This comprehensive study investigates has been made to assess the water quality of Al-Gharraf River, which considered the main branch of Tigris River south of Iraq using the overall Index of Pollution (OIP), depending on 9 physical, chemical, and biological important parameters of water quality were analyzed:  hydrogen ion concentration (pH), turbidity (NTU), total dissolved solid (TDS), dissolved oxygen (DO), biological oxygen demand (BOD5) , total hardness (TH), sulfate (SO4), nitrate (NO3),and fecal coliform (FC), which measured monthly at twenty one stations on the river during 2016-2017. Water quality deterioration  has occurred in the last ten stations, consequently, the health status of the river

Water quality of Al-Gharraf River, which considered the main branch of Tigris River south of Iraq was examined using the Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI) for aquatic life protection and irrigation. Water samples were collected monthly from five sampling stations during 2013-2014 and 17 physicochemical parameters were analyzed: Temperature, hydrogen ion concentration (pH), electrical conductivity, dissolved oxygen, turbidity, alkalinity, chloride, calcium, magnesium, sulfate, phosphate, nitrate, sodium, lead, cadmium, nickel and zinc.
The model classified water of Al-Gharraf River as poor for aquatic life protection and fair for irrigation with seasonal overall WQI value of 30-39 and among

Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

This research was conducted to investigate the water quality of the lesser Zab
river, to evaluate the water suitability for agricultural usings and report the effect of
human activities on this water. Samples were collected along the river stream
starting from Dukan area till the convergence with Tigris River. All the tests were
conducted at the labs of Environmental sciences and Technology College /
University of Mosul and Erbil water project/Erbil city.
The results of using Piper diagram showed that the water is alkine, due to the effect of the origional rock's components of that area on the water quality. While the using of Stiff diagram elucidate that the water samples contain ions belong to the area of the lesser Z

      The current study aims to assess the water quality of the Al-Diwaniyah River in the city of Al-Diwaniyah to drink in terms of chemical properties and heavy metals and their impact on the health of the local population. The results showed that most of the parameters in the river water are of low concentrations due to the limited human activities in polluting the river water. The study concluded that the water quality is suitable for drinking depending on major cations and anions in all seasons. The Heavy Metal Pollution Index (HPI) showed that the river water was clean and safe, except two slightly polluted samples. The study concluded that river water for drinking or various domestic uses does not pose any danger to human heal

The study attempts to assess water quality in Abu-Zirig Marsh which used epiphytic Diatom community for assessing water quality. Many of Diatom indices {Trophic diatom index (TDI), Diatom index (DI), Generic diatom index (GDI) have been used to give qualitative information about the status of the freshwater ecosystem(good, moderate, high pollution). In this study, the epiphytic diatoms on both host aquatic plants Phragmites australis and Typha domengensis were collected from Abu-Zirig Marsh within Thi-Qar Province at three sites in Autumn, 2018 and winter, 2019. Epiphytic diatoms were Identified by the preparation of permanent slides method, some species of epiphytic diatom showed dominance such as Cyclotella menegh

The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est

The time series of statistical methods mission followed in this area analysis method, Figuring certain displayed on a certain period of time and analysis we can identify the pattern and the factors affecting them and use them to predict the future of the phenomenon of values, which helps to develop a way of predicting the development of the economic development of sound

The research aims to select the best model to predict the number of infections with hepatitis Alvairose models using Box - Jenkins non-seasonal forecasting in the future.

Data were collected from the Ministry of Health / Department of Health Statistics for the period (from January 2009 until December 2013) was used