【摘要】 水环境执法监管是水生态保护的重要手段，但传统执法方式已难以适应经济社会绿色转型发展要求，加之环境违法行为日趋隐蔽，基层执法压力持续加剧。人工智能技术在识别、溯源、预测等方面展现出强大潜力，为水环境执法实现精准化、科学化、规范化提供了新路径。对此，在剖析基层执法现状问题的基础上，提出一种基于人工智能技术的水环境执法监管大模型构建方案，以开发的智能体研究探索了提升执法决策能力的可行性，并展望了大模型在超标预警、污染溯源、证据固定等方面的应用，以期为推进精准、科学治污提供可复制、推广的智慧监管方案。更多还原

【Abstract】 Water environment law enforcement and supervision is a crucial measure for aquatic ecological protection.However, traditional enforcement methods can no longer meet the requirements of economic and social green transformation development. Coupled with the increasingly concealed nature of environmental violations, grassroots enforcement pressure continues to intensify. Artificial intelligence technology demonstrates strong potential in areas such as identification,traceability, and prediction, offering a new pathway to achieve precise, scientific, and standardized water environment law enforcement. Based on an analysis of the current situation and challenges in grassroots enforcement, this paper proposes a framework for constructing a large AI-based model for water environment law enforcement and supervision. It explores the feasibility of enhancing enforcement decision-making capabilities through the development of an intelligent agent module,and anticipates the model’s applications in areas such as exceedance warning, pollution traceability, and evidence solidification. The aim is to provide a replicable and scalable intelligent supervision solution for advancing precise and scientific pollution control.更多还原