Guidelines for Modeling and Simulation of Digital Twins for Water Conservancy Projects - T/XJBX 0167-2025

Scope

Water conservancy projects are characterized by large system scale, diverse structural types, complex operating boundary conditions, long service cycles, and significant safety responsibilities. Throughout the entire process of project construction and operation management, they involve multiple objectives such as flood control dispatch, water supply assurance, power generation operation, ecological regulation, project safety monitoring, equipment operation and maintenance, emergency response, and asset management. Traditional management models often face issues such as "model disconnect from actual conditions, data fragmentation and isolation, difficulty in real-time calibration of simulations, unclosed forecasting and early warning chains, reliance on experience for scenario simulation, and low efficiency of cross-disciplinary collaboration". With the development of technologies such as sensor monitoring, Internet of Things, remote sensing mapping, cloud-edge collaboration, numerical calculation, and artificial intelligence, digital twins for water conservancy projects are gradually transitioning from conceptual exploration to engineering application, becoming an important technical path for improving fine-grained management of projects, enhancing risk early warning capabilities, and supporting scientific decision-making. The core of digital twins for water conservancy projects lies in constructing a virtual model consistent with the project's geometric form, structural characteristics, operating conditions, and environmental boundaries, and achieving real-time synchronization of virtual and physical states, state mapping, and closed-loop calibration through twin data. In practical implementation, different project types (such as reservoirs and dams, gate and pump hubs, water diversion and irrigation projects, river regulation and flood control projects, irrigation districts, and urban water supply systems) have significantly different requirements for model gran

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