A Fuzzy Logic Model for Sustainable Water and Energy Resource Management in Mediterranean Greenhouses

Water scarcity, rising energy costs, and limited technology adoption challenge Mediterranean greenhouse horticulture. Although irrigation automation and digital decision-support tools have been widely studied, adoption barriers and integrated water–energy decision support are often addressed separately, particularly under farmers’ real operational constraints. This study combines a survey of greenhouse farmers in Almería, southeastern Spain, with an interpretable Mamdani fuzzy logic model to assess irrigation automation and support water–energy management. Survey results show that 61% of farms use basic irrigation systems, 33% use semi-automated systems, and only 6% use fully automated irrigation; 87% rely exclusively on grid electricity. The main barriers were high initial investment, reliability and configuration concerns, and limited willingness to undertake specialized training. Automation was positively associated with cultivated area and educational attainment, but not with age or crop type. The fuzzy model integrates reservoir level, irrigation demand, irrigation mode, tariff period, and energy-supply configuration to estimate irrigation cost and feasible operating time. Scenario-based validation differentiated grid-connected, hybrid photovoltaic, and off-grid configurations and highlighted the potential of renewable integration and time-sensitive irrigation management to reduce dependence on conventional energy. By linking farmer adoption constraints with interpretable operational decision support, the framework provides a practical basis for gradual irrigation modernization and supports water–energy–food nexus management in Mediterranean greenhouse horticulture.