Abstract
Amid global climate change and increasing water scarcity, optimizing agricultural irrigation is crucial for ensuring food security and sustainable agricultural development. This paper proposes a big data-driven approach to optimize agricultural irrigation, integrating climate conditions, water resources, soil types, and crop demands to provide precise irrigation solutions for various crops. A data-driven irrigation model is developed by analyzing the dynamic impacts of climate change on crop water requirements, the water retention capacity of different soil types, and the water demand characteristics of diverse crops. IoT and sensor technology application in smart irrigation systems is further explored, with proposed design and implementation strategies. Through case studies and field validation, this paper demonstrates the method’s significant impact on enhancing the efficiency of agricultural water management. This paper aims to guide the selection of optimal irrigation solutions for different crops, improving irrigation efficiency and optimizing water resource management.
