Flume experiments were performed to test four plant mimics with different stiffness to reveal the effect of plant stiffness on the wave dissipation and turbulence process. The mimics were built of silica gel rod groups, and their bending elastic modulus was measured as a proxy for stiffness. The regular wave velocity distribution, turbulence characteristics, and wave dissipation effect of different groups were studied in a flume experiment. Results show that, when a wave ran through the flexible rod groups, the velocity period changed gradually from unimodal to bimodal, and the secondary wave peak was more apparent in the more flexible mimics. The change in the turbulence intensity in the different rod groups showed that the higher the rod stiffness, the greater the turbulence intensity. With an increase in the bending elastic modulus of a rod group, the wave dissipation coefficient increased. The increase in the wave dissipation coefficient was not linearly correlated with the bending elastic modulus, but it was sensitive within a certain range of the elastic modulus.

Refined urban flood risk assessment serves as a fundamental safeguard for urban sustainability. However, most studies based on scenario analysis method tend to rely on a single risk evaluation criterion, with limited consideration of applicability differences arising from underlying computational principles. Furthermore, as flood events are inherently dynamic spatial–temporal processes, most studies often overlook the three-dimensional characteristics of flood risk, particularly the connectivity of risk in physically adjacent spaces. To address these issues, this paper proposes a comprehensive flood risk assessment framework that integrates the spatial–temporal characteristics of disaster-causing factors. An improved analysis method for grid-scale flood assessment is proposed based on the comprehensive mechanical analysis method and the drowning factor. In addition, a quantitative approach for characterizing the spatial aggregation of urban flood risk is established using risk thresholds and aggregation area thresholds. These methods are then integrated through a combination weighting–cluster analysis framework for comprehensive flood risk assessment. The results show that the improved analysis method can better reflect the change in risk of flow velocity and water depth combined. Spatiotemporally, the Yinshan Road and western section of the Dongzhong Road, exhibiting high localized risk, moderate overall risk, high risk on the time scale and high spatial agglomeration status, are comprehensively assessed as extremely high-risk flooded zones. The proposed framework effectively characterizes the spatial–temporal distribution of disaster-causing factors, providing a scientific basis for disaster prevention and contributing to urban sustainability.

Accurately characterizing the spatiotemporal distribution of tropical cyclone rainfall is fundamental to enhancing coastal flood defense capabilities. Taking western Guangdong Province as the study case and utilizing hourly rainfall data from 2005 to 2025, this paper employs the Locally Linear Embedding algorithm, K-means clustering, and composite analysis to classify the spatiotemporal patterns of tropical cyclone rainfall and to explore the linkage mechanisms between each pattern and the synoptic fields. The results indicate that, during 2005–2025, a total of 49 tropical cyclones made landfall in western Guangdong, predominantly during the period from June to October. The tropical cyclone rainfall can be categorized into three spatiotemporal patterns: Pattern 1 is a bimodal migrating type, characterized by a southwest-to-northeast migration of the rainfall center and the strongest spatial variability; Pattern 2 is a unimodal balanced type, featuring the most spatially uniform distribution and a broad areal influence; Pattern 3 is a bimodal locked type, with the rainstorm center persistently anchored over the Yangjiang, the highest mean rainfall intensity, and the strongest spatial concentration. For Pattern 1, tropical cyclones with northwest and northward tracks allow the right-front quadrant of heavy precipitation to dominate the migration of the rainstorm center. For Pattern 2, the dispersed low-level wind field jointly suppress the migration and concentration of the rainstorm center. For Pattern 3, the superposition of high-value moisture transport and funnel-shaped topographic forced lifting appears to be a primary contributing factor to the stable maintenance of the rainstorm center. The findings of this paper can provide scientific evidence for tropical cyclone rainfall forecasting and flood defense in western Guangdong.