With global climate warming, the frequency and intensity of typhoons are increasing, highlighting the significance of studying storm surges for coastal engineering disaster mitigation. In this study, we assessed the predictive capabilities of the new ERA5 reanalysis model and the traditional Fujita−Takahashi model for storm surges. We found that the traditional Fujita−Takahashi model, utilizing a prelandfall typhoon wind field, exhibited higher accuracy in storm surge predictions, while the ERA5 reanalysis model, employing a postlandfall wind field, demonstrated superior performance. By considering the strengths and weaknesses of both wind field models and analyzing the impact of Typhoon In-fa (2021) on the East China Sea, we determined the influence of this typhoon on storm surge heights along the eastern coastal region. These research findings provide valuable insights for the development of effective protection strategies, offering valuable references for coastal resilience planning.

Flow resistance, velocity distribution, and turbulence intensity are significantly influenced by aquatic vegetations (AV) in riparian zones. Understanding the hydraulics of flow with planted floodplains is of great significance for determining the velocity distribution profile and supporting the fluvial processes management. However, the traditional flume experiment method is inefficient. Therefore, the multigroup simultaneous flume test method was carried out to describe the flow patterns affected by emerged rigid (reed and wooden stick) and submerged flexible vegetations (grass and chlorella). The Acoustic Doppler Velocimeter (ADV) was utilized to measure the velocity at one point for different experimental conditions. The results showed that hydraulic features were influenced by different types of vegetation. Furthermore, the relative depth (z/h) was a determining factor of those variations. In addition, the time-averaged velocity distributions of planted floodplains are not logarithmic. Instead, they represented “s-shape” profiles. In detail, for the vegetated floodplains, reed and wood followed an s-shape profile, but for grass and chlorella, they followed reverse s-shape profile. For all cases, turbulence is not isotropic and the change law of turbulence intensity is different in different sections. The flow resistance, turbulence intensities, and Reynold stresses influenced by different types of vegetation were also analyzed.

This study employs the Delft3D numerical model to elucidate nonlinear interactions in velocity dynamics across four key marine regions during typhoon-induced storm surges (Typhoon In-fa, No. 2106). To address gaps in understanding how typhoon winds drive storm surges, this study aims to analyze the relative contributions of bottom friction, wind stress, and convective terms to storm surge dynamics, providing insights for predictive modeling and marine hazard mitigation. Introducing a novel metric, the “Flow Velocity Nonlinear Coupling Proportion” (“FVNCP”, abbreviated as “NCP”), this research quantifies the interactive effects of storm surge flow velocity by dissecting the contributions of bottom friction, wind stress, and the convective term. Through decision tree modeling, wind stress emerges as the primary driver of NCP in open sea and sheltered areas, with peak values reaching 1.50 × 10⁻⁴ and 2.14 × 10⁻⁴ m/s², respectively. In contrast, the convective term dominates the strait and bypassing regions, exhibiting maximum impacts of 3.21 × 10⁻⁴ and 2.94 × 10⁻⁴ m/s², while bottom friction’s influence is consistently minor across all regions. Wind stress contributes the most to NCP in open waters, at an average of 48.28%, while the convective term exerts a comparable 38.85% effect. In confined areas like the strait and bypassing regions, the convective term accounts for 40–44% of the NCP, with wind stress contributing 32–39%. The role of bottom friction is the least among the three factors though its impact intensifies in shallower zones. These findings offer critical insights for advancing predictive models and informing strategies to mitigate typhoon-driven marine hazards.

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.