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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]

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]