基于地理国情监测数据的SWMM模型优化
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TU992.4

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Optimization of SWMM Model Based on GeographicalNational Monitoring Data
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    摘要:

    SWMM作为动态模拟的城市暴雨积涝模型,被广泛应用于城市积涝负荷估算研究,并在很多小尺度研究中取得了很好的效果。随着中国城市发展不断加快,城市积涝研究的空间尺度也随之变大,如何科学合理的构造模型,并且保证模型的精度成为研究中一个重要问题。本文基于地理国情监测数据分析了SWMM应用于城市区域暴雨积涝模拟时,地理国情监测数据对模型精度的影响,并在此基础上,在汇水区划分、管网概化、节点选取等三方面对其参数进行优化。以陕西省延安市为例,利用优化后的模型对三场真实降雨相关数据进行分析,给出了对延安市内涝风险的区域划分。实验表明:溢流节点和超载管段基本符合街道淹没情况,为延安市内涝风险防治提供了科学参考。

    Abstract:

    As a dynamic simulated urban stormwater accumulation model, SWMM is widely used in urban accumulation load estimation research and has achieved good results in many small-scale studies. As China"s urban development continues to accelerate, the spatial scale of urban accumulation research has also become larger. How to construct the model scientifically and reasonably, and to ensure the accuracy of the model has become an important issue in research. This paper mainly analyzes the impact of geographic national condition monitoring data on model accuracy when SWMM was applied to urban area storm accumulation simulation. On the basis of this, in the three aspects of watershed division, pipe network generalization and node selection, the parameters were optimized. Using the optimized model to simulate under three real rainfalls, the results showed that the overflow node and the overloaded pipe section were basically in line with the street flooding situation. Finally, this model was used to divide the risk area of Yan"an City, which further illustrates the practical value of the optimized model.

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张春森,于振,吴满意. 基于地理国情监测数据的SWMM模型优化[J]. 科学技术与工程, 2020, 20(2): 453-459.
Zhang Chunsen, Yu Zhen, Wu Manyi. Optimization of SWMM Model Based on GeographicalNational Monitoring Data[J]. Science Technology and Engineering,2020,20(2):453-459.

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历史
  • 收稿日期:2019-04-08
  • 最后修改日期:2019-07-18
  • 录用日期:2019-08-09
  • 在线发布日期: 2020-04-16
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