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Abstract ▼ AI-Helper

Major factors affecting water quality in rivers are transportation, input of pollutant loads and kinetic transformation of pollutants. Government level decision makings on water quality management are based on steady state water quality modeling. However, it is more than often that such a steady sta...

Major factors affecting water quality in rivers are transportation, input of pollutant loads and kinetic transformation of pollutants. Government level decision makings on water quality management are based on steady state water quality modeling. However, it is more than often that such a steady state assumption is far from real situations in rivers. Therefore, it is unavoidable to have modeling errors in water quality modeling especially for steady state modeling for longer period of time. Authors attempted to identify sources of errors in results of steady state models and thus tried to find out ways to minimize those errors. Three water quality models, QUAL2E (Brown et al., 1983), QUAL2K (Chapra et al., 2006) and CAP (Seo and Lee, 2000) were applied to the lower stream of the Geum River. $BOD_5$ and COD tend to underestimate observed data while TN and TP showed relatively smaller errors. QUAL2E model provided best calibration results for BOD5 and TP and QUAL2K model showed best calibration results for TN. Since these errors are only relative values, it was difficult to conclude which model is better performing in certain situations. The most probable reasons for errors in water quality modeling are; 1) inappropriate consideration on flow characteristics, 2) lack of information on incoming pollutant load and 3) inappropriate location of sampling for water quality analysis.

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