ArcHydro is a model developed for building hydrologic information systems to synthesize geospatial and temporal water resources data that support hydrologic modeling and analysis. Raster-based digital elevation models (DEMs) play an important role in distributed hydrologic modeling supported by geographic information systems (GIS). Digital Elevation Model (DEM) data have been used to derive hydrological features, which serve as inputs to various models. Currently, elevation data are available from several major sources and at different spatial resolutions. Detailed delineation of drainage networks is the first step for many natural resource management studies. Compared with interpretation from aerial photographs or topographic maps, automation of drainage network extraction from DEMs is an efficient way and has received considerable attention. This study aims to extract drainage networks from Digital Elevation Model (DEM) for Lesser Zab River Basin. Composition parameters of the drainage network including the numbers of streams and the stream lengths are derived from the DEM beside the delineation of catchment areas in the basin. The results from this application can be used to create input files for many hydrologic models.
This study was done to determine the concentration of several heavy metals in the water of Al-Saddah agricultural drainage in Al-Saddah District in Babylon Province/Iraq. The concentrations of six heavy metals were measured (Pb, Cd, Cu, Hg, Fe, Zn). It was found that Pb concentration ranged from 0.06 mg/L at St.2 in autumn to 0.13 mg/L at St.2 in winter. Fe concentrations ranged from 0.04 mg/L at St.2 in autumn and winter to 0.41 at St.2 in Summer. Cd concentrations ranged from 0.008 mg/L at St.2 in summer to 0.05 mg/L at St.2 in winter. Cu concentrations ranged from 0.01 mg/L at St.1 in both autumn and winter to 0.63 mg/L at St.2 in winter. Hg concentrations was ranged from 0.002 mg/
Intestinal parasites present in freshwater from the Al- Fallujah, Al- Habbaniyah and Al-Alwarar, of the Euphrates river in Iraq are Cryptosporidium spp (25.3%), Giardia sp (3.3%), Eimeria sp (3.3%), Pinworm eggs (3.3%), Naegleria sp (15.3%), Lecane niwati (1.3%), Trichomonas hominis (19.3%), Acanthamoeba spp (24.6%), Entamoeba coli (20.6%), Balantidium coli (12%), Ascaris sp (3.3%), Volvox sp (26%), Chilomastix mesnili (4%), Pelomyxa palustris (2.6%), Trinema enchelys (2.6%), Actinophrys Sol (7.3%), Amobea Vespertilio (9.3%), Rhabditea (5.3%), paramecium bursaria (9.3%), cyst of cestode (6%), Oocyst protozoa (16%), Euglena gracilis (10.6%).were isolated. The study's goal was to isolate some of the parasites that pollute the Euphrat
... Show MoreAbstract—The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients’ quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, w
... Show MoreIn current article an easy and selective method is proposed for spectrophotometric estimation of metoclopramide (MCP) in pharmaceutical preparations using cloud point extraction (CPE) procedure. The method involved reaction between MCP with 1-Naphthol in alkali conditions using Triton X-114 to form a stable dark purple dye. The Beer’s law limit in the range 0.34-9 μg mL-1 of MCP with r =0.9959 (n=3) after optimization. The relative standard deviation (RSD) and percentage recoveries were 0.89 %, and (96.99–104.11%) respectively. As well, using surfactant cloud point extraction as a method to extract MCP was reinforced the extinction coefficient(ε) to 1.7333×105L/mol.cm in surfactant-rich phase. The small volume of organi
... Show MoreImage Fusion Using A Convolutional Neural Network
In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi
... Show MoreAbstract. Geographical and remote sensing, which gave a picture of the change in the area of agricultural land in the study area for selected years (1980, 1990, 2000, 2010, 2020). In particular and Iraq in general, as this led to a reduction in the areas of agricultural lands and in return an increase in arid lands and their desertifica- tion and the loss of their productive value, which as a result leads to the migration of the population, the change of land sex, the failure to achieve food security and dependence on the import of the food basket.