This study aims to assess the water quality index (WQI) according to the Canadian Council of Ministers of the Environment's Water Quality Index method (CCME WQI). Four locations (measurement stations) are selected along the Tigris River, in Iraq.  Two of them are located in the north near Mosul City, (Mosul Dam and Mosul city), and the other two are located in the south near Al-Amarah city, (Ali Garbi and Al-Amarah). The water data collected is for the period 2011 to 2013, including eleven water quality parameters. These are magnesium (Mg⁺²), calcium (Ca²⁺), potassium (K⁺), sodium (Na⁺), sulfate (SO₄^2-), chloride (Cl^-), nitrate (NO₃<

This study aims to assess the concentrations of some Poly Aromatic
Hydrocarbons in water, in order to monitor effectively and provide possible
recommendations to improve the water quality in the aquatic ecosystem of Tigris
River near Al-Dora refinery. Distribution and concentration of the sixteen polycyclic
aromatic hydrocarbons (PAHs) were studied in surface water. Solid-phase extraction
was used for water samples, and then analyzed by HPLC. Results showed that the
highest and the most dominant (PAH) was ancephthlnene (3-ring PAH), with
concentration of (40.33 ng/l), while the lowest concentration was for Indeno (1, 2, 3-
cd) pyrene (5-ring PAH), with (0.33 ng/l). The highest and the lowest mean
concentrations

Stable isotope (?18O, ?D) values were determined along with the chemical compositions at 10 different locations along the Tigris river between Baghdad-Ammara cities of Iraq. The physico-chemical parameters and isotopic data were measured. The sampling site represents 34 % of total Tigris river in the republic of Iraq. The systematically increased in values of stable isotope as move from the downstream of the river and the most significantly appears at Kut lake. This increase occurs as a result of several factors, viz. (a) evaporation occurs low water level in the river and its tributaries, and (b) return flow water to the river from irrigation water in groundwater systems. The change in ion distribution and in the isotopic values related di

A number of aqueous samples were collected from river Tigris in Baghdad city, enriched ~1000 times using solid phase extraction (SPE), then extracted the trace concentrations of some polychlorinated biphenyls (PCB) using an aqueous two-phase system (ATPS) composed of 1Methylpyridinium chloride [MePy]Cl and KH2PO4 salt. High performance liquid chromatography technique coupled with ultraviolet (HPLC-UV) is used for the quantification. Extraction under the optimized conditions of pH, solvent composition, duration and temperature has given with a yield of PCB about 91%. The limit of detection (LOD) and limit of quantification (LOQ) for analyses are 0.11-0.62 µg.L−1 and 2.67–3.43 µg.L−1 respectively with relative stan

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat