Abstract
This study uses big data and artificial intelligence technologies to analyze the impact mechanisms of multi-level soil characteristics and topsoil thickness on nitrogen denitrification. By collecting environmental data such as different soil structures, textures, and moisture content, a predictive model for nitrogen denitrification was constructed. The results show that soil structure and moisture content significantly affect the denitrification rate, while topsoil thickness plays a key role in nitrogen transformation by regulating soil aeration and microbial activity. The study also evaluates the risk of nitrogen loss under different topsoil thicknesses and proposes strategies for optimizing topsoil management and reducing nitrogen loss. This research provides new practical references for improving nitrogen use efficiency and promoting the development of precision agriculture.
