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자료유형
학술저널
저자정보
저널정보
한국환경보건학회 한국환경보건학회지 한국환경보건학회지 제42권 제4호
발행연도
2016.1
수록면
280 - 292 (13page)

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Objectives: The objective of this study was to build COD regression models for the Han River and evaluatewater quality. Methods: Water quality data sets for the dry season (as of January) during a four-year period (2012-2015) werecollected from the database of the Han River automatic water quality monitoring stations. Statistical techniques,including combined genetic algorithm-multiple linear regression (GA-MLR) were used to build five-descriptorCOD models. Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis(CA) are useful tools for extracting meaningful information. Results: The r2 of the best COD models provided significant high values (> 0.8) between 2012 and 2015. Totalorganic carbon (TOC) was a surrogate indicator for COD (as COD/TOC) with high reliability (r2=0.63 in 2012,r2=0.75 for 2013, r2=0.79 for 2014 and r2=0.85 for 2015). The ratios of COD/TOC were calculated as 2.08 in2012, 1.79 in 2013, 1.52 and 1.45 in 2015, indicating that biodegradability in the water body of the Han Riverwas being sustained, thereby further improving water quality. The BOD/COD ratio supported these findings. Thecluster analysis revealed higher annual levels of microorganisms and phosphorous at stations along the Hangang-Seoul and Hantangang areas. Nevertheless, the overall water quality over the last four years showed anobservable trend toward continuous improvement. These findings also suggest that non-point pollution controlstrategies should consider the influence of upstreams and downstreams to protect water quality in the Han River. Conclusion: This data analysis procedure provided an efficient and comprehensive tool to interpret complexwater quality data matrices. Results from a trend analysis provided much important information about sourcesand parameters for Han River water quality management.

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