The study aimed to explaining the concepts of water footprint and virtual water and how these two concepts could use to achieve water savings at the local level to meet the water supply deficit in Iraq, which is expected to increase in the coming years and influence of that on food security in Iraq by using these concepts when drawing production, irrigated and import plans in Iraq. The study aimed to studying the water footprint and virtual water and their impact on the foreign trade for wheat and rice crops during the period 2000-2022 and estimating the most important indicators of virtual water and the water footprint of the study crops due to the importance of these criteria in determining the amount of increase or decrease in the area of the studied crops, according to the foreign trade policy. This study was concluded that the average total water footprint of the wheat and rice crops during the study period is (20.27,13.89) billion m3 respectively, and the average percentage of dependence on external water resources for both crops are (20.49%,67.98%) respectively, and the average percentage of self-sufficiency in water resources are (79.51%,32.01%) respectively, and the average unit productivity of irrigation water for both crops is (0.19,0.10) kg/m3 respectively during 2000-2022.The average for the water needs of wheat and rice crops during the study period were (6.04,10.19) m3/kg respectively, the average amounts of water used in local production for both crops are (14.23,4.01) billion m3 respectively, the average amounts of virtual water imported for both crops are (6.19,10.03) billion m3 respectively, and the average value of the imported virtual water for both crops is (382,529) thousand dollars during the period 2000-2022. The study recommended to taking in account these concepts in plans of production and distributing irrigation water.
In this paper we prove the boundedness of the solutions and their derivatives of the second order ordinary differential equation x ?+f(x) x ?+g(x)=u(t), under certain conditions on f,g and u. Our results are generalization of those given in [1].
The foreguts of a total of 515 fish of Chondrostoma regium (Heckel, 1843) (locally: Bala’aot Malloky) were studied. These fish were collected from Tigris River at Salah Al-Deen Province (between Al-Hagag & Yathrib) for 20 months between March and October of the next year. Detritus, plant in origin materials (19.6%, 23.0% & 24.9%); green and blue green algae, mostly Cladophora, Cosmarium and Merismpedia sp. (17.1%, 12.9% & 12.2%) and diatoms, mostly Diatoma, Chanathes, Amphora and Cyulbella sp. (16.9%, 8.8% & 8.2%) were the main food categories taken by these fishes according to occurrence (O%), volumetric methods (V%) and ranking index (R%). Debris (not part of the diet) took 45.3% of the studied fish foreguts by volume. Detritus was also
... Show MoreNew microphotometer was constructed in our Laboratory Which deals with the determination of Molybdenum (VI) through its Catalysis effect on Hydrogen peroxide and potasum iodide Reaction in acid medium H2SO4 0.01 mM. Linearity of 97.3% for the range 5- 100 ppm. The repeatability of result was better than 0.8 % 0.5 ppm was obtanined as L.U. (The method applied for the determination of Molybdenum (VI) in medicinal Sample (centrum). The determination was compared well with the developed method the conventional method.
thin films of se:2.5% as were deposited on a glass substates by thermal coevaporation techniqi=ue under high vacuum at different thikness
Radiation therapy plays an important role in improving breast cancer cases, in order to obtain an appropriateestimate of radiation doses number given to the patient after tumor removal; some methods of nonparametric regression werecompared. The Kernel method was used by Nadaraya-Watson estimator to find the estimation regression function forsmoothing data based on the smoothing parameter h according to the Normal scale method (NSM), Least Squared CrossValidation method (LSCV) and Golden Rate Method (GRM). These methods were compared by simulation for samples ofthree sizes, the method (NSM) proved to be the best according to average of Mean Squares Error criterion and the method(LSCV) proved to be the best according to Average of Mean Absolu
... Show MoreThe present study aimed to determine the genetic divergence of seven maize genotypes (Al-Maha, Sumer, Al-Fajr, Baghdad, 5018, 4 × 1 single hybrid, and 4 × 2 single hybrid) under two varied levels of nitrogen fertilization (92 and 276 kg N ha-1). The experiment occurred in 2022 in a randomized complete block design (RCBD) with a split-plot arrangement and three replications at the College of Agricultural Engineering Sciences, University of Baghdad, Iraq. The nitrogen fertilization levels served as main plots, with the maize genotypes allocated as the subplots. The results revealed that genetic variance was higher than the environmental variance for most traits, and the coefficient of phenotypic variation was close to the genetic va
... Show MoreThe present study dealt with the removal of methylene blue from wastewater by using peanut hulls (PNH) as adsorbent. Two modes of operation were used in the present work, batch mode and inverse fluidized bed mode. In batch experiment, the effect of peanut hulls doses 2, 4, 8, 12 and 16 g, with constant initial pH =5.6, concentration 20 mg/L and particle size 2-3.35 mm were studied. The results showed that the percent removal of methylene blue increased with the increase of peanut hulls dose. Batch kinetics experiments showed that equilibrium time was about 3 hours, isotherm models (Langmuir and Freundlich) were used to correlate these results. The results showed that the (Freundlich) model gave the best fitting for adsorption capacity. D
... Show MoreThe proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A
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