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.

Climate extreme events such as floods and droughts in any area have a significant impact on human life, infrastructure, agriculture, and the economy. In the last two years, flash floods caused by heavy rainstorms have become frequent and destructive in many catchments in Northern Iraq. The present study aims to examine flash floods in the Erbil region, Northern Iraq using Remote sensing (RS), Geographic Information System (GIS), and Principal Component Analysis (PCA) for geomorphic data. PCA results revealed that 12 geomorphic parameters exhibited a significant correlation with two different statistical components. To facilitate practical application, ranks are assigned based on the calculated parameters for flood susceptibility mapping. Out of the 24 basins in the current study, three basins (16, 3, and 14) have the highest geomorphometric values (36–39), indicating the zone most susceptible to flash floods and making up a maximum area of 38.58% of the studied region. Six basins (4, 8, 9, 10, 12, and 15), which have geomorphometric values between 30 and 35 and cover a land area of 27.86%, are the most moderately vulnerable to floods. The remaining basins, which make up 33.47% of the research, are occasionally subject to floods and have geomorphometric scores below 30. The precision of the flood susceptibility mapping was validated using the bifurcation ratio and drainage density relationship as well as past flood damages, such as economic losses and human casualties. Most of the recorded injuries and fatalities took place in areas that were particularly prone to severe past flooding. Additionally, the investigation revealed that 44.56% of all populated areas are located in extremely vulnerable basins. The findings demonstrate a notable correlation between the identified flood-susceptible areas and the occurrence of past flood damage.

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.

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.