Agrometeorological hazards significantly impact agricultural production and rural economic development. The interdisciplinary nature of studying these hazards poses challenges such as poor data interoperability in research. This paper proposes a method for analyzing agrometeorological hazards using knowledge graphs to understand occurrence patterns and devise response strategies. The study involves classifying agricultural and meteorological knowledge and designing a hazard entity model based on the characteristics and influencing factors of agrometeorological hazards. Data mining and extraction techniques are used to extract relevant information from multiple sources, and a knowledge graph for knowledge fusion and storage is built. The retrieval and inference capabilities of the knowledge graphs are used to intelligently analyze agrometeorological hazards. Results indicate that analyzing agrometeorological hazards using knowledge graphs is an innovative method that offers new perspectives and ideas for agricultural meteorological hazard research, thereby promoting the sustainable development of agricultural production and the stable growth of the rural economy.