High-frequency automated detection and energy-based characterization of tidal bore front dynamics and height in the Qiantang River Estuary

In macro-tidal estuaries that host tidal bores, accurate detection of bore front dynamics and height underpins assessments of navigation safety, sediment transport, morphodynamic evolution, and habitat condition. This study presents a statistical detection framework for estimating tidal bore height from 200 Hz pressure measurements in the Qiantang River Estuary. Bore arrival is identified in two steps, first by the ratio of Short-Term to Long-Term Averages (STA/LTA) and then by change point refinement using the Akaike Information Criterion (AIC), while bore front termination is detected with sliding window spectral analysis of high frequency energy decay. Results show that with increasing inflow Froude number, upstream curvature height and influence length decrease, whereas roller length increases. A dissipation parameter α = 1/28 is obtained by fitting the observed roller length to a new energy balance model, reflecting moderate turbulence intensity under field conditions. Spectral analysis confirms a surge in high frequency energy during impact, followed by rapid attenuation. The model predicts the roller length of breaking bores with high accuracy using relative bore height and Froude number as inputs. These findings support a physics based, automated approach for bore front characterization with implications for flood risk mitigation and hydraulic structure design. • Developed a combined STA/LTA and AIC-based method for automated detection of tidal bore arrival with subsecond accuracy. • Identified bore front termination via high-frequency energy decay triggered by short-lived turbulence bursts. • Proposed and validated an energy-based model for roller length prediction,informing infrastructure design. • Revealed clear scaling relationships between inflow Froude number and tidal bore geometric features.