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.

Land use change is a crucial driving factor in hydrological processes. Understanding its long-term dynamics is essential for sustainable water resources management. This study sought to quantify and analyze land use change between 1985 and 2021 and its impacts on the hydrology of the Sejnane watershed, northern Tunisia. Remote sensing and a SWAT model using the SUFI-2 algorithm to identify the most sensitive parameters were used to achieve this objective. Land use maps were developed for 1985, 2001 and 2021. For the last 37 years, the watershed experienced a slight decrease in forest, scrubland and forage crops, a significant reduction in grassland, and a conspicuous expansion of olive trees and vegetable crops. Given the scarcity of observed discharge data, a SWAT model was calibrated for the period 1997–2010 and validated for 2011–2019. Model performance was good for both calibration (NSE = 0.78, PBIAS = −6.6 and R² = 0.85) and validation (NSE = 0.70, PBIAS = −29.2 and R² = 0.81). Changes in land use strongly affected the water balance components. Surface runoff and percolation were the most influenced, showing an increase in runoff and a decrease in percolation by 15.5% and 13.8%, respectively. The results revealed that the construction of the Sejnane dam, the extension of irrigated perimeters and olive tree plantations were the major contributors to changes in hydrology.

A LOICZ Budget Model is applied to the Ichkeul Lake, a wetland ecosystem of the South Mediterranean-North African region, to evaluate its functioning in order to boost water management. The Ichkeul Lake water and nutrient budget, net ecosystem metabolism (NEM), nutrient availability, and their seasonal changes are estimated using field data. A considerable anthropogenic-driven amount of nitrogen is transferred into N₂/N₂O to the atmosphere during the dry season with predominance of denitrification-anammox processes. The primary production is impacted by forcing the ecosystem respiration to reduce the NEM so that the system is functioning as heterotrophic. Climate change and anthropogenic pressures are expected to exacerbate the current trends of water quality degradation, with possible negative impacts on Palearctic birds’ population. Mitigation actions are possible, through the implementation of National Wetland Management Strategies that include nutrient load and water resources management.

This study aims to assess the trophic level of Lake Ichkeul and predict the effect of climate change and anthropogenic pressures on European eel using the trophic index TRIX and the Random Forest RF model. The TRIX values show the poor water quality of the lake. While the RF model shows that eel landing depends on water level, turbidity, and salinity. The RF model gave an R2 =58.4% > R2 =40.3% from Multiple linear regression, confirming the high performance of the RF model. The combination of the two models is an appropriate approach to be used in decision making by civil authorities.

Experimental and numerical approaches were used to assess the functioning of a flagship coastal wetland ecosystem for improved water management. Very pronounced seasonal contrast in Salinity and Chlorophyll a were found, with high correlation between Chla and Phosphorus during winter and Chla and Nitrogen during summer. Water and Dissolved Inorganic Phosphorus (DIP) and Dissolved Inorganic Nitrogen (DIN) fluxes exhibited seasonal variation, where the lake is a source of DIN and DIP during the wet season. A considerable anthropogenic-driven amount of nitrogen is transferred into N₂/N₂O to the atmosphere during the dry season with predominance of denitrification-anammox processes. The primary production is impacted by forcing the respiration of the ecosystem to reduce the Net Ecosystem Metabolism so that the system is functioning as heterotrophic. Climate change and anthropogenic pressures explain the deterioration of water quality and possibly the decrease in populations of Palearctic birds, warranting depollution and effective National Wetland Management Strategies through improved water resources management.