Carbon biomass of plankton community, Total Organic Carbon (TOC) and Chlorophyll a (chl.a) concentration were examined in the SeoNakdong river from January to December in 2014, to assess composition of phyto- and zoo-plankton variation, to certify the correlation between chl.a and TOC and to determine the level of contribution of plankton carbon content to TOC in the reservoir-river ecosystem. The correlation level between TOC and chl.a was low in the year 2014 but exceptionally was highly correlated only during the period with cyanobacterial bloom. The high level of contribution of plankton carbon content to TOC was attributed to cyanobacterial carbon biomass from May to November and to Cladocera carbon biomass from March to May, November and December despite of its low abundance. These results suggest that there were inter-relationships between phytoplankton, zooplankton and TOC and also subtle consistency of their properties through the year. These patterns should be discussed in relation to the physiochemical and biological characteristics of the environment, as well as to allochthonous organic matters from non-point pollution sources.

Recently, Total Organic Carbon (TOC) which can be measured instantly can be used as an organic pollutant index instead of BOD or COD due to the diversity of pollutants and non-degradable problem. The primary purpose of the present study is to reveal the properties of time series data for TOC which have been measured by real-time monitoring in Juam Lake and, in particularly, to understand the long- and short-term characteristics with the extraction of the respective components based on the different return periods. For the purpose, we proposed Discrete Wavelet Transform (DWT) as the methodology. The results from the DWT showed that the different components according to the respective periodicities could be extracted from the time series data for TOC and the variation of each component with respect to time could emerge from the return periods and the respective energy ratios of the decomposed components against the raw data.