Experimental and numerical model studies of dike-break induced flood processes over a typical floodplain domain

Xia, Junqiang; Cheng, Yifei; Deng, Shanshan; Zhang, Xiaolei

doi:10.1007/s11069-022-05744-7

Cited by 5 publications

(4 citation statements)

References 30 publications

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“…By increasing rainwater infiltration and reducing surface runoff, sponge cities can decrease the risk of waterlogging, thereby having considerable research and practical significance in sustainable urban ecological development. Secondly, embankment construction is a crucial engineering measure for addressing river problems, playing a role in improving the ecological environment of rivers and enhancing flood control and drainage capabilities [12][13][14]. Additionally, non-engineering measures have emerged for urban flood control and disaster reduction, such as improving emergency management systems, establishing flood forecasting and warning systems, and strengthening flood disaster management [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Analyzing the Mitigation Effect of Urban River Channel Flood Diversion on Waterlogging Disasters Based on Deep Learning

Sun,

Zhu,

Zhang

et al. 2024

Water

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In recent years, urban waterlogging disasters have become increasingly prominent. Physically based urban waterlogging simulation models require considerable computational time. Therefore, rapid and accurate simulation and prediction of urban pluvial floods are important for disaster prevention and mitigation. For this purpose, we explored an urban waterlogging prediction method based on a long short-term memory neural network model that integrates an attention mechanism and a 1D convolutional neural network (1DCNN–LSTM–Attention), using the diversion of the Jinshui River in Zhengzhou, China, as a case study. In this method, the 1DCNN is responsible for extracting features from monitoring data, the LSTM is capable of learning from time-series data more effectively, and the Attention mechanism highlights the impact of features on input effectiveness. The results indicated the following: (1) The urban waterlogging rapid prediction model exhibited good accuracy. The Pearson correlation coefficient exceeded 0.95. It was 50–100 times faster than the InfoWorks ICM model. (2) Diversion pipelines can meet the design flood standard of a 200-year return period, aligning with the expected engineering objectives. (3) River channel diversion significantly reduced the extent of inundation. Under the 30-year return period rainfall scenario, the maximum inundation area decreased by 1.46 km2, approximately equivalent to 205 international standard soccer fields.

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Section: Introductionmentioning

confidence: 99%

Analyzing the Mitigation Effect of Urban River Channel Flood Diversion on Waterlogging Disasters Based on Deep Learning

Sun,

Zhu,

Zhang

et al. 2024

Water

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“…The dike-break wave propagates approximately in an elliptical shape within the flood-prone area, centered around the breach. Furthermore, the flood propagation time and peak velocity vary significantly across flood-prone areas with different roughness coefficients 9,10 . Specifically, when urban street blocks serve as flood-prone areas during dike-break floods, the floodwater takes on complex flow patterns consisting of shock waves and reflected waves due to the intricate nature of residential areas.…”

Section: Introductionmentioning

confidence: 99%

Experimental Study on the Buffering Effects of Urban Trees Group in Dike-Break Floods

Zhang

Zhao

et al. 2023

Preprint

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The process of dike-break flood propagation in typical urban street blocks is highly complex. The presence of buildings and trees groups in urban street blocks profoundly alters the flood dynamics, impacting the drainage capacity of the area. In this study, a generalized sink model representing a typical urban street block was established, including trees groups, buildings, sidewalks, and stormwater drainage systems. The study measured the fluctuation of water levels within the street block and the pressure variation in the pressurized stormwater drainage network during the dike-break flood propagation. Furthermore, it conducted a comparative analysis to assess the influence of different arrangements of trees groups on the maximum water depth in buildings and the discharge capacity of the pressurized stormwater drainage network. Dike-break floods give rise to large-scale water leaps and the formation of thin layer water sheets near the buildings under the influence of buildings, water tank sidewalls, and tree groups. The water leap zones exhibit lateral migration and superposition on the sidewalks during the flood propagation, gradually dissipating and disappearing in the longitudinal direction of the street block. In the presence of tree groups, the water levels significantly decrease in buildings and downstream street blocks, while the discharge capacity of the pressurized stormwater drainage network shows a slight improvement as the road's flood-carrying capacity increases. The pressure in the main pipes fluctuates due to the switching of the grate inlet drainage mode and the hydraulic transition process in the branch pipes. The research findings not only provide valuable validation data for numerical simulations but also offer theoretical guidance for urban flood management and landscape design.

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“…The dike-break wave propagates approximately in an elliptical shape within the flood-prone area, centered around the breach. Furthermore, the flood propagation time and peak velocity vary significantly across flood-prone areas with different roughness coefficients 9 , 10 . Specifically, when urban street serve as flood-prone areas during dike-break floods, the floodwater takes on complex flow patterns consisting of shock waves and reflected waves due to the intricate nature of residential areas.…”

Section: Introductionmentioning

confidence: 99%

Experimental study on the buffering effects of urban trees group in dike-break floods

Liu,

Zhang,

et al. 2023

Sci Rep

Self Cite

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The process of dike-break flood propagation in typical urban street is highly complex. The presence of buildings and trees groups in urban street profoundly alters the flood dynamics, impacting the drainage capacity of the area. In this study, a generalized sink model representing a typical urban street was established, including trees groups, buildings, sidewalks, and stormwater drainage systems. The study measured the fluctuation of water levels within the street block and the pressure variation in the pressurized stormwater drainage network during the dike-break flood propagation. Furthermore, it conducted a comparative analysis to assess the influence of different arrangements of trees groups on the maximum water depth in buildings and the discharge capacity of the pressurized stormwater drainage network. Dike-break floods give rise to large-scale water leaps and the formation of thin layer water sheets near the buildings under the influence of buildings, water tank sidewalls, and tree groups. The water leap zones exhibit lateral migration and superposition on the sidewalks during the flood propagation, gradually dissipating and disappearing in the longitudinal direction of the street. In the presence of tree groups, the water levels significantly decrease in buildings and downstream street, while the discharge capacity of the pressurized stormwater drainage network shows a slight improvement as the road’s flood-carrying capacity increases. The pressure in the main pipes fluctuates due to the switching of the grate inlet drainage mode and the hydraulic transition process in the branch pipes. The research findings not only provide valuable validation data for numerical simulations but also offer theoretical guidance for urban flood management and landscape design.

show abstract

Experimental and numerical model studies of dike-break induced flood processes over a typical floodplain domain

Cited by 5 publications

References 30 publications

Analyzing the Mitigation Effect of Urban River Channel Flood Diversion on Waterlogging Disasters Based on Deep Learning

Analyzing the Mitigation Effect of Urban River Channel Flood Diversion on Waterlogging Disasters Based on Deep Learning

Experimental Study on the Buffering Effects of Urban Trees Group in Dike-Break Floods

Experimental study on the buffering effects of urban trees group in dike-break floods

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