Component analysis and temporal evaluation of water quality in the Yamuna River, Uttarakhand, India
(2026) In Frontiers in Water 8. p.1-21- Abstract
Monitoring water quality of rivers is essential in establishing the level of human impact on freshwater ecosystem, in addition to natural variability. The physicochemical, nutritional, and microbiological parameters were studied under seasonal conditions at seven different sites of the river Yamuna upper. The main mechanisms that influence the water quality were determined using descriptive statistics and Principal Component Analysis (PCA). In the present study, mean electrical conductivity (EC) ranged from 149.57 ± 62.46 μS cm−1 (summer) to 195.57 ± 87.93 μS cm−1 (winter), dissolved oxygen (DO) from 3.88 ± 0.30 mg L−1 (summer) to 10.30 ± 0.99 mg L−1(winter), and biochemical oxygen demand (BOD) from 1.59 ± 0.79 mg L−1(summer) to 1.60 ±... (More)
Monitoring water quality of rivers is essential in establishing the level of human impact on freshwater ecosystem, in addition to natural variability. The physicochemical, nutritional, and microbiological parameters were studied under seasonal conditions at seven different sites of the river Yamuna upper. The main mechanisms that influence the water quality were determined using descriptive statistics and Principal Component Analysis (PCA). In the present study, mean electrical conductivity (EC) ranged from 149.57 ± 62.46 μS cm−1 (summer) to 195.57 ± 87.93 μS cm−1 (winter), dissolved oxygen (DO) from 3.88 ± 0.30 mg L−1 (summer) to 10.30 ± 0.99 mg L−1(winter), and biochemical oxygen demand (BOD) from 1.59 ± 0.79 mg L−1(summer) to 1.60 ± 0.95 mg L−1(winter). PCA was used to indicate two to three major components among seasons, explaining over 90% of the total variability, with the first component being always mostly dominated by the variables of ionic enrichment, organic matter indicators, and microbial parameters. The latter components put emphasis on nutrient related variability especially NO3− and PO43− which denoted diffuse input. The results showed a moderate decline in water quality which was mainly caused by domestic effluents and agricultural discharge. This is a holistic statistical approach that will tell the impact of hydrological seasonality and human activities on the chemical composition of the Yamuna River.
(Less)
- author
- Sharma, Madhuben ; Rawat, Sameeksha ; Lodh, Abhishek LU ; Kumar, Pradeep ; Pathak, Vinayak Vandan and Awasthi, Amit
- organization
- publishing date
- 2026-05
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- environmental management, Himalayan Basin, multivariate statistics, principal component analysis, seasonal variation, water quality, Yamuna River
- in
- Frontiers in Water
- volume
- 8
- article number
- 1743011
- pages
- 21 pages
- publisher
- Frontiers Media S. A.
- external identifiers
-
- scopus:105040915649
- ISSN
- 2624-9375
- DOI
- 10.3389/frwa.2026.1743011
- language
- English
- LU publication?
- yes
- id
- bb8e52ee-7297-4365-a3f7-25684b65e77f
- date added to LUP
- 2026-07-03 13:11:01
- date last changed
- 2026-07-03 13:12:08
@article{bb8e52ee-7297-4365-a3f7-25684b65e77f,
abstract = {{<p>Monitoring water quality of rivers is essential in establishing the level of human impact on freshwater ecosystem, in addition to natural variability. The physicochemical, nutritional, and microbiological parameters were studied under seasonal conditions at seven different sites of the river Yamuna upper. The main mechanisms that influence the water quality were determined using descriptive statistics and Principal Component Analysis (PCA). In the present study, mean electrical conductivity (EC) ranged from 149.57 ± 62.46 μS cm−1 (summer) to 195.57 ± 87.93 μS cm−1 (winter), dissolved oxygen (DO) from 3.88 ± 0.30 mg L−1 (summer) to 10.30 ± 0.99 mg L−1(winter), and biochemical oxygen demand (BOD) from 1.59 ± 0.79 mg L−1(summer) to 1.60 ± 0.95 mg L−1(winter). PCA was used to indicate two to three major components among seasons, explaining over 90% of the total variability, with the first component being always mostly dominated by the variables of ionic enrichment, organic matter indicators, and microbial parameters. The latter components put emphasis on nutrient related variability especially NO<sub>3</sub>− and PO<sub>4</sub>3− which denoted diffuse input. The results showed a moderate decline in water quality which was mainly caused by domestic effluents and agricultural discharge. This is a holistic statistical approach that will tell the impact of hydrological seasonality and human activities on the chemical composition of the Yamuna River.</p>}},
author = {{Sharma, Madhuben and Rawat, Sameeksha and Lodh, Abhishek and Kumar, Pradeep and Pathak, Vinayak Vandan and Awasthi, Amit}},
issn = {{2624-9375}},
keywords = {{environmental management; Himalayan Basin; multivariate statistics; principal component analysis; seasonal variation; water quality; Yamuna River}},
language = {{eng}},
pages = {{1--21}},
publisher = {{Frontiers Media S. A.}},
series = {{Frontiers in Water}},
title = {{Component analysis and temporal evaluation of water quality in the Yamuna River, Uttarakhand, India}},
url = {{http://dx.doi.org/10.3389/frwa.2026.1743011}},
doi = {{10.3389/frwa.2026.1743011}},
volume = {{8}},
year = {{2026}},
}