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水力发电学报 ›› 2023, Vol. 42 ›› Issue (5): 53-66.doi: 10.11660/slfdxb.20230507

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城市化下产汇流参数不确定性分析及洪涝模拟——以晋城市金村区为例

  

  • 出版日期:2023-05-25 发布日期:2023-05-25

Uncertainty analysis of runoff generation and concentration parameters under urbanization and simulation of flooding and waterlogging. Case study of Jincun District, Jincheng

  • Online:2023-05-25 Published:2023-05-25

摘要: 识别敏感参数,降低模型不确定性,是提高城市雨洪模拟结果科学性与准确性的重要步骤之一。本文以晋城市金村区为例,构建城市洪涝模拟模型,分别采用局部和全局方法识别敏感性参数,同时分析不同下垫面特征的参数敏感性。基于敏感性分析,模拟不同降雨情景和城市化进程中不同下垫面的洪涝特征值。结果表明:不透水区洼蓄量较敏感;降雨重现期增大,最大下渗率局部敏感性增强而全局敏感性减弱;硬化地面较多区域,不透水面相关参数较为敏感;不同区域洪涝特征值均随重现期的增大而增大;同一重现期下,特征指标值随城市化进程分布更加集中。本研究可以为城市分布式雨洪模型参数不确定性分析与洪涝特征响应分析,以及城市韧性提升提供一定的参考。

关键词: 城市洪涝, 敏感性, 不确定性, 分布式模型, 城市韧性, 暴雨洪水管理模型

Abstract: Identifying sensitive parameters and reducing model uncertainty is a key step to improve urban flood simulation accuracy. This paper constructs an urban flood simulation model for the Jincun District of Jincheng City, identifies sensitivity parameters using a local method and a global method separately, and examines parameter sensitivity for different land surface conditions. Based on sensitivity analysis, flooding and waterlogging characteristics under different land surface conditions are simulated for different rainfall scenarios and urbanization processes. The results show that the puddle storage in impervious areas is more sensitive. The sensitivity of maximum infiltration rate is increased locally and decreased globally as the rainfall return period increases. Parameters related to impervious surfaces are more sensitive in the areas with more hardened ground surfaces. Flooding and waterlogging in different areas are more severe with a longer return period. Under the same return period, waterlogging is more concentrated under the condition of urbanization. This study reveals parameter uncertainties and flooding and waterlogging characteristic responses for application of the urban distributed rainfall-flood model and urban resilience enhancement.

Key words: urban flooding, sensitivity, uncertainty, distributed model, urban resilience, storm water management model

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