• Journal of Korean Society on Water Environment
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• v.23 no.6
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• pp.863-871
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• 2007

Spectroscopic characteristics of river water from four major watersheds in the Ulsan area were measured to examine their potential for estimating water quality parameters. The total 176 river samples were collected from 44 sites of small streams within the watersheds during the year 2006. Spectroscopic characteristics investigated included protein-like fluorescence (FLF) intensity, fulvic-like fluorescence (FLF) intensity, terrestrial humic-like fluorescence (TLF) intensity, UV absorbance at 254 nm, and UV absorbance difference at 220 nm and 254 nm. Protein-like fluorescence intensity showed linear relationships with biochemical oxygen demand (BOD), chemical oxygen demand (COD), total phosphorous (TP) concentrations of the samples with the correlation of 0.784, 0.779, and 0.733, respectively. Due to the UV absorption characteristics of nitrate at 220 nm, UV absorbance difference at 220 nm and 254 nm was selected to represent total nitrogen (TN) concentration. Exclusion of some samples with PLF intensity higher than 5.0 improved the correlation between the UV absorbance difference and TN as demonstrated by the increase of the correlation coefficient from 0.392 to 0.784. Instead, for the samples with PLF intensity lower than 5.0, the highest correlation of TN was achieved with UV absorbance at 254 nm. The results suggest that PLF intensity could be used as the estimation index for BOD, COD, and TP concentration of river water, and as the primary screening index for the prediction of TN using UV absorbance difference. Some BOD-based water quality levels among the river water were statistically discriminated by the PLF intensity. Low p-values were obtained from the t-tests on the samples with the first level and the second level (p=0.0003) and the samples with the second and the third levels (p=0.0413). Our combined results demonstrated that the selected spectroscopic characteristics of river water could be utilized as a tool for on-site real-time monitoring and/or the primary estimation of water quality.