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 GEP  Vol.7 No.8 , August 2019
The Water Quality Evaluation in Balihe Lake Based on Principal Component Analysis
Abstract:
The water pollution situation in Balihe Lake, the biggest tributary of Shaying River Basin in Anhui Province, China, has brought a huge pressure on the improvement of water quality in Huai River. On October 16th, 2017, 11 major pollution indexes were observed at 15 sampling points in Balihe Lake. Based on the data experimentally measured, the water quality in Balihe Lake was analyzed utilizing the Principal Component Analysis (PCA) of SPSS. The result suggested that the major components were oxygenated pollutants, water eutrophication pollutants and ammonia nitrogen, in which oxygenated pollutants played a dominant role. In addition, the upper part of Balihe Lake suffered serious situation and needed a focus on oxygenated pollutants.
Cite this paper: Zhang, L. , Zhong, M. , Xu, Y. , Wang, Z. and Huang, H. (2019) The Water Quality Evaluation in Balihe Lake Based on Principal Component Analysis. Journal of Geoscience and Environment Protection, 7, 38-48. doi: 10.4236/gep.2019.78003.
References

[1]   Chang, K., Gao, J. L., Wu, W. Y., & Yuan, Y. X. (2011). Water Quality Comprehensive Evaluation Method for Large Water Distribution Network Based on Clustering Analysis. Journal of Hydroinformatics, 13, 390.
https://doi.org/10.2166/hydro.2011.021

[2]   Debels, P., Figueroa, R., Urrutia, R., Barra, R., & Niell, X. (2005). Evaluation of Water Quality in the Chillán River (Central Chile) Using Physicochemical Parameters and a Modified Water Quality Index. Environmental Monitoring and Assessment, 110, 301-322.
https://doi.org/10.1007/s10661-005-8064-1

[3]   Deng, D., & Li, Y. J. (2010). Application of Rough Set and Fuzzy Comprehensive Evaluation Method in Water Quality Assessment. In International Conference on Computing, Control and Industrial Engineering (pp. 126-128). Wuhan: IEEE.
https://doi.org/10.1109/CCIE.2010.150

[4]   Environmental Protection Administration of Peoples Republic of China (2002). Surface Water Environmental Quality Standards (GB 3838-2002). (In Chinese)

[5]   Environmental Protection Administration of Peoples Republic of China (2009). Monitoring and Analysis Methods of Water and Wastewater (4th ed.). Beijing: China Environmental Science Press. (In Chinese)

[6]   Friedman, J., Hastie, T., & Tibshirani, R. (2010). The Elements of Statistical Learning (Vol. 1, No. 10). New York: Springer.

[7]   Mena-Rivera, L., Salgado-Silva, V., Benavides-Benavides, C., Coto-Campos, J. M., & Swinscoe, T. H. A. (2017). Spatial and Seasonal Surface Water Quality Assessment in a Tropical Urban Catchment: Burío River, Costa Rica. Water, 9, 558.
https://doi.org/10.3390/w9080558

[8]   Noori, R., Berndtsson, R., Hosseinzadeh, M., Adamowski, J. F., & Abyaneh, M. R. (2019). A Critical Review on the Application of the National Sanitation Foundation Water Quality Index. Environmental Pollution, 244, 575-587.
https://doi.org/10.1016/j.envpol.2018.10.076

[9]   Olsen, R. L., Chappell, R. W., & Loftis, J. C. (2012). Water Quality Sample Collection, Data Treatment and Results Presentation for Principal Components Analysis—Literature Review and Illinois River Watershed Case Study. Water Research, 46, 3110-3122.
https://doi.org/10.1016/j.watres.2012.03.028

[10]   Ouyang, Y. (2005). Evaluation of River Water Quality Monitoring Stations by Principal Component Analysis. Water Research, 39, 2621-2635.
https://doi.org/10.1016/j.watres.2005.04.024

[11]   Sina, Z. (2017). Modification of Expected Conflicts between Drinking Water Quality Index and Irrigation Water Quality Index in Water Quality Ranking of Shared Extraction Wells Using Multi Criteria Decision Making Techniques. Ecological Indicators, 83, 368-379.
https://doi.org/10.1016/j.ecolind.2017.08.017

[12]   Singh, K. P., Malik, A., Mohan, D. 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.
https://doi.org/10.1016/j.watres.2004.06.011

[13]   Sun, X. W., Zhang, H. Y., Zhong, M. F., Wang, Z. Y., Liang, X. Q., Huang, T. S., & Huang, H. (2019). Analyses on the Temporal and Spatial Characteristics of Water Quality in a Seagoing River Using Multivariate Statistical Techniques: A Case Study in the Duliujian River, China. International Journal of Environmental Research and Public Health, 16, 1020.
https://doi.org/10.3390/ijerph16061020

[14]   Wong, H., & Hu, B. Q. (2013). Application of Interval Clustering Approach to Water Quality Evaluation. Journal of Hydrology, 491, 1-12.
https://doi.org/10.1016/j.jhydrol.2013.03.009

[15]   Wu, D. F. (2019). Application of Set Pair Model Based on Principal Component Analysis in Water Quality Evaluation. Water Conservancy Science and Technology and Economy, 25, 1-7. (In Chinese)

[16]   Yang, Y. (2010). Management of Agricultural Pollution in China: Current Status and International Experience. In International Conference on Management and Service Science (pp. 939-946). Wuhan: IEEE.
https://doi.org/10.1109/ICMSS.2010.5576720

[17]   Zhong, M. F., Zhang, H. Y., Sun, X. W., Wang, Z. Y., Tian, W., & Huang, H. (2018). Analyzing the Significant Environmental Factors on the Spatial and Temporal Distribution of Water Quality Utilizing Multivariate Statistical Techniques: A Case Study in the Balihe Lake, China. Environmental Science and Pollution Research, 25, 29418-29432.
https://doi.org/10.1007/s11356-018-2943-9

 
 
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