Riparian or aquatic vegetation thrives with seasons. The understanding of canopies' Submergence‐Ratio (SR = stem height/water depth) influence on suspended sediment transport is still limited. Thus, Large Eddy Simulations coupled with the Discrete Phase Method are used to investigate the particles' three‐dimensional distribution in a partially vegetated straight channel. The spanwise distribution of particles are quantified by the probability density function (PDF), showing a non‐uniformity of particles in time as quantified by the PDF variance. We found that (a) with SR rising, the particles' depletion effects exerted by the vegetation‐side mixing layer is improved along the interface between vegetated and vegetation‐side bare channel region. However, the SR has little effect on the variance of the particles' PDF in the spanwise direction when the mixing layer is fully developed. (b) During the developing stage of the over‐canopy mixing layer, submerged vegetation with higher SR gains a stronger upwards (vertical) entrainment capability. The case (SR = 60%) has a higher sediment concentration than other cases in the fully developed vertical mixing layer region over canopy. (c) The vertical suspension of particles in the vegetation‐side bare channel region is analyzed. Particles migrating from the vegetated region are entrained into the vegetation‐side bare channel region by turbulent structures. Nevertheless, the vertical concentration profile is more uniform in the vegetated region than in the vegetation‐side bare channel at the same streamwise location. The cases SR = 40% and 60% still have higher sediment concentration than other cases in the vegetation‐side bare channel's upper region.

In recent years, the frequency and intensity of global extreme weather events have gradually increased, leading to significant changes in urban rainfall patterns. The uneven distribution of rainfall has caused varying degrees of water security issues in different regions. Accurately grasping the spatiotemporal distribution patterns of rainfall is crucial for understanding the hydrological cycle and predicting the availability of water resources. This study collected rainfall data every five minutes from 62 rain gauge stations in the main urban area of Kunming City from 2019 to 2021, constructing an unsupervised hybrid dimensionality reduction-clustering (HDRC) model. The model employs the Locally Linear Embedding (LLE) algorithm from manifold learning for dimensionality reduction of the data samples and uses the dynamic clustering K-Means algorithm for cluster analysis. The results show that the model categorizes the rainfall in the Kunming area into three types: The first type has its rainfall center distributed on the north shore of Dian Lake and the southern part of Kunming’s main urban area, with spatial dynamics showing the rainfall distribution gradually developing from the Dian Lake water body towards the land. The second type’s rainfall center is located in the northern mountainous area of Kunming, with a smaller spatial dynamic change trend. The water vapor has a relatively fixed and concentrated rainfall center due to the orographic uplift effect of the mountains. The third type’s rainfall center is located in the main urban area of Kunming, with this type of rainfall showing smaller variations in all indicators, mainly occurring in May and September when the temperature is lower, related to the urban heat island effect. This research provides a general workflow for spatial rainfall classification, capable of mining the spatiotemporal distribution patterns of regional rainfall based on extensive data and generating typical samples of rainfall types.

Bend sections are ubiquitous in natural sandy river systems. This study employs Computational Fluid Dynamics–Discrete Phase Model (CFD-DPM) methodology to analyze particle transport dynamics in U-bend channel flows, focusing on the distinctions between partially vegetated (Case No.1) and non-vegetated (Case No.2) scenarios. The research aims to unravel the intricate relationships among bending channel-induced secondary flow, vegetation blockage, and particle aggregation, employing both quantitative and qualitative approaches. (I) The key findings reveal that vegetation near the inner walls of curved channels markedly diminishes the intensity of secondary circulation. This reduction in circulation intensity is observed not only within vegetated areas but also extends to adjacent non-vegetated zones. Additionally, the study identifies a close correlation between vertical vortices and particle distribution near the channel bed. While particle distribution generally aligns with the vortices’ margin, dynamic patch-scale eddies near vegetation patches induce deviations, creating wave-like patterns in particle distribution. (II) The application of the Probability Density Function (PDF) provides insights into the radius-wise particle distribution. In non-vegetated channels, particle distribution is primarily influenced by secondary flow and boundary layers. In contrast, the presence of vegetation leads to a complex mixing layer, altering the particle distribution pattern and maximizing PDF values in non-vegetated free flow subzones. (III) Furthermore, the research quantifies spatial–temporal sediment heterogeneity through PDF variance. The findings demonstrate that variance in non-vegetated channels increases towards the outer wall in bending regions. Vegetation-induced turbulence causes higher variance, particularly in the mixing layer subzone, underscoring the significance of eddy size in sediment redistribution. (IV) The study of vertical concentration profiles in vegetated U-bend channels offers additional insights, while secondary flow in non-vegetated channels facilitates upward sediment transport and vegetation presence, although increasing the Turbulent Kinetic Energy (TKE), restricts channel space, and impedes secondary flow, thereby reducing vertical particle suspension. Sediment concentrations are found to be higher in the lower layers of vegetated bends, contrary to the pattern in non-vegetated bends. These findings highlight the complex interplay between vegetation, secondary flow, and sediment transport, illustrating the reduced effectiveness of secondary flow in promoting vertical particle transportation in bending channels due to the vegetation obstruction.

Mountain rivers are characterized by steep gradients, high flow velocities, and flash flood regimes, and the interaction between in-stream bridge pier groups and flood flows is a persistent challenge in bridge hydraulics. This study investigates the flood hydrodynamic characteristics at a mountain river bridge section and clarifies the coupled pier–flow–debris interaction mechanism, using the 19 July 2024 collapse of Yanpingcun Bridge No. 2 over the Jinqian River in Shangluo, Shaanxi Province, China, as a case study. High-resolution topographic data (0.5 m) derived from three-dimensional laser scanning point clouds were used to construct a two-dimensional hydrodynamic model (IFMS) and a three-dimensional air–water two-phase flow model (volume-of-fluid method, approximately 8 million cells) of the bridge site. Six scenarios were simulated to quantify the effects of pier arrangement, tie beam elevation, and flood protection works on water level rise, velocity distribution, and main flow direction, and the models were validated against surveyed water marks and video-based velocity measurements. The results show the following. (1) The pier group produced a marked flow-blocking effect: the maximum water level upstream of Pier 10 rose by 1.28 m relative to the natural channel, the main flow direction deflected clockwise by about 18°, and a triangular confluence zone formed between the pier group and the right-bank retaining wall. (2) The existing skewed pier arrangement raised the upstream water level by 0.78 m compared with a flow-aligned arrangement and produced a disordered flow pattern unfavourable to debris passage. (3) Three-dimensional analysis showed local water level rises of 0.52–1.20 m on the upstream faces of the piers, with maximum local velocities of 5.5–6.3 m/s along the pier flanks; the maximum velocity occurred at a water depth of 1.0–2.0 m rather than at the free surface. (4) Tie beams exposed above the bed intensified local flow blockage and increased inter-pier velocities (0.3–0.8 m/s), so that debris was readily trapped beneath the tie beams, forming a blockage–backwater–load positive feedback loop. The findings indicate that the large angle between the piers and the main flow, the dense pier group, exposed tie beams, and debris blockage were the key hydrodynamic factors in the collapse, and that the amplifying feedback among piers, flow, and debris was the core mechanism of structural failure. The results provide a scientific basis for the design optimization and flood safety assessment of bridges aligned along mountain rivers.