The aim of this research is to use robust technique by trimming, as the analysis of maximum likelihood (ML) often fails in the case of outliers in the studied phenomenon. Where the (MLE) will lose its advantages because of the bad influence caused by the Outliers. In order to address this problem, new statistical methods have been developed so as not to be affected by the outliers. These methods have robustness or resistance. Therefore, maximum trimmed likelihood: (MTL) is a good alternative to achieve more results. Acceptability and analogies, but weights can be used to increase the efficiency of the resulting capacities and to increase the strength of the estimate using the maximum weighted trimmed likelihood (MWTL). In order to perform t

LandSat Satellite ETM+ image have been analyzed to detect the different depths of regions inside the Tigris river in order to detect the regions that need to remove sedimentation in Baghdad in Iraq Country. The scene consisted of six bands (without the thermal band), It was captured in March ٢٠٠١. The variance in depth is determined by applying the rationing technique on the bands ٣ and ٥. GIS ٩. ١ program is used to apply the rationing technique and determined the results.

Baghdad Metro is a vital project to fulfill the rapidly increased traffic volume requirements. The proposed metro will connect both sides of Baghdad City, passing under the Tigris River. This study is employed finite elements software (PLAXIS 3D) to evaluate the seepage force developed around the sub-river segment during different construction stages and for other water levels of Tigris. The study found that when the water level changes from maximum to minimum, the developed seepage force decreases by (8 to 13%) and (22 to 27%) respectively. The seepage forces were found to be maximum during the excavation stage. The concrete lining process led to a noticeable reduction in seepage forces at all locations. The study also

Aromatic hydrocarbons present in Iraqi national surface water were believed to be raised principally from combustion of various petroleum products, industrial processes and transport output and their precipitation on surface water.
Polycyclic aromatic hydrocarbons (PAHs) were included in the priority pollutant list due to their toxic and carcinogenic nature. The concern about water contamination and the consequent human exposure have encouraged the development of new methods for
PAHs detection and removal.
PAHs, the real contaminants of petroleum matter, were detected in selected sites along Tigris River within Baghdad City in summer and winter time, using Shimadzu high performance liquid chromatography (HPLC) system.
Analysi

A solid Phase Extraction (SPE) followed by HPLC-UV method is described for the simultaneous quantitative determination of nine priority pollutant phenols : Phenol, 2- and 4-Nitrophenol, 2,4-Dimethylphenol, 2-, 2,4-Di-, 2,4,6-Tri-, and Penta- chlorophenol, 4 Chloro-3-methylphenol. The phenols were separated using a C-18 column with UV detector at wave length of 280nm. The Flow of mobile phase was isocratic consisted of 50:50 Acetonitrile: phosphate buffer pH=7.1, column temperature 45 C°, Flow Rate 0.7 ml/min. Calibration curves were linear (R2 = 0.9961-0.9995). The RSDs (1.301-5.805)%, LOD(39.1- 412.4) µg/L, LOQ(118.5-1250.8) µg/L, the Robustness (1.55-4.89), Ruggedness (2.82-4.00), Repeatability (2.1-4.95), Recoveries%

This study was conducted to examine the discharge capacity of the reach of the Tigris River between Kut and Amarah Barrages of 250km in length. The examination includes simulation the current capacity of the reach by using HEC-RAS model. 247cross sections surveyed in 2012 were used in the simulation. The model was calibrated using observed discharges of 533, 800, 1025 and 3000m³/s discharged at Kut Barrage during 2013, 1995, 1995 and 1988, respectively, and its related water level at three gauge stations located along the reach. The result of calibration process indicated that the lowest Root Mean Square Error of 0.095 can be obtained when using Manning’s n coefficient of 0.026, 0.03 for th

In developing countries, conventional physico-chemical methods are commonly used for removing contaminants. These methods are not efficient and very costly. However, new in site strategy with high treatment efficiency and low operation cost named constructed wetland (CW) has been set. In this study, Phragmites australis was used with free surface batch system to estimate its ability to remediate total
petroleum hydrocarbons (TPH) and chemical oxygen demand (COD) from Al-Daura refinery wastewater. The system operated in semi-batch, thus, new wastewater was weekly added to the plant for 42 days. The results showed high removal percentages (98%) of TPH and (62.3%) for COD. Additionally, Phragmites australis biomass increased significant

The objective of this study is to evaluate the bacterial count and heavy metal concentration of river water on fish micronuclei. Fish and water samples are carried out in 1 May to 1 June 2013 from Tigris River. A total of fifty three fish sample are studied. The bacteriological quality of water showed that the total viable count is ranged from 150×103 to 352×103 cfu/ml and fecal coliform counts was 1250 cell/100ml during the study period. All the metals (Cu, Hg, Pb, and Zn) are within the normal limit, but Cd was slightly elevated in river water samples. The appearance of micronuclei in red blood cells of all fish species is detect , by recording a larger number of it, in ( Abu Alsomere , Hishne , Bannini Kaber al fam & Karkoor

In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.