Environmental degradation is reducing crop productivity in many regions of Egypt. Moreover, unsustainable surface water drainage contributes to salinized soil conditions, which negatively impact crops. Egypt is seeking solutions to mitigate the problem of surface water drawdown and its consequences by exploring renewable and sustainable sources of energy. Geothermal energy and the desalination of saline water represent the only solutions to overcoming the fresh water shortage in agricultural industry and to providing sustainable fresh water and electricity to villages and the Bedouin livelihood. In Egypt, the Siwa Oasis contains a cluster of thermal springs, making the area an ideal location for geothermal exploration. Some of these thermal springs are characterized by high surface temperatures reaching 20 °C to 40 °C, and the bottom-hole temperatures (BHT) range from 21 °C to 121.7 °C. Pre-Cambrian basement rocks are usually more than 440 m deep, ranging from 440 m to 4724.4 m deep. It is this feature that makes the Siwa Oasis locality sufficient for geothermal power production and industrial processes. This study utilized both the Horner and the Gulf of Mexico correction methods to determine the formation temperatures from BHT data acquired from 27 deep oil wells. The present study revealed a geothermal gradient ranging from 18 to 42 °C/km, a heat flux of 24.7–111.3 mW/m², and a thermal conductivity of 1.3–2.65 W/m/k. The derived geothermal, geophysical, and geological layers were combined together with space data and the topographic layer to map relevant physiographic variables including land surface elevation, depth to basement, lineament density, land surface temperature, and geologic rock units. The ten produced variables were integrated in GIS to model the geothermal potential map (GTP) for the Siwa Oasis region. According to the model, both the eastern side and north and northeastern portions of the study region contain high and very high geothermal potential energy. Combining bottom-hole temperature measurements with satellite remote sensing and geospatial analysis can considerably enhance geothermal prospecting in Egypt and other East African areas that have geologically and tectonically similar settings. In addition to identifying sustainable resources needed for food production, this research has implications for renewable energy resources as well.

New Hanover County, North Carolina, has been experiencing rapid population growth and is expected to continue this growth, leading to increased land use and development in the area. The county is also threatened by sea level rise (SLR) and its effects because of its coastal location and frequent occurrences of major storms and hurricanes. This study used a land change modeler to map the land cover change throughout the county over a period of 20 years, and predicted land cover distribution in the area in the years 2030 and 2050. Statistics revealed that the developed land in the area increased by 85 km² between 2000 and 2010, and by 60 km² between 2010 and 2020. Such land is predicted to increase by another 73 km² by 2030, and 63 km² by 2050. This increase in development is expected to occur mainly in the central area of the county and along the barrier islands. Modeling of SLR illustrated that the northwestern part of New Hanover County along the Cape Fear River, as well as the beach towns located on the barrier islands, are estimated be the most affected locations. Results indicate that sections of major highways throughout the county, including I-140 near downtown Wilmington and US-421 in Carolina Beach, may be inundated by SLR, which might delay residents during mandatory evacuations for emergency situations such as hurricanes. Some routes may be unusable, leading to traffic congestion on other routes, which may impede some residents from reaching safety before the emergency. Wrightsville Beach and Carolina Beach are estimated to have the highest levels of inundation, with 71.17% and 40.58% of their land being inundated under the most extreme SLR scenario of 3 m, respectively. The use of the present research approach may provide a practical, quick, and low-cost method in modeling rapidly growing urban areas along the eastern United States coastline and locating areas at potential risk of future SLR inundation.