The growing water demand has raised serious concerns about the future of irrigated agriculture in many parts all over the world, changing environmental conditions and shortage of water (especially in Iraq) have led to the need for a new system that efficiently manages the irrigation of crops. With the increasing population growing at a rapid pace, traditional agriculture will have a tough time meeting future food demands. Water availability and conservation are major concerns for farmers. The configuration of the smart irrigation system was designed based on data specific to the parameters concerning the characteristics of the plant and the properties of soil which are measured once in the research (permeability, pH, humidity, porosity, etc.), the soil moisture content sensors are placed in the root zone of plants when the crop needs to be irrigated the sensors send notifications to the user of the system from the application on a smartphone to operate the water pump and on the contrary when the soil saturated the sensors notify the user to turn off the water pump. This paper aims to discuss the aspects related to designing and fabricating an automatic irrigation system using sensors of soil moisture content using this method will save time and money significantly. The study found that the quantity of water consumed to irrigate the yellow corn crop in the portion assigned for smart irrigation technique in an area of 875 m2 is less than the amount of consumed water utilized in the section allocated for fixed sprinkler irrigation in the same area by 34.444%, furthermore, the yield of the yellow corn crop grown using smart irrigation technique exceeds that of the crop grown by fixed sprinkler irrigation. And also, human intervention will be reduced.
The alluvial fan of Mandali located between latitude 30˚45’00” N longitude 45˚30’00” E in east of Diyala Governorate, Iraq. Thirty-five wells were identified in the study area with average depth of 84 m and estimated area of 21550 ha. A three-dimensional conceptual model was prepared by using GMS program. From wells cross sections, four geological layers have been identified. The hydraulic conductivity of these layers was calculated for steady state condition, where the water levels for nine wells distributed over the study area were observed at same time. Afterward, PEST facility in the GMS was used to estimate the aquifer hydraulic characteristics. Other characteristics such as storage coefficient and specific yield have
... Show MoreGroundwater is an important source of fresh water especially in countries having a decrease in or no surface water; therefore itis essential to assess the quality of groundwater and find the possibility of its use in different purposes (domestic; agricultural; animal; and other purposes). In this paper samples from 66 wells lying in different places in Baghdad city were used to determine 13 water parameters, to find the quality of groundwater and evaluate the possibility of using it for human, animal and irrigation by calculating WQI, SAR, RSC and Na% and TDS indicators. WQI results showed that the groundwater in all wells are not qualified for human use, while SAR and RSC indicated that most samples are suitable for irrigation use, and
... Show MoreAn experiment was carried out to study the effect of soil organic carbon (SOC) and soil texture on the distance of the wetting front, cumulative water infiltration (I), infiltration rate (IR), saturated water conductivity (Ks), and water holding capacity (WHC). Three levels ( 0, 10, 20, and 30 g OC kg-1 ) from organic carbon (OC) were mixed with different soil materials sandy, loam, and clay texture soils. Field capacity (FC) and permanent wilting point (PWP) were estimated. Soil materials were placed in transparent plastic columns(12 cm soil column ), and water infiltration(I) was measured as a function of time, the distance of the wetting front and Ks. Results showed that advance we
irrigation use at many stations along the Euphrates River inside the Iraqi lands and to try to correlate the results with the satellite image analyses for the purpose of making a colored model for the Euphrates that can be used to predict the quality classifications of the river for irrigation use at any point along the river. The Bhargava method was used to calculate the water quality index for irrigation use at sixteen stations along the river from its entrance to the Iraqi land at Al-Qaim in Anbar governorate to its union with the Tigris River at Qurna in Basrah governorate. Coordinates of the sixteen stations of the Euphrates River were projected at the mosaic of Iraq satellite image which was taken from LANDSAT satellite for bands 1, 2
... Show MorePurpose: the purpose of this study is to investigate how managers working for the General Authority for Irrigation and Reclamation Projects react to the impact of Emotional Intelligence (EI) on their performance. Theoretical framework: The current study includes an intellectual framework on two variables, namely EI and Manager Performance (MP), because it is essential to investigate the relationship between these two variables and the impact of EI on MP. Design/methodology/approach: The research problem is that a manager's capacity to make wise decisions about their work or interactions with subordinates is diminished when they have inadequate EI. The questionnaire is used as a tool for gathering data for the study, and the st
... Show MoreA study of irrigation water was conducted Baghdad city to find out extent of its pollution by some heavy metals (Pb, Cd, Ni, Co, CU, Cr, Zn and Fe). Water samples were collected randomly from different sources (river, well and stream). Results showed that the concentration of studied heavy metals were as follows: Lead between 0.43-11.75 mg L-1, Cadmium between 0.01-0.95 mg L-1, Nickel between 0.008-0.46 mg L-1, Cobalt between Nil - 0.185 mg L-1, Copper is between 0.326 - 1.58 mg L-1, Chromium is between Nil-0.068 mg L-1, Zinc 0.398-1.182 mg L-1, as for Iro
An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to
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