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Water Quality Level Model Using the Discriminant Analysis for the Small Streams of Rural Area in the Han River Watersheds
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 Title & Authors
Water Quality Level Model Using the Discriminant Analysis for the Small Streams of Rural Area in the Han River Watersheds
Choi, Chul-Mann; Lee, Jong-Sik; Cho, Nam-Jun; Ryu, Hui-Yong; Park, Seong-Jin; Kim, Jin-Ho; Yun, Sun-Gang; Lee, Jeong-Taek;
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 Abstract
The main purpose of this work is the development of water quality level model using the data such as DO, EC, BOD, , T-N, T-P, and SS in 88 agricultural streams of the Han river watersheds. To grant water quality level for each parameters, it divided into 20% respectively in the order of water quality level. On the basis of the lowest water quality level, water quality of streams was assigned. As the result, number of stream corresponding to Level Ⅰ was 0, Level II was 1 stream, Level III was 3 streams, Level IV was 22 streams, and Level V was 62 streams. By standardized canonical discriminant function coefficient, was the highest in 0.427 at the discriminant power. According to discriminant function for water quality level, it was equal to from Level II to Level V, respectively. As a result of test at real data of the Han river watersheds in 2007, the suitability of water quality level model was high to 88.4%.
 Keywords
Water quality level model;Discriminant analysis;Discriminant function;Han river watershed;
 Language
Korean
 Cited by
 References
1.
Liding, C. and Bojie, F. (2000) Farm ecosystem management and control of nonpoint source pollution. Chinese J. Environ. Sci. 21, 98-100

2.
Peterson, J. M. and Boisvert, R. N. (2001) Control of nonpoint source pollution through voluntary incentive-based policies: an application to nitrate contamination in New York. Agricultural and Resource Economices Review 30(2), 127-138

3.
Bedient, P. B., Lambert, J. L. and Springer, N. K. (1980) Storm-water pollution load-runoff relationship. J. WPCF. 52(9), 2396-2404

4.
Ra, D. G. and Kim, K. S. (1996) Effect of nonpoint source pollutants on water quality. J. of Industrial Technology Institute Sunchon National Univ. 10, 139-149

5.
Kim, J. G. (2002) Evaluation of water quality in the Keum river using statistics analysis. J. Kor. Env. Sci. 11(12), 1281-1289 crossref(new window)

6.
Ryu, J. K. (2004) A real time monitoring for water quality of river. J. KSWQ. 20(1), 1-11

7.
Petersen, W. Bertino, L. Callies, U. and Zorita, E. (2001) Process identification by principal component analysis of river water-quality data. Ecological Modeling 138, 193-213 crossref(new window)

8.
Haag, I. and Westrich, B. (2002) Processes governing river water quality identified by principal component analysis. Hydrol. Process. 16, 3113-3592 crossref(new window)

9.
Kim, J. G. (2006) The evaluation of water quality in coastal sea of Incheon using a multivariate analysis. J. Kor. Env. Sci. 15(11), 1017-1025 crossref(new window)

10.
Kim, J. H., Choi, C. M., Kim, W. I., Lee, J. S., Jung, G. B., Han, K. H., Ryu, J. S., Lee, J. T. and Kwun, S. K. (2007) Multi-variate statistical analysis for evaluation of water quality properties in Korean rural watershed. Kor. J. Environ. Agric. 26(1), 17-24 crossref(new window)

11.
Park, S. H., Cho, S. S. and Kim, S. S. (2005) SPSS (ver. 12.0k). Datasolution, Seoul. p.519

12.
Jung, C. Y. and Choi, E. G. (1999) Statistical analysis for spsswin, Muyok publishing company, Seoul, p.359-388

13.
Lee, M. O. and Baek, S. H. (1998) The prediction of red tides in Jinhae bay using a discriminant function. J. Kor. Env. Sci. 7(1), 8-19

14.
Kim, J. H., Choi, C. M., Ryu, J. S., Jung, G. B., Shin, J. D., Han, K. H., Lee, J. T. and Kwun, S. K. (2007) Development and Application of water quality level model for the small streams of rural watersheds with discriminant analysis. J. KSWQ. 23(2), 260-265