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      Application of Multivariate Statistical Analysis in Evaluation of Surface River Water Quality of a Tropical River

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      Journal of Chemistry
      Hindawi Limited

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          Abstract

          The present study evaluated the spatial variations of surface water quality in a tropical river using multivariate statistical techniques, including cluster analysis (CA) and principal component analysis (PCA). Twenty physicochemical parameters were measured at 30 stations along the Batang Baram and its tributaries. The water quality of the Batang Baram was categorized as “slightly polluted” where the chemical oxygen demand and total suspended solids were the most deteriorated parameters. The CA grouped the 30 stations into four clusters which shared similar characteristics within the same cluster, representing the upstream, middle, and downstream regions of the main river and the tributaries from the middle to downstream regions of the river. The PCA has determined a reduced number of six principal components that explained 83.6% of the data set variance. The first PC indicated that the total suspended solids, turbidity, and hydrogen sulphide were the dominant polluting factors which is attributed to the logging activities, followed by the five-day biochemical oxygen demand, total phosphorus, organic nitrogen, and nitrate-nitrogen in the second PC which are related to the discharges from domestic wastewater. The components also imply that logging activities are the major anthropogenic activities responsible for water quality variations in the Batang Baram when compared to the domestic wastewater discharge.

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          Most cited references23

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          Assessment of surface water quality using multivariate statistical techniques: A case study of the Fuji river basin, Japan

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            Understanding the influence of suspended solids on water quality and aquatic biota.

            Over the last 50 years the effects of suspended solids (SS) on fish and aquatic life have been studied intensively throughout the world. It is now accepted that SS are an extremely important cause of water quality deterioration leading to aesthetic issues, higher costs of water treatment, a decline in the fisheries resource, and serious ecological degradation of aquatic environments. As such, government-led environmental bodies have set recommended water quality guidelines for concentrations of SS in freshwater systems. However, these reference values are often spurious or based on the concept of turbidity as a surrogate measure of the concentration of SS. The appropriateness of these recommended water quality values is evaluated given: (1) the large variability and uncertainty in data available from research describing the effects of SS on aquatic environments, (2) the diversity of environments that these values are expected to relate to, and (3) the range of conditions experienced within these environments. Furthermore, we suggest that reliance solely upon turbidity data as a surrogate for SS must be treated with caution, as turbidity readings respond to factors other than just concentrations of SS, as well as being influenced by the particle-size distribution and shape of SS particles. In addition, turbidity is a measure of only one of the many detrimental effects, reviewed in this paper, which high levels of SS can have in waterbodies. In order to improve the understanding of the effects of SS on aquatic organisms, this review suggests that: First, high-resolution turbidity monitoring should be supplemented with direct, measurements of SS (albeit at lower resolution due to resource issues). This would allow the turbidity record to be checked and calibrated against SS, effectively building a rating-relationship between SS and turbidity, which would in-turn provide a clearer picture of the exact magnitude of the SS problem. Second, SS should also be characterised in terms of their particle-size distribution and chemical composition. This would provide information to develop a more comprehensive understanding of the observed variable effects of a given concentration of SS in aquatic habitats. These two suggested improvements, combined with lower-resolution concurrent measures of aquatic ecological status, would improve our understanding of the effects of SS in aquatic environments and together with a more detailed classification of aquatic environments, would provide an environment-specific evidence base for the establishment of effective water quality guidelines for SS.
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              Assessment of the surface water quality in Northern Greece.

              The application of different multivariate statistical approaches for the interpretation of a large and complex data matrix obtained during a monitoring program of surface waters in Northern Greece is presented in this study. The dataset consists of analytical results from a 3-yr survey conducted in the major river systems (Aliakmon, Axios, Gallikos, Loudias and Strymon) as well as streams, tributaries and ditches. Twenty-seven parameters have been monitored on 25 key sampling sites on monthly basis (total of 22,350 observations). The dataset was treated using cluster analysis (CA), principal component analysis and multiple regression analysis on principal components. CA showed four different groups of similarity between the sampling sites reflecting the different physicochemical characteristics and pollution levels of the studied water systems. Six latent factors were identified as responsible for the data structure explaining 90% of the total variance of the dataset and are conditionally named organic, nutrient, physicochemical, weathering, soil-leaching and toxic-anthropogenic factors. A multivariate receptor model was also applied for source apportionment estimating the contribution of identified sources to the concentration of the physicochemical parameters. This study presents the necessity and usefulness of multivariate statistical assessment of large and complex databases in order to get better information about the quality of surface water, the design of sampling and analytical protocols and the effective pollution control/management of the surface waters.
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                Author and article information

                Journal
                Journal of Chemistry
                Journal of Chemistry
                Hindawi Limited
                2090-9063
                2090-9071
                2017
                2017
                : 2017
                :
                : 1-13
                Article
                10.1155/2017/5737452
                dcf0e5e7-1fb3-437f-9708-c011d4483233
                © 2017

                http://creativecommons.org/licenses/by/4.0/

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