Spatio-temporal variation of heavy metals in fresh water after dam construction: a case study of the Manwan Reservoir, Lancang River

Zhao, Qinghe; Liu, Shiliang; Deng, Li; Zhang, Yang; Dong, Shikui; Zhang, Zhaoling

doi:10.1007/s10661-011-2260-y

Cited by 48 publications

(16 citation statements)

References 59 publications

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“…Reservoir in comparison with other reservoirs of Central Asia [23,24] and referenced mountain reservoirs of Kazakhstan. It is also necessary to take into account that the runoff of the Syrdarya River and its tributaries is formed in the mountainous part of the basin, which includes groundwater.…”

Section: Discussionmentioning

confidence: 99%

Statistical approach to estimate the anthropogenic sources of potentially toxic elements on the shardara reservoir (Kazakhstan)

Krupa¹,

Ss²,

Amirgaliev³

et al. 2017

MOJES

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In June of 2015, we investigated the distribution of biogenic elements, heavy metals, and pesticides in the waters of the Shardara Reservoir. The average content of ammonium, nitrates, nitrites and phosphates in the water did not exceed the limit values set for the fishery water bodies. Zinc concentration in the water averaged 0.121, copper -0.040, cadmium -0.003, lead -0.034 mgdm -3 , isomers of hexachlorcyclohexane (HCCH) -0.0041 mg dm -3 . Wafer plots were built in order to identify the distribution correlation of hydro-chemical and toxic variables with the sources of pollution in Shardara reservoir, and statistical methods were used as well (correlation, multiple regression analysis methods, canonical correspondence analysis, and ecological mapping with the Statistica 12.0 Program). It was found that copper, nitrates, and isomers of HCCH enter the reservoir mainly with the drainage water discharged from irrigated fields along the southern bank. The source of mineral phosphorus, polyphosphates, nitrites and zinc is the river runs off rom the east. High concentration of heavy metals in the water could also be related to natural causes, as the water reservoir and its tributaries are located in a metallogenic province.

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Section: Discussionmentioning

confidence: 99%

Statistical approach to estimate the anthropogenic sources of potentially toxic elements on the shardara reservoir (Kazakhstan)

Krupa¹,

Ss²,

Amirgaliev³

et al. 2017

MOJES

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“…Water pollution caused both by anthropogenic activities such as urbanization [4], industrial accidents [5][6][7], dam construction [8], and natural phenomena like soil erosion [9] and climate The basin lies in a subtropical wet climate zone with a distinct alternation from a wet to a dry season (see Figure 2) with an annual mean precipitation of 1710 mm and annual mean temperature of 17.5˝C. Water resources in the Poyang Lake Basin are rich, but water managers now face a series of difficulties as the awareness of global climate impacts on precipitation patterns increases.…”

Section: Introductionmentioning

confidence: 99%

Water Quality Assessment and Pollution Source Identification of the Eastern Poyang Lake Basin Using Multivariate Statistical Methods

Duan

Nover³

et al. 2016

Sustainability

189

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Multivariate statistical methods including cluster analysis (CA), discriminant analysis (DA) and component analysis/factor analysis (PCA/FA), were applied to explore the surface water quality datasets including 14 parameters at 28 sites of the Eastern Poyang Lake Basin, Jiangxi Province of China, from January 2012 to April 2015, characterize spatiotemporal variation in pollution and identify potential pollution sources. The 28 sampling stations were divided into two periods (wet season and dry season) and two regions (low pollution and high pollution), respectively, using hierarchical CA method. Four parameters (temperature, pH, ammonia-nitrogen (NH 4 -N), and total nitrogen (TN)) were identified using DA to distinguish temporal groups with close to 97.86% correct assignations. Again using DA, five parameters (pH, chemical oxygen demand (COD), TN, Fluoride (F), and Sulphide (S)) led to 93.75% correct assignations for distinguishing spatial groups. Five potential pollution sources including nutrients pollution, oxygen consuming organic pollution, fluorine chemical pollution, heavy metals pollution and natural pollution, were identified using PCA/FA techniques for both the low pollution region and the high pollution region. Heavy metals (Cuprum (Cu), chromium (Cr) and Zinc (Zn)), fluoride and sulfide are of particular concern in the study region because of many open-pit copper mines such as Dexing Copper Mine. Results obtained from this study offer a reasonable classification scheme for low-cost monitoring networks. The results also inform understanding of spatio-temporal variation in water quality as these topics relate to water resources management.

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“…In this study, Fe was used as the reference element because it mainly originates from natural lithogenic sources, its distribution is not related to other heavy metals and this element is commonly used as reference element in the assessment of EF [35,36]. The levels of heavy metal pollution were interpreted according to [37] with EF < 1.50 as no enrichment, 1.50 < EF < 3.00 as minor enrichment, and 3.00 < EF < 5.00 as moderate enrichment.…”

Section: Methodsmentioning

confidence: 99%

Reservoir’s Impact on the Water Chemistry of the Teesta River Mountain Course (Darjeeling Himalaya)

Wiejaczka

Prokop

Kozłowski

et al. 2018

Ecological Chemistry and Engineering S

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Spatio-temporal variation of heavy metals in fresh water after dam construction: a case study of the Manwan Reservoir, Lancang River

Cited by 48 publications

References 59 publications

Statistical approach to estimate the anthropogenic sources of potentially toxic elements on the shardara reservoir (Kazakhstan)

Statistical approach to estimate the anthropogenic sources of potentially toxic elements on the shardara reservoir (Kazakhstan)

Water Quality Assessment and Pollution Source Identification of the Eastern Poyang Lake Basin Using Multivariate Statistical Methods

Reservoir’s Impact on the Water Chemistry of the Teesta River Mountain Course (Darjeeling Himalaya)

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