Evaluation of water quality parameters for the Mamasin dam in Aksaray City in the central Anatolian part of Turkey by means of artificial neural networks |
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Authors: | Hatim Elhatip M Aydin Kömür |
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Institution: | (1) Faculty of Engineering, Environmental Engineering Department, Aksaray University, 68100 Aksaray, Turkey;(2) Faculty of Engineering, Civil Engineering Department, Aksaray University, 68100 Aksaray, Turkey |
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Abstract: | Sustaining the human ecological benefits of surface water requires carefully planned strategies for reducing the cumulative
risks posed by diverse human activities. The municipality of Aksaray city plays a key role in developing solutions to surface
water management and protection in the central Anatolian part of Turkey. The responsibility to provide drinking water and
sewage works, regulate the use of private land and protect public health provides the mandate and authority to take action.
The present approach discusses the main sources of contamination and the result of direct wastewater discharges into the Melendiz
and Karasu rivers, which recharge the Mamasın dam sites by the use of artificial neural network (ANN) modeling techniques.
The present study illustrates the ability to predict and/or approve the output values of previously measured water quality
parameters of the recharge and discharge areas at the Mamasin dam site by means of ANN techniques. Using the ANN model is
appreciated in such environmental research. Here, the ANN is used for estimating if the field parameters are agreeable to
the results of this model or not. The present study simulates a situation in the past by means of ANN. But in case any field
measurements of some relative parameters at the outlet point “discharge area” have been missed, it could be possible to predict
the approximate output values from the detailed periodical water quality parameters. Because of the high variance and the
inherent non-linear relationship of the water quality parameters in time series, it is difficult to produce a reliable model
with conventional modeling approaches. In this paper, the ANN modeling technique is used to establish a model for evaluating
the change in electrical conductivity (EC) and dissolved oxygen (DO) values in recharge (input) and discharge (output) areas
of the dam water under pollution risks. A general ANN modeling scheme is also recommended for the water parameters. The modeling
process includes four main stages: (1) source data analysis, (2) system priming, (3) system fine-tuning and (4) model evaluation.
Results of the ANN modeling scheme indicate that the output values are agreeable to the water quality parameters, which were
measured at the field in the static water mass of the Mamasın dam lake. Water contamination at the dam site is caused by the
continuous increase of nutrient contents and decrease of the O2 level in water causing an anaerobic condition. It may stimulate algae growth flow in such water bodies, consequently reducing
water quality. |
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Keywords: | Mamasin dam Water quality parameters ANN modeling approach ANN application |
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