scholarly journals Interpretation of the results of surface water quality applying multivariate analysis

2015 ◽  
Vol 69 (1) ◽  
pp. 29-36 ◽  
Author(s):  
Borko Matijevic ◽  
Djendji Vastag ◽  
Milena Becelic-Tomin ◽  
Bozo Dalmacija ◽  
Suzana Apostolov

Monitoring of surface water, through the analysis of physical-chemical and chemical parameters is a very important factor in the control of water quality and the health of living beings. Surface water quality is largely determined by the nature (atmospherics) and anthropogenic processes (discharge of municipal and industrial waste water). The results of monitoring of surface water are usually too expensive and difficult for correct interpreting, due to the spatial and temporal variations in water quality. By applying Multivariate statistical analysis can achieve significant reductions of the ampleness of the available data and the better interpretation of the obtained results about the quality and ecological status/potential of water. In this paper, were analyzed selected results of the analysis of surface water in AP Vojvodina in 2011 year by using multivariate statistical analysis (cluster analysis and principal components analysis). These techniques allow the interpretation of the results of the monitoring program of investigated surface water bodies and simultaneous identification of registered influence and potential sources of pollution on the quality of the given water bodies. With both methods applied and the division of water bodies tested in the same manner at the origin (natural and artificial) and on the basis of territorial belonging monitoring stations (Banat and Backa). Individual variations are discussed in corresponding differences in individual measuring stations in relation to others. Application of the given method, a grouping of the examined indicators of water quality in the following factors: hydro-chemical factor, ecological factor, the factor point pollution and diffusion. The obtained results confirm the initial hypothesis that the use of different statistical methods can identify the main factors that have an impact on the ecological status and ecological potential of water bodies and to improve the existing monitoring. In addition, analysis of the extracted surface water bodies where it is necessary to implement simultaneous monitoring of the biological quality elements to determine whether chemical parameters ensure the functioning of ecosystems.

Author(s):  
Matias Bonansea ◽  
Raquel Bazán ◽  
Susana Ferrero ◽  
Claudia Rodríguez ◽  
Claudia Ledesma ◽  
...  

2020 ◽  
Vol 24 (10) ◽  
pp. 67-71
Author(s):  
A.I. Kurbatova ◽  
A.D. Dalidenok ◽  
K.Yu. Mikhaylichenko ◽  
E.V. Savenkova ◽  
E.V. Kruglikova ◽  
...  

The impact of Moscow Domodedovo Airport wastewater on nearby surface water bodies, nameless streams which are tributaries of the Gnilusha and Muranikha rivers was investigated. Water quality was assessed by 16 indicators, the Specific Combinatorial Water Pollution Index (SCWPI) was also calculated. The quality degree of the studied reservoirs was determined.


Author(s):  
Nguyen Huu Hue ◽  
◽  
Nguyen Huu Thanh

The aim of this study is to assess the spatial variability and to determine the main contamination sources in surface water quality of the Nhue River, Viet Nam by using multivariate statistical analysis techniques, including principal component analysis (PCA) and cluster analysis (CA). Eight water quality parameters were measured at 21 sites along the Nhue River and its tributaries during irrigated periods from 2016 to 2019. The spatial variability of water quality in the Nhue River and its tributaries was determined separately from cluster analysis. The result determined two tributaries, including Yen Xa Canal (NT9 monitoring site) and To Lich River (NT3 monitoring site) leading to severe pollution at To Bridge (N4 monitoring site) region in the Nhue River. The PCA determined a reduced number of two principal components that explained 47.75% of the total variation in the data. The first PC indicated that water temperature (WT) and pH are the dominant polluting factors which are attributed to craft villages, domestic sewage and industrial wastewater. Following is nitrate nitrogen NO3¯ in the second PC which is related to fertilizer application in the farms nearby. The results indicated that CA multivariate statistical analysis technique is useful for the assessment of the spatial water quality variability in a river which has a number of tributaries.


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