Distributed Acoustic Sensing (DAS) provides a promising approach for continuous, high-resolution monitoring of hydrodynamic processes by converting optical fibers into dense vibration-sensing arrays. This presentation focuses on the application of DAS to two representative water-related dynamic processes: water-flow state monitoring and nearshore wave–coast interactions. For water-flow processes, DAS signals can be used to identify variations in flow states in large-scale hydraulic infrastructure, offering a new pathway for real-time condition monitoring and water management. For nearshore environments, DAS combined with deep clustering analysis enables the detection and classification of wave-induced vibration events along island coastlines. A field study on Zhairuoshan Island demonstrated that millions of wave events can be automatically grouped into physically meaningful categories, including underwater waves, ocean wave noise, bubble plumes, and breaking waves. The results further reveal the influence of tidal level, shoreline geometry, and wave impact intensity on the spatial and temporal characteristics of coastal responses. These studies indicate that DAS, integrated with data-driven analysis, can serve as an effective tool for understanding water-flow processes, wave impacts, and wave–coast dynamics. The proposed framework provides technical support for island-reef geotechnical monitoring, coastal erosion assessment, and the intelligent maintenance of hydraulic and coastal engineering systems.

Distributed acoustic sensing (DAS),Water-Flow Processes,Nearshore Wave–Coast Dynamics,Hydrodynamic Monitoring,Coastal Monitoring