Spatio-Temporal Variability of Water Quality in the Upper Chao Phraya River, Thailand, between 2008 and 2018
Variability of water quality in the three largest tributaries of the Upper Chao Phraya River Basin (Ping, Nan, and Chao Phraya rivers) was examined over 11 years (2008-2018) using annual averages of 12 water quality parameters from six surface water stations. We applied two multivariate methods, nam...
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Format: | Article |
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2023
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Online Access: | https://repository.li.mahidol.ac.th/handle/123456789/83240 |
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Institution: | Mahidol University |
Summary: | Variability of water quality in the three largest tributaries of the Upper Chao Phraya River Basin (Ping, Nan, and Chao Phraya rivers) was examined over 11 years (2008-2018) using annual averages of 12 water quality parameters from six surface water stations. We applied two multivariate methods, namely a self-organizing map (SOM) and principal component analysis (PCA) to assess the spatio-temporal variation. The results revealed strong spatio-temporal patterns of water quality conditions, evidenced by three distinct clusters of samples (ANOSIM, p&L•lt;0.05). The PCA explains as much variation as possible in two dimensions, which eigenvalues of two axis is 45.08 %. The graphical PCA shows that cluster B is completely separated, while the cluster A and C overlap. Parameters in cluster A (comprising many of the Ping, Nan, and Chao Phraya samples between 2009-2018, and further separated by drought and floods years) were within the regulated standards for surface water. In cluster B, which only included the Chao Phraya stations during the dry period from 2013-2015, the water quality was affected by community waste, as indicated by high total coliform bacteria and fecal coliform bacteria. Meanwhile, cluster C comprised 2008, 2011, 2012 and 2017 samples from the Ping, Nan, and Chao Phraya rivers in high flood periods, and was further divided into two sub-clusters. It was characterized by high turbidity (121.70±47.59 NTU) and total solids (240.96±30.75 mg-1), which were caused by heavy rains and flooding. Our analyses show that the variability of water quality in the studied area was largely affected by human activities and seasonal variation. |
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