Year 2025, Volume 10, Issue 3

Year : 2025
Volume : 10
Issue : 3
   
Authors : Reyhan SAĞLAM, Ferhat GÖKBULAK
Title : AN INTEGRATED ASSESSMENT OF WATER QUALITY IN THE RIVA (ÇAYAĞZI) STREAM USING MULTIVARIATE STATISTICAL AND SPATIAL APPROACHES
Abstract : This study evaluates the spatial variability of water quality and identifies pollutant sources in the Riva (Çayağzı) Stream watershed, located in Istanbul, Türkiye. Monthly, water samples were collected from five strategically selected locations throughout 2024. In situ measurements included physicochemical parameters (pH, electrical conductivity, dissolved oxygen, water temperature, and stream flow velocity). At the same time, laboratory analyses included major cations, nutrients, and heavy metals (Pb, Cd, Cr, Cu, Ni, Zn). A multivariate statistical approach—comprising Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Pearson correlation—was employed to uncover pollutant patterns and site similarities. These analyses were further integrated with land use classification derived from Landsat-8 imagery, using the Random Forest algorithm. PCA results revealed distinct pollution signatures: Öyümce was characterized by pronounced heavy metal contamination (Pb, Cd, Cr, Cu, Ni, Zn); Ömerli exhibited moderate metal levels; Riva was dominated by high ionic content (EC, Na, Mg) and suspended solids; Pasamandıra displayed intermediate pollution; and Ömerli Dam Outlet represented the least-impacted, reference site with high dissolved oxygen and minimal contaminants. HCA supported these spatial groupings, clustering sites by their dominant pollution profile. Land use assessments indicated significant urban and industrial pressure in the downstream Riva area, agricultural influence in Öyümce and Ömerli, and forest dominance in the dam upstream watershed. Strong correlations among pollutants suggested that urban runoff and agricultural activities were the primary drivers of contamination. These findings highlight the value of integrating statistical and remote sensing-based spatial analyses for source apportionment.
For citation : Sağlam, R., Gökbulak, F. (2025).An integrated assessment of water quality in the Riva (Çayağzi) stream using multivariate statistical and spatial approaches. AGROFOR International Journal, Volume 10. Issue No. 3. pp. 101-109. DOI:10.7251/AGREN2503101S
Keywords : Water quality, Pollution source, Multivariate statistical analysis, Remote sensing.
   
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