Statistical Analysis of Bursa Nilufer Creek’s Water Quality Parameters for Period of 2002-2010

Yolcu, İpek Diğdem; Karaer, Feza; Işiğiçok, Erkan; Albek, Erdem

doi:10.4236/jep.2012.328111

JEP

2012

DOI: 10.4236/jep.2012.328111

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Statistical Analysis of Bursa Nilufer Creek’s Water Quality Parameters for Period of 2002-2010

İpek Diğdem Yolcu¹,

Feza Karaer²,

Erkan Işiğiçok³

et al.

Abstract: Increasing contamination of water resources in the world and our country and decreasing water quality over time, not having met the objectives of utilization of water resources; it has increased the importance of water management. The monitoring of the water resources and evaluation of these monitoring results have given direction to the studies' outcome in order to control factors that pollute water resources and reduce water quality. Nilüfer Creek is very important for both being a source of drinking and pot… Show more

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“…This can be done using statistical analysis. This method has been used in determining whether seasonal or spatial variability is more pronounced in the River Benue in Nigeria (Eneji et al, 2012) and to describe parameters important for water quality in the Nilűfer Creek in Turkey (Yolcu et al, 2012). Another example is a study performed by Nnane et al (2011), where cost-effective monitoring of fecal pollution was achieved by identifying bacteriological indices with the use of statistical analysis.…”

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Reducing Monitoring Costs in Industrially Contaminated Rivers: Cluster and Regression Analysis Approach

et al. 2014

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Monitoring contamination in river water is an expensive procedure, particularly for developing countries where pollution is a significant problem. This study was conducted to provide a pollution monitoring strategy that reduces the cost of laboratory analysis. The new monitoring strategy was designed as a result of cluster and regression analysis on field data collected from an industrially influenced river. Pollution sources in the study site were coal mining, metallurgy, chemical industry, and metropolitan sewage. This river resembles those in other areas of the world, including developing countries where environmental monitoring is financially constrained. Data were collected on variability of contaminant concentrations during four seasons at the same points on tributaries of the river. The variables described in the study are pH, electrical conductivity, inorganic ions, trace elements, and selected organic pollutants. These variables were divided into groups using cluster analysis. These groups were then tested using regression models to identify how the behavior of one variable changes in relation to another. It was found that up to 86.8% of variability of one parameter could be determined by another in the dataset. We adopted 60, 65, and 70% determination levels () for accepting a regression model. As a result, monitoring could be reduced by 15 (60% level) and 10 variables (65 and 70%) out of 43, which comprises 35 and 23% of the monitored variable total. Cost reduction would be most effective if trace elements or organic pollutants were excluded from monitoring because these are the constituents most expensive to analyze.

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Reducing Monitoring Costs in Industrially Contaminated Rivers: Cluster and Regression Analysis Approach

et al. 2014

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Epilithic diatom assemblages and their relationships with environmental variables in the Nilüfer Stream Basin, Bursa, Turkey

Karacaoğlu

Dalkıran

2017

Environ Monit Assess

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Patterns of epilithic diatom species distribution in relation to environmental variables from 12 sampling sites on the main stream and some of its tributaries in the Nilüfer Stream Basin were determined using multivariate statistical techniques. The stream basin has been heavily influenced by anthropogenic effects. The upper part of the basin that is distant from pollution sources mostly has a spring water quality, while the lower part where the stream flows through the urban area and receives domestic and industrial wastewater has a quite low quality. Ordination techniques using both diatom taxa and 21 environmental variables revealed non- to slightly polluted upper basin sites and highly polluted lower basin sites along the stream. The results showed that the stream catchment is polluted gradually from upstream to downstream and that most of the downstream sites have very low water quality especially in summer months. A total of 134 epilithic diatom taxa belonging to 50 genera were recorded for 12 sample sites. Partial CCA results indicated that water temperature (T), discharge (Q), and total phosphorus (TP) were the most important variables affecting the distribution of diatom species. Unpolluted or slightly polluted upper basin sites were dominated by Achnanthidium minutissimum, Cocconeis placentula var. euglypta, Gomphonema olivaceum, and Navicula tripunctata. Highly polluted lower basin sites were characterized by high levels of organic and inorganic matters and low dissolved oxygen (DO) values. Species widespread in the highly polluted lower basin sites such as Nitzschia umbonata, Nitzschia amphibia, Nitzschia capitellata, Nitzschia palea, Nitzschia paleacea, Luticola mutica, and Stephanodiscus niagarae were mostly related to pollution indicator variables such as ammonium nitrogen (NH-N), sodium (Na), total phosphorus (TP), and total organic matter (TOM).

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Statistical assessment of seasonal variations in water quality for different regions in Lake Van (Türkiye)

Turan

Aldemır

2022

Environ Monit Assess

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Statistical Analysis of Bursa Nilufer Creek’s Water Quality Parameters for Period of 2002-2010

Cited by 3 publications

References 1 publication

Reducing Monitoring Costs in Industrially Contaminated Rivers: Cluster and Regression Analysis Approach

Reducing Monitoring Costs in Industrially Contaminated Rivers: Cluster and Regression Analysis Approach

Epilithic diatom assemblages and their relationships with environmental variables in the Nilüfer Stream Basin, Bursa, Turkey

Statistical assessment of seasonal variations in water quality for different regions in Lake Van (Türkiye)

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