River water salinity impact on drinking water treatment plant performance using artificial neural network
Other Title(s)
تأثير ملوحة مياه النهر على أداء محطة معالجة مياه الشرب باستخدام الشبكة العصبية الصناعية
Joint Authors
al-Ubaydi, Basim Husayn Khudayr
Abbas, Sabirin Haydar
Jafar, Mahdi Shanshal
Source
Issue
Vol. 25, Issue 8 (31 Aug. 2019), pp.149-159, 11 p.
Publisher
University of Baghdad College of Engineering
Publication Date
2019-08-31
Country of Publication
Iraq
No. of Pages
11
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
Topics
Abstract EN
The river water salinity is a major concern in many countries, and salinity can be expressed as total dissolved solids.
So, the water salinity impact of the river is one of the major factors effects of water quality.
Tigris river water salinity increase with streamline and time due to the decrease in the river flow and dam construction from neighboring countries.
The major objective of this research to developed salinity model to study the change of salinity and its impact on the Al-Karkh, Sharq Dijla, Al-Karama, Al-Wathba, Al-Dora, and Al-Wihda water treatment plant along Tigris River in Baghdad city using artificial neural network model (ANN).
The parameter used in a model built is (Turbidity, Ec, T.s, S.s, and TDS in) to predict the salinity TDSout.
Results showed that the effectiveness of the artificial neural network model to predicting the salinity is a good agreement between observed and the predicted value of the TDS, through the determination coefficient of the model is (0.998, 0.966, 0.997, 0.998, 0.996, and 0.996) for Al.
Karkh, Sharq Dijla, Al.Karama, Al.Wathba, Al.Dora and Al.Wihda respectively.
From this value can be shown that ANN is a successful tool for predicting the nonlinear equation of the salinity under different and complicated environmental case along the river.
American Psychological Association (APA)
Abbas, Sabirin Haydar& al-Ubaydi, Basim Husayn Khudayr& Jafar, Mahdi Shanshal. 2019. River water salinity impact on drinking water treatment plant performance using artificial neural network. Journal of Engineering،Vol. 25, no. 8, pp.149-159.
https://search.emarefa.net/detail/BIM-891323
Modern Language Association (MLA)
Abbas, Sabirin Haydar…[et al.]. River water salinity impact on drinking water treatment plant performance using artificial neural network. Journal of Engineering Vol. 25, no. 8 (Aug. 2019), pp.149-159.
https://search.emarefa.net/detail/BIM-891323
American Medical Association (AMA)
Abbas, Sabirin Haydar& al-Ubaydi, Basim Husayn Khudayr& Jafar, Mahdi Shanshal. River water salinity impact on drinking water treatment plant performance using artificial neural network. Journal of Engineering. 2019. Vol. 25, no. 8, pp.149-159.
https://search.emarefa.net/detail/BIM-891323
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 159
Record ID
BIM-891323