| 基于流溪河模型的连江流域洪水模拟 |
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| 引用本文： | 林博安,陈洋波,虞云飞,覃建明,王幻宇.基于流溪河模型的连江流域洪水模拟[J].广东水利水电,2016(7):1-8. |
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| 作者姓名： | 林博安 陈洋波 虞云飞 覃建明 王幻宇 |
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| 作者单位： | 1. 中山大学水资源与环境系,广东广州,510275;2. 广东省飞来峡水利枢纽管理处,广东清远,511825 |
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| 基金项目： | 水利部公益性行业科研专项经费项目(201301070)，广东省科技计划项目(2013B020200007)，12·5科技支撑计划项目(2012BAK10B06－04)。 |
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| 摘 要： | 为了提高连江流域洪水预报的技术水平和精度，探讨流溪河模型在大流域洪水预报中应用的效果，该文采用SRTM和USGS的DEM数据，分别建立了连江流域洪水预报流溪河模型，采用1场实测洪水对模型参数进行了优选，并对2场实测洪水进行了模拟，发现流溪河模型可较好的模拟连江流域洪水过程。研究发现，采用空间分辨率为90 m的SRTM的DEM建立的流溪河模型计算量是以1000 m的USGS的DEM建立的模型的计算量的56倍，但两者洪水模拟的效果相当。
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| 关 键 词： | 流域洪水预报 分布式物理水文模型 流溪河模型 参数优选 数字地形高程模型 |
| 收稿时间： | 2016/5/20 0:00:00 |
| 修稿时间： | 2016/5/20 0:00:00 |
Flood Simulation of Lianjiang Watershed Based on Liuxihe Model |
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| LIN Bo''an,CHEN Yangbo,YU Yunfei,QIN Jianming and WANG Huanyu.Flood Simulation of Lianjiang Watershed Based on Liuxihe Model[J].Guangdong Water Resources and Hydropower,2016(7):1-8. |
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| Authors: | LIN Bo'an CHEN Yangbo YU Yunfei QIN Jianming and WANG Huanyu |
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| Affiliation: | Department of Water Resources and Environment, Sun Yat-sen University, Guangzhou 510275, China,Department of Water Resources and Environment, Sun Yat-sen University, Guangzhou 510275, China,The Management Office of Feilaixia Hydro-junction, Guangdong Province,Qingyuan 511825, China,Department of Water Resources and Environment, Sun Yat-sen University, Guangzhou 510275, China and Department of Water Resources and Environment, Sun Yat-sen University, Guangzhou 510275, China |
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| Abstract: | To improve the flood forecasting accuracy and technical level, and to explore the possibility of employing Liuxihe Model for large watershed flood forecast, the Liuxihe Model is set up for flood forecasting of Lianjiang Watershed with the SRTM and USGS DEM.The model parameters are optimized by using one observed flood event, and two flood events are simulated by using the model with optimized parameters.The results show that the Liuxihe Model could simulate the flood events of Lianjiang Watershed satisfac-torily.It is found that the computation time for running the model setting up with SRTM 90m DEM is 56 times as that for running the model setting up with USGS 1000m DEM, but the simulated results by both model have no significant differences. |
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| Keywords: | watershed flood forecasting distributed hydrological model Liuxihe model parameter optimization DEM |
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