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Prediction of Raw Water Turbidity at the Intakes of the Water Treatment Plants along Tigris River in Baghdad, Iraq using Frequency Analysis
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Different frequency distributions models were fitted to the monthly data of raw water Turbidity at water treatment plants (WTPs) along Tigris River in Baghdad. Eight water treatment plants in Baghdad were selected, with raw water turbidity data for the period (2008-2014). The frequency distribution models used in this study are the Normal, Log-normal, Weibull, Exponential and two parameters Gamma type. The Kolmogorov-Smirnov test was used to evaluate the goodness of fit. The data for years (2008-2011) were used for building the models. The best fitted distributions were Log-Normal (LN) for Al-Karkh, Al-Wathbah, Al-Qadisiya, Al- Dawrah and, Al-Rashid WTPs. Gamma distribution fitted well for East Tigris and Al-Karamah WTPs. As for Al-Wehda WTP Weibull distributions, was the best model. The best fitted distributions were used to forecast ten sets of monthly data for each plant that were compared with the observed data for years (2012-2014). The Kolmogorov-Smirnov test results indicated the capability of these models to produce data that has the same frequency distribution of the observed data. Moreover the frequency of occurrence of the observed and generated series in each plant indicated the capability of the model to produce results with frequency occurrence of probabilities of turbidity values > 50, 80, 100, 120, and 150 NTU.

Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
An Environmental Study of Epiphytic Algae on Ceratophyllum demersum in Tigris River within Baghdad City, Iraq
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The present study was conducted in the Tigris River within Baghdad (University of Baghdad campus). The study included some physicochemical parameters and qualitative of epiphytic algae on the host plant (Ceratophyllum demersum) during summer season 2013. The results revealed that the study area was alkaline, hard and oxygenated water. A total of 105 taxa of epiphytic algae was identified. Bacillariophyceae diatoms composed 44.7% of the total and were represented by 42.4% of the order Pennales and 1.9 %of the order Centrales. Chlorophyceae composed 32.3%, followed by Cyanophyceae composed 22.8 % of the total. The total number of epiphytic algae was fluctuated among the study period. Most of the identified algae were benthos type and a few

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Morphological and Molecular Identification of Limnodrilus Claparede,1862 Species(clitellata: naiDIDAE) IN Tigris River, Baghdad/Iraq
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Sludge worm samples were collected from the Tigers River sediment during the period from November 2018 to June 2019 in Al Sarafiya District/ Baghdad- Iraq. Biometric morphological measurements focusing on the form of penis sheath and chaetal morphology were used for species identification, in addition to molecular analysis by amplification of conserved 18s rRNA encoding gene using ITS1 and ITS4 universal primers.According to the morphological measurement records, the results revealed the existence of Limnodrilus hoffmeisteri Claparede 1862, L. claparedeianus Ratzel, 1868 and L. cervix Brinkhurst 1963. Other two groups of specimens, with short penis sheath, were identified by molecular technology as L

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Publication Date
Sun May 01 2016
Journal Name
Journal Of Engineering
Prediction of Ryznar Index for the treated water from WTPs on Al-Karakh side of Baghdad City using Artificial Neural Network (ANN) technique
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In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Produced Water Treatment Using Ultrafiltration and Nanofiltration Membranes
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The application of ultrafiltration (UF) and nanofiltration (NF) processes in the handling of raw produced water have been investigated in the present study. Experiments of both ultrafiltration and nanofiltration processes are performed in a laboratory unit, which is operated in a cross-flow pattern. Various types of hollow fiber membranes were utilized in this study such as poly vinyl chloride (PVC) UF membrane, two different polyether sulfone (PES) NF membranes, and poly phenyl sulfone PPSU NF membrane. It was found that the turbidity of the treated water is higher than 95 % by using UF and NF membranes. The chemical oxygen demand COD (160 mg/l) and Oil content (26.8 mg/l) were found after treatment according to the allowable limits set

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Water Quality Assessment and Total Dissolved Solids Prediction using Artificial Neural Network in Al-Hawizeh Marsh South of Iraq
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The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The develope

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Engineering/
Water quality assessment and total dissolved solids prediction using artificial neural network in Al-Hawizeh marsh south of Iraq
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The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Application of Artificial Neural Network for Predicting Iron Concentration in the Location of Al-Wahda Water Treatment Plant in Baghdad City
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Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Engineering
Artificial Neural Networks Modeling of Total Dissolved Solid in the Selected Locations on Tigris River, Iraq
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The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge

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Publication Date
Mon Aug 07 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Equilibrium Isotherm Removal OF Chromium From Waste Water By Aquatic Plants Using Batch Process Adsorption
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      This study was carried out in Baghdad (Al-Jadiriya) in 2006 by  detecting ability of aquatic reed plant to remove heavy metals (Chromium) from waste water by batch process of adsorption with considering that acidic solution is best selection for such process with constant initial chromium concentration(60 mg/l),speed of shaking(300 rpm), temperature (30 Co) and constant contact time (4 h) but with different weights of adsorbent (reed) (0.5 ,1 ,2 ,3 and 4 )gm for each 100 ml volume of sample .          The results showed that the percentage of the removed chromium were ( 8% ,17.5% ,31% ,40% and 50%) respectively for each sample according to the mass of adsorb

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Publication Date
Tue Feb 22 2022
Journal Name
Water
Subsurface Flow Phytoremediation Using Barley Plants for Water Recovery from Kerosene-Contaminated Water: Effect of Kerosene Concentration and Removal Kinetics
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A phytoremediation experiment was carried out with kerosene as a model for total petroleum hydrocarbons. A constructed wetland of barley was exposed to kerosene pollutants at varying concentrations (1, 2, and 3% v/v) in a subsurface flow (SSF) system. After a period of 42 days of exposure, it was found that the average ability to eliminate kerosene ranged from 56.5% to 61.2%, with the highest removal obtained at a kerosene concentration of 1% v/v. The analysis of kerosene at varying initial concentrations allowed the kinetics of kerosene to be fitted with the Grau model, which was closer than that with the zero order, first order, or second order kinetic models. The experimental study showed that the barley plant designed in a subsu

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