The high and low water levels in Tigris River threaten the banks of the river. The study area is located on the main stream of Tigris River at Nu’maniyah City and the length of the considered reach is 5.4 km, especially the region from 400 m upstream Nu’maniyah Bridge and downstream of the bridge up to 1250 mwhich increased the risk ofthe problemthat itheading towardsthe streetand causingdanger tonearbyareas.

The aim of this research is to identify the reason of slope collapse and find proper treatments for erosion problem in the river banks with the least cost. The modeling approach consisted of several steps, the first of which  is by using “mini” JET (Jet Erosion Test) d

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.

Transportability refers to the ease with which people, goods, or services may be transferred. When transportability is high, distance becomes less of a limitation for activities. Transportation networks are frequently represented by a set of locations and a set of links that indicate the connections between those places which is usually called network topology. Hence, each transmission network has a unique topology that distinguishes its structure. The most essential components of such a framework are the network architecture and the connection level. This research aims to demonstrate the efficiency of the road network in the Al-Karrada area which is located in the Baghdad city. The analysis based on a quantitative evaluation using graph th

Water produced from power plants is one of the most important sources of water pollution, especially for areas like Baghdad, Contaminated industrial wastewater is a major environmental challenge due to the rapid growth of industries, leading to increased accumulation of harmful pollutants in water resources, the work is intended to study the impact of water generated from a power plant in the south on the level of heavy metals before and after the treatment process and after its discharge to the Tigris River. Objective is to determine the extent of heavy metals such as iron, copper, chromium, and zinc concentration in water extracted from various points and subsequently study the monthly variations of these elements with a view to assessmen

Various heavy metals, cations and anions of the Tigris River water in Baghdad regionwere studied during the winter, spring, summer and autumn of 2009, for 4 samplingsites. In the present investigation the levels of studied heavy metals, cations and anionswere found in the range of (0.011-0.333 mg/L) for As, in the water samples(undetectable-0.0043 mg/L) for Sb,( 0.011-0.080 mg/L) for Ti, (0.150-0.730 mg/L) forV, (0.01-1.06 mg/L) for Fe, (0.1-0.4 mg/L) for Zn, (0.011-0.15 mg/L) for Pb, (0.01-0.05mg/L) for Cd, (0.01-0.04 mg/L) for Ni, (50-290 mg/L) for Ca, (97-270 mg/L) for Mg,(0.65-1.74 mg/L) for K, (11-38.33) for Na, (35-113 mg/L) for Cl, (150-256 mg/L) forHCO3, (96-479 mg/L) for SO4, (0.93-3.9 mg/L) for NO3 and (undetectable - 0.360 mg/L)f

The monthly time series of the Total Suspended Solids (TSS) concentrations in Euphrates River at Nasria was analyzed as a time series. The data used for the analysis was the monthly series during (1977-2000).

The series was tested for nonhomogenity and found to be nonhomogeneous. A significant positive jump was observed after 1988. This nonhomogenity was removed using a method suggested by Yevichevich (7). The homogeneous series was then normalized using Box and Cox (2) transformation. The periodic component of the series was fitted using harmonic analyses, and removed from the series to obtain the dependent stochastic component. This component was then modeled using first order autoregressive model (Markovian chain). The above a