Estimating the organic matter loadings from individual treated sewage has become important for establishment of effective management strategies to control refractory organic matter (R-OM) in watersheds. For this study, regression equations were constructed using treated sewage data to convert the chemical oxygen demand (COD) concentrations, which are mostly available from open database, into total organic carbon (TOC) and R-OM concentrations. Effluent samples were collected from five major sewage treatment plants (STPs) located upstream of the lake Paldang. Variations in the OM concentrations were not associated with either the location of the STP or the sampling season. The effluent investigated were characterized by higher ratio of R-OM with respect to biodegradable organic matter (B-OM) and higher presence of dissolved organic matters (DOM) versus particulate organic matter (POM). Compared to COD(Mn), COD(Cr) exhibited higher oxidation efficiencies and greater variations in the concentrations. The concentrations of COD(Mn) were positively correlated with dissolved organic carbon (DOC), total organic carbon (TOC), and R-OM concentrations. There was nearly no seasonal and annual variation in the regression equations between COD(Mn) and TOC or R-OM concentrations. The constructed regression equations for TOC and R-OM were 0,650(±0,071)×COD(Mn)+l.426(±0,575) and 0,340(±0,083)×COD(Mn),+2.054(±0.670), respectively. The established equations are expected to contribute to estimating OM loadings from the STPs into the lake Paldang and also to compensating for the deficiency of the data for effluent OM concentrations in STP.