Climate change and increasing water scarcity are intensifying pressure on irrigated agriculture, which currently represents 70% of global freshwater withdrawals. Remote sensing technologies have become essential tools for monitoring soil moisture, evapotranspiration, crop growth, and irrigation performance across multiple spatial and temporal levels. This review synthesizes 83 peer-reviewed studies published between 2002 and 2025, focusing on the use of optical, thermal, and microwave sensors to support irrigation water management under climate variability. The analysis highlights progress in multi-sensor integration, UAV-based monitoring, crop and agro-hydrological modeling, and emerging machine learning approaches that enhance irrigation scheduling, soil moisture estimation, and crop water stress detection. Despite these advancements, several methodological challenges persist, including data integration constraints, sensor-specific limitations, model transferability issues, insufficient ground validation, and difficulties in translating remote sensing outputs into operational decision support systems. In addition, structural gaps at the policy level restrict the evaluation of irrigation efficiency and climate resilience. This review aims to clarify current limitations and outline priority research directions to enhance the climate resilience and sustainability of irrigated agricultural systems.
Rossi et al. (Sat,) studied this question.