Fourteen surface water and nine surface sediment samples were collected from the Peacock River and analyzed for organochlorine pesticides (OCPs) by gas chromatograph-electron capture detector (GC-ECD). All the analyzed organochlorine pesticides, except o,p'-DDT, were detected in sediments from the Peacock River; but in the water samples, only β-HCH, HCB, p,p'-DDD, and p,p'-DDT were detected at some sites. The ranges for total OCPs in the water and sediments were from N.D. to 195 ng l( - 1) and from 1.36 to 24.60 ng g( - 1), respectively. The only existing HCH isomer in the water, β-HCH, suggested that the contamination by HCHs could be attributed to erosion of the weathered agricultural soils containing HCHs compounds. Composition analyses showed that no technical HCH, technical DDT, technical chlordanes, endosulfans, and HCB had been recently used in this region. However, there was new input of γ-HCH (lindane) into the Peacock River. The most probable source was water flowing from Bosten Lake and/or agricultural tailing water that was returned directly into the Peacock River. DDT compounds in the sediments may be derived mainly from DDT-treated aged and weathered agricultural soils, the degradation condition was aerobic and the main product was DDE. HCB in the sediment might be due to the input from Bosten Lake and the lake may act as an atmospheric deposition zone. There was no significant correlation between the concentrations of OCPs (including ∑HCH, ∑DDT, chlordanes, endosulfans, HCB and total OCPs) and the content of fine particles (<63 μm). The concentrations of OCPs were affected by salinity.
Traditional methods for hydrochemical analyses are effective but less diversified, and are constrained to limited objects and conditions. Given their poor accuracy and reliability, they are often used in complement or combined with other methods to solve practical problems. Cluster analysis is a multivariate statistical technique that extracts useful information from complex data. It provides new ideas and approaches to hydrogeochemical analysis, especially for groundwater hydrochemical classification. Hierarchical cluster analysis is the most widely used method in cluster analysis. This study compared the advantages and disadvantages of six hierarchical cluster analysis methods and analyzed their objects, conditions, and scope of application. The six methods are: The single linkage, complete linkage, median linkage, centroid linkage, average linkage (including between-group linkage and within-group linkage), and Ward’s minimum-variance. Results showed that single linkage and complete linkage are unsuitable for complex practical conditions. Median and centroid linkages likely cause reversals in dendrograms. Average linkage is generally suitable for classification tasks with multiple samples and big data. However, Ward’s minimum-variance achieved better results for fewer samples and variables.
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