 

Keywords: Fecal Pollution, Messida Coastal Canal, Pathogens Bacteria, Physico-chemical Parameters, Principal Component Analysis, Water Quality

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