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Thermal energy is utilized as an environmentally friendly energy source for seasonal heat and cold storage on a global scale. Specifically, the aquifer thermal energy storage system is highlighted for being cost-effective in cooling and heating applications. The study assesses the sustainability of the aquifer thermal energy storage in the Halabja-Khurmal sub-basin by evaluating six critical criteria: groundwater transmissivity, groundwater temperature, groundwater discharge, groundwater chemistry, population density, and per capita GDP. A multi-criteria decision analysis judgment is applied to analyze all criteria, resulting in a consistency ratio of 0.3% in the analytical hierarchy process. Consequently, the sustainability map for Aquifer Thermal Energy Storage in the Halabja-Khurmal sub-basin for heating reveals that 26.45% of the area is strongly sustainable located in the north and southwestern part of the sub-basin, 73.53% is moderate in the east, central, southeast, and southern regions, 0.02% is weakly sustainable as a tiny area in the southwestern. On the other hand, the sustainability map for Aquifer Thermal Energy Storage in the Halabja-Khurmal sub-basin for cooling reveals that 19% of the area is strongly sustainable located in the north, and southwestern parts of the sub-basin, 78% is moderate in the northeast, east, southeast, west, central, and southern regions, 3% is weakly sustainable as spots in the west and southwestern areas. [ABSTRACT FROM AUTHOR]

Methane (CH4) is a greenhouse gas resulting from human activities, especially landfills, and it has many potential environmental issues, such as its major role in global warming. On the other hand, methane can be converted to liquid fuel or electricity using chemical conversion or gas turbine generators. Therefore, reusing such gases could be of great environmental and economic benefit. In this context, this study aims to estimate the emissions of methane gas from the landfills in Al-Hillah City, Iraq, from 2023 to 2070 and the producible electric energy from this amount. The estimating process was carried out using the Land GEM model and compared with traditional models. The obtained results demonstrated that the total estimated landfill methane emissions for 48 years are 875,217 tons, and the average annual methane emission is 18,234 tons based on a yearly waste accumulation rate of 1,046,413 tons and a total waste amount of 50,227,808 tons. The anticipated loads of methane gas can be utilized to generate about 287,442 MW/year of electricity from 2023 to 2070. In conclusion, the results obtained from this study could be evidence of the potential environmental and economic benefits of harvesting and reusing methane gas from landfills. [ABSTRACT FROM AUTHOR]

In recent years, there has been a serious request for innovative, accurate approaches to be determined and controlled for dam failures. The present study aims to explore and evaluate the flood wave parameters that result from a dam break due to piping failure occurring in the body of the dam and routing the flood waves. Mosul Dam, which lies in the north of Iraq, and a reach of the Tigris River downstream the dam to Samarra Barrage at about 470 km are selected as a case study. A two-dimensional Hydrologic Engineering Center River Analysis System (2D HEC-RAS) and the Geographic Information System (GIS) have been supposed to be suitable for development calculations of the flood wave parameters based on the Digital Elevation Model (DEM) and land cover satellite images that enhance the calculations. The reservoir and twodimensional flow area are delineated and incorporated with DEM. Manning`s coefficient for the whole area has been extracted according to the Land Cover satellite image, which showed that its value ranges between 0.025 to 0.037 with a correlation coefficient R² equal to 0.845 and 0.801 for the calibration and validation processes, respectively. The results of the scenario display a substantial performance of the maps produced from the model that represented the depth, velocity, and water surface elevation. All the maximum values of dam break parameters lie near the dam body and slightly decrease downstream. It is pre-eminent that the 2D HEC-RAS model is appropriate for analyzing and simulating the occurrence of dam breaches by visualizing the distribution of flood wave depth and velocities in two dimensions. Hence, the clear improvement in producing maps, which monitor the spread of hydrodynamic waves, gives an indication of risk areas that are threatened by inundation and aids in the formulation of emergency plans. [ABSTRACT FROM AUTHOR]

Vast parts of the globe are facing a water scarcity problem owing to the increasing water demand of the growing population and urban expansion, and intensive agriculture and industrial activities. Arid and semiarid areas already suffer from a severe shortage of surface water supplies due to climatic conditions such as a temperature rise, evaporation rates, and diminution of rainfall amounts with discontinued intervals. Delineation of suitable sites for the groundwater potential recharging zones is one of the available solutions to recompense surface water shortages in the Al-Mohammedi basin in the Iraqi Western Desert. Recently, the utilization of modern geospatial techniques such as remote sensing (RS) data and geographic information system (GIS) in combination with multi-criteria decision-making (MCDM) approaches has proven an efficient tool for groundwater demarcation. In this study, RS data, such as Landsat 8 images and SRTM Digital Elevation Model (DEM), published geological maps, and metrological data were used to generate eight thematic layers of criteria--geomorphology, geology, lineament, rainfall, soil infiltration, slope, land use and land cover, and drainage density. All thematic maps were generated and transformed into the raster format depending on the raster conversion tool in ArcGIS 10.8 software. The output map of groundwater potential zones (GWPZs) was generated by integrating all the thematic layers according to the weightage values generated depending on the Analytical Hierarchal Process (AHP) approach. Finally, the prospective zones were examined and validated with present yield wells data. Twenty-two out of twenty-eight validation boreholes (76.87%) matched the predicted classes of the yield boreholes, and the cross-correlation value certified this result as R² = 0.67. [ABSTRACT FROM AUTHOR]

In times of water scarcity, groundwater is a vital resource that provides an alternate source of water for human consumption. In Iraq, the quality of rivers has been greatly affected by climate change and the dwindling availability of surface water. Examining and classifying the groundwater in this region is now vital. The present study sought to incorporate the groundwater property data (drinking purpose) with a geographic information system (GIS). Eleven variables were measured in 25 wells to investigate the physio-chemical properties around the Babylon province of Iraq. On the basis of the acceptability of groundwater for drinking, GWQI was categorized into four primary groups in the results. Approximately 28% of the twenty-five wells (1811.04 km2) are of excellent quality, 24% are of good quality (1552.3 km2), 44% are of low quality (2845.9 km2), and 4% are extremely contaminated (2587.2 km2). The average GWQI for the entire study region was 110.7, making it inappropriate for human consumption. It has been determined that approximately 52% of the groundwater from the examined wells can be deemed safe for consumption, although certain measurements surpass the permissible limits. To guarantee that the residents in these areas are supplied with water of superior quality and safety, treatment of the tested groundwater is recommended before use. [ABSTRACT FROM AUTHOR]

This study assessed the quality of water in the Shatt Al-Hillah River by adopting some variables of physical, chemical, and heavy metal elements. The samples have been taken at six sites along the river in 2020 (from January to December). The water quality index has been determined by using the weighted-arithmetic method which is including a series of equations. Also, the model of Inverse-Distance-Weighting in the Geographic information system was applied to create a map of the water quality in the study area. Eleven physicochemical variables and five elements of heavy metals were comprised of calcium, magnesium, dissolved oxygen, Hydrogen Ions, chloride, sulfate, total hardness, total dissolved solids, turbidity, alkalinity, electric conductivity, cadmium, copper, iron, lead, and zinc. The results showed the values of the water quality index ranged from 245 to 253 (with a category of 200–300). The water quality index was rated as very poor for the selected locations along the Shatt Al-Hillah River. The GIS result illustrated the distributing map of water quality for the Shatt Al-Hillah River for household uses. The combination of the water quality index calculations with GIS in the current study might be used as a guide for future studies. [ABSTRACT FROM AUTHOR]

Accurate forecasting techniques for a stochastic pattern of water demand are essential for any city that faces high variability in climate factors and a shortage of water resources. This study was the first research to assess the impact of climatic factors on urban water demand in Iraq, which is one of the hottest countries in the world. We developed a novel forecasting methodology that includes data preprocessing and an artificial neural network (ANN) model, which we integrated with a recent nature-inspired metaheuristic algorithm [marine predators algorithm (MPA)]. The MPA-ANN algorithm was compared with four nature-inspired metaheuristic algorithms. Nine climatic factors were examined with different scenarios to simulate the monthly stochastic urban water demand over 11 years for Baghdad City, Iraq. The results revealed that (1) precipitation, solar radiation, and dew point temperature are the most relevant factors; (2) the ANN model becomes more accurate when it is used in combination with the MPA; and (3) this methodology can accurately forecast water demand considering the variability in climatic factors. These findings are of considerable significance to water utilities in planning, reviewing, and comparing the availability of freshwater resources and increasing water requests (i.e., adaptation variability of climatic factors). [ABSTRACT FROM AUTHOR]

Evolving groundwater vulnerability from DRASTIC to modified DRASTIC methods helps choose the most accurate areas that are most delicate toward pollution. This study aims to modify DRASTIC with land use and water quality index for groundwater vulnerability assessment in the Halabja-Khurmal sub-basin, NE/Iraq. The Halabja-Khurmal sub-basin groundwater vulnerability index is calculated from nine hydrogeological parameters by the overlay weighting method. As a result, 1.3% of the total area has a very high vulnerability value and 46.1% with high vulnerability. The regions with high groundwater vulnerability have a high-water table and groundwater recharge. Nitrate concentration was used to validate the result, and the Pearson correlation and recession analysis between the modified DRASTIC index and nitrate concentration depicted a strong relation with 0.76 and 0.7, respectively. [ABSTRACT FROM AUTHOR]

Accurate streamflow prediction is significant when developing water resource management and planning, forecasting floods, and mitigating flood damage. This research developed a novel methodology that involves data pre-processing and an artificial neural network (ANN) optimised with the coefficient-based particle swarm optimisation and chaotic gravitational search algorithm (CPSOCGSA-ANN) to forecast the monthly water streamflow. The monthly streamflow data of the Tigris River at Amarah City, Iraq, from 2010 to 2020, were used to build and evaluate the suggested methodology. The performance of CPSOCGSA was compared with the slim mold algorithm (SMA) and marine predator algorithm (MPA). The principal findings of this research are that data pre-processing effectively improves the data quality and determines the optimum predictor scenario. The hybrid CPSOCGSA-ANN outperformed both the SMA-ANN and MPA-ANN algorithms. The suggested methodology offered accurate results with a coefficient of determination of 0.91, and 100% of the data were scattered between the agreement limits of the Bland–Altman diagram. The research results represent a further step toward developing hybrid models in hydrology applications. [ABSTRACT FROM AUTHOR]

Modelling drought is vital to water resources management, particularly in arid areas, to reduce its effects. Drought severity and frequency are significantly influenced by climate change. In this study, a novel hybrid methodology was built, data preprocessing and artificial neural network (ANN) combined with the constriction coefficient-based particle swarm optimisation and chaotic gravitational search algorithm (CPSOCGSA), to forecast standard precipitation index (SPI) based on climatic factors. Additionally, the marine predators algorithm (MPA) and the slime mould algorithm (SMA) were used to validate the performance of the CPSOCGSA algorithm. Climatic factors data from 1990 to 2020 were employed to create and evaluate the SPI 1, SPI 3, and SPI 6 models for Al-Kut City, Iraq. The results indicated that data preprocessing methods improve data quality and find the best predictors scenario. The performance of CPSOCGSA-ANN is better than MPA-ANN and SMA-ANN algorithms based on various statistical criteria (i.e., R2, MAE, and RMSE). The proposed methodology yield R2 = 0.93, 0.93, and 0.88 for SPI 1, SPI 3, and SPI 6, respectively. [ABSTRACT FROM AUTHOR]

Surface water and groundwater are significant for population and other activities due to the decreasing surface water flow toward Iraq. Therefore, there is a need to analyze groundwater's quality and classification and its applicability as an alternative in various human activities in the study area. This study utilized the groundwater quality index model for drinking uses (GW.Q.I.) and entered the resulting values in the GIS environment. This model was applied to 56 wells in Al-Hillah city by measuring twelve variables in each well. The measured variables were calcium (Ca), magnesium (Mg), sodium (Na), chloride (Cl), sulfate (SO4), bicarbonate (HCO3), total hardness (TH), total dissolved solids (TDS), nitrate (NO3), and electric conductivity (EC). The prediction map of GW.Q.I. was produced in the GIS. Then, the distributing map was divided into six categories based on the suitability of groundwater for drinking uses. The areas' values of six categories with their ratings were about 5 km2 (excellent), 122 km2 (good), 610 km2 (poor), 63 km2 (very poor), 36 km2 (contaminated), and 24 km2 (very contaminated). For the entire study area, the average value of the GW.Q.I. was 177, classified as poor for drinking uses. [ABSTRACT FROM AUTHOR]

Iraq has been suffering from decreasing Euphrates discharge due to the construction of dams within upstream countries and the use of surface irrigation systems. The country is facing a problem with meeting the increasing demand for water as a result of population growth and development in the industrial and agricultural sectors. Therefore, a simulation modelling was applied for western Iraq (Ramadi city as a case study) using the Water Evaluation and Planning System (WEAP) for the period 2018-2035. This research follows a four-step approach that involves: (i) evaluating the available water of the Euphrates River under declined water imports caused by the construction of dams in Turkey and Syria, (ii) assessing present and future water demands of the domestic, industrial, and agricultural sectors, (iii) improving water productivity (WP) by means of saving more water, (iv) estimating the economic returns under improved water use. The results showed that Iraq would face a serious problem in the coming years, represented by the limited storage of Haditha Dam, which is considered the strategic water storage site for the central and southern regions of Iraq. The study indicated the necessity of finding alternative sources of water supply by adopting new water management strategies to reduce the water deficit. [ABSTRACT FROM AUTHOR]

This work aims to evaluate water scarcity in Thi-Qar governorate, Iraq, based on GIS estimation, environmental data, climate-change effects, and detection of the changes in marshes over the last three decades (1991–2021). The methodology process included collecting and analysing the related data sets such as water quality indicators, surface water quantity, climatic data, and Landsat’s images. GIS-based data and spatial data were acquired from the USGS website. Arc GIS 10.4.1 software was used to create a hydrological analysis. The results showed that generally, in Iraq, the annual volume of water available per person is 1,390.95 m³/cap/year, which is lower than the threshold for water scarcity (1700 m³/cap/year). The average daily potable water per person in Thi-Qar governorate was 284 L/cap/day, lower than the general average daily potable water per person of Iraq (340 L/cap/day). Meanwhile, 6% of the months along 1998–2018 did not meet the water demands. Water quality tests exhibited some high amounts of pollutants in drinking water, e.g., biological pollution was recorded in 55% of the total number of annual samples. Landsat’s images illustrated a high variation in water areas of marshes over the selected period, whereas the highest marshes area was 1548.21 km² in 1991 compared to the lowest area, 65.45 km² found in 1999. To sum up, the research outcomes revealed that the study area faced a serious water scarcity, which had a negative impact on the local people. Also, this research offered a scientific view for the decision-makers to mitigate and manage the water scarcity problem. [ABSTRACT FROM AUTHOR]

Salinity is a classic problem in water quality management since it is directly associated with low water quality indices. Debate continues about selecting the best model for water quality forecasting, it remains a major challenge and causes much uncertainty. Accordingly, identifying the optimal modelling that can capture the salinity behaviour is becoming a common trend in recent water quality research. This study applies novel combined techniques, including data pre- processing and artificial neural network (ANN) optimised with constriction coeffi- cient-based particle swarm optimisation and chaotic gravitational search algorithm (CPSOCGSA) to forecast monthly salinity data. Historical monthly total dissolved solids (TDS) and electrical conductivity (EC) data of the Euphrates River at Al- Musayyab, Babylon, and climatic factors from 2010 to 2019 were used to build and validate the methodology. Additionally, for more validation, the CPSOCGSA-ANN was compared with the slime mould algorithm (SMA-ANN), particle swarm optimisation (PSO-ANN) and multi-verse optimiser (MVO-ANN). The results reveal that the pre-processing data approaches improved data quality and selected the best predictors’ scenario. The CPSOCGSA-ANN algorithm is the best based on several statistical criteria. The proposed methodology accurately simulated the TDS and EC time series based on R² = 0.99 and 0.97, respectively, and SI = 0.003 for both parameters. [ABSTRACT FROM AUTHOR]

The presence of an economical solution to predict soil behaviour is essential for new construction areas. This paper aims to investigate the ultimate interpolation method for predicting the soil bearing capacity of An-Najaf city-Iraq based on field investigation information. Firstly, the engineering bearing capacity was calculated based on the in-site N-SPT values using dynamic loading for 464 boreholes with depths of 0–2 m, using the Meyerhof formula. The data then were classified and imported to the GIS program to apply the interpolation methods. Four deterministic and two geostatistical interpolation methods were applied to produce six bearing capacity maps. The statistical analyses were performed using two methods: the common cross-validation method by the coefficient of determination (R2) and root mean square error (RMSE), where the results showed that ordinary kriging (OK) is the ultimate method with the least RMSE and highest R2. These results were confusing so, the backward elimination regression (BER) procedure was applied to gain the definite result. The results of BER show that among all the deterministic methods, the IDW is the optimal and most significant interpolation method. The result of geostatistical methods shows that EBK is the best method in our case than the OK method. BER also applied to all six methods and shows that IDW is the ultimate significant method. The results indicate no general ultimate interpolation method for all cases and datasets type; therefore, the statistical analyses must be performed for each case and dataset. [ABSTRACT FROM AUTHOR]

This study was undertaken to estimate the energy potential of municipal solid waste via creating a relationship between the high heating value (HHV) and the fractions of physical composition of municipal solid waste MSW (% food, % plastic, % paper, % wood, % textile) into the two scenarios, namely wet MSW (as discarded) and dry (free moisture). The created models were determined based on the results of obtained from the analysis of the components of the Al-Diwaniyah MSW and then from previous studies which involved experimental ultimate analysis (% C, % O, % H, % N, %S) of MSW, supported by the equations and models of previous studies which were used for HHV calculation. SPSS Statistical software was used to prepare the models. For each scenario, the input datasets were 60 cases, taking into account the minimization of the data and the average of HHV that result from equations. Four models were created, two models for each status where R2 was 1.00 and 0.999 for dry and wet situation, respectively. However, the equations of verification process showed that the models which depended on the dry fractions are more accurate. The produced HHV from the dry and wet MSW components in the Al-Diwaniyah City is 8655 KJ/Kg and 6440 KJ/Kg, respectively (as discarded). [ABSTRACT FROM AUTHOR]

Iraq currently undergoing the problem of water shortage, although Iraq has two Rivers (Euphrates and Tigris) pass throughout most of its areas, and they have represented a major source of water supply. In the current research, to evaluate the quality of the Euphrates river in Iraq based on the values of total dissolved salts (TDS), the TDS concentrations were collected from sixteen sections along the river in the three succeeding years (2011, 2012, and 2013). The evaluation of the river was done depending on the classification of (W.H.O. (World Health Organization). (2003). Total Dissolved Salts in Drinking-water: Background document for development of W.H.O. Guidelines for Drinking-water Quality. World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland). of rivers for drinking uses. Inverse Distance Weighting Technique (IDWT) as a tool in the GIS was employed to establish the maps of the river that using interpolation/prediction for the TDS concentrations to each selected year and the average values of TDS for these 3 years. Based on the five categories of rivers' classification of the TDS concentrations according to the (W.H.O. (World Health Organization). (2003). Total Dissolved Salts in Drinking-water: Background document for development of W.H.O. Guidelines for Drinking-water Quality. World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland), the Euphrates river was classified, and the maps of classification for the years 2011, 2012 and 2013 and the average values for 3 years were created. The average values for 3 years of TDS along the Euphrates river indicated that the sections from SC-1 to SC-4 as moderate-water-quality-Category-3, the sections from SC-5 to SC-10 as poor-water-quality-Category-4, while the sections between SC-11 to SC-16 as very poor-water-quality-Category-5. The interpolation maps showed that the Euphrates river in Iraq was ranged from moderate water quality (Category-3) to very poor water quality (Category-5). [ABSTRACT FROM AUTHOR]

A field survey has been conducted for the study area using the Global Positioning System (GPS) and geological and geomorphological maps of the area. The study area is one of the important areas in Iraq characterized by scarce water resources. The purpose of the study is to determine the hydro-chemical processes and their relationship to groundwater quality carried out in the southwestern desert region of Iraq, where the region lacks extensive studies of water resources. Twenty-eight groundwater samples were collected from wells distributed between the eastern borders of Saudi Arabia and the West Bank of the Euphrates River. For the purpose of hydrogeochemical analyses, the Fetter method was used to collect and examine samples. A large part of the recharge area is located in Saudi Arabia, where the groundwater bearing aquifer represented by the Dammam formation extends to Iraq and Saudi Arabian International borders. The analysis determined the order of cations (Na+ > Ca2+ > Mg2+ > K+ ) and anions (Cl– > SO4 2– > HCO3 – ). High values of the variation coefficient (CV) correspond to the concentration of potassium, sodium and chloride ions (CV: 68.7, 64.7 and 64 respectively). To identify the hydrochemical water facies, the Piper diagram was used. It was found that 53% of the water samples belong to the Na-Cl type and 40% are of the Ca-Mg-Cl type, while the rest of the samples are the Ca-Cl type. To identify geochemical processes, it was found that ion exchange processes via chloroalkaline indices 1 and 2 are prevalent between Ca2+, Mg2+ in the groundwater and Na+, K+ in water bearing rocks. To learn more about the processes that led to the concentration of certain ions, such as sodium, it was found that they tend to be of silicate minerals related to surface runoff of water in recharge areas and carbonic rocks. It was also found that rock / soil-groundwater interaction and evaporation processes were the formal processes in the saturated zone and evaporation in the unsaturated zone are prevalent processes of groundwater ion concentration. [ABSTRACT FROM AUTHOR]

Currently, desertification is a major problem in the western desert of Iraq. The harsh nature, remoteness, and size of the desert make it difficult and expensive to monitor and mitigate desertification. Therefore, this study proposed a comprehensive and cost-effective method, via the integration of geographic information systems (GISs) and remote sensing (RS) techniques to estimate the potential risk of desertification, to identify the most vulnerable areas and determine the most appropriate sites for rainwater conservation. Two indices, namely, the Normalized Differential Vegetation Index (NDVI) and Land Degradation Index (LDI), were used for a cadastral assessment of land degradation. The findings of the combined rainwater harvesting appropriateness map, and the maps of NDVI and LDI changes found that 65% of highly suitable land for rainwater harvesting lies in the large change and 35% lies in the small change of NDVI, and 85% of highly suitable land lies in areas with a moderate change and 12% lies in strong change of LDI. The adoption of the weighted linear combination (WLC) and Boolean methods within the GIS environment, and the analysis of NDVI with LDI changes can allow hydrologists, decision-makers, and planners to quickly determine and minimize the risk of desertification and to prioritize the determination of suitable sites for rainwater harvesting. [ABSTRACT FROM AUTHOR]

The investigation region is found in the central part of Iraq within the of Karbala Governorate, where it is located in the western part of the Governorate and Lake Razaza in the north of the region, while in the western and southern part of the region is Anbar Governorate and geographically (43° 10′ 25.7″, 43° 39″ 0.3″) longitude and (32° 10′ 25.7″, 32° 36′ 25.7″) latitude. The area of study is about 2400 Km2. The groundwater modeling system (GMS) v10.3 program was used for the modeling of ground water in the area containing about 22 wells distributed throughout the study area and the discharge of these wells ranges from 7 to 100 l/s and the rate of discharge of these wells up to 36 l/s. The model was initially operated within a steady state and after obtaining a match between the models results with the initial values of groundwater levels, the results of this case were adopted as inputs to run the model within the unsteady state. The model was worked within the sight of the above wells for 3 years and the results of the operation indicate a decrease in groundwater levels ranging from 2 to 21 m distributed uniformly throughout the study area. [ABSTRACT FROM AUTHOR]

Most of the hydraulic structures rest on an impervious foundation to reserve water at the upstream side. The water heads difference leads to water movement from the higher to the lower head through the porous soil layer beneath the foundation, generating an uplift pressure under the structure floor. In this study, a new method is presented to estimate the uplift pressures at key points by performing sub-surface flow analysis using the Analysis SYStem (ANSYS) software. Then a statistical analysis to validate the proposed equations is conducted using the SPSS software. The case study for this research is a barrage in Kufa city-Iraq. The used data to implement this study was water levels, soil permeability, and length of imperious foundation. The obtained results show good outcomes from using the proposed method to develop uplift pressure equations. The comparison of the current study results with Khosla's equation showed good agreement where the coefficient of determination (R2) and the standard error of estimation (SEE) for the equations were between (99.9–97.8) and (0.024–0.11), respectively. [ABSTRACT FROM AUTHOR]

This study intends to evaluate university students' awareness regarding water pollution in Iraq to show the environmental education contribution in reducing water pollution. The study was conducted in Wasit university, Wasit province, Iraq by field questionnaire survey with 388 students from the civil engineering department and engineering college. The questionnaires were divided according to the pollution causes into industrial, agricultural and sewage water pollutants. The data were analyzed utilizing the thematic analysis to assess environmental knowledge and awareness of water pollution risks. The results show that most students have high interest in environmental conservation, yet, a lack of education in general environmental education, as the educational curriculum focuses on theoretical aspects more than the practical ones. The results also show that the media role is inactive concerning environmental awareness of water pollution. This study provides a scientific view of policymakers for potential future conditions to find solutions that achieve sustainability goals. [ABSTRACT FROM AUTHOR]

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized support vector regression model with a genetic algorithm (SVR-GA) over the other ML forecasting models for monthly river flow forecasting using 90%–10% data division. In addition, it was found to improve the accuracy in forecasting high flow events. The unique architecture of developed SVR-GA due to the ability of the GA optimizer to tune the internal parameters of the SVR model provides a robust learning process. This has made it more efficient in forecasting stochastic river flow behaviour compared to the other developed hybrid models. [ABSTRACT FROM AUTHOR]

Mosul Dam is an earth fill dam, with a storage capacity of 11.11 km3 constructed on highly karstified gypsum beds alternating with marl and limestone. After impounding in 1986, seepage locations were recognized. The dam situation now indicates that it is in a state of extreme relative risk. If it fails, then 6 million people will be affected and 7202 km2 area will be flooded. Grouting operations will elongate the life of the dam but will not solve the problem. Building a protection dam downstream will be the best measures to secure the safety of the downstream area and its' population. [ABSTRACT FROM AUTHOR]

Iraqi Kurdistan Region is located in the northeastern part of the Arabian Plate which is colliding with the Eurasian (Iranian) Plate and is located within the Zagros Foreland Basin. This collision, which is still active with convergent type of tectonic boundary, has caused deformation of the rocks in the Zagros Foreland Basin with different intensities. The deformation intensity decreases southwest wards since the exerted stresses from the collision is in a NE–SW direction. Depending on the deformation intensity and many other factors, the tectonic framework of the region which is part of the main tectonic frame of Iraq is divided into three main tectonic units among them only two units are within Kurdistan Region. The two zones are from NE–SW direction: (1) Shalair Terrane, and (2) Outer Platform. In the current study, evidences about Neotectonic activities are presented from different parts of Kurdistan Region depending on different geomorphological and structural features. Among those features are: abnormal trends of valleys, dislocated and dissected alluvial fans, regional lineaments, water and wind gaps, faulted rocks of Pliocene–Pleistocene age, active faults. The Neotectonic evidences were recognized using satellite images and the existing Neotectonic data, and validated in the field. [ABSTRACT FROM AUTHOR]

In many parts of the world, groundwater quality is decreasing due to urbanization industrialization and use of agricultures in rural areas. This subject has formed an urgent need to determine the suitability of groundwater for various purposes. The aim of this study is to determine a groundwater index for groundwater use for irrigation in agriculture. The study is carried out in an agricultural area; near Al Kufa city, North of Al Najaf province, Iraq. Many chemical variables are used in this model, including (total dissolved solids TDS, electrical conductivity EC, sodium Na, potassium K and iron Fe), in addition to some of the heavy metals (cadmium Cd, lead Pb, chromium Cr, and nickel Ni), that also added to the index. The weight's parameters are determined using analytical hierarchy process (AHP) and classified into five groups based on the human health significance of these parameters and negative effect on agriculture. The result of this study indicates that the water quality index (WQI) records values between (0 and 4.33), and in which the value of (2.16) represents the limit between unpolluted and polluted groundwater. This study confirms that all groundwater samples over the study area are suitable for agriculture. The final WQI values are exported to ArcMap environment to prepare the final WQI maps of study area. [ABSTRACT FROM AUTHOR]

The unified soil classification system (USCS) first proposed by Casagrande and subsequently developed by the Army Corps of Engineers. It widely used in many building codes and books. An-Najaf city is the most important city in Iraq due to its religious and spiritual value in the Muslim world, so it is fast expanding and continuous developing city in Iraq. The data from 464 boreholes in the study area for depths of 0–26 m have been used. 13 Soil samples were collected from each borehole with 13 depths level (0–26) m with 2 m intervals. The USCS was applied to the soil samples from 13 depth levels borehole. This research aims to create a geodatabase for soil properties for An-Najaf. The ArcGIS 10.5 software was used to interpolate the spatial data to produce 33 geotechnical maps for fine soil, coarse soil and USCS for 13 depth levels. For numerical soil data, Ordinary Kriging has been used for interpolation mapping of Fine and Coarse percentage data for each depth. For non-numerical (nominal) soil data (USCS class), the Indicator Kriging method is used. The results show that the coarse soil occupied 85–95% for depth 0–16 m and consist of (SP, SP-SM, SM) while fine soil occupied 5–15% consisting of (OL, CH, ML) subsequently, this soil when compacted has a permeability of pervious to semi impervious, good shearing strength, low to very low compressibility and acceptable workability as a construction material. The results also show that after 16 m depths until 26 m, the fine soil percentage increased to 40% with a coarse soil percentage of 60%, indicating changes in soil characteristics as the permeability became semi-pervious to impervious, fair shearing strength, medium compressibility and fair workability as a construction material. The study results will provide help and saving time, efforts and money in preliminary engineering designs. [ABSTRACT FROM AUTHOR]

Oil well drilling data from 23 oil wells in northern Iraq are analyzed and optimized controllable drilling parameters are found. The most widely used Bourgoyne and Young (BY) penetration rate model have been chosen for roller cone bits, and parameters were extracted to adjust for other bit types. In this regard, the collected data from real drilling operation have initially been averaged in short clusters based on changes in both lithology and bottom hole assemblies. The averaging was performed to overcome the issues related to noisy data negative effect and the lithological homogeneity assumption. Second, the Dmitriy Belozerov modifications for polycrystalline diamond bits compacts have been utilized to correct the model to the bit weight. The drilling formulas were used to calculate other required parameters for the BYM. Third, threshold weight for each cluster was determined through the relationship between bit weight and depth instead of the usual Drill of Test. Fourth, coefficients of the BYM were calculated for each cluster using multilinear regression. Fifth, a new model was developed to find the optimum drill string rotation based on changes in torque and bit diameter with depth. The above-developed approach has been implemented successfully on 23 oil wells field data to find optimum penetration rate, weight on bit and string rotation. [ABSTRACT FROM AUTHOR]

Al-Hawizeh Marsh is considered a major marsh in the south of Iraq with a longitude of 47° 32″–47° 45″ and latitude of 31° 30″–31° 42″, length of 80 km and width of 30 km, while the depth is from 1.5 to 4 m. It has a significant impact on the ecosystem and provides habitat for several types of living creatures. The surface water and the agricultural lands surrounding this marsh suffered from high level degrees of salinity. In the last decades, radical deterioration of water quality in this marsh happened because of the post-war-related events and several human activities. Landsat-8 data was used to predict and evaluate the spatial variation and map distributions of the salinity, SO4 and CaCO3 within Al-Hawizeh Marsh during the two seasons in the year 2017 based on the development of salinity and minerals mathematical equations. The evaluated values for salinity, SO4 and CaCO3 are found to be minimal in winter and maximum in autumn. The values of correlation coefficient (R2) between the real data and the equation results for the salinity, SO4 and CaCO3 during the two seasons are 0.95, 0.96 and 0.92, respectively. [ABSTRACT FROM AUTHOR]

Prudent management of Iraqi water resources under climate change conditions requires plans to be based on actual figures of the storage capacity of existing reservoirs. With the absence of sediment flushing measures, the actual storage capacity of Dokan Reservoir (operated since 1959) has been affected by the amount of sediment delivered during its operational life leading to an undetermined reduction in its storage capacity. In consequence, there has not been an update on the dam's operational storage capacity curves. In this research, new operational curves were established for the reservoir based on a recent bathymetric survey undertaken in 2014. The reduction in reservoir capacity during the period between 1959 and 2014 was calculated by the mean of the difference between the designed storage capacity and the storage capacity which was concluded from the 2014 bathymetric survey. Moreover, the rate of sediment transported to the reservoir was calculated based on the overall quantities of accumulated sediment and the water discharge of the Lesser Zab River into the reservoir. The results indicate that the dam capacity is reduced by 25% due to sedimentation of an estimated volume of 367 million cubic metres at water level 480 m.a.s.l. The annual sedimentation rate was about 6.6 million cubic metres, and the sediment yield was estimated to be 701.2 t∙km−3∙year. [ABSTRACT FROM AUTHOR]

The capability of the extreme learning machine (ELM) model in modeling stochastic, nonlinear, and complex hydrological engineering problems has been proven remarkably. The classical ELM training algorithm is based on a nontuned and random procedure that might not be efficient in convergence of excellent performance or possible entrapment in the local minima problem. This current study investigates the integration of a newly explored metaheuristic algorithm (i.e., Salp Swarm Algorithm (SSA)) with the ELM model to forecast monthly river flow. Twenty years of river flow data time series of the Tigris river at the Baghdad station, Iraq, is used as a case study. Different input combinations are applied for constructing the predictive models based on antecedent values. The results are evaluated based on several statistical measures and graphical presentations. The river flow forecast accuracy of SSA-ELM outperformed the classical ELM and other artificial intelligence (AI) models. Over the testing phase, the proposed SSA-ELM model yielded a satisfactory enhancement in the level accuracies (8.4 and 13.1 percentage of augmentation for RMSE and MAE, respectively) against the classical ELM model. In summary, the study ascertains that the SSA-ELM model is a qualified data-intelligent model for monthly river flow prediction at the Tigris river, Iraq. [ABSTRACT FROM AUTHOR]

Evaporation, one of the fundamental components of the hydrology cycle, is differently influenced by various meteorological variables in different climatic regions. The accurate prediction of evaporation is essential for multiple water resources engineering applications, particularly in developing countries like Iraq where the meteorological stations are not sustained and operated appropriately for in situ estimations. This is where advanced methodologies such as machine learning (ML) models can make valuable contributions. In this research, evaporation is predicted at two different meteorological stations located in arid and semi-arid regions of Iraq. Four different ML models for the prediction of evaporation – the classification and regression tree (CART), the cascade correlation neural network (CCNNs), gene expression programming (GEP), and the support vector machine (SVM) – were developed and constructed using various input combinations of meteorological variables. The results reveal that the best predictions are achieved by incorporating sunshine hours, wind speed, relative humidity, rainfall, and the minimum, mean, and maximum temperatures. The SVM was found to show the best performance with wind speed, rainfall, and relative humidity as inputs at Station I (R2 =.92), and with all variables as inputs at Station II (R2 =.97). All the ML models performed well in predicting evaporation at the investigated locations. [ABSTRACT FROM AUTHOR]

Landfill site's selection represents a complicated process due to the large number of variables to be adopted. In this study, an arid area (Babylon Governorate as a case study) was selected. It is located in the middle region of Iraq. In this area, the landfills do not satisfy the required international criteria. Fifteen of the most significant criteria were selected for this purpose. For suitable weight for each criterion, the multi-criteria decision-making (MCDM) methods were applied. These methods are AHP and RSW. In the GIS software 10.5, the raster maps of the chosen criterion were arranged and analyzed. The method of change detection was implemented to determine the matching pixels and non-matching pixels. The final results showed that there are two candidate locations for landfills for each district in the governorate (ten sites). The areas of the selected sites were sufficient to contain the cumulative quantity of solid waste from 2020 until 2030. [ABSTRACT FROM AUTHOR]

The Tectonic Activity of regions with active tectonics can be assessed by using of the geomorphic indices. Six Geomorphic indices including stream-gradient index (SL), drainage basin asymmetry (Af), drainage basin shape (Bs), hypsometric integral (Hi), valley floor width-valley height ratio (Vf), and mountain-front sinuosity (Smf) were calculated using GIS technique in Kifri Chai Basin; northeast Iraq, which belongs to the Western Zagros Mountain. The basin was divided into eighteen sub-basins depending on the 4th, 5th and 6th stream orders of the drainage within Kirfi Basin. It was found that the SL, Af, Bs, Hi, Vf, and Smf (J) values are uniform and exhibit almost the same classes. However, few exceptions occur, especially in Bs values, but the exceptional values do not influence significantly on the acquired results, in each of the eighteen sub-basin. From these indices the relative active tectonics index value (Iat) was determined. The results of average Iat values (2.35) showed that the tectonic activity in the whole basin is Moderate. Moreover, an attempt was carried out to compare the regional Neotectonic activity with the relative tectonic activity in the basin. The results showed that there is a positive relation between the two comparatives; especially the subsidence amount and scored relative tectonic activity. [ABSTRACT FROM AUTHOR]

Marshes represent a unique ecosystem covering a large area of southern Iraq. In a major environmental disaster, the marshes of Iraq were drained, especially during the 1990s. Since then, droughts and the decrease in water imports from the Tigris and Euphrates rivers from Turkey and Iran have prevented them from regaining their former extent. The aim of this research is to extract the values of the normalized difference vegetation index (NDVI) for the period 1977–2017 from Landsat 2 MSS (multispectral scanner), Landsat 8 OLI (operational land imager) and Sentinel 2 MSI (multi-spectral imaging mission) satellite images and use supervised classification to quantify land and water cover change. The results from the two satellites (Landsat 2 and Landsat 8) are compared with Sentinel 2 to determine the best tool for detecting changes in land and water cover. We also assess the potential impacts of climate change through the study of the annual average maximum temperature and precipitation in different areas in the marshes for the period 1981–2016. The NDVI analysis and image classification showed the degradation of vegetation and water bodies in the marshes, as vast areas of natural vegetation and agricultural lands disappeared and were replaced with barren areas. The marshes were influenced by climatic change, including rising temperature and the diminishing amount of precipitation during 1981–2016. [ABSTRACT FROM AUTHOR]

Mosul Dam is one of the biggest hydraulic structures in Iraq. It was constructed in 1986 on the Tigris River in the north of Iraq. The initial storage capacity and water surface area of its reservoir reaches 11.11 km3 and 380 km2 respectively at the maximum operation level 330 m a.s.l. The dam was operated in 1986. A total of 56 samples were collected from the bottom of Mosul reservoir covering most of the reservoir area. The results of the analysis of these samples revealed that they were composed of gravel (3.8%), sand (15%), silt (55.5%) and clay (25.7%). The distribution of these sediments indicates that the silt portion represents the highest followed by clay and then sand. However, sand percentages are the highest in the northern zone of the reservoir where the River Tigris enters the reservoir and decreases gradually toward the dam site. In the meantime, silt percentage decreases toward the dam site while the finer fraction (i.e. clay) increases. [ABSTRACT FROM AUTHOR]

Mosul Dam is one of the biggest hydraulic structures in Iraq. Its storage capacity is 11.11 × 109m3at a maximum operation level of 330 m a.s.l. The dam became operational in 1986 and no survey has been conducted to determine its storage capacity and establish new operational curves since this date. A topographic map of scale 1:50 000 dated 1983 was converted into triangulated irregular network (TIN) format using the ArcGIS program to evaluate the operational curves. Then the reservoir was surveyed in 2011 to establish the reduction in its storage capacity and to develop new operational curves. The results indicated that the reduction in the storage capacity of the reservoir was 14.73%. This implies that the rate of sedimentation within the reservoir was 45.72 × 106m3year−1. These results indicate that most of the sediment was deposited within the upper zone of the reservoir where the River Tigris enters the reservoir. EditorD. Koutsoyiannis CitationIssa, E.I., Al-Ansari, N., and Knutsson, S., 2013. Sedimentation and new operational curves for Mosul Dam, Iraq.Hydrological Sciences Journal, 58 (7), 1456–1466. [ABSTRACT FROM AUTHOR]

The evaluation of groundwater quality in the Dammam formation, Faddak farm, Karbala Governorate, Iraq proved that the sulfate (SO42−) concentrations have high values; so, this water is not suitable for livestock, poultry and irrigation purposes. For reclamation of this water, manufacturing of new sorbent for permeable reactive barrier was required through precipitation of Mg and Fe hydroxides nanoparticles on the activated carbon (AC) surface with best Mg/Fe molar ratio of 7.5/2.5. Mixture of 50% coated AC and 50% scrap iron was applied to eliminate SO42− from contaminated water with efficiency of 59% and maximum capacity of adsorption equals to 9.5 mg/g for a time period of 1 h, sorbent dosage 40 g/L, and initial pH = 5 at 50 mg/L initial SO42− concentration and 200 rpm shaking speed. Characterization analyses certified that the plantation of Mg and Fe nanoparticles onto AC was achieved. Continuous tests showed that the longevity of composite sorbent is increased with thicker bed and lower influent concentration and flow rate. Computer solution (COMSOL) software was well simulated for continuous measurements. The reclamation of real contaminated groundwater was achieved in column set-up with efficiency of 70% when flow rate was 5 mL/min, bed depth was 50 cm and inlet SO42− concentration was 2301 mg/L. [ABSTRACT FROM AUTHOR]

Using solely an optical remotely sensed dataset to obtain an accurate thematic map of land use and land cover (LU/LC) is a serious challenge. The dataset fusion of multispectral and panchromatic images play a big role and provide an accurate estimation of LU/LC map simply because using a dataset from different spectrum portions with different spatial and spectral characteristics will improve image classification. For this study, the Landsat operational land imager multispectral and panchromatic images were adopted. This study aimed to investigate the effectiveness of using a panchromatic highly spatial resolution to refine the methodology for LU/LC mapping in Baghdad city, Iraq, by performing a comparison of classifications using different algorithms on multispectral and fused images. Different classification algorithms were employed to classify the data set; minimum distance (MD) and the maximum likelihood classifier (MLC). A suitable classification method was proposed to map LU/LC based on the outcome results. The result evaluation was conducted by applying a confusion matrix. An overall accuracy of a fused image using a principal component-based spectral sharpening algorithm and classified by the MLC classifier reveals the highest accurate results with an overall accuracy and kappa coefficient of 98.90% and 0.98, respectively. Results showed that the best methodology for LU/LC mapping of the study area is found from fusion of multispectral with panchromatic images via principal component-based spectral algorithm with MLC approach for classification. [ABSTRACT FROM AUTHOR]

In recent years, the problem of rising salinity levels in the Shatt al-Arab river in southern Iraq has been repeated, which has directly affected the living and health situation and the agricultural activity of these areas. Six sampling stations were selected along Shatt al-Arab to estimate the concentration of total dissolved solids (TDS) in the river; these stations included the following: Qurna, Labani, City Centre, Kateban, Corniche, and Sihan. In addition, three Landsat-8 satellite images which were taken at the same time as collected samples also used for detecting the salinity in the river. After processing of atmospheric correction and inserted remote sensing indices, the reflectance of water extracted from satellite images was used to express the spectral characteristics of different TDS concentrations. Correlation and regression were used to obtain accurate models for detecting the salinity depending on the spectral reflectance of Landsat 8 operational land image OLI. The results presented Pearson correlation (r) value of 0.70, 0.97, and 0.71, and correlation coefficient (R2) of 0.56, 0.94, and 0.85 between field data with spectral data of salinity index 2 (SI-2) derived from the green and blue bands of Landsat obtained in 2015, 2017, and 2018 respectively. In conclusion, remote sensing and GIS technologies coupled with spectral modeling are useful tools for providing a solution of future water resources planning and management, and also offer great undertaking as a means to improve knowledge of water quality and support water decision making. [ABSTRACT FROM AUTHOR]

Twenty daily time step–based SWAT simulation models for the Duhok, Adhaim and Dokan dam watersheds, in Iraq, were implemented using five land cover (LC) and digital elevation model (DEM) of different resolutions. The optimal LC and DEM for computing the most accurate streamflow for each watershed were specified. Results indicated that delineation of the flat watersheds is significantly affected by the DEM resolution and there was no evident trend on the computation of watersheds' total areas, boundaries, number of subbasins and stream networks. Moreover, there is no significant trend between the increase in LC and DEM resolutions and accuracy of the computed streamflow. The most accurate streamflows for the Duhok, Adhaim and Dokan watersheds were computed using LC (DEM) of 30 m, 1000 m and 1000 m. [ABSTRACT FROM AUTHOR]

The energy sector is integral to the wellbeing of the entire Iraqi economy and will remain so well into the future. In the current study, the Intergovernmental Panel on Climate Change (IPCC) methodology was used to estimate CO2, CH4, and N2O emissions from oil refining and electricity generation in Iraq for a period exceeding 25 years. From 1990, Iraq experienced two wars and an economic siege, then faced political, social, and security instability, which affected its energy production. The results showed that the CO2, CH4, and N2O emissions from the oil refining and electricity generation in Iraq experienced a sharp decline in the years 1991, 2003, and 2007 due to a decrease in the production of oil derivatives in refineries, according to political and security conditions. The total CO2 emissions from the types of fuel used in electricity generation in Iraq was approximately 14,000 Gg and 58,000 Gg in 1990 and 2017, respectively. The increase in CO2 emissions was greater than 300% between 1990 and 2017. The continued use of poor types of fuel, such as fuel oil and crude oil, will lead to an increase in greenhouse gas (GHG) emissions from these sources, and higher levels of environmental pollution. [ABSTRACT FROM AUTHOR]

Agricultural land in the south of Iraq provides habitat for several types of living creatures. This land has a significant impact on the ecosystem. The agricultural land of Al-Hawizeh marsh covers an area of more than 3500 km2 and is considered an enriched resource to produce several harvests. A total of 74% of this area suffers from a high degree of salinity and chemical pollution, which needs to be remedied. Several human-made activities and post-war-related events have caused radical deterioration in soil quality in the agricultural land. The goal of this research was to integrate mathematical models, remote sensing data, and GIS to provide a powerful tool to predict, assess, monitor, manage, and map the salinity and chemical parameters of iron (Fe), lead (Pb), copper (Cu), chromium (Cr), and zinc (Zn) in the soils of agricultural land in Al-Hawizeh marsh in southern Iraq during the four seasons of 2017. The mathematical model consists of four parts. The first depends on the B6 and B11 bands of Landsat-8, to calculate the soil moisture index (SMI). The second is the salinity equation (SE), which depends on the SMI result to retrieve the salinity values from Landsat-8 images. The third part depends on the B6 and B7 bands of Landsat-8, which calculates the clay chemical index (CCIs). The fourth part is the chemical equation (CE), which depends on the CCI to retrieve the chemical values (Fe, Pb, Cu, Cr, and Zn) from Landsat-8 images. The average salinity concentrations during autumn, summer, spring, and winter were 1175, 1010, 1105, and 1789 mg/dm3, respectively. The average Fe concentrations during autumn, summer, spring and winter were 813, 784, 842, and 1106 mg/dm3, respectively. The average Pb concentrations during autumn, summer, spring, and winter were 4.85, 3.79, 4.74, and 7.2 mg/dm3, respectively. The average Cu concentrations during autumn, summer, spring, and winter were 3.9, 3.1, 4.45, and 7.5 mg/dm3, respectively. The average Cr concentrations during autumn, summer, spring, and winter seasons were 1.28, 0.73, 1.03, and 2.91 mg/dm3, respectively. Finally, the average Zn concentrations during autumn, summer, spring, and winter were 8.25, 6, 7.05, and 12 mg/dm3, respectively. The results show that the concentrations of salinity and chemicals decreased in the summer and increased in the winter. The decision tree (DT) classification depended on the output results for salinity and chemicals for both SE and CE equations. This classification refers to all the parameters simultaneously in one stage. The output of DT classification results can display all the soil quality parameters (salinity, Fe, Pb, Cu, Cr, and Zn) in one image. This approach was repeated for each season in this study. In conclusion, the developed systematic and generic approach may constitute a basis for determining soil quality parameters in agricultural land worldwide. [ABSTRACT FROM AUTHOR]

Growing populations, socio-economic development, the pollution of rivers, and the withdrawal of fresh water are all signs of increasing water scarcity, and with 85% of global use, agriculture is the biggest freshwater user. The water footprint (WF) and virtual water (VW) are concepts used recently for freshwater resources assessment. The WF reflects how much, when and where the water was used whereas VW reveals the volume of water embedded in goods when traded. The first goal of this research is to determine the WF per ton and the WF of production (Mm3/yr) of wheat, barley, rice, and maize in Iraq. The second goal is estimating the quantities of the 4 main cereal crops imported into Iraq and assessing the impact on reducing WF and land savings for 10 years from 2007 to 2016. The results showed that the WF per ton was 1736, 1769, 3694, 2238 m3/ton and the WF of production was 5271, 1475, 997, 820 Mm3/yr for wheat, barley, rice, and maize, respectively. The median total VW imported was 4408 Mm3/yr, the largest volume was 3478 Mm3/yr from wheat, and Iraq saved about 2676 Mm3 of irrigated water and 1,239,539 M ha of land by importing crops every year during 2007–2016. The study revealed the significance of better irrigation management methods to decrease the WF through a selection of crops that need less water and cultivation in rain-fed areas, as well as the use of cereal import to conserve scarce water resources, which is crucial both in terms of water resource management and preservation of the environment. The results of this research could be used as a guideline for better water management practices in Iraq and can provide helpful data for both stakeholders and policymakers. [ABSTRACT FROM AUTHOR]

Groundwater and soil pollution caused by (PAHs) spills, mostly from the oil industry and petrol stations in urban areas, represent a major environmental concern worldwide. However, infiltration into groundwater is decreasing due to the natural attenuation processes of PAHs in the vadose zone, which protect invaluable groundwater resources against contamination. This study was conducted to evaluate the effect of improper management of the petroleum industry on the groundwater and soil surrounding the petrol station and an oil refinery unit and, furthermore, to prepare the polluted risk intensity (PRI) map. Fifty-one soil samples and twenty-five water samples were analyzed for Light Non-aqueous Phase Liquid (LNAPLs), and one soil sample for Dense Non-Aqueous Phase Liquid (DNAPLs); furthermore, six soil samples analyzed for Tetraethyl Lead (TEL) analysis. The results showed that seventeen wells were polluted with LNAPLs and the soils were highly contaminated with different DNAPLs components and mainly was in the form of Polycyclic Aromatic Hydrocarbons (PAHs). Seven factors introduced to the GIS platform to produce PRI map, which is the distance to source, depth to water table, slope, lineaments, lithology, soil, and recharge rate. The final map revealed that the eastern and western parts of the study area are at a very high-risk level, whereas the center is at a very low to low-risk level. [ABSTRACT FROM AUTHOR]

Cost and time performance are considered to be the most important aspects in the construction industry. The exceptional conditions that took place in Iraq since the beginning of the third millennia had a huge vicious impact on the cost and time performance of local construction projects. This may represent the principal motivation for the local authorities to enact some four successive legislations in order to control the performance of the construction industry. In this research, an evaluation is made to the cost and time performance of local construction projects and their variation due to the multiple changes in the internal factors that affect project performance, and changes in the surrounding events include legislative, economic, and security environment during the period that lasted from 2003 to 2014. Data is collected from 30 governmental projects to conduct the evaluation. A comprehensive questionnaire is performed to estimate a quantitative value for the impact of several factors that concern both the owner and the contractor, with special consideration to their variation through the successive legislation periods. These estimates are, in turn, utilized in a system dynamics model, in which the project development process is simulated. The final cost and duration changes in the project are accumulated in the form of stocks to give an indication of the cost and time performance of the project. The developed model returned a progressive reduction of 10.9% for the change in project cost and 135.37% for the change in project schedule throughout the eleven years period. [ABSTRACT FROM AUTHOR]

The current study was conducted to determine the quality of the water of Al- Sabil River in Al-Shinafiya district, Province of Al- Diwaniyah, for the period from September 2018 to August 2019. Three sites were selected along the river, a quantitative and qualitative study of the diatoms as well as its indices to assess the quality of water in the river, such as trophic diatom Index (TDI), Trophic State Index (TSI), Diatomic Index (DI), and General Diatoms Index (GDI). The current study was diagnosed about 136 species of diatoms at three sites, where the central diatoms was 12 species while the pannals diatoms reached 124 species, and recorded total numbers of diatoms (35453.8, 29447.2 and 36504.76) cell*310/L, and rates (2954.48, 2453.93 and 3042.06) cells*310/L for the three locations respectively, as shown by the results of the trophic diatom Index(TDI) values ranged from (23.33 to 55.54) and the values of Trophic State Index (TSI) ranged from (0.07 to 0.81) and the Diatomic Index (DI) values ranged from (9.08 to 16.20) and the values of the General Diatoms Index (GDI) ranged from (2.23 to 3.17). It was noted that the water quality was Oligotrophic to Mesotrophic based on TDI and TSI, while its moderate to Good based on DI and GDI, and concluded that the higher the evidence values indicated that the water quality tended to be good, free or low pollution, suitable for living well, and that water was few nutrients, while its low values indicated the deterioration of the water quality in the river. [ABSTRACT FROM AUTHOR]

[Display omitted] • High-resolution prediction of air fine particular matter concentration is conducted. • New developed machine learning algorithms are adopted for this purpose. • Prediction for temporal/spatial variability of PM 2.5 over Iraq region is studied. • Research provided good forecasting spatial variability of PM 2.5 at high resolution. This study uses machine learning (ML) models for a high-resolution prediction (0.1°×0.1°) of air fine particular matter (PM 2.5) concentration, the most harmful to human health, from meteorological and soil data. Iraq was considered the study area to implement the method. Different lags and the changing patterns of four European Reanalysis (ERA5) meteorological variables, rainfall, mean temperature, wind speed and relative humidity, and one soil parameter, the soil moisture, were used to select the suitable set of predictors using a non-greedy algorithm known as simulated annealing (SA). The selected predictors were used to simulate the temporal and spatial variability of air PM 2.5 concentration over Iraq during the early summer (May-July), the most polluted months, using three advanced ML models, extremely randomized trees (ERT), stochastic gradient descent backpropagation (SGD-BP) and long short-term memory (LSTM) integrated with Bayesian optimizer. The spatial distribution of the annual average PM 2.5 revealed the population of the whole of Iraq is exposed to a pollution level above the standard limit. The changes in temperature and soil moisture and the mean wind speed and humidity of the month before the early summer can predict the temporal and spatial variability of PM 2.5 over Iraq during May-July. Results revealed the higher performance of LSTM with normalized root-mean-square error and Kling-Gupta efficiency of 13.4% and 0.89, compared to 16.02% and 0.81 for SDG-BP and 17.9% and 0.74 for ERT. The LSTM could also reconstruct the observed spatial distribution of PM 2.5 with MapCurve and Cramer's V values of 0.95 and 0.91, compared to 0.9 and 0.86 for SGD-BP and 0.83 and 0.76 for ERT. The study provided a methodology for forecasting spatial variability of PM 2.5 concentration at high resolution during the peak pollution months from freely available data, which can be replicated in other regions for generating high-resolution PM 2.5 forecasting maps. [ABSTRACT FROM AUTHOR]

Covid-19 was first reported in Iraq on February 24, 2020. Since then, to prevent its propagation, the Iraqi government declared a state of health emergency. A set of rapid and strict countermeasures have taken, including locking down cities and limiting population's mobility. In this study, concentrations of four criteria pollutants, NO 2 , O 3 , PM 2.5 and PM 10 before the lockdown from January 16 to February 29, 2020, and during four periods of partial and total lockdown from March 1 to July 24, 2020, in Baghdad were analysed. Overall, 6, 8 and 15% decreases in NO 2 , PM 2.5 , and PM 10 concentrations, respectively in Baghdad during the 1st partial and total lockdown from March 1 to April 21, compared to the period before the lockdown. While, there were 13% increase in O 3 for same period. During the 2nd partial lockdown from June 14 to July 24, NO 2 and PM 2.5 decreases 20 and 2.5%, respectively. While, there were 525 and 56% increase in O 3 and PM 10 , respectively for same period. The air quality index (AQI) improved by 13% in Baghdad during the 1st partial lockdown from March 1 to April 21, compared to its pre-lockdown. The results of NO 2 tropospheric column extracted from the Sentinel-5P satellite shown the NO 2 emissions reduced up to 35 to 40% across Iraq, due to lockdown measures, between January and July, 2020, especially across the major cities such as Baghdad, Basra and Erbil. The lockdown due to COVID-19 has drastic effects on social and economic aspects. However, the lockdown also has some positive effect on natural environment and air quality improvement., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)