In light of population growth and climate change, groundwater is one of the most important water resources globally. Groundwater is crucial for sustaining many vital sectors in Syria, including industrial and agricultural sectors. However, groundwater exploitation has significantly escalated to meet different water needs especially in the post-war period and the earthquake disaster. Therefore, the goal was this study delineation of the groundwater potential zones (GPZs) by integrating the analytic hierarchy process (AHP) method in a geographic information systems (GIS) within the AlAlqerdaha river basin in western Syria. In this study, ten criteria were used to map the spatial distribution of GPZs, including slope, geomorphology, drainage density, land use/land cover (LU/LC), lineament density, lithology, rainfall, soil, curvature and topographic wetness index (TWI). GPZs map was validated by using the location of 74 wells and the Receiver Operating Characteristic Curve (ROC). The findings suggest that the study area is divided into five GPZs: very low, 21.39 km² (10.87%); low, 52.45 km² (26.65%); moderate, 65.64 km² (33.35%); high, 40.45 km² (20.55%) and very high, 16.90 km² (8.58%). High and very high zones mainly corresponded to the western regions of the study area. The conducted spatial modeling indicated that the AHP-based GPZs map showed a remarkably acceptable correlation with wells locations (AUC = 87.7%, n = 74), demonstrating the precision of the AHP–GIS as a rating method. The results of this study provide objective and constructive outputs that can help decision-makers to optimally manage groundwater resources in the post-war phase in Syria.

Globally, green spaces are considered as a fundamental part of biodiversity to balance the environment in an ecosystem particularly in urban areas. Contrary to this, urban green is declining in the least developing nations particularly due to rapid urbanization. This impact alter the condition of environmental services in term of non-provision and insufficient urban green spaces for the local population. This study takes Shahdara Town as an area of interest that is a congested urban area of Lahore Pakistan, and currently facing social injustice in terms of a dense urban area with few green spaces. The study uses Geographical Information Science for the identification of green spaces, calculation of their total area, and quantification of green cover extent by using NDVI, to comparing them with population to analyzed the environmental justice. To check the social perspective of the population regarding green areas and their importance among urban people, a comparison has been made with the presence of parks in the area, their association with living conditions and quality of life of locals. This social prospective was investigated by applying the Multiple Linear Regression Model (MLRM) by taking the availability of park/urban green in area as dependent variable and accessibility to parks, its total distance from a house, and frequency of visit as independent variables. The resultant analysis shows that according to international standards, per capita green spaces are less in this town, of Lahore. This imbalance provision of environmental services is a challenging task, for policymakers and a hurdle for urban sustainability. Finally, the outcomes of the research provide a documented base evidence and social analysis for environmental sustainability in terms of provisions of environmental services for the urban dwellers in the region.

As a result of climate change, many lands are under risk due to the rising sea levels (RSL). Studies show that the mean sea level will likely rise by 0.16 to 0.63 metres before 2050, and 0.2 to 2.5 metres by 2100. Lower-lying islands are more endangered from RSL. One of such islands is Failaka, a small island in Kuwait lying at the entrance of Kuwait Bay, which is located on the north-western side of the Arabian Gulf (Also called the Persian Gulf). Most of Failaka Island is lower than three meters. The Governmental plans are to develop and populate the island. SLR should be considered in such planning. This study focuses particularly on detecting the areas of Failaka Island which are under high threat from the SLR. To detect these areas, spatial analysis of the Digital elevation model (DEM) are used. DEM is estimated for three SLR scenarios (1, 2 and 3 metres). It is expected that 31% of the island will be under sea level height for the SLR of 1 m; 54% for the SLR of 2 metres; and 87% for the SLR of 3 m. Coastal Vulnerability Index (CVI) is estimated as well. The CVI shows that the eastern coast is the most susceptible with regard to the SLR. The model was validated through using ground elevation points (n = 40), and a positive correlation was found with of 0.8019. Geographic Information System (GIS) and Remote sensing (RS) are confirmed to be effective tools for estimating spatial influence of the SLR.

Mapping bathymetry is essential for many fields, including science, engineering, and the military, among others. Bathymetry is extremely important in the scientific field because it is linked to many physical and environmental issues such as coastal erosion, sea-level rise, and water quality. Traditionally, conventional methods, such as pre-measured cable passage, were used to estimate depths. Lately, echo-sounder assessments were used on hydrograph ships. This method is effective, but it is very costly in both economic and time terms. Remote sensing technology provides modern methods for mapping bathymetry, such as the use of active and passive remote sensing. Many satellite sensors cover multispectral bands. Some are commercial, such as IKONOS and WorldView, while others are freely available, such as Landsat 8 and Sentinel-2. In this study, Landsat 8 (15 meters spatial resolution) was used to estimate the depths of the waters of Kuwait, an Arabian Gulf country located on the Northwestern side of the gulf. Ground truthing points (GTPs) were used to build a bathymetric model of Kuwaiti territorial water (KTW) using the ratio transform algorithm (RTA) applied on Landsat 8 data. The results showed a good ability of Landsat 8 and RTA to estimate the depths of Kuwait’s waters, where the relationship between the derived model from Landsat 8 and the GTPs was positive (r2 = 0.9634). Meanwhile, the accuracy of the derived bathymetric model was evaluated by computing the Root Mean Square Error (RMSE = ± 1.66 meters) and Mean Absolute Error (MAE ± = 1.29).