The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The develope

The heavy metals Cd, Cu, Fe, pb, and Zn were determined in dissolved and particulate phases of the water,in addition to exchangeable and residual phases of the sediment and in the selected organs of the fish Cyprinus carpio collected from the Euphrates River near Al-Nassiriya city center south of Iraq during the summer period / 2009 .Also sediment texture and total organic carbon(TOC) were measured. Analysis emploing a flam Atomic Absorption Spectrophotometers . The mean regional concentrations of the heavy metals in dissolved (µg/l) and particulate phases (µg/gm) dry weight were Cd (0.15,16.13) ,Cu (0.59,24.48) ,Fe (726,909.4) ,Pb (0.20, 49.95) and Zn (2.5,35.62) respectively,and those for exchangeable and residual phases of the

This paper describes the use of remote sensing techniques in verification of the polluted area in Diyala River and Tigris River and the effected of AL-Rustamiyah wastewater treatment plant, which is located on Diyala River, one of the branches of Tigris River in south of Baghdad. SPOT-5 a French satellite image of Baghdad, Iraq was used with ground resolution of 2.5 m in May 2016. ENVI 5.1 software programming was utilized for Image processing to assess the water pollution of Diyala and Tigris River’s water. Five regions were selected from a study area and then classified using the unsupervised ISODATA method. The results indicated that four classes of water quality which are successful in assessing and mapping water pollution which confi

Concentrations and distribution of major, minor, and trace elements were
studied in thirteen sediment samples from Al-Hammar Marsh.
Multivariate statistical techniques such as Principal Component Analysis (PCA)
and Agglomerative Hierarchal Cluster Analysis (AHCA) as well as pollution
analysis such as Enrichment Factor (EF) were used to process the data and identify
the possible sources of elemental constituents in sediment samples.Results of
chemical analysis revealed that Major element mean concentrations were in the
order of Ca> Si> K> Mg> and minor elements were in the order of Al> Fe>S>Cl>
Ti> P>Mn> Sr> N and trace elements were in the order of Cr> Ni> Zr>V>Zn&gt

     The aim of the study is the measuring of changes in the spectral reflectivity water quality, analyzing the seasonal difference of Tigris River within Mosul City in the north of Iraq using Geographic Information Systems (GIS) and remote sensing techniques during the period (2014-2018). For this paper, Satellite images of the 8 Landsat in 2018 for four seasons have been selected in order to study the seasonal changes on the river they took place during 2018.  A total of ten sample datasets were taken at the upstream, midstream and downstream along the Tigris River. This research focuses on analyzing the locational variance of reflectance, analyzing seasonal difference, and finding modeling algal amount change.

The aim of this research is to measure the changes of Iraqi Marshland's area as well as the changes in the spectral reflectivity water quality, analyzing seasonal difference in AL-Hawizah marshes, South of Iraq using Geographic Information Systems (GIS) and remote sensing techniques. For this paper, the samples were taken at 10 sites along the study area. Satellite images of the 8 Landsat on 20/5/2017, 8/8/2017, 11/10/2017 and 14/12/2017 have been selected in order to study the seasonal changes on the marshes took place during 2017. The reflectance values of red, green, blue and near infrared bands showed that are significantly associated with a seasonal factor. All bands show that reflectivity of the marsh has been affected by locationa

Devastated by the combined impact of massive drainage works and upstream damming since the 1980's, Al-Hammar Marsh, Southern Iraq, has completely collapsed with 94 % of its land cover transformed into bare land and salt crusts by 2000. After a policy initiated to restore the Iraqi marshes again in 2003, the marsh recovered about half of its former area. As a part of the ecological recovery assessment of this newly inundated marsh, it is important to investigate the extend impact of desiccation after 3 years of inundation on water quality as the latter plays an important role in the restoration process of the marshes. Therefore, from a restoration point of view, major and trace element distribution and sourcing as well as seasonal variati

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.

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

Biodiversity is one of the important biological factors in determining water quality and maintaining the
ecological balance. In this study, there are 223 species of phytoplankton were identified, and they are as
follows: 88 species of Bacillariophyta and were at 44%,70 species of Chlorophyta and they were at 29 %, 39
species of Cyanophyta and they were at 16 %, 12 species of Euglenozoa and they were at 4 %, four species of
Miozoa and they were at 3 %, and, Phylum Charophyta and Ochrophyta were only eight and two species,
respectively and both of them were at 2%. The common phytoplankton recorded in the sites studied
include Nitzschia palea, Scenedesmus quadricauda, Oscillatoria princeps, and Peridinium