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.

While the sponge city construction initiative is drawing attentions and fast spreading in China, some challenges and risks remain. This research surveyed some pilot cities and identified a broad array of challenges from technical, physical, regulatory, financial to community, and institutional. The survey results show that challenges may appear in various shapes, scales, and degrees depending on geographical locations, socio-economic context, and other conditions; however, certain common themes exhibit throughout the survey results. The most dominant challenges involve uncertainties and risks. To resolve the issues, this study also identified various gateways to improve China’s sponge city construction, and recommendations are proposed including urging local governments to adopt sponge city regulations and permits to alleviate water quality and urban pluvial flooding, fully measuring and accounting of economic and environmental benefits, embracing regional flexibility and results-oriented approaches, and focusing on wider range of funding resources for sponge city construction. Coordination among other government agencies is critical, and this is true at all levels of government. Only through greater coordination, education, and broader funding could sponge city construction be advanced meaningfully and sustainably.

Low impact development (LID), which aims at either infiltrating, evapotranspiring or storing water at the source, plays an important role in managing urban rainwater. This paper summarizes the effects of four individual LIDs (i.e., bioretention, green roof, porous pavement, and grass swales) and several combinations of those LID practices on rainfall-runoff management. The survey shows that both individual and combined LIDs are effective in controlling small and medium rainfalls, and the performances are less obvious with increases of the rainfall depths. Hence, the individual or combined LIDs applied with noticeable effects on low or moderate rainfalls might not be useful for heavy rain events which would probably cause urban floods in cities in China. Cities located in different regions show big differences in rainfall characteristics. Rainfall intensity is an even more important factor than rainfall depth that influences performances of LID practices. In the future, more studies should be directed to the effects of LID measures on large storm runoff managements under different rainfall intensity-duration-frequency (IDF), which would be helpful to select suitable LID practices for cities in China.