Corrosion control is an important aspect of safe drinking water supplies. The effects of corrosion which may not be evident without monitoring are an important issue concerning both public health and economical aspects. Chemical stability parameters of water quality in water treatment plants in Baghdad city can improve drinking water quality. The treated water quality from water treatment plants in Baghdad city was investigated along the water flow path in this study. The water quality parameters related to chemical stability included temperature, alkalinity as mg/L Ca-CO3, calcium mg/L as Ca, pH and total dissolved solids (TDS) mg/L for different samples from WTPs within Baghdad city were investigated. The two water quality indices, Langelier saturation index (LSI) and the Ryznar stability index (RSI), were calculated in order to evaluate the chemical stability of the drinking water samples. The results of LSI and RSI of the effluents from Baghdad's WTPs during 2000-2013 classified that corrosive water is produced and this indicates that the water is not safe for domestic use and will need the further treatment. The present study demonstrated the application of water stability indices in estimating/understanding the treated water chemical stability and appeared to be promising in the field of treated water quality management.
The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be 14.9 %, 39.5 %, 22.8 %, 6.1 %, and 16.7 %, respectively. Additionally, to anticipate changes in groundwater WQI, IBM® SPSS® Statistics 19 software (SPSS) was used to develop an artificial neural network model (ANNM). With the application of this ANNM model, the results obtained illustrated high prediction efficiency, as the sum of squares error functions (for training and testing samples) and coefficient of determination (R2), were found to be (0.038 and 0.005) and 0.973, respectively. However, the parameters pH and Cl influenced model prediction significantly, thereby becoming crucial factors in the anticipation carried out by using ANNM model.
In this study water quality was indicated in terms of Water Quality Index that was determined through summarizing multiple parameters of water test results. This index offers a useful representation of the overall quality of water for public or any intended use as well as indicating pollution, which are useful in water quality management and decision making. The application of Water Quality Index (WQI) with ten physicochemical water quality parameters was performed to evaluate the quality of Euphrates River water for drinking usage. This was done by subjecting the water samples collected from seven stations within Al-Anbar province during the period 2004-2010 to comprehensive physicochemical analysis. The ten physicochemical parameters included: pH value, Alkalinity (ALK), Orthophosphate (PO4-3), Nitrate (NO3-),Sulphate (SO4-2), Chloride (Cl-), Total Hardness (TH), Calcium (Ca), Magnesium (Mg), and Total Dissolved Solids (TDS). The average annual overall WQI was found to be 107.59 through the study period. The high WQI obtained is a result of the high concentrations of Orthophosphate and Magnesium which can be attributed to the various human activities taking place along the river banks. From this analysis the quality of the Euphrates River is classified as "very poor quality" ranging poor water at the river upstream near station (E1) and unsuitable for drinking at the river downstream near station (E7) with an annual minimum WQI of 89.34 in 2008 and maximum 112.44 in 2009. The present study demonstrated the application of WQI in estimating and understanding the water quality of Euphrates River. WQI appears to be promising in water quality management and a valuable tool in categorizing pollution sources in surface waters
This study investigated the ability of using crushed glass solid wastes in water filtration by using a pilot plant, constructed in Al-Wathba water treatment plant in Baghdad. Different depths and different grain sizes of crushed glass were used as mono and dual media with sand and porcelaniate in the filtration process. The mathematical model by Tufenkji and Elimelech was used to evaluate the initial collection efficiency η of these filters. The results indicated that the collection efficiency varied inversely with the filtration rate. For the mono media filters the theoretical ηth values were more than the practical values ηprac calculated fromthe experimental work. In the glass filter ηprac was obtained by multiplying ηth by a factor 0.945 where this factor was 0.714 for the sand filter. All the dual filters showed that ηth was less than ηprac. Whereas the dual filter 35cm porcelanite and 35cm glass showed the highest collection efficiency. To obtain ηprac in the dual filter glass and sand, ηth is multiplied by 1.374, as for the dual filters porcelanite and glass the factor was 1.168 and 1.204.
Asset management involves efficient planning of economic and technical performance characteristics of infrastructure systems. Managing a sewer network requires various types of activities so the network can be able to achieve a certain level of performance. During the lifetime of the network various components will start to deteriorate leading to bad performance and can damage the infrastructure. The main objective of this research is to develop deterioration models to provide an assessment tool for determining the serviceability of the sewer networks in Baghdad city the Zeppelin line was selected as a case study, as well as to give top management authorities the appropriate decision making. Different modeling techniques were used based on statistical methods such as discriminant, and artificial neural network (ANN) which were used to build the deterioration models. The results of the discriminant model gave correct classification of 68.9% for the condition class of this line. The main significant influencing variables that play an important role in sewer networks were: sewer age, planning, performance and maintenance which is known as the Management function. From ANN model the confusion matrix gave correct classification of 76.7% and MSE 0.128.This study providing a good source of information for future planning.
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