Selecting the appropriate desalination and renewable energy technologies is crucial for the success of desalination projects, as each technology offers distinct advantages and disadvantages tailored to specific project requirements. This research investigates the application of both the analytic hierarchy process and fuzzy logic techniques to develop four decision-making models: two for selecting the optimal desalination technology and two for selecting the optimal renewable energy technology in coastal communities. For desalination technology selection, the analytic hierarchy process model is structured into four hierarchical levels: the main goal, criteria, sub-criteria, and alternatives. The criteria level encompasses four groups, while the sub-criteria level comprises 26 factors. The alternatives considered are reverse osmosis, electrodialysis, and multi-stage flash. In parallel, the analytic hierarchy process model for renewable energy technology selection is similarly structured, with four criteria groups and 24 sub-criteria factors. The alternatives evaluated include photovoltaic, concentrated solar power, and wind energy. Additionally, fuzzy logic models are developed for both desalination and renewable energy technology selection. These models enhance the decision-making framework by incorporating the uncertainty and vagueness that are inherent in real-world scenarios. The integration of analytic hierarchy process and fuzzy logic methodologies provide a robust approach to identifying optimal technologies, thereby supporting sustainable development in Egypt’s water–energy nexus. The research outcomes highlight the effectiveness of integrating analytic hierarchy process and fuzzy logic in decision-making processes, offering decision-makers systematic and reliable approaches for selecting the most suitable technologies to achieve sustainability in water–energy nexus projects. The results of the research indicate that the best alternative for desalination was reverse osmosis, and for renewable energy was photovoltaics.

Desalination of sea water projects are critical for addressing water scarcity in regions like Egypt, but they face numerous risks that can hinder their success. This study identifies and analyzes 53 risk factors affecting renewable energy desalination projects through expert interviews, literature review, and a questionnaire survey completed by 47 experts. Statistical methods, including descriptive statistics (mean, mode, standard error, and standard deviation), Pearson correlation, and Cronbach's alpha, were employed to validate the reliability and significance of these factors. The overall questionnaire showed excellent reliability (α = 0.815 for probability of occurrence; α = 0.921 for degree of impact). The results indicate a strong consensus among industry experts. Inflation and price fluctuations was ranked as the highest-probability risk (mean = 4.32/5), while faulty design of plant components (intake, outfall, mechanical systems) was ranked as the highest-impact risk (mean = 4.51/5). Conversely, environmental disasters (earthquakes, floods) showed the lowest probability of occurrence (mean = 1.91/5), and social pressures from entities not directly invested in the project’s success showed the lowest degree of impact (mean = 2.70/5). These statistically validated findings provide project stakeholders with critical insights into the most significant threats to desalination initiatives in Egypt's unique operational context. These findings provide a robust basis for understanding and managing risks in desalination projects, contributing to grow the knowledge on desalination project sustainability and offers actionable insights for stakeholders in Egypt and similar arid regions.