In order to comparatively analyze the influence of different fineness of subsurface on flood simulation, 2020.7 floods were selected, and the two-dimensional storage and retention floodplain model with different finenesses was constructed with Arakusa Erxu and Arakusa Sanxu as the research object, and the hour-by-hour water levels (unit: m) of three typical gauging stations at the mouth of the Xianghe River, Xiaoxiao Station, and Jinji Gate were simulated, and the simulation of the flood in the storage and retention floodplain was carried out. The evolution of flood water in the stagnant flood zone was simulated, and the final flood inundation economic loss was counted, and the results were compared and analyzed.
The high-detail two-dimensional floodplain model adopts 12.5 m resolution digital elevation data as the model support terrain data, and at the same time, the terrain is dissected by an unstructured grid with a smaller area, whereas the lower-detail two-dimensional floodplain model adopts 30 m resolution digital elevation data, which is a common application, and the area of the grid cell is also relatively larger. The grid cells are relatively larger in area.
| collect time | 2020/07/01 - 2020/07/31 |
|---|---|
| collect place | Typical flood storage and detention areas in the lower reaches of the Yangtze River |
| data size | 171.7 KiB |
| data format | *.xlsx,*.log |
| Coordinate system |
The data in this dataset are derived from the results of one- and two-dimensional hydrodynamic model runs constructed for typical flood storage areas. There is a certain degree of reliability.
Based on the river cross-section and high-resolution remote sensing image data, a refined flood simulation model of the flood storage area coupled with a one-dimensional river channel and a two-dimensional flood storage area was constructed in the Chu River basin. A total of three floods of 1991.6, 2015.6 and 2020.7 were selected as model inputs and combined with flood loss accounting in the flood storage area and flood simulation comparisons with different fineness of the subsurface, and finally the corresponding result data sets were obtained after simulation by the constructed model.
From the one-dimensional river model rate determination results, the Chu River mainstem typical station simulation of the water level process and the measured water level process is relatively close to the simulation of the highest water level and the actual value of the maximum difference of no more than 0.3m, the Chu River mainstem typical station simulation and the actual value of the relative error of the average value of the average value of the value of the value of the value of the value of the value of the value of the average value of the relative error is less than 5%, which indicates that the one-dimensional model of the river is built with a higher degree of accuracy.
From the flood simulation results of the flood storage area, 1991.6, 2015.6 and 2020.7, a total of three flood simulation results and the actual situation analysis of the trend of change is consistent with the overall, indicating that the model calculation results are more reliable.
From the flood loss accounting results of the storage and retention flood area, 2015.6 and 2020.7 floods, Arakusa two dikes, three dikes storage and retention flood area simulation calculation of flood loss and the actual situation error is less than 10%, indicating that the model calculation results are more reliable.
| # | number | name | type |
| 1 | 2021YFC3000100 | Lower Yangtze River Flood Disaster Integration and Control and Emergency De-risking Technology and Equipment | National key R & D plan |
This work is licensed under a
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| # | title | file size |
|---|---|---|
| 1 | _ncdc_meta_.json | 5.0 KiB |
| 2 | 滁河流域典型测站2020.7场次洪水一维水动力学模型模拟数据集 | |
| 3 | 滁河流域典型测站2020.7场次洪水二维水动力学模型模拟数据集 |
| # | category | title | author | year |
|---|---|---|---|---|
| 1 | patent | Flood dispatch method and system for flood storage and detention areas based on virtual river channel replacement of sluice discharge calculation | Yun Zhaode, Liu Yong, Zhao Yajun, etc | 2024 |
| 2 | achievements | Flood Control Ecological Joint Optimization Dispatch Management System V1.0 for Flood Storage and Detention Areas | Nanjing Institute of Water Resources Science, Liu Yong, etc | 2024 |
| 3 | achievements | Flood Dispatch Simulation and Analysis Processing Platform for Flood Storage and Detention Areas V1.0 | Nanjing Institute of Water Resources Science, Liu Yong, etc | 2024 |
Flood detention area one-dimensional hydrodynamic model two-dimensional hydrodynamic model
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