Assessing the Water Quality of a Stream and Its Relationship with Climate Change Using Water Quality Index and Multivariate Statistical Methods
Toxics, cilt.14, sa.6, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 14 Sayı: 6
- Basım Tarihi: 2026
- Doi Numarası: 10.3390/toxics14060520
- Dergi Adı: Toxics
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, EMBASE, Directory of Open Access Journals, Natural Science Collection (ProQuest), Biological Science Database (ProQuest)
- Anahtar Kelimeler: climate change, statistical evaluation, water quality index
- Bursa Uludağ Üniversitesi Adresli: Evet
Özet
Industrial and domestic wastewaters, nonpoint pollution sources, and climate change affect stream ecosystems, water quantity, and quality. Within the scope of this study, the water quality of Nilüfer Stream was evaluated using the Water Quality Index (WQI), One-Way ANOVA, the Kruskal–Wallis Test, and Principal Component Analysis (PCA). In the study, 4686 water quality data from seven sampling stations between 2008 and 2024 were used. WQI results showed a distinct decrease in water quality from the upstream to the downstream of the Stream. Average WQI values for the stations were found to be between 140.83 and 487.83. The lowest WQI value was found at Station 1 and the highest WQI value was found at Station 7. According to WQI, the ranking of the stations by magnitude was St7 > St4 > St5 > St6 > St2 > St3 > St1. A statistically significant difference was observed between the stations in terms of WQI, ANOVA, and Kruskal–Wallis Test (p < 0.05), and water quality was found to be seasonally diverse. Generally, at stations (except for two stations), the seasonal WQI values ranked by magnitude were autumn > summer > winter > spring. The PCA showed that relationships among parameters originating from industrial wastewater associated with the textile, automotive, and metal industries were stronger (component loadings > 0.75), whereas the groups identified in the upstream basin indicated domestic pollution and agricultural pollution from fertilizers and pesticides. PCA conducted between meteorological parameters and the WQI values of the stations showed that climate change could be effective at only two stations. It was determined that the region located before the wastewater treatment plant (St4) was associated with precipitation, humidity, and evaporation, while the downstream region (St7) was related to wind speed. It was observed that water quality was more influenced by industrial, urban, and agricultural pollution sources than by climate change.