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- Title
Research on Surface Water Quality Assessment and Its Driving Factors: A Case Study in Taizhou City, China.
- Authors
Deng, Sihe; Li, Cheng; Jiang, Xiaosan; Zhao, Tingting; Huang, Hui
- Abstract
It is necessary to assess and analyze the factors that influence surface water since they are crucial to human activities such as agriculture, raising livestock, and industry. Previous research has mostly focused on how land use and landscape patterns affect the quality of surface waters; it has seldom addressed the industrial and agricultural production activities that are directly connected to human society. Therefore, the research area's surface water quality was assessed by single factor index (SFI) and composite water quality index (WQI), divided into flood and non-flood periods, and water quality indicators with severe pollution and significant seasonal variations were selected; A total of 28 indicators were selected from three main factors-topography, socio-economic, and land use type-and analyzed using the Spearman correlation coefficient model. (1) SFI data reveal substantial seasonal changes in pH, DO, NH3-N, TN, and TP water quality indicators. The well-developed agricultural and aquaculture in the studied region is the primary cause of the excess TN and NH3-N concentrations; (2) The sample points' water quality index (WQI) scores range from 50 to 80, with 62% of them having "medium" water quality; (3) The study area's seasonal variation in water quality is primarily caused by human socio-economic activities (GDP, industrial effluent discharge, COD discharge, aquatic product quality, and the proportion of primary, secondary, and tertiary industries), as well as land use type (forest, shrubland, and cropland). Topography has little effect on the study area's surface water quality. This study offers a fresh viewpoint on surface water quality management and driver analysis, and a new framework for managing and safeguarding aquatic ecosystems.
- Subjects
CHINA; WATER quality; WATER quality management; INDUSTRIAL wastes; RANK correlation (Statistics); SURFACE area; SECONDARY forests
- Publication
Water (20734441), 2023, Vol 15, Issue 1, p26
- ISSN
2073-4441
- Publication type
Article
- DOI
10.3390/w15010026