Drought is a fundamental physical feature of the climate pattern worldwide. Over the past few decades, a natural disaster has accelerated its occurrence, which has significantly impacted agricultural systems, economies, environments, water resources, and supplies. Therefore, it is essential to develop new techniques that enable comprehensive determination and observations of droughts over large areas with satisfactory spatial and temporal resolution. This study modeled a new drought index called the Combined Terrestrial Evapotranspiration Index (CTEI), developed in the Ganga river basin. For this, five Machine Learning (ML) techniques, derived from artificial intelligence theories, were applied: the Support Vector Machine (SVM) algorithm, decision trees, Matern 5/2 Gaussian process regression, boosted trees, and bagged trees. These techniques were driven by twelve different models generated from input combinations of satellite data and hydrometeorological parameters. The results indicated that the eighth model performed best and was superior among all the models, with the SVM algorithm resulting in an R² value of 0.82 and the lowest errors in terms of the Root Mean Squared Error (RMSE) (0.33) and Mean Absolute Error (MAE) (0.20), followed by the Matern 5/2 Gaussian model with an R² value of 0.75 and RMSE and MAE of 0.39 and 0.21 mm/day, respectively. Moreover, among all the five methods, the SVM and Matern 5/2 Gaussian methods were the best-performing ML algorithms in our study of CTEI predictions for the Ganga basin.

Understanding the spatiotemporal distribution of future droughts is essential for effective water resource management, especially in the Mediterranean region where water resources are expected to be scarcer in the future. In this study, we combined meteorological and hydrological drought indices with the Soil and Water Assessment Tool (SWAT) model to predict future dry years during two periods (2035–2050and 2085–2100) in a typical Mediterranean watershed in Northern Morocco, namely, Bouregreg watershed. The developed methodology was then used to evaluate drought impact on annual water yields and to identify the most vulnerable sub-basins within the study watershed. Two emission scenarios (RCP4.5 and RCP8.5) of a downscaled global circulation model were used to force the calibrated SWAT model. Results indicated that Bouregreg watershed will experience several dry years with higher frequency especially at the end of current century. Significant decreases of annual water yields were simulated during dry years, ranging from −45.6% to −76.7% under RCP4.5, and from −66.7% to −95.6% under RCP8.5, compared to baseline. Overall, hydrologic systems in sub-basins under the ocean or high-altitude influence appear to be more resilient to drought. The combination of drought indices and the semi-distributed model offer a comprehensive tool to understand potential future droughts in Bouregreg watershed.

Most recent studies confirm a decreasing trend in water resources availability in the northern African region; the high competition between the sectors that use this vital resource, and the changing climate are considered as the main factors behind this situation. Under such very dynamic interactions between the natural resources, climate and the socioeconomic sectors, scientists from different perspectives have a challenging task to provide up-to-date and reliable insights to guide potential sustainable management strategies. Through the case of the Souss-Massa, the present study aims to provide state of the art scientific research on water resources. It is based on data from publications in the two databases Scopus and Web of Science, unpublished papers and reports as well as various theses. The Vosviewer data visualization tool was used to analyze different aspects of the publications, including the time distribution of water resources related research, the research topics as well as the different approaches adopted by the authors. In addition, this review summarizes results of previous research investigations carried out on the quantity and quality of water resources in relation to agriculture as well as to climate change and variability. The study showed that the period 2016–2021 was the most significant in terms of the number of research papers published. The maps of publications analyzed showed that researchers working in the area focus more on the study of the quality, chemical processing and the impacts of climate change on the availability of water resources. The results showed that Souss-Massa is a region where an important amount of research on climate and water has been carried out. Hence, to keep up with the rapid evolution of land use and other anthropogenic actions in the basin there remain several gaps in knowledge and constraints to address. In order to provide potential research opportunities in the Souss-Massa basin, in terms of scope and methods, this review identifies several gaps in research namely data quality and availability, as well as gaps in water resources modelling. A detailed discussion has been provided on the possibilities to develop and address the research gaps in the region.