Abstract
Agricultural water management is essential for food security in high-altitude cold regions, such as the Qinghai–Tibet Plateau, the Rocky Mountains, and the Alps. However, extreme environmental conditions—including low temperatures, intense radiation, and complex terrain—impede traditional hydrological monitoring. This narrative review systematically evaluates “space-air-ground” multi-source sensing technologies, summarizing recent advances in satellite remote sensing, low-altitude Unmanned Aerial Vehicles (UAVs), and cold-resistant ground sensors to address these constraints. Beyond individual platforms, this study synthesizes how multi-source data fusion and edge computing enhance hydrological modeling and decision-making for regional drought monitoring, crop assessment, and precision irrigation. Finally, current challenges—such as insufficient cross-platform integration, limited data consistency, and poor model generalization—are critically analyzed, and future research directions are proposed to provide a theoretical framework for advancing smart irrigation.