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http://dx.doi.org/10.17663/JWR.2015.17.4.348

Water Quality Analysis of Hongcheon River Basin Under Climate Change  

Kim, Duckhwan (Department of Civil Engineering, Inha university)
Hong, Seung Jin (Department of Civil Engineering, Inha university)
Kim, Jungwook (Department of Civil Engineering, Inha university)
Han, Daegun (Department of Civil Engineering, Inha university)
Hong, Ilpyo (Korea Institute of Civil Engineering and Building Technology)
Kim, Hung Soo (Department of Civil Engineering, Inha university)
Publication Information
Journal of Wetlands Research / v.17, no.4, 2015 , pp. 348-358 More about this Journal
Abstract
Impacts of climate change are being observed in the globe as well as the Korean peninsula. In the past 100 years, the average temperature of the earth rose about 0.75 degree in celsius, while that of Korean peninsula rose about 1.5 degree in celsius. The fifth Assessment Report of IPCC(Intergovermental Panel on Climate Change) predicts that the water pollution will be aggravated by change of hydrologic extremes such as floods and droughts and increase of water temperature (KMA and MOLIT, 2009). In this study, future runoff was calculated by applying climate change scenario to analyze the future water quality for each targe period (Obs : 2001 ~ 2010, Target I : 2011 ~ 2040, Target II : 2041 ~ 2070, Target III : 2071 ~ 2100) in Hongcheon river basin, Korea. In addition, The future water quality was analyzed by using multiple linear regression analysis and artificial neural networks after flow-duration curve analysis. As the results of future water quality prediction in Hongcheon river basin, we have known that BOD, COD and SS will be increased at the end of 21 century. Therefore, we need consider long-term water and water quality management planning and monitoring for the improvement of water quality in the future. For the prediction of more reliable future water quality, we may need consider various social factors with climate components.
Keywords
Climate Change; Hongcheon River Basin; Multiple Linear Regression Analysis; Artificial Neural Network; Water Quality Analysis;
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Times Cited By KSCI : 11  (Citation Analysis)
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