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.

Blue-green algae blooms present persistent environmental challenges in freshwater ecosystems, yet ecological interactions within the bacterial communities of Cylindrospermopsis-bloom reservoirs remain poorly understood. In this study, water samples were collected from February to May 2024 from 11 sampling sites in a Cylindrospermopsis-bloom reservoir in western Guangdong province, China. At each sampling point, a water sample was collected every month. High-throughput sequencing was applied to analyze the interaction between Cylindrospermopsis and other bacteria. As shown in our results, the phyla Actinobacteriota, Proteobacteria, Bacteroidota, Verrucomicrobiota, and Cyanobacteria were revealed as dominant phyla. Bacterial communities exhibited significant seasonal differences between flood and non-flood periods (ANOSIM: R = 0.472, p = 0.001). Cylindrospermopsis (dominance index Y = 0.53) acted as the keystone in the co-occurrence network (Z_i < 2.5, P_i > 0.62) and closely interacted with other bacteria. For better management of the blue-green algae bloom reservoir, the phyla of Actinobacteriota, Dependentiae, Acidobacteriota, Armatimonadota, Gemmatimonadota, and Desulfobacterota were proposed as microbial indicators for the eutrophic process. This study provides a new insight into the interactions of Cyanobacteria with other bacteria and the management of blue-green algae outbreaks in reservoirs.

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.

Foam pollution in the tailwater discharge from coastal power plants poses a significant challenge. However, the mechanisms underlying foam formation and stability remain understudied, which hinders the development of effective control strategies. This study investigated the impacts of temperature and algal concentration on foam stability in tailwater discharge from coastal power plants through simulation experiments to elucidate mechanisms of foam stability. A laboratory simulation device was developed to adjust temperature and algal concentration and measure foam layer height, half-life, bubble diameter, surface tension, and viscosity. This device was used to replicate foam scenarios typical of coastal power plant tailwater discharge to analyze the effects of temperature and algal concentration on foam stability through comprehensive data collection and analysis across various operational conditions. The findings revealed that foam stability decreased with increasing temperatures (15–45 °C). However, during hot summer months, higher temperatures (range of 30–40 °C) hindered foam dissipation owing to algal blooms and the release of surface-active substances. The functional relationship between foam stability index (half-life, foam layer height, bubble diameter) and temperature and algae concentration was established, which provides a scientific basis for predicting foam stability under different conditions. This research elucidates the complex dynamics of foam in the tailwater discharge from coastal power plants and provides insights for developing more effective foam control strategies, potentially mitigating adverse impacts on the marine ecosystem. In future research, by adding experimental conditions such as pH, ionic strength, and different types of protein polysaccharides, a more comprehensive understanding of the mechanism of bubble generation can be achieved, providing more accurate foam suppression optimization solutions for future engineering practices.

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.

Coastal power plants draw seawater from the open ocean through their cooling-water circulation systems. The cooling water falls over an overflow weir inside the siphon well, entraining large quantities of air, and generates a foam pollution plume upon discharge to the sea. By combining physical model experiments with numerical simulation, this study investigates the key factors governing foam stability and the aeration behavior of the water downstream of the siphon-well overflow weir. The principal conclusions are as follows: among the three single-factor variables tested in controlled laboratory conditions—temperature, salinity, and shellfish-flesh suspension concentration—the biological substance proxy showed the strongest effect on foam stability; when the shellfish-flesh suspension concentration reaches 20% (mass/volume basis, independently prepared), the foam volume and half-life increase by factors of 1.4 and 3.36, respectively, relative to the 4% baseline condition. When the dimensionless aeration depth z/z₉₀ < 0.75, the air-concentration profile rises relatively slowly with depth, whereas it increases more rapidly as the free surface is approached. Within the investigated viscosity range of 1.0–8.3 mPa·s (1.0 mPa·s for the pure-water control and 1.5–8.3 mPa·s for the measured viscosities of the 4–20% shellfish-flesh suspensions), the cross-sectional mean air concentration shows an overall decreasing trend as the liquid-phase viscosity increases, and the total bubble number density decreases correspondingly. The findings provide a laboratory-based indication of the mechanisms that must be addressed in the development of physical foam-suppression technologies; confirmation against field discharge water is required.