Analyzing agricultural and hydrological drought at different timescales is essential for designing adaptation strategies. This study aimed to assess agricultural and hydrological drought in the Abbay Basin of Ethiopia by using multiple indices, namely the standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), normalized difference vegetation index (NDVI), vegetation condition index (VCI), and drought severity index (DSI). Climate extremes were assessed over the Abbay Basin between 1981 and 2022. The results indicate that the years 1982 and 2014 were the most drought-prone, while the year 1988 was the wettest year in the Abbay Basin. The results revealed the presence of extremely dry and severely dry conditions, potentially impacting agricultural output in the region. Agricultural drought was identified during the main crop seasons (June to September). The VCI results indicated the presence of extremely wet and severely wet conditions. In 2012, 65% of the area was affected by extreme drought conditions, while nearly half of the Basin experienced extreme drought in 2013 and 2022. The DSI results indicated the occurrence of agricultural drought, although the spatial coverage of extreme dry conditions was lower than that of the other indices. In 2003, 78.49% of the Basin experienced moderate drought conditions, whereas severe drought affected 20% of the region. In 2010, about 90% of the Basin experienced moderate drought. This study provides valuable insights for agricultural communities, enabling them to mitigate the impact of drought on crop yields by utilizing different adaptation strategies. An adequate knowledge of agricultural and hydrological drought is essential for policymakers to assess the potential effects of drought on socioeconomic activities and to recognize the significance of implementing climate change adaptation measures.

Countries face challenges of excess, scarcity, pollution, and uneven water distribution. This study highlights the benefits of advances in groundwater engineering that improve the understanding of utilizing local geological characteristics due to their crucial role in resisting drought in southern Lebanon. The type of drought in the region was determined using the Standardized Precipitation Index (SPI), Standardized Vegetation Index (NDVI), Vegetation Condition Index (VCI), and Soil Moisture Anomaly Index (SM). The dry aquifer and its characteristics were analyzed using mathematical equations and established hydrogeological principles, including Darcy’s law. Additionally, a morphometric assessment of the Litani River was performed to evaluate its suitability for artificial recharge, where the optimal placement of the water barrier and recharge tunnels was determined using Spearman’s rank correlation coefficient. This analysis involved excluding certain parameters based on the Shapiro–Wilk test for normality. Accordingly, using the Geographic Information System (GIS), we modeled and simulated the potential water table. The results showed the importance and validity of linking groundwater engineering and morphometric characteristics in combating the drought of groundwater layers. The Eocene layer showed a clearer trend for the possibility of being artificially recharged from the Litani River than any other layer. The results showed that the proposed method can enhance artificial recharge, raise the groundwater level to four levels, and transform it into a large, saturated thickness. On the other hand, it was noted that the groundwater levels near the surface will cover most of the area of the studied region and could potentially store more than one billion cubic meters of water, mitigating the effects of climate change for decades.

Groundwater is a significant source of water supply, especially with depleted and quality-deteriorated surface water. The number of drilled boreholes for groundwater has been increased, but erroneous results often occur while selecting sites for digging boreholes. This makes it necessary to follow a science-based method indicating potential zones for groundwater storage. The LithoSFR Model is a systematic approach we built to create an indicative map with various categories for potential groundwater sites. It is based mainly on retrieved geospatial data from satellite images and from available thematic maps, plus borehole data. The geospatial data were systematically manipulated in a GIS with multi-criteria applications. The novelty of this model includes the empirical calculation of the level each controlling factor (i.e., weights and rates), as well as the LithoSFR Model, adopting new factors in its design. This study was applied on a representative Mediterranean region, i.e., Lebanon. Results showed that 44% of the studied region is characterized by a very high to high potentiality for groundwater storage, mainly in areas with fractured and karstified carbonate rocks. The obtained results from the produced map were compared with datasets which were surveyed from representative boreholes to identify the discharge in the dug boreholes, and then to compare them with the potential zones in the produced map The reliability of the produced map exceeded 87%, making it a significant tool to identify potential zones for groundwater investment.

The global energy demand is steadily on the rise, and the increased utilization of fossil fuels has significantly contributed to escalating pollution levels. primarily fueled by the rapid expansion of the world's population. Simultaneously, there is a global shift towards harnessing renewable energy sources, driven by a heightened awareness of environmental preservation. We worked to identify the most suitable zones in southern Lebanon for construction renewable energy power plants according to an innovative and modern methodology that requires integrating Geographic Information Systems with geomorphological and environmental data, in addition to crucial new climate criteria. The selection of these zones is guided by specific criteria and subcriteria, meticulously defined through remote sensing and a comprehensive review of relevant legal regulations. Then we weigh these criteria based on the percentage of impact on the desired goals, and using spatial analysis tools in geographic information systems, we obtain the optimal places to build these stations. Our findings reveal that climatic and geomorphological factors were the main determinants of the optimal locations for building renewable energy plants. By highlighting the statistical values of the approved standards, it became clear that there are two key factors of additional special importance, namely, cloudiness and elevation, which played a pivotal role in determining the ultimate results. This methodology resulted in a clear change in how to choose the optimal zones to construction renewable energy plants in mountainous areas. It can be used with results in various high-altitude regions around the world that have suitable geomorphological and climatic characteristics that may be somewhat distant from the specific characteristics of the studied area.