An Integrated Multi-Sensor Information System for Real-Time Reservoir Monitoring and Management.

Reservoirs face growing challenges in safety and sustainable management, requiring systematic approaches that integrate monitoring, analysis, and decision support. To address this need, this study develops an integrated information system framework with a four-layer architecture, encompassing "perception," "data," "model," and "application." The perception layer establishes a multi-platform monitoring network based on fused multi-sensor data. The data layer manages heterogeneous information through correlation mechanisms at the physics, semantics, and application levels. The model layer supports decision-making through a cross-coupled analytical framework for the coordinated management of water safety, resources, environment, and ecology. Finally, the application layer utilizes virtual-physical mapping and dynamic reasoning to implement a closed-loop management system encompassing forecasting, warning, simulation, and planning. This framework was implemented and validated at the Ye Fan Reservoir in Hubei Province, China. By integrating components like "One Map," flood dispatching, safety monitoring, early warning, video surveillance, and operational supervision, a three-dimensional perception network was constructed. This deployment significantly improved the precision, reliability, and scientific basis of reservoir operation. The integrated monitoring and management system presented in this paper, driven by heterogeneous sensor networks, provides an effective and generalizable solution for modern reservoir management, with the potential for extension to broader water resource and infrastructure systems.