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Article

Multivariate Statistical Analysis of Water Quality and Trophic State in an Artificial Dam Reservoir

Department of Bioscience and Biotechnology, Chungnam National University, Daejeon 34134, Korea
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Author to whom correspondence should be addressed.
Water 2021, 13(2), 186; https://doi.org/10.3390/w13020186
Received: 9 November 2020 / Revised: 21 December 2020 / Accepted: 10 January 2021 / Published: 14 January 2021
(This article belongs to the Special Issue Assessing Water Quality by Statistical Methods)
Paldang Reservoir, located in the Han River basin in South Korea, is used for drinking water, fishing, irrigation, recreation, and hydroelectric power. Therefore, the water quality of the reservoir is of great importance. The main objectives of this study were to evaluate spatial and seasonal variations of surface water quality in the reservoir using multivariate statistical techniques (MSTs) along with the Trophic State Index (TSI) and Trophic State Index deviation (TSID). The empirical relationships among nutrients (total phosphorus, TP; total nitrogen, TN), chlorophyll-a (CHL-a), and annual variations of water quality parameters were also determined. To this end, 12 water quality parameters were monitored monthly at five sites along the reservoir from 1996 to 2019. Most of the parameters (all except pH, dissolved oxygen (DO), and total coliform bacteria (TCB)) showed significant spatial variations, indicating an influence of anthropogenic activities. Principal component analysis combined with factor analysis (PCA/FA) suggested that the parameters responsible for water quality variations were primarily correlated with nutrients and organic matter (anthropogenic), suspended solids (both natural and anthropogenic), and ionic concentrations (both natural and anthropogenic). Stepwise spatial discriminant analysis (DA) identified water temperature (WT), DO, electrical conductivity (EC), chemical oxygen demand (COD), the ratio of biological oxygen demand (BOD) to COD (BOD/COD), TN, TN:TP, and TCB as the parameters responsible for variations among sites, and seasonal stepwise DA identified WT, BOD, and total suspended solids (TSS) as the parameters responsible for variations among seasons. COD has increased (R2 = 0.63, p < 0.01) in the reservoir since 1996, suggesting that nonbiodegradable organic loading to the water body is rising. The empirical regression models of CHL-a-TP (R2 = 0.45) and CHL-a-TN (R2 = 0.27) indicated that TP better explained algal growth than TN. The mean TSI values for TP, CHL-a, and Secchi depth (SD) indicated a eutrophic state of the reservoir for all seasons and sites. Analysis of TSID suggested that blue-green algae dominated the algal community in the reservoir. The present results show that a significant increase in algal chlorophyll occurs during spring in the reservoir. Our findings may facilitate the management of Paldang Reservoir. View Full-Text
Keywords: multivariate statistical methods; Trophic State Index; water quality; empirical model; Paldang Reservoir multivariate statistical methods; Trophic State Index; water quality; empirical model; Paldang Reservoir
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MDPI and ACS Style

Mamun, M.; Kim, J.Y.; An, K.-G. Multivariate Statistical Analysis of Water Quality and Trophic State in an Artificial Dam Reservoir. Water 2021, 13, 186. https://doi.org/10.3390/w13020186

AMA Style

Mamun M, Kim JY, An K-G. Multivariate Statistical Analysis of Water Quality and Trophic State in an Artificial Dam Reservoir. Water. 2021; 13(2):186. https://doi.org/10.3390/w13020186

Chicago/Turabian Style

Mamun, Md; Kim, Ji Y.; An, Kwang-Guk. 2021. "Multivariate Statistical Analysis of Water Quality and Trophic State in an Artificial Dam Reservoir" Water 13, no. 2: 186. https://doi.org/10.3390/w13020186

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