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建议BK-SWMM洪水模拟框架用于基于不确定性参数众包数据的城市风暴洪水建模,这些数据来自单个功能区域
Chengshuai Liu1, Wenzhong Li1, Chenchen Zhao1
1Yellow River Laboratory, Zhengzhou University, Zhengzhou, 450001, China.
Journal of environmental management
|July 6, 2023
概括
本研究介绍了BK-SWMM,这是城市洪水模型的快速构建框架. 它通过对基于城市功能区的模型参数进行集群来提高模拟准确性,帮助 flood 控制决策.
科学领域:
- 环境工程环境工程
- 水文学的水文学
- 城市规划 城市规划
背景情况:
- 城市洪水是由于大雨造成的日益严重的威胁,影响基础设施和安全.
- 准确和快速的城市洪水模拟对于有效的洪水控制和减少灾害至关重要.
- 复杂的模型校准阻碍了现有的城市雨水洪水模型的效率和准确性.
研究的目的:
- 开发城市雨水洪水模型的快速施工方法,解决校准挑战.
- 提出BK-SWMM框架,将机器学习与风暴水管理模型 (SWMM) 整合起来.
- 提高城市洪水模拟和预测的效率和准确性.
主要方法:
- 构建了SWMM不确定性参数的众包数据集.
- 采用贝叶斯信息标准 (BIC) 和K-means集群来识别城市功能区域的参数模式.
- 将BIC和K-means与SWMM模型结合起来,创建BK-SWMM洪水模拟框架.
主要成果:
- 在工业和商业区域 (ICA),住宅区域 (RA) 和公共区域 (PA) 中确定了七个关键SWMM不确定性参数的独特分布模式.
- 在三个空间尺度上,BK-SWMM表现出优于标准SWMM的性能,REQ,NSEQ和RD2指数分别超过0.80,0.85,并显示出不到10%的误差.
- 随着研究区域地理规模的增加,模拟准确性下降,突出显示了规模依赖.
结论:
- BK-SWMM框架有效地提高了城市雨水洪水模型的构建和模拟准确性.
- 参数分布在不同的城市功能区之间有很大的差异,影响了洪水建模.
- 需要进一步的研究,以解决城市风暴洪水模型的规模依赖,以获得更广泛的适用性.
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