One of the core Operational Research-based methodologies is Multi-Criteria Decision Making (MCDM), which provides systematic tools for evaluating and ranking alternatives under multiple conflicting criteria. In this study, we develop a hierarchical Fuzzy Weighted Aggregated Sum Product Assessment – Hierarchical (Fuzzy-WASPAS-H) model to optimize irrigation water allocation for sustainable olive cultivation in water-scarce regions. The model structures criteria into a hierarchy, generating partial rankings at each sub-criterion node and a global ranking at the top-level goal, enhancing decision transparency and reliability. Criteria weights are determined using the Fuzzy Analytic Hierarchy Process (Fuzzy-AHP), allowing the model to incorporate expert judgment while handling uncertainty and subjectivity in the relative importance of criteria. Key criteria, including water reliability, crop productivity, economic feasibility, environmental impact, and socio-political acceptability, are assessed using linguistic expert judgments represented as fuzzy numbers, addressing qualitative uncertainties. The approach supports strategic prioritization and efficient allocation of limited irrigation water, enabling policymakers and farmers to optimize irrigation practices and improve overall resource management. The results indicate that Localized Drip Irrigation is the most suitable alternative, followed by Saline Water Management and Deficit Irrigation, whereas Smart/Precision and Subsurface Drip Irrigation are less preferred, reflecting practical constraints in the study region. A case study in the Tunis region demonstrates the framework’s effectiveness in data-driven, evidence-based decision-making, highlighting the potential of hierarchical fuzzy MCDM as an intelligent, robust tool for sustainable water resource management in agriculture.