title: Risk assessment of water pollution sources based on an integrated k-means clustering and set pair analysis method in the region of Shiyan, China.
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.
authors.affiliation: Key Laboratory for Water and Sediment Sciences of Ministry of Education, Beijing Normal University, Beijing 100875, China.
authors.forename: Chunhui
authors.initials: C
authors.lastname: Li
authors.affiliation: Key Laboratory for Water and Sediment Sciences of Ministry of Education, Beijing Normal University, Beijing 100875, China.
authors.forename: Lian
authors.initials: L
authors.lastname: Sun
authors.affiliation: Key Laboratory for Water and Sediment Sciences of Ministry of Education, Beijing Normal University, Beijing 100875, China; Water Conservancy Bureau of Dezhou, Dezhou 251599, China.
authors.forename: Junxiang
authors.initials: J
authors.lastname: Jia
authors.affiliation: State Key Laboratory of Water Environment Simulation, Beijing Normal University, Beijing 100875, China; Beijing Engineering Research Center for Watershed Environmental Restoration & Integrated Ecological Regulation, School of Environment, Beijing Normal University, Beijing 100875, China. Electronic address: yanpeng.cai@bnu.edu.cn.
authors.forename: Yanpeng
authors.initials: Y
authors.lastname: Cai
authors.affiliation: State Key Laboratory of Water Environment Simulation, Beijing Normal University, Beijing 100875, China; Beijing Engineering Research Center for Watershed Environmental Restoration & Integrated Ecological Regulation, School of Environment, Beijing Normal University, Beijing 100875, China.
authors.forename: Xuan
authors.initials: X
authors.lastname: Wang
mesh_terms: D002681:China; D016000:Cluster Analysis; D004784:Environmental Monitoring / Q000379:methods*; D008962:Models, Theoretical; D018570:Risk Assessment / Q000379:methods; D014874:Water Pollutants, Chemical / Q000032:analysis; D014876:Water Pollution / Q000706:statistics & numerical data*; D014881:Water Supply / Q000706:statistics & numerical data*
chemical_list: D014874:Water Pollutants, Chemical
keywords: Danjiangkou Reservoir; Risk assessment; Set pair analysis (SPA); k-means clustering