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Improved Principal Component-Fuzzy Comprehensive Assessment Coupling Model for Urban River Water Quality: A Case Study in Chongqing, China
- Source :
- Water, Vol 12, Iss 1375, p 1375 (2020), Water, Volume 12, Issue 5
- Publication Year :
- 2020
- Publisher :
- MDPI AG, 2020.
-
Abstract
- An improved principal component-fuzzy comprehensive assessment coupling model for urban river water quality is proposed, which fully considers the influence of water quality and quantity. This model can not only choose the key indexes, but also specify the spatial variation and class of water quality. This proposed model was used to assess the water quality of the Qingshui and Fenghuang streams in Chongqing, China. Data of twelve indexes used in the assessment were collected from 17 monitoring points. The assessment results show that the key indexes include TN, TP, NH3-N, CODcr, pH, DO and velocity. Water quality of 14 monitoring points is classified as class Bad V, and that of the remaining points is class V. Mainly affected by the deposition of garbage and discharge of domestic sewage, water quality of the midstream is the worst. The upstream is mainly influenced by farmland non-point source pollution and rural domestic sewage pollution. The downstream is close to the scenic area, and environmental control measures such as river dredging and artificial aeration are regularly carried out. The water quality of it is the best. The results provide valuable information that allow local environmental departments to discover the source of pollutant and formulate water resource management strategies.
- Subjects :
- Pollution
lcsh:Hydraulic engineering
principal component analysis
media_common.quotation_subject
Geography, Planning and Development
Midstream
Sewage
water quantity
Aquatic Science
Qingshui and Fenghuang streams
Biochemistry
key indexes
lcsh:Water supply for domestic and industrial purposes
lcsh:TC1-978
Quality (business)
water quality assessment
Water Science and Technology
media_common
Upstream (petroleum industry)
Pollutant
lcsh:TD201-500
business.industry
fuzzy comprehensive assessment
Environmental science
Water quality
business
Water resource management
Garbage
Subjects
Details
- Language :
- English
- ISSN :
- 20734441
- Volume :
- 12
- Issue :
- 1375
- Database :
- OpenAIRE
- Journal :
- Water
- Accession number :
- edsair.doi.dedup.....af16718aca6ec05a175c6588cc16368f