Multivariate statistical technique in the assessment of coastal water quality of Oman

2020 ◽  
Vol 15 (3) ◽  
pp. 141-153
Author(s):  
Prerana Chitrakar ◽  
Mahad Said Baawain ◽  
Ahmad Sana ◽  
Abdullah Al-Mamun
Author(s):  
Di Zhou ◽  
Miao Yu ◽  
Junbao Yu ◽  
Yunzhao Li ◽  
Bo Guan ◽  
...  

Biotemas ◽  
2011 ◽  
Vol 23 (1) ◽  
Author(s):  
José Carlos Simonassi ◽  
Mariana Coutinho Hennemann ◽  
Dávia Talgatti ◽  
Aguinaldo Nepomuceno Marques Jr.

Author(s):  
Mohammad Mustafizur Rahman ◽  
Normawaty Mohammad Noor ◽  
Shahbudin Saad ◽  
Kamaruzzaman Yunus

2017 ◽  
Vol 2017 ◽  
pp. 1-12
Author(s):  
Chen-Lin Soo ◽  
Cheng-Ann Chen ◽  
Shabdin Mohd-Long

The study on Sarawak coastal water quality is scarce, not to mention the application of the multivariate statistical approach to investigate the spatial variation of water quality and to identify the pollution source in Sarawak coastal water. Hence, the present study aimed to evaluate the spatial variation of water quality along the coastline of the southwestern region of Sarawak using multivariate statistical techniques. Seventeen physicochemical parameters were measured at 11 stations along the coastline with approximately 225 km length. The coastal water quality showed spatial heterogeneity where the cluster analysis grouped the 11 stations into four different clusters. Deterioration in coastal water quality has been observed in different regions of Sarawak corresponding to land use patterns in the region. Nevertheless, nitrate-nitrogen exceeded the guideline value at all sampling stations along the coastline. The principal component analysis (PCA) has determined a reduced number of five principal components that explained 89.0% of the data set variance. The first PC indicated that the nutrients were the dominant polluting factors, which is attributed to the domestic, agricultural, and aquaculture activities, followed by the suspended solids in the second PC which are related to the logging activities.


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