支流洪水组合对干流区域的致灾影响模拟分析

Simulation and Analysis of the Impact of Tributary Flood Combinations on the Mainstream Area

为了探究不同支流洪水组合对干流区域的致灾影响,构建了一二维耦合水动力模型并进行验证.采用耦合模型分别对理想Y型流域和宁波市海曙区三江口区域进行建模,模拟了不同峰现时差的支流洪水过程,选取了干流洪峰流量、积水量、淹没面积、最大淹没水深和最大漫出距离5个指标来反映洪水在干流区域的致灾情况.研究结果表明:(1)所构建的一二维耦合模型可以较好地反映一维河道和二维地表的水量交换过程;(2)在理想算例中,随着支流洪水峰现时差的增加,洪水对干流区域的致灾情况明显减轻,所选取的5个指标分别削减了1.52%~22.34%、5.70%~75.48%、8.49%~97.60%、1.88%~36.45%和2.03%~37.56%;(3)随着余姚江和奉化江洪水峰现时差的增加,甬江区域受洪水的影响明显下降,所选取的5个指标分别削减了10.03%~21.47%、52.28%~94.16%、56.05%~97.55%、11.69%~28.46%和29.21%~76.64%.以期该研究为平原河网区域的防洪工作开展提供参考.

In order to explore the disaster-causing impacts of different combinations of tributary floods on the mainstream area,a one-and two-dimensional coupled hydrodynamic model was constructed and validated.The coupled model was applied to model an ideal Y-shaped basin and the Sanjiangkou area in Ningbo.Simulations of tributary flood processes with different peak time lags were conducted,and five indicators-mainstream peak flow,inundation volume,inundation area,maximum inundation depth,and maximum overflow distance were selected to reflect the disaster situation caused by floods in the mainstream area.The results indicate the following:(1)The coupled model constructed in this study can effectively reflect the exchange of water between one-dimensional river channels and two-dimensional land surfaces.(2)In the ideal Y-shaped basin,as the peak time lag of tributary floods increases,the disaster impact on the mainstream area significantly reduces.The five indicators selected in this study decrease by 1.52%to 22.34%,5.70%to 75.48%,8.49%to 97.60%,1.88%to 36.45%,and 2.03%to 37.56%,respectively.(3)As the peak time lag between Yuyao River and Fenghua River floods increases,the impact of floods on the Yong River area significantly decreases.The five indicators selected in this study decrease by 10.03%to 21.47%,52.28%to 94.16%,56.05%to 97.55%,11.69%to 28.46%,and 29.21%to 76.64%,respectively.This study can provide certain references for flood prevention work in plain river network areas.