The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge have the most significant affect on the predicted TDS concentrations. The results showed that a network with (8) hidden neurons was highly accurate in predicting TDS concentration. The correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE) between measured data and model outputs were calculated as 0.975, 113.9 and 11.51%, respectively for testing data sets. Comparisons between final results of ANNs and multiple linear regressions (MLR) showed that the ANNs model could be successfully applied and provides high accuracy to predict TDS concentrations as a water quality parameter.
After restoration of Iraqi marshes during 2003, three locations were chosen, one in each main marsh (Um Al-Naaj site in Al-Hwaizeh marsh; Al-Nagarah site in Al-Hammar marsh and Al-Baghdadia site in Al-Chebaysh marsh) to determine the concentrations of nutrients (Nitrate, Nitrite, Phosphate and Silicate) in water seasonally for the period winter, spring, summer, and autumn at 2007. Five water replicates were collected from each site, seasonally. In the Lab., the samples were analyzed by colorimetric methods; the results showed that Um-Al-Naaj site has the highest nutrients level, while Al-Nagarah site has the lowest level. The statistical program t-test was applied at the significant levels (P-value < 0.01) and (P-value < 0.05) to know
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In this study, a total of 209 individuals of leeches were collected from Al-Hindyia River / Babil Province. 116 individuals were identified as Erpobdella octaculata (Linnaeus, 1758), 50 individuals as Erpobdella punctata (Leidy,1870) and 43 individuals as Hemiclepsis marginata (Müller, 1774). Four samples were collected monthly during a period from February to June 2018. Some physical and chemical water properties were also examined, including air and water temperature, potential of hydrogen pH, Electrical Conductivity EC, Total Dissolved Solid TDS, Dissolved Oxygen DO, and the Biological Oxygen Demand BOD₅. Air and water temperature were r
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Two oil wells were tested to find the abnormal pressure zones using sonic log technique. We found that well Abu-Jir-3 and Abu-Jir-5 had an abnormal pressure zones from depth 4340 to 4520 feet and 4200 to 4600 feet, respectively. The maximum difference between obtained results and the field measured results did not exceed 2.4%.
In this paper, the formation pressures were expressed in terms of pressure gradient which sometimes reached up to twice the normal pressure gradient.
Drilling and developing such formations were dangerous and expensive.
The plotted figures showed a clear derivation from the normal trend which confirmed the existence of abnormal pressure zones.
Present study was conducted in order to assess Slabiaat water quality by measuring some physical and chemical factors of river water, the study included a choice of three stations along of Slabiaat River in Samawa city, water samples collected a monthly during the period from September 2013 August 2014. The study involved measuring the Air & water temperatures, pH, Electrical conductivity, Total dissolved solids, Dissolved oxygen, Total hardness, calcium hardness, magnesium, turbidity, and some types of bacteria in River water. The study results showed that the values of air & water temperatures have ranged between (20.1-36.6)?C , (10-21.8) in Slabiaat River, respectively . pH values ranged between (6.6-8.7). Electrical conductivity in
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The Normalized Difference Vegetation Index (NDVI) is commonly used as a measure of land surface greenness based on the assumption that NDVI value is positively proportional to the amount of green vegetation in an image pixel area. The Normalized Difference Vegetation Index data set of Landsat based on the remote sensing information is used to estimate the area of plant cover in region west of Baghdad during 1990-2001. The results show that in the period of 1990 and 2001 the plant area in region of Baghdad increased from (44760.25) hectare to (75410.67) hectare. The vegetation area increased during the period 1990-2001, and decreases the exposed area.