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基于HEC-RAS的胖头泡蓄滞洪区洪水模拟与灾损评估 被引量:3

Flood Simulation and Disaster Loss Assessment of Flood Storage and Detention Areas Based on HEC-RAS
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摘要 近年来,我国洪水灾害频繁发生并造成巨大的人员伤亡和财产损失。洪水模拟有助于洪水风险管理,降低洪水灾害损失。本文基于90 m精度的DEM及HEC-RAS模型的2D模块构建了松花江流域胖头泡蓄滞洪区的洪水模拟模型,并根据模拟结果统计分析并评估洪灾损失。模拟结果显示在1956、1960、1969以及1998年四个典型洪水过程下,胖头泡蓄滞洪区的淹没面积分别为792.68 km2、740.29 km2、800.87 km2、796.01 km2。其中,当发生与1969年典型洪水过程相同的洪水时,胖头泡蓄滞洪区的损失最为严重,即受灾人口8.75万人,受灾耕地面积223.99 km2,受影响GDP为20.61亿元;义顺蒙古乡、民意乡、新站镇、浩德乡为蓄滞洪区内受灾较严重的乡镇,并且水深大部分分布在4.0 m以上。研究表明HEC-RAS模型的模拟效率高、操作方便,可用于蓄滞洪区的洪水模拟。研究成果可为当地的防洪预警发布、风险规避、人员转移等管理工作提供参考。 In recent years, floods occurred frequently and caused huge casualties and property losses in China. Flood simulation is profound for flood risk management, which could help reduce flood disaster losses. Based on DEM with 90 m accuracy and 2D module of HEC-RAS model, the flood simulation model of the Pangtoupao storage and detention area in the Songhua river basin was built. According to the simulation results, statistical analysis and evaluation of flood losses were carried out in this study. Under the four typical floods of 1956, 1960, 1969 and 1998, the flooded areas of the Pangtoupao storage and detention areas are 792.68 km2, 740.29 km2, 800.87 km2 and 796.01 km2, respectively. Compared to the other three typical floods, the Pangtoupao storage and detention area suffers the most serious flood losses from the typical 1969 flood process, which led to the influence on 87,500 people, flooded land area of 223.99 km2 and GDP losses of 2.061 billion yuan. Townships of Yishun, Minyi, Xinzhan and Haode are badly affected by the typical disaster of 1969, and most of the water depths are above 4.0 m. The results obtained in this study show that HEC-RAS model can be used for flood simulation in flood storage and detention areas with high efficiency and convenient operation. The research results can also provide a reference for the local early flood warning, risk avoidance, personnel transfer and other management works.
出处 《水资源研究》 2020年第1期42-51,共10页 Journal of Water Resources Research
基金 该研究是在国家重点研发计划课题(2016YFC0402203)、国家自然科学基金青年项目(51708086)、中央高校基本科研业务费(DUT18RC(3)072)的资助下完成的。
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