Browsing by Author "Mutlu, E, Tokatli, C, Islam, AMT, Islam, MS, Muhammad, S"

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • No Thumbnail Available
    Publication
    Water quality assessment of Şehriban stream (Kastamonu, Türkİye) from a multi-statistical perspective
    (2023-01-01) Mutlu E., Tokatlı C., Islam A.R.M.T., Islam M.S., Muhammad S.; Mutlu, E, Tokatli, C, Islam, AMT, Islam, MS, Muhammad, S
    In this paper, water quality of Sehriban Stream, a rare freshwater ecosystem far from human impact and located in the western part of Türkiye’s Karadeniz Region, was studied over a long period of time (a hydrological year). Multivariate statistical approaches such as Pearson Correlation Index (PCI), Factor Analysis (FA), Cluster Analysis (CA) and self-organising maps (SOM) were used to evaluate the water quality and physico-chemical datasets. Samples were taken monthly during February 2019–January 2020 from 12 stations and a total of 21 physicochemical parameters were investigated. The spatiotemporal averages of some organic pollution parameters investigated in the basin were determined as follows: 344 μS/cm for EC, 0.80 mg/L for COD, 0.42 mg/L for BOD, 0.02 mg/L for PO42-, 34.4 mg/L for SO42-, 0.00009 mg/L for NO2, 1.36 mg/L for NO3 and 0.0002 mg/L for NH4−. According to the findings of this study, despite a modest decline in water quality from upstream to downstream, Sehriban Stream was revealed to have first-class water quality features in general and all parameters detected in all seasons at all the investigated stations were below the limit values reported by WHO. The SOM analysis detected three spatial patterns, e.g. pH-salinity-K+-PO42--Mg2+-NO2; DO-Ca2+-NH4− and TDS-EC-Cl−-SO42--COD-BOD-Na+ in water. As a result of PCI, significant positive and negative correlations were recorded among the investigated parameters. Results of FA showed that 2 factors elucidated 85% of total variances, which are named ‘Agricultural Factor’ and ‘Natural Factor’. As a result of CA, 3 significant clusters were identified, which are named ‘Lower Polluted Zone’, ‘Moderate Polluted Zone’ and ‘Higher Polluted Zone’. Overall, this work showed that multi-statistical approaches can be used to assess the water quality in a rare, unpolluted habitat over time and space.