Assessment of the Surface Water Quality of the Gomti River, India, Using Multivariate Statistical Methods

被引:5
作者
Kushwah, Vinod Kumar [1 ]
Singh, Kunwar Raghvendra [1 ]
Gupta, Nakul [1 ]
Berwal, Parveen [2 ]
Alfaisal, Faisal M. [3 ]
Khan, Mohammad Amir [2 ]
Alam, Shamshad [3 ]
Qamar, Obaid [4 ]
机构
[1] GLA Univ, Dept Civil Engn, Mathura 281406, India
[2] Galgotias Coll Engn & Technol, Dept Civil Engn, Greater Noida 201310, India
[3] King Saud Univ, Coll Engn, Dept Civil Engn, Riyadh 11421, Saudi Arabia
[4] Yeungnam Univ, Dept Environm Sci & Engn, Gyongsan 38541, South Korea
关键词
Gomti Basin; water quality; cluster analysis; principal component analysis; ARTIFICIAL NEURAL-NETWORK; GROUNDWATER QUALITY; SEASONAL-VARIATIONS; BASIN; SOUTH;
D O I
10.3390/w15203575
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In the present study, the quality of the surface water of the Gomti river (Lucknow, India) was investigated. Lucknow is situated in the centre of Uttar Pradesh, which is most the populated state in India. The locality has experienced rapid, unregulated development activities and population growth in recent decades, both of which have had a negative impact on its ecosystem and environment. Continuous monitoring is required to maintain the ecosystem at the desired level. Nine samples of river water were collected from the Gomti River in Lucknow, and they were analysed for a total of nine different characteristics, including pH, turbidity (Tur), dissolved oxygen (DO), total dissolved solids (TDSs), chemical oxygen demand (COD), chloride ion (Cl-) concentration, temperature (T), biochemical oxygen demand (BOD5) and total hardness (TH). The observed data were analysed using multivariate statistical methods. A cluster analysis (CA) was used to sort the sampling locations into different groups, and a principal component analysis (PCA) was used to find the different sources of pollution. Using a cluster analysis, all the water quality parameters were divided into three groups. Cluster 1 represented the less polluted sites, cluster 2 represented the moderately polluted sites and cluster 3 represented the highly polluted sites. Sampling sites SS8, SS4, S99 and SS7 were highly polluted because of nearby pollution sources such as domestic wastewater and runoff storm water. The principal component analysis yielded two meaningful components that explained 82.4% of the total variation in the data. The first factor and second factor explained 59.022 and 23.363 percentages of the total variance, respectively. It was noticed that major sources of pollution for the Gomti river are storm water runoff and the release of domestic and industrial wastewater from residents and industries, respectively. This study will help policy makers to ensure sustainable practices and reduce negative impacts on the availability and quality of water, allowing for the most efficient use of the Gomti River.
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页数:13
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