References
- Bouguerne, A., Boudoukha, A., and Benkhaled, A.-H., 2017. Assessment of surface water quality of Ain Zada dam (Algeria) using multivariate statistical techniques. International Journal of River Basin Management, 15, 133–143. doi: 10.1080/15715124.2016.1215325
- Carpenter, S.R., et al., 1998. Nonpoint pollution of surface waters with phosphorous and nitrogen. Ecological Applications, 8, 559–568. doi: 10.1890/1051-0761(1998)008[0559:NPOSWW]2.0.CO;2
- Chang, H. 2008. Spatial analysis of water quality trends in the Han River basin, South Korea. Water Research, 42, 3285–3304. doi: 10.1016/j.watres.2008.04.006
- Chen, W.B. and Liu, W.C., 2015. Water quality modeling in reservoirs using multivariate linear regression and two neural network models. Journal Advances in Artificial Neural Systems, 6, 1–12.
- Choi, I.-C., et al., 2017. Water policy reforms in South Korea: a historical review and ongoing challenges for sustainable water governance and management. Water, 9, 717–737. doi: 10.3390/w9090717
- Choi, S.H., Kim, H.D., and Kim, D.H., 2014. The evaluation of water quality characteristics using a multivariate statistical analysis in the artificial lake. Journal of Korea Commission on Irrigation and Drainage, 21, 87–100.
- Helena, B., Pardo, R., and Vega, M., 2000. Temporal evolution of groundwater composition in an alluvial aquifer (Pisuerga River, Spain) by principal component analysis. Water Research, 34, 807–816. doi: 10.1016/S0043-1354(99)00225-0
- Iscen, F.C., et al., 2008. Application of multicariate statistical tecniques in the assessment of surface water quality in Uluabat Lake. Journal of Environmental Science and Health, Part A, 40, 1775–1790.
- Kazi, T.G., Arain, M.K., and Jamali, N.J., 2009. Assessment of water quality of polluted lake sing multivariate statistical techniques: a case study. Ecotoxicology and Environmental Safety, 72, 301–309. doi: 10.1016/j.ecoenv.2008.02.024
- Kim, Y.J., 2003. Evaluation of urban lake water quality using principal component analysis. Journal of Korean Society of Environmental Administration, 9, 197–203.
- Koo, J.H., et al., 2015. A counterfactual assessment for interagency collaboration on water quality: the case of the Geum River basin, South Korea. Water International , 40, 664–688. doi: 10.1080/02508060.2015.1067749
- Kuppusamy, M.R. and Giridhar, V.V., 2006. Factor analysis of water quality characteristics including trace metal speciation in the coastal environmental system of Chennai Ennore. Environment International, 32, 174–179. doi: 10.1016/j.envint.2005.08.008
- Lee, E.-J., 2007. A study of project about Ganwol lake in Seosan city for water quality. Master thesis.
- Lee, C.-L. and Jeon, B.-I., 2010. Comparison of Fish Fauna in Lake Ganwol and Lake Bunam Watersheds. Korean Journal Limnol, 43, 175–182.
- Li, Z., Liu, H., and Li, Y., 2012. Review on HSPF model for simulation of hydrology and water quality processes. Environmental Science, 33, 2217–2223.
- Lim, K.H., Lee, Y.S., and Kim, L.H., 2006. Estimation of pollutant loadings from watershed into lakes of Ganwol and Boonam. Korean Wetland Society, 8, 33–40.
- Ministry of Land, Infrastructure and Transportation of Korea (MOLIT), 2011. (2011–2020): water vision 2020 [The long-term comprehensive water resource plan (2011–2020): the second revised water vision 2020]. Korea: MOLIT. (In Korean).
- Paerl, H.W., et al., 2016. Mitigating cyanobacterial harmful algal blooms in aquatic ecosystems impacted by climate change and anthropogenic nutrients. Harmful Algae, 54, 213–222. doi: 10.1016/j.hal.2015.09.009
- Paerl, H.W., Hall, N.S., and Calandrino, E.S., 2011. Controlling harmful cyanobacterial blooms in a world experiencing anthropogenic and climatic-induced change. Science of The Total Environment, 409, 1739–1745. doi: 10.1016/j.scitotenv.2011.02.001
- Shrestha, S. and Kazama, F., 2007. Assessment of surface water quality using multivariate statistical techniques: A case study of the Fuji river basin, Japan. Environmental Modeling & Software, 22, 464–475. doi: 10.1016/j.envsoft.2006.02.001
- Singh, K.P., et al., 2004. Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)-a case study. Water Research, 38, 3980–3992. doi: 10.1016/j.watres.2004.06.011
- Singh, K.P., Malik, A., and Sinha, S., 2005. Water quality assessment and apportionment of pollution sources of Gomti river (India) using multivariate statistical techniques: a case study. Analytica Chimica Acta, 538, 355–374. doi: 10.1016/j.aca.2005.02.006
- Srivastra, A., et al., 2015. Status, Alert system, and Prediction of Cyanobacterial Bloom in South Korea. BioMed Research International, 1, 1–6.
- Varol, M., Gökot, B., and Bekleyen, A., 2012. Water quality assessment and apportionment of pollution sources of Tigris river (Turkey) using multivariate statistical techniques – a case study. River Research and Applications, 28, 1428–1438. doi: 10.1002/rra.1533
- Vega, M., Pardo, R., Barrado, E., and Deban, L., 1998. Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis. Water Research, 32, 3581–3592. doi: 10.1016/S0043-1354(98)00138-9
- Wang, Y., Wang, P., and Bai, Y.J., 2013. Assessment of surface water quality via multivariate statistical techniques: A case study of the Songhua river Harbin region, China. Journal of Hydro-Environment Research, 7, 30–40. doi: 10.1016/j.jher.2012.10.003
- Zhao, Z.W. and Cui, F.Y., 2009. Multivariate statistical analysis for the surface water quality of Luan river, China. Journal of Zhejiang University Science A, 10, 142–148.