This study analyzes the 96 h flow velocity time series data from the Zhoushan Sea during Typhoon In−fa to investigate the conditions for extreme flow velocities. Through force analysis of the unit fluid and statistical analysis of topographic features, we identified the critical water depth, slope, and sea surface width for extreme flow velocities under ideal conditions as 15 m, 4.5°, and 2000 m, respectively. The Submarine Topographic Characteristic Index (STCI) is introduced for the first time in this study, revealing its significant impact on extreme flow velocities. Three types of “extreme velocity points”—associated with constant storm surge, astronomical tide, and typhoon storm surge—were defined, occurring over 85% of the time during typhoon events. These extreme velocity points were analyzed in relation to their topographic characteristics, including water depth, slope, and sea surface width. Simulations of Typhoon In−fa in the Zhoushan Sea area were used to construct the STCI model, resulting in the following weightings: water depth = 0.96, slope = 0.39, and sea surface width = 0.49. Typhoon In−fa occurred in 2021, exhibited a maximum wind speed of approximately 35 m/s, and played a key role in the hydrodynamic processes investigated in this study. Validation with Typhoons Muifa (2021) and Bebinca (2413) confirmed the model’s high consistency. The STCI model provides insight into the occurrence of extreme velocities, categorizing them according to tidal phase and typhoon influence. Preliminary findings indicate the model’s applicability under varying typhoon intensities, offering a robust tool for predicting extreme seabed flow velocities during typhoon events.

Suspended sediment concentration (SSC) is a critical proxy for coastal water quality, geomorphological evolution, and biogeochemical cycles. In shallow macro-tidal embayments like Sanmen Bay (SMB), China, surface SSC exhibits highly dynamic spatiotemporal variations driven by intense, multi-scale tidal forcing. Using Sentinel-2 MSI imagery processed with the ACOLITE Dark Spectrum Fitting (DSF) algorithm, this study reconstructs the spatial distribution of surface SSC across the embayment. We then introduce the normalized Suspended Sediment Concentration Asymmetry Index ($A_{ssc}$) to quantitatively diagnose asymmetrical sediment responses across spring–neap and flood–ebb cycles. The results reveal a spatially divergent, dual-control mechanism governing sediment transport across the embayment’s hydro-geomorphic gradients. Quantitative trend-surface fittings and stratified regressions demonstrate that net sediment transport in deep bedrock channels is primarily governed by tidal pumping. Conversely, sediment dynamics on intertidal mudflats and shallow subtidal shoals are modulated by geomorphic resistance, exhibiting high morphodynamic sensitivity to minute water depth variations. By bridging process-based estuarine tidal theory with discrete satellite observations, this reproducible framework transforms multi-temporal remote sensing snapshots into spatially continuous diagnostics, providing a practical decision-support paradigm for coastal engineering and ecosystem management in dynamically analogous macro-tidal environments.