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黄河干流水质评价与时空变化分析
引用本文:刘彦龙,郑易安.黄河干流水质评价与时空变化分析[J].环境科学,2022,43(3):1332-1345.
作者姓名:刘彦龙  郑易安
作者单位:兰州大学资源环境学院,甘肃省环境污染预警与控制重点实验室,兰州 730000
基金项目:国家自然科学基金项目(22178156);甘肃省自然科学基金重点项目(21JR7RA441);兰州大学中央高校基本科研业务费专项-学科交叉创新团队建设项目(lzujbky-2021-ct12)
摘    要:在黄河流域生态保护的实施中,分析流域的水质污染状况以及时空变化规律,成为保证流域水安全的首要任务.为了全面了解黄河流域近年来的水环境状况,基于流域8个监测断面2004~2018年的水质数据,使用Mann-Kendall(M-K)趋势检验、层次聚类分析和主成分分析等多元数据分析方法,结合改进的综合水质标识指数(WQI),...

关 键 词:水质评价  综合水质标识指数  时空变化  层次聚类分析  主成分分析  黄河流域
收稿时间:2021/6/15 0:00:00
修稿时间:2021/8/17 0:00:00

Water Quality Assessment and Spatial-temporal Variation Analysis in Yellow River Basin
LIU Yan-long,ZHENG Yi-an.Water Quality Assessment and Spatial-temporal Variation Analysis in Yellow River Basin[J].Chinese Journal of Environmental Science,2022,43(3):1332-1345.
Authors:LIU Yan-long  ZHENG Yi-an
Institution:Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
Abstract:During the implementation of ecological protection in the Yellow River basin, understanding the water pollution status and spatio-temporal variation of water quality has become the most important thing for water safety in the basin. To analyze the water quality in recent years, the water quality data in the Yellow River basin from 2004 to 2018 were firstly collected from eight typical monitoring stations. Using a combination of multivariate data analysis methods including the Mann-Kendall (M-K) trend test, hierarchical clustering analysis (HCA), principal component analysis (PCA), and modified comprehensive water quality identification index (WQI), the spatio-temporal variation characteristics of the water quality were then explored in the Yellow River basin. The results indicated that in terms of time variation, the HCA from the water quality time series showed that the water quality of the Yellow River basin could be divided into the wet season, normal season, and dry season, being basically consistent with the hydrological period. Combined with the M-K trend test and WQI-based water quality assessment, the water quality of the Yellow River basin was improving gradually, with 2010 as the critical year. The water quality in the wet season was superior to that in the dry season. The pollution indicator NH4+-N and permanganate index were dominant in both the wet season and dry season. According to the spatial variation analysis, the water quality for all the studied stations improved significantly. Spatial clustering showed that the S6 (Shanxi Yuncheng Hejin Bridge) was obviously different from others, and further comparative study demonstrated that S6 was constantly seriously polluted. The S7 (Henan Jiyuan Xiaolangdi) exhibited different characteristics in the wet and dry season. In all stations, NH4+-N was considered to be the most common pollution indicator, whereas the permanganate index and DO were also relatively serious for S6. In different hydrological seasons, NH4+-N and the permanganate index showed different characteristics, and their variety was related to the fact that the former mainly came from domestic and industrial sources, whereas the latter was mainly derived from agricultural sources. The modified WQI showed obvious advantages over single-factor water quality assessment, and the findings from this study can provide scientific evidence for water pollution control and comprehensive water quality management in the Yellow River basin.
Keywords:water quality assessment  comprehensive water quality identification index  spatio-temporal variation  hierarchical clustering analysis  principal component analysis  Yellow River basin
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