本文以北京市北运河流域为研究对象, 系统阐述了数字孪生北运河建设的探索与实践过程。针对北运河流域管理中存在的数据分散、防洪减灾能力不足、水资源调度不精准等问题, 按照“统筹规划、急用先行、分步建设、共建共享”的基本原则, 构建了包含数据底板、模型平台、知识平台和业务应用的数字孪生北运河流域体系。详细介绍了L1~L3级空间数据建设、物联感知网络部署、水文水动力模型构建等关键技术, 以及防洪减灾、水资源调度等业务应用实践。通过试点建设, 实现了从传统洪水预报向点 (闸坝、断面) 、线 (干流) 、面 (流域) 多维预报转变, 延长了洪水预见期, 提高了预报精度。实践表明, 数字孪生技术在提升流域精细化、智能化管理水平方面具有显著成效, 为全国数字孪生流域建设提供了可借鉴的经验。

This paper takes the North Canal watershed in Beijing as the research subject and systematically elaborates on the exploration and practical process of Digital Twin North Canal construction. Addressing issues in North Canal watershed management such as fragmented data, insufficient flood prevention and disaster mitigation capabilities, and inaccurate water resource regulation, a Digital Twin North Canal watershed system was constructed following the basic principles of “integrated planning, prioritizing urgent needs, step-by-step construction, and joint construction and sharing. ” The system comprises a data foundation, modeling platform, a knowledge platform, and business applications. The paper details key technologies such as L1-L3 level spatial data construction, deployment of IoT sensing networks, and the development of hydrological and hydrodynamic models, as well as practical business applications in flood control and disaster mitigation, water resource regulation. Through pilot implementation, the system has achieved a transformation from traditional flood forecasting to multi-dimensional forecasting at points (gate dams, cross-sections) , lines (main stream) , and areas (watershed) , thereby extending the flood forecasting lead time and improving forecasting accuracy. Practical results indicate that Digital Twin Technology has significantly enhanced the precision and intelligence of watershed management, providing valuable experience for the nationwide construction of Digital Twin watersheds.