Yassin, S., Abdulla, S. (2025). Multivariate Assessment of Gomaspan Reservoir Water Quality in Erbil, Iraqi Kurdistan Region. , 20(4), 10-30. doi: 10.32894/kujss.2025.163419.1236
Sidra Qubad Yassin; Siraj Muhammed Abdulla. "Multivariate Assessment of Gomaspan Reservoir Water Quality in Erbil, Iraqi Kurdistan Region". , 20, 4, 2025, 10-30. doi: 10.32894/kujss.2025.163419.1236
Yassin, S., Abdulla, S. (2025). 'Multivariate Assessment of Gomaspan Reservoir Water Quality in Erbil, Iraqi Kurdistan Region', , 20(4), pp. 10-30. doi: 10.32894/kujss.2025.163419.1236
Yassin, S., Abdulla, S. Multivariate Assessment of Gomaspan Reservoir Water Quality in Erbil, Iraqi Kurdistan Region. , 2025; 20(4): 10-30. doi: 10.32894/kujss.2025.163419.1236
Multivariate Assessment of Gomaspan Reservoir Water Quality in Erbil, Iraqi Kurdistan Region
1Department of Environmental Science and Health, College of Science, Salahaddin University-Erbil, Erbil, Kurdistan Region, Iraq
2Department of Environmental Science and Health, College of Science, Salahaddin University-Erbil, Erbil, Kurdistan region, Iraq
Abstract
Reservoir water quality in semi-arid catchments is shaped by short, intense runoff pulses and early impoundment effects. This study uses a mix of physicochemical and biological water quality measures to assess the water quality of the Gomaspan reservoir on monthly basis using statistical analyses included two‑way ANOVA (Month, Site), Pearson correlations, PCA, and Bray–Curtis cluster analysis. Over the course of four months (November 2024 to February 2025), measurements were made of thirteen important water quality at nine sample locations. These included air and water temperature, pH, EC, TDS, TSS, turbidity, BOD5, DO, TN, TP, MPN, and chlorophyll-a. To evaluate pollution levels and establish a baseline for further monitoring, data were compared to WHO criteria. Good water quality was indicated by the Water Pollution Index (WPI) value of 0.52. Significant temporal and spatial variation were found in a number of factors using two-way ANOVA, most notably in temperature, microbial load, and nutrient content. PCA (first four PCs) explained 78.66% of the variance. Two‑way ANOVA detected significant month and site effects (p < 0.05) for temperature, nutrients (TN, TP), and biological indicators (MPN, Chl‑a). By grouping stations according to similarities in water quality, cluster analysis highlighted regional sources of contamination. For the sampled window only (Nov–Feb), most parameters met WHO guideline values, but pronounced temporal and site‑specific variability indicates the need for a dry‑season campaign (Mar–Sep) to characterize the full hydrological year.