Recently, the "Water Conservancy Standards AI Large Model," independently developed by the China Institute of Water Resources and Hydropower Research (IWHR) based on multi-source corpora under the organization of the Department of International Cooperation, Science and Technology of the Ministry of Water Resources, was officially released and has been put into practical application in the special evaluation of water conservancy technical standards.

    Based on the IWHR "SkyLIM" system, the model adopts a technical architecture of "massive knowledge base + DeepSeek/Qwen dual models + standards services," deeply integrating technologies such as natural language processing, knowledge graphs, and multimodal data fusion. It enables digital and intelligent management across the entire lifecycle of water conservancy standards—from project initiation, formulation, and implementation to supervision—filling the gap in intelligent tools in China's water conservancy standardization field and representing the latest achievement in applying AI intelligent technology to water conservancy standardization management.

    The model integrates more than 1,800 water conservancy and hydropower standards, over 500 water conservancy-related laws, regulations, and policy documents, water conservancy scientific research achievements from the "13th Five-Year Plan" and "14th Five-Year Plan" periods, papers from core journals such as Journal of Hydraulic Engineering and Advances in Water Science, as well as multi-source corpora including 280,000 patents and the catalog of advanced and practical water conservancy technologies and scientific and technological achievement promotion from the past 10 years, with continuous dynamic updating. Equipped with a domain-adaptive DeepSeek/Qwen dual-model foundation and through specialized training, it possesses the ability to parse water conservancy terminology and achieve expert-level cognition of water conservancy standards. Based on advanced semantic algorithms, it enables cross-text intelligent comparison and features multidimensional functions such as AI-powered intelligent duplicate checking and comparison, querying, drafting, review, evaluation, forecasting, and publicity of water conservancy standards, effectively enhancing the coordination, timeliness, and advancement of standards. In practical application, the accuracy of duplicate checking and comparison exceeds 96.7%, standard drafting efficiency increases by 2.5 times, standard evaluation and review efficiency increases by 3 times, standard retrieval accuracy reaches over 99.5%, and efficiency improves by more than 5 times, significantly enhancing standard management effectiveness.

    Next, R&D efforts will continue to be intensified, relevant resources will be continuously expanded, the knowledge base will be enriched and dynamically managed, and full support will be provided for the practice of AI intelligent management of water conservancy standards, helping to improve the technical standards system oriented toward new quality productive forces in water conservancy and to build an advanced and practical water conservancy science and technology support system.