| Title |
Assessment of Water Quality Characteristics in the Middle and Upper Watershed of the Geumho River Using Multivariate Statistical Analysis and Watershed Environmental Model |
| Authors |
서영민 ( Seo Youngmin ) ; 권구호 ( Kwon Kooho ) ; 최윤영 ( Choi Yun Young ) ; 이병준 ( Lee Byung Joon ) |
| DOI |
https://doi.org/10.15681/KSWE.2021.37.6.520 |
| Keywords |
Cluster analysis; Hydrological simulation program-fortran; Principal component analysis; Water quality |
| Abstract |
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 chemical oxygen demand (COD), total organic carbon (TOC), suspended solids (SS) and total phosphorus (T-P) are classified as non-point source pollutants that are highly correlated with river discharge. Total nitrogen (T-N), which has no correlation with river discharge and inverse relationship with water temperature, behaves like a point source with slow and consistent release. Biochemical oxygen demand (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 the cluster 1 of the watersheds was characterized as upstream watersheds with good water quality and high proportion of forest. The cluster 3 shows however indicates the most polluted watersheds with substantial discharge of BOD and nutrients from urban sewage, agricultural and industrial activities. The cluster 2 shows intermediate characteristics between the clusters 1 and 3. The results of hydrological simulation program-Fortran (HSPF) model simulation indicated that the seasonal patterns of BOD, T-N and T-P are affected substantially by agricultural and livestock farming activities, untreated wastewater, and environmental flow. The spatial analysis on the model results indicates that the highly-populated watersheds are the prior contributors to the water quality degradation of the river. |