다변량통계분석 및 유역환경모델을 이용한 금호강 중·상류 유역의 수질특성평가 (Assessment of Water Quality Characteristics in the Middle and Upper Watershed of the Geumho River Using Multivariate Statistical Analysis and Watershed)

서지정보

· 발행기관 : 한국물환경학회
· 수록지 정보 : 한국물환경학회지 / 37권 / 6호 / 520 ~ 530페이지
· 저자명 : 서영민, 권구호, 최윤영, 이병준

초록

Multivariate statistical analysis and an environmental hydrological model were applied for investigating the causes of water pollution and providing best management practices for water quality improvement in urban and agricultural watersheds. Principal component analysis (PCA) and cluster analysis (CA) for water quality time series data show that COD, TOC, SS, and T-P are classified as non-point source pollutants that are highly correlated with river discharge. T-N, which has no correlation with river discharge and has an inverse relationship with water temperature, behaves like a point source with slow and consistent release. BOD shows intermediate characteristics between point and non-point source pollutants. The results of the PCA and CA for the spatial water quality data indicate that cluster 1 of the watersheds is characterized as upstream watersheds with good water quality and high proportion of forest. However, cluster 3 shows the most polluted watersheds with substantial discharge of BOD and nutrients from urban sewage, and agricultural and industrial activities. Cluster 2 shows intermediate characteristics between clusters 1 and 3. The results of hydrological simulation program-Fortran (HSPF) model simulation indicate that the seasonal patterns of BOD, T-N, and T-P are substantially affected by agricultural and livestock farming activities, untreated wastewater, and environmental flow. Spatial analysis of the model results indicates that the highly-populated watersheds are prior contributors to water quality degradation in the river.

영어초록

Multivariate statistical analysis and an environmental hydrological model were applied for investigating the causes of water pollution and providing best management practices for water quality improvement in urban and agricultural watersheds. Principal component analysis (PCA) and cluster analysis (CA) for water quality time series data show that COD, TOC, SS, and T-P are classified as non-point source pollutants that are highly correlated with river discharge. T-N, which has no correlation with river discharge and has an inverse relationship with water temperature, behaves like a point source with slow and consistent release. BOD shows intermediate characteristics between point and non-point source pollutants. The results of the PCA and CA for the spatial water quality data indicate that cluster 1 of the watersheds is characterized as upstream watersheds with good water quality and high proportion of forest. However, cluster 3 shows the most polluted watersheds with substantial discharge of BOD and nutrients from urban sewage, and agricultural and industrial activities. Cluster 2 shows intermediate characteristics between clusters 1 and 3. The results of hydrological simulation program-Fortran (HSPF) model simulation indicate that the seasonal patterns of BOD, T-N, and T-P are substantially affected by agricultural and livestock farming activities, untreated wastewater, and environmental flow. Spatial analysis of the model results indicates that the highly-populated watersheds are prior contributors to water quality degradation in the river.

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