Water Quality Assessment of the Mudurnu River, Turkey, Using Biotic Indices

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), <InlineEquation ID="IEq1"> <EquationSource Format="TEX">${\rm{NO}}_{3}^{-}$</EquationSource> </InlineEquation>–N (Nitrate–Nitrogen), <InlineEquation ID="IEq2"> <EquationSource Format="TEX">${\rm{PO}}_{4}^{-3}$</EquationSource> </InlineEquation>–P (Phosphate–Phosphorous), <InlineEquation ID="IEq3"> <EquationSource Format="TEX">${\rm{NH}}_{4}^{+}$</EquationSource> </InlineEquation>–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. Copyright Springer Science+Business Media B.V. 2011