A total of 60 species of aquatic oligochaetes were identified in different sites within Tigris-Euphrates basin / Iraq, including River Tigris, River Euphrates, Southern marshes ( Al-Haweiza , Al-Hammar and Al-Chebaiesh ) , Shutt Al-Germa, and Shatt Al-Arab. In River Euphrates 39 species were identified, 40 species from River Tigris and 32 species from Shatt-Al-Arab and southern marshes.The identified species were classified as four species of Family Aeolosomatidae, 54 species of Naididae ( 31 Naidinae , 8 Pristininae and 15 Tubificid worms), one species of each of Lumbriculidae ( Lumbriculus variegates ) and Lumbricidae ( Eiseiella tetraedra). Among Aeolosomatidae , Aelosoma aquaternarium, A. Liedyi, A. variegatum and A. hemprichi

339 individuals , were sorted from 22 samples collected from three sites in Tigris River including , Al- Sarafiya district (S1), Al- Jaderiyah district (S2) and Al-Za'afaraniya district (S3), in addition to one site in the irrigation canal of the Al- Jaderiyah campus of the University of Baghdad (S4) , and in Al- Jeish canal(S5) east Baghdad. The sorting results revealed that the highest number of individuals of 102 was recorded at S4, whereas the lowest number of 24 individuals was recorded at S2. Regarding the sites, site S4 was the richest site with 30% of the total number represented 16 species, while each of S3 and S5 had 8 species only with 17.11% and 28.60% of the total individuals number respectively. The values of Jaccared Sim

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.

The quality of groundwater in the Al-Hawija area was assessed using a water quality index. Data of nine physico-chemical parameters of 28 groundwater wells were used to calculate the water quality index (WQI). A heterogeneous water quality was reported, where in close proximity to the Lesser Zab River (LZR), it has low WQI values and permissible for human consumptions due to the dilution processes by fresh water; whereas, it becomes deteriorated in areas located far away the river. The values of WQI ranges from 22 to 336, indicating a good to very poor groundwater quality.

The present study deals with the assessment of water Quality Index to theAl-
Khadhimiya Groundwater city, by collection groundwater from 13wells during four
seasons, subjecting the samples to a comprehensive physicochemical analysis. The
13 parameters have been considered: pH, total hardness, calcium, magnesium,
turbidity, nitrate, electrical conductivity, total dissolved solid, Sulfate, Chloride,
zinc, manganic, and iron, that are used for calculating the WQI. From the result
shown, the most groundwater quality lies in Unfit for human drinking purpose. The
wells (1 and 11) and wells (3 and 10) were a bad water quality for drinking purpose
since they lie in poor and in very poor respectively according to the WQI.

Studied Seen fungi water in nine stations or selected sites along the Tigris River began from the city of Mosul in the north to Qurna in episodes were measured some chemical agents and Alvezaúah water ranged pH values ??(11p) between 7.0 to 8.3 either temperatures ranged between 10to 28 m study showed isolated 22 species of 14 genera of fungi

This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters wer