• Title/Summary/Keyword: Nakdoing river

Search Result 2, Processing Time 0.019 seconds

Water Quality Analysis in Nakdong River Tributaries for the Determination of Priority Management Areas (관리 우선순위 선정을 위한 낙동강 지류·지천 지점의 수질 오염 특성 분석)

  • Im, Tae Hyo;Na, Seungmin;Shin, Sangmin;Son, Younggyu
    • Journal of Korean Society of Environmental Engineers
    • /
    • v.38 no.10
    • /
    • pp.558-565
    • /
    • 2016
  • Water quality data including flow rates and BOD/COD/T-N/T-P/SS/TOC concentrations in Nakdong river tributaries were analyzed to determine priority management areas using 699 data sets from 195 locations in 2015. It was pointed out that the coefficients of variation, the ratio of the standard deviation to the mean, for the concentrations and loading rates of BOD, T-P, and TOC in each monitoring location were so large that average values of water quality monitoring data might be not appropriate to determine the priority management areas among all 195 monitoring stations in Nakdoing river. Therefore we suggested two evaluation methods using each water quality data independently. In the first method the excess numbers of the BOD, T-P, and TOC concentrations comparing to the water quality standards in the medium-sized management areas in Nakdong river was evaluated for each monitoring station. In the second method the percentile ranks of the loading rates of the BOD, T-P, and TOC were obtained for each monitoring data. The two groups of the priority management areas determined by each method were compared and the water quality characteristics in Nakdoing river were investigated.

Water Quality Analysis in Nakdong River Tributaries (낙동강 지류·지천 모니터링 결과를 이용한 수질환경 평가)

  • Im, Tae Hyo;Son, Younggyu
    • Journal of Environmental Science International
    • /
    • v.25 no.12
    • /
    • pp.1661-1671
    • /
    • 2016
  • Water quality in Nakdong river was analyzed using 699 monitoring data sets including flow rates and water quality concentrations collected at 195 tributary monitoring stations (the priority management areas: 35 stations, the non-priority management areas: 160 stations) in 2015. The highest average concentrations of all data for BOD, COD, T-N, T-P, SS, and TOC were 30~600 times higher than the lowest concentrations while the highest average loading rates were 800,000~2,700,000 times higher than the lowest loading rates. Because of the very large differences in the concentrations and loading rates, the variation of the concentrations and loading rates in a priority management monitoring station for BOD, T-P, and TOC was analyzed using the coefficient of variation, the ratio of the standard deviation value to the mean value. For BOD, T-P, and TOC, the coefficients of variation for concentration were mostly less than 100%, whereas the coefficients of variation for loading rate ranged from 31.1% to 232.2%. The very big difference in the loading rates was due to the large variation in flow rates. As a result of this, the estimation of water quality at each monitoring station using the average values of the concentrations and loading rates might be not rational in terms of their representativeness. In this study, new water quality analysis methods using all collected monitoring data were suggested and applied according to the water quality standard in medium-sized management areas.