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Citation
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HERO ID
908963
Reference Type
Journal Article
Title
Water Quality Assessment of the Mudurnu River, Turkey, Using Biotic Indices
Author(s)
Ogleni, N; Topal, B
Year
2011
Is Peer Reviewed?
1
Journal
Water Resources Management
ISSN:
0920-4741
Volume
25
Issue
10
Page Numbers
2487-2508
Language
English
DOI
10.1007/s11269-011-9822-1
Web of Science Id
WOS:000293136700008
URL
http://www.springerlink.com/index/10.1007/s11269-011-9822-1
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Abstract
In this study, the effect of domestic and industrial pollutants on the water quality of Mudurnu River was searched. Water and benthic macroinvertebrate samples were taken from five stations selected on Mudurnu River during 12 months (2006-2007). COD (Chemical Oxygen Demand), BOD (Biochemical Oxygen Demand), TKN (Total Kjeldahl Nitrogen), NO(3)(-)-N (Nitrate-Nitrogen), PO(4)(-3)-P (Phosphate-Phosphorous), NH(4)(+)-N (Ammonium-Nitrogen), Phenol data and scores of BMWP (Biological Monitoring Working Party) score system, ASPT (Average Score per Taxon), TBI (Trent Biotic Index), BBI (Belgian Biotic Index), Margalef's index (R), Shannon-Wiener diversity index (H), Simpson's diversity index (D) were determined. The relationship between data of chemical parameters and scores of biotic indices were investigated by using statistical methods. With decision tree technique, artificial neural network (ANN) and logistic regression model, chemical water quality was predicted from scores of biotic indices. A success at 67% was provided in the prediction of chemical water quality class of Mudurnu River.
Keywords
Biotic indices Water quality; Mudurnu River; Decision tree; Artificial neural network; Logistic regression
Tags
IRIS
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Nitrate/Nitrite
Supplemental LitSearch Update 1600-2015
WoS
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