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Risk assessment of water pollution sources based on an integrated k-means clustering and set pair analysis method in the region of Shiyan, China.
- Source :
-
Science of the Total Environment . Jul2016, Vol. 557, p307-316. 10p. - Publication Year :
- 2016
-
Abstract
- Source water areas are facing many potential water pollution risks. Risk assessment is an effective method to evaluate such risks. In this paper an integrated model based on k -means clustering analysis and set pair analysis was established aiming at evaluating the risks associated with water pollution in source water areas, in which the weights of indicators were determined through the entropy weight method. Then the proposed model was applied to assess water pollution risks in the region of Shiyan in which China's key source water area Danjiangkou Reservoir for the water source of the middle route of South-to-North Water Diversion Project is located. The results showed that eleven sources with relative high risk value were identified. At the regional scale, Shiyan City and Danjiangkou City would have a high risk value in term of the industrial discharge. Comparatively, Danjiangkou City and Yunxian County would have a high risk value in terms of agricultural pollution. Overall, the risk values of north regions close to the main stream and reservoir of the region of Shiyan were higher than that in the south. The results of risk level indicated that five sources were in lower risk level (i.e., level II), two in moderate risk level (i.e., level III), one in higher risk level (i.e., level IV) and three in highest risk level (i.e., level V). Also risks of industrial discharge are higher than that of the agricultural sector. It is thus essential to manage the pillar industry of the region of Shiyan and certain agricultural companies in the vicinity of the reservoir to reduce water pollution risks of source water areas. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00489697
- Volume :
- 557
- Database :
- Academic Search Index
- Journal :
- Science of the Total Environment
- Publication Type :
- Academic Journal
- Accession number :
- 114990238
- Full Text :
- https://doi.org/10.1016/j.scitotenv.2016.03.069