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Identification of long-term trends and seasonality in high-frequency water quality data from the Yangtze River basin, China

机译:识别中国长江流域高频水质数据的长期趋势和季节性

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摘要

Comprehensive understanding of the long-term trends and seasonality of water quality is important for controlling water pollution. This study focuses on spatio-temporal distributions, long-term trends, and seasonality of water quality in the Yangtze River basin using a combination of the seasonal Mann-Kendall test and time-series decomposition. The used weekly water quality data were from 17 environmental stations for the period January 2004 to December 2015. Results show gradual improvement in water quality during this period in the Yangtze River basin and greater improvement in the Uppermost Yangtze River basin. The larger cities, with high GDP and population density, experienced relatively higher pollution levels due to discharge of industrial and household wastewater. There are higher pollution levels in Xiang and Gan River basins, as indicated by higher NH4-N and CODMn concentrations measured at the stations within these basins. Significant trends in water quality were identified for the 2004–2015 period. Operations of the three Gorges Reservoir (TGR) enhanced pH fluctuations and possibly attenuated CODMn, and NH4-N transportation. Finally, seasonal cycles of varying strength were detected for time-series of pollutants in river discharge. Seasonal patterns in pH indicate that maxima appear in winter, and minima in summer, with the opposite true for CODMn. Accurate understanding of long-term trends and seasonality are necessary goals of water quality monitoring system efforts and the analysis methods described here provide essential information for effectively controlling water pollution.
机译:全面了解水质的长期趋势和季节性对于控制水污染很重要。本研究结合季节性Mann-Kendall检验和时间序列分解,研究长江流域的时空分布,长期趋势和水质的季节性。使用的每周水质数据来自2004年1月至2015年12月的17个环境站。结果表明,在此期间,长江流域的水质逐渐改善,而长江上游流域的水质得到较大改善。具有较高GDP和人口密度的较大城市由于排放工业和家庭废水而遭受了相对较高的污染水平。湘江和赣江流域的污染水平较高,这两个流域内的站点测得的NH4-N和CODMn浓度较高。在2004年至2015年期间,确定了水质的重大趋势。三峡水库(TGR)的运行增加了pH的波动,并可能减弱了CODMn和NH4-N的运输。最后,对于河流排放中污染物的时间序列,检测到强度变化的季节性循环。 pH值的季节性模式表明,最大值出现在冬季,而最小值出现在夏季,而CODMn则相反。准确了解长期趋势和季节性是水质监测系统工作的必要目标,此处介绍的分析方法为有效控制水污染提供了重要信息。

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