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http://dx.doi.org/10.3741/JKWRA.2018.51.10.863

Assessment of climate change impact on aquatic ecology health indices in Han river basin using SWAT and random forest  

Woo, So Young (Department of Civil, Environmental and Plant Engineering, Konkuk University)
Jung, Chung Gil (Department of Civil, Environmental and Plant Engineering, Konkuk University)
Kim, Jin Uk (Department of Civil, Environmental and Plant Engineering, Konkuk University)
Kim, Seong Joon (Department of Civil, Environmental and Plant Engineering, Konkuk University)
Publication Information
Journal of Korea Water Resources Association / v.51, no.10, 2018 , pp. 863-874 More about this Journal
Abstract
The purpose of this study is to evaluate the future climate change impact on stream aquatic ecology health of Han River watershed ($34,148km^2$) using SWAT (Soil and Water Assessment Tool) and random forest. The 8 years (2008~2015) spring (April to June) Aquatic ecology Health Indices (AHI) such as Trophic Diatom Index (TDI), Benthic Macroinvertebrate Index (BMI) and Fish Assessment Index (FAI) scored (0~100) and graded (A~E) by NIER (National Institute of Environmental Research) were used. The 8 years NIER indices with the water quality (T-N, $NH_4$, $NO_3$, T-P, $PO_4$) showed that the deviation of AHI score is large when the concentration of water quality is low, and AHI score had negative correlation when the concentration is high. By using random forest, one of the Machine Learning techniques for classification analysis, the classification results for the 3 indices grade showed that all of precision, recall, and f1-score were above 0.81. The future SWAT hydrology and water quality results under HadGEM3-RA RCP 4.5 and 8.5 scenarios of Korea Meteorological Administration (KMA) showed that the future nitrogen-related water quality in watershed average increased up to 43.2% by the baseflow increase effect and the phosphorus-related water quality decreased up to 18.9% by the surface runoff decrease effect. The future FAI and BMI showed a little better Index grade while the future TDI showed a little worse index grade. We can infer that the future TDI is more sensitive to nitrogen-related water quality and the future FAI and BMI are responded to phosphorus-related water quality.
Keywords
Aquatic ecology health; Climate change; Water quality; SWAT; Random forest;
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1 Ahn, S. R., and Kim, S. J. (2017). "Assessment of integrated watershed health based on the natural environment, hydrology, water quality, and aquatic ecology." Hydrology and Earth System Sciences, Vol. 21, No. 1, pp. 5583-5602.   DOI
2 An, K., Lee, J., and Jang, H. (2005). "Ecological health assessments and water quality patterns in Youdeung stream." Korean Journal of Limnology, Vol. 38, No. 3, pp. 341.
3 Arnold, J. G., Williams, J. R., Srinivasan, R., and King, K. W. (1996). SWAT manual. USDA, Agricultural Research Service and Blackland Research Center, Texas.
4 Breiman, L. (2001). "Random forests." Machine Learning, Vol. 45, No. 1, pp. 5-32.   DOI
5 Goutte, C., and Gaussier, E. (2005). "A probabilistic interpretation of precision, recall and F-score, with implication for evaluation." Proceedings European Conference on Information Retrieval, Springer, Berlin, Heidelberg, pp. 345-359.
6 Jung, S. W., Park, S. H., and Lee, J. H. (2008). "Environmental studies in the lower part of the Han river IIX. Assessment for water quality using epilithic diatom assemblage index to organic water pollution (DAIpo) in dry season." Korean Journal of Environmental Biology, Vol. 26, No. 3, pp. 233-239.
7 Kim, S. (2015). "A corporate credit ratings model with random forests." Master thesis, Kookmin University, pp. 1-31.
8 Kim, T. J., and Lee, O. M. (2009). "Assessment of water quality in the Sum-river and the Dal-stream using epilithic diatom-based indices." Journal of Korean Society on Water Quality, Vol. 25, No. 4, pp. 606-614.
9 Langley, P., and Simon, H. A. (1995). "Applications of machine learning and rule induction." Communications of the ACM, Vol. 38, No. 11, pp. 54-64.   DOI
10 Lee, J. W., Jung, C. G., Kim, D. R., and Kim, S. J. (2018). "Assessment of future climate change impact on groundwater level behavior in Geum river basin using SWAT." Journal of Korea Water Resources Association, Vol. 51, No. 3, pp. 247-261.   DOI
11 Meng, W., Zhang, N., Zhang, Y., and Zheng, B. (2009). "Integrated assessment of river health based on water quality, aquatic life and physical habitat." Journal of Environmental Sciences, Vol. 21, No. 8, pp. 1017-1027.   DOI
12 Ministry of Environment (2015). Nationwide Aquatic Ecological Monitoring Program, National Institute of Environmental Research, Incheon, South Korea.
13 Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D., and Veith, T. L. (2007). "Model evaluation guidelines for systematic quantification of accuracy in watershed simulations." Transactions of the ASABE, Vol. 50, No. 3, pp. 885-900.   DOI
14 Nash, J. E., and J. E. Sutcliffe (1970). "River flow forecasting though conceptual models: Part I, A discussion of principles." Journal of Hydrology, Vol. 10, No. 3, pp. 282-290.   DOI
15 Neitsch, S. L., Arnold, J. G., Kiniry, J. R., and Williams, J. R. (2001). Soil and water assessment tool: theoretical documentation. U.S Agricultural Research Service, Temple, Texas, pp. 340-367.
16 Pal, M. (2005). "Random forest classifier for remote sensing classification." International Journal of Remote Sensing, Vol. 26, No. 1, pp. 217-222.   DOI
17 Ponader, K. C., Charles, D. F., and Belton, T. J. (2007). "Diatombased TP and TN inference models and indices for monitoring nutrient enrichment of New Jersey streams." Ecological Indicators, Vol. 7, No. 1, pp. 79-93.   DOI
18 Santhi, C., Arnold, J. G., Williams, J. R., Dugas, W. A., Srinivasan, R., and Hauck, L. M. (2001). "Validation of the swat model on a large RWER basin with point and nonpoint sources." Journal of the American Water Resources Association, Vol. 37, No. 5, pp. 1169-1188.   DOI
19 Water Environment Information System (2018). http://water.nier.go.kr/waterData/easyDataBt.do?menuIdx=3_1_2.
20 Won, D. H., Byun, M. S., Park, J. H., Lee, S. W., and Hwang, S. J. (2010). "Evaluation of the current status of aquatic ecosystem health in five major rivers in Korea." A Pulication of Korean Society of Civil Engineers, pp. 149-160.