Groundwater is an important resource that can be used for various purposes. Various factors can change the chemistry of the GW, such as the chemical composition of an aquifer as well as the leaching of human waste into groundwater. The study area is a barren land covered by some sabkhas, in addition to some agricultural fields. The study aims to assess groundwater quality for drinking purposes using the Water Quality Index. The groundwater is chemically heterogeneous and has a wide quality range from very poor to excellent. Evaporation appears to be the controlling factor among the other shallow waters, while relatively deep water is related to rock-soil dominance. Rocks, land use and land cover have helped control the groundwater q

The present research deals with the spatial variance analysis in Jwartadistrict and conducting a comparison on the spatial and seasonal changes of the vegetation cover between (2007-2013) in order to deduce the relationship between the vegetation density and the areas which are exposed to the risk of water erosion by using Plant Variation Index  NDVI) C (coefficient and by using Satellite images of Landsat satellite which are taken in 2/7/2007 and Satellite images of Landsat satellite taken in 11/1/ 2013, the programs of remote sensitivity and the Geographic Information Systems.

    The study reveals that there is a variance in the density of vegetation cover of the area under study betwee 2007 and 2013. Howev

Nanoparticles of humic acid and iron oxide were impregnated on the inert sand to produce sorbent for treating groundwater contained of cadmium and copper ions by technology of permeable reactive barrier (PRB). Sewage sludge was the source of the humic acid to prepare the coated sand by humic acid—iron oxide (CSHAIO) sorbent; so, this work is consistent with sustainable development. For 10 mg/L metal concentration, batch tests at speed of 200 rpm signified that the removal efficiencies are greater than 90% at sorbent dosage 0.25 g/ 50 mL, pH 6 and contact time 1 h. The kinetic data was well described by the Pseudo first-order model indicating that physicosorption is the predominant mechanism. The maximum adsorption capacities (qmax) were c

The toxicological risks and lifetime cancer risks associated with exposure to disinfection by-products (DBPs) including Halloacetic acids (HAAs) and trihalomethanes (THMs) compounds by drinking water in several districts in Wassit Province were estimated. The seasonal variation of HAAs and THMs compounds in drinking water have indicated that the mean values for total HAAs (THAAs) and total THMs (TTHMs) ranged from 43.2 to 72.4 mg/l and from 40 to 115.5 mg/l, respectively. The World health organization index for additive toxicity approach was non-compliant with the WHO guideline value in summer and autumn seasons and this means that THMs concentration has adverse toxic health effects. The multi-pathway of lifetime hu

Conducted Althilelat chemical models of crude oil back to the reservoir Fertile from the fields of Baghdad and Kut and models of crude oil back to the reservoir ??????? of Haklbe Tikrit and Baghdad were calculated their properties Alvezaúah Kalkthaqh and weight, quality and degree of August j (API) and know the quality Nfothma that was light or heavy and make the comparison between Alinvtin also conducted chemical analyzes of the two models of Almia associated with each of the oil above Almkmnin and measured Ktvthma and Zojithma and concentrations of some dissolved salts in them and clarify the relationship between the oil reservoir and water associated with oil fields...

Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul