山前平原型城市雨洪模拟与应用——以济南市为例

Simulation of urban rainfall-runoff in piedmont cities: Case study of Jinan city, China

近年来,我国城市区域暴雨洪涝灾害频发,而山前平原型城市由于地形地貌特殊,其造成的人员伤亡和经济损失尤为严重。文章以济南市黄台桥排水片区为研究对象,基于SWMM模型构建了山前平原型城市雨洪模拟模型。根据研究区地形地貌及汇流规律的差异将子汇水区分为山区、平原区和主城区三类,通过控制模型汇流演算方式、模型演算面积比及河道糙率系数设置情景,并采用遗传算法对模型参数进行率定与验证,从而定量分析子汇水区不同汇流方式及河道糙率对模拟结果的影响。研究结果表明:当采用SWMM模型传统汇流方式时,难以考虑山前平原型城市地形差异,模型模拟结果整体表现较差(平均Nash系数仅为0.61);当针对山前平原型城市不同地形特点设置相应的汇流演算方式、模型演算面积比及河段糙率系数时,模型模拟精度得到显著提高(平均Nash系数达0.86)。研究结果可为山前平原型城市雨洪灾害的模拟与研究提供科学基础,并为区域防洪减灾提供相应的技术支撑。

During the past decades, frequent flooding disasters in urban areas resulted in catastrophic impacts such as human life casualties and property damages especially in piedmont cities for their specific topography. This study develops a piedmont urban flooding model for the Huangtaiqiao drainage area based on SWMM. The sub-catchments in this study area are divided into mountainous area, plain area and main urban area according to the variations in surface topography. The impact of different routing modes and channel roughness on the simulations is analyzed under different types of scenarios, and a genetic algorithm is used to optimize model parameters. Results show that the simulation is poor（with a mean Nash coefficient of 0.61） when using the traditional routing mode in SWMM model, which usually ignores the difference in surface topography in piedmont areas. However, when the differences in routing modes, percent routed and channel roughness are considered, prediction accuracy is significantly increased（with a mean Nash coefficient of 0.86）, indicating the significant affect of the difference in surface topography on the simulations of piedmont cities.