Chemometrics data of water quality and environmental heterogeneity analysis in Pu River, China

Gao, Hongjie; Lv, Chunjian; Song, Yonghui; Zhang, Yu; Zheng, Liduan; Wen, Yujie; Peng, Jianfeng; Yu, Han‐Qing

doi:10.1007/s12665-015-4233-x

Cited by 19 publications

(15 citation statements)

References 8 publications

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“…Spring flooding is a key hydrological process in cold regions, the snowmelt is not only of considerable importance in water supply of soil and river systems, but also influences physicochemical properties of the river (Gao et al, 2015). Moreover, due to global climate change, the recession rate has been enhanced and snowfall has increased coupled with frequently occurred snowstorms, which may alter many aspects of hydrology during this period, such as flooding, erosion, hydrochemical and output (Stepanauskas et al, 2000;Ollivier et al, 2006;Vilímek et al, 2015), likewise the Songhua River Basin (Wang and He, 2013).…”

Section: Introductionmentioning

confidence: 99%

Variations of total dissolved iron and its impacts during an extreme spring flooding event in the Songhua River

Guan

Yan

Yuan

2016

Journal of Geochemical Exploration

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Section: Introductionmentioning

confidence: 99%

Variations of total dissolved iron and its impacts during an extreme spring flooding event in the Songhua River

Guan

Yan

Yuan

2016

Journal of Geochemical Exploration

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“…4 and 5). The Ward's method of agglomerative hierarchical clustering was used with squared Euclidean distance as the objective function [18,20,22,23,28,29].…”

Section: Cluster Analysismentioning

confidence: 99%

“…Principal Component Analysis provides information on the most important water quality indices that describe the entire data set by performing data reduction with minimal loss of original information carried by the data [21,22,24,28,29,45].…”

Section: Principal Component Analysis/factor Analysismentioning

confidence: 99%

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Glebokie Lake in Szczecin after hydrotechnical regulations

Miller

Svobodová

Meller

et al. 2016

Ecological Chemistry and Engineering S

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Water quality of the Glebokie Lake in Szczecin (NW-Poland) was studied in years 2012-2014. Glebokie Lake is a reservoir with a negative water balance related to the location draining groundwater drinking water intake for Szczecin agglomeration. In 2004 hydrotechnical regulations were conducted aimed at maintaining a constant amount of water in the lake, which involved a temporary feeding Glebokie Lake with Gunica River waters. In order to determine the hydrochemical status of the Lake waters and the factors shaping water quality -19 water quality indices within 25 months were measured: temperature, pH and water oxygen status, nutrients (N, P) and ionic macrocomponents and Fetot. Trophic status of the lake waters using the Carlson criteria was defined. On the basis of chemometric analysis of measurement data (CA, PCA/FA and DA) we established that statistically significant factors affecting water quality in the study period were: seasonal (the climatic seasons) changes in the biological processes activity, periodical (in April and November) waters inflows from the Gunica River, anthropopressure in during swimming season and the coagulant (FeSO4) presence in the ecosystem. The possibility of applying the chemometric techniques to interpret measurement data in the lake type like Glebokie Lake with a small amount of data has been shown.

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“…Water pollution, especially river pollution, has received increased research attention in recent years. So far, much of the literature on river pollution in China has focused on water quality of an individual river or within a single river basin, such as the Qiantang River in Zhejiang Province (Huang, Wang, Lou, Zhou, & Wu, ; Su, Xiao, Mi, et al., ; Su, Xiao, Xu, et al., ), Liao River and its tributaries in Liaoning Province (Bu, Wan, Zhang, & Meng, ; Chen, Li, Fan, & Wang, ; Gao et al., ; Yu et al., ), the Dongjiang River in Guangdong (Zhou, Wu, & Peng, ), the Yellow River (Wang et al., ), the Jin River in Fujian Province (Chen, Teng, Yue, & Song, ), Tarim River Basin (Bo, Liu, Jiao, Chen, & Cao, ), the Yangtze River in Three Gorges Dam area (Zhao, Fu, Lei, & Li, ), the Huai River (Dou, Zhang, & Li, ; Li et al., ; Zhai, Xia, & Zhang, ; Zhang, Liu, Yuan, & Wang, ; Zuo, Chen, Dou, Zhang, & Li, ), the Jinshui River in Shaanxi Province (Bu, Liu, Song, & Zhang, ), and the Xiang River Basin in Hunan Province (Xie, ). These studies revealed the extent and sources of water pollution and provided important guidance for pollution control in those basins.…”

Section: Introductionmentioning

confidence: 99%

Spatial characteristics and influencing factors of river pollution in China

Wang

et al. 2019

Water Environment Research

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Based on recent water quality data collected from 763 monitoring sections nationwide, this study examined the concentration of major pollutants in China's major rivers. A spatial autocorrelation analysis confirmed that river pollution was spatially uneven and clustered. While pollution of surface water was a nationwide concern, most serious water pollution happened in the Huai, Hai, Yellow, and Liao river Basins in Northern China. The results of the spatial regression analysis showed that GDP per capita, surface water stock, population, and economic structure were all significantly correlated with surface water pollution, with population having strongest impact, followed by level of economic development. By investigating the common characteristics shared by the “hotspot” cities where serious water pollution occurred, this study recommended a regional or basin approach to assessing water quality and controlling river pollution that cuts across jurisdiction boundaries. While China has made considerable progress in improving water productivity, there is still enormous potential in water conservation. It is also imperative to restructure local economy and develop water‐efficient, less polluting industries and services. Practitioner points River pollution in China was spatially uneven and clustered. Most serious water pollution happened in the Huai, Hai, Yellow, and Liao river basins in Northern China. GDP per capita, surface water stock, population, and economic structure correlated with surface water pollution, with population having strongest impact. A regional or basin approach was recommended to assess water quality and controlling river pollution across jurisdiction boundaries. It is also imperative to restructure local economy and develop water‐efficient, less polluting industries and services.

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Chemometrics data of water quality and environmental heterogeneity analysis in Pu River, China

Cited by 19 publications

References 8 publications

Variations of total dissolved iron and its impacts during an extreme spring flooding event in the Songhua River

Variations of total dissolved iron and its impacts during an extreme spring flooding event in the Songhua River

Glebokie Lake in Szczecin after hydrotechnical regulations

Spatial characteristics and influencing factors of river pollution in China

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