A Computationally Efficient and Physically Based Approach for Urban Flood Modeling Using a Flexible Spatiotemporal Structure
A Computationally Efficient and Physically Based Approach for Urban Flood Modeling Using a Flexible Spatiotemporal Structure
复制标题
DOI：
10.1029/2019wr025769
复制
发表时间：
2020-01
影响因子：
5.4
通讯作者：
S. Saksena;Sayan Dey;V. Merwade;P. Singhofen
中科院分区：
文献类型：
--
作者：
S. Saksena;Sayan Dey;V. Merwade;P. Singhofen
最近发生的史无前例的事件凸显出，现有的洪水风险管理方法不足以应对复杂的城市系统，因为它过度依赖大尺度粗分辨率的简单方法，缺乏使用松散水文-水力耦合的模型物理性，并且缺乏大尺度的城市水基础设施。分布式模型是一种潜在的替代方案，因为它们可以通过同时跟踪水文和水动力过程来捕获这些事件的复杂性质。然而，在不影响时空分辨率、空间尺度、模型精度和局部尺度流体动力学的情况下，它们在大规模洪水测绘和预报中的应用仍然具有挑战性。因此，有必要开发能够解决城市系统中这些问题的技术，同时最大限度地提高计算效率并保持大规模的准确性。本研究提出了一种基于物理但计算高效的方法，使用称为互连通道和池塘路由的分布式模型对极端事件进行大规模（面积> 103 km2）洪水建模。将所提出方法的性能与 60 米分辨率的超分辨率固定网格模型进行了比较。与固定分辨率模型相比，应用所提出的方法可将计算元素数量减少 80%，并将飓风哈维的模拟时间缩短约 4.5 倍。结果表明，所提出的方法可以高精度地模拟多个水位的洪水阶段和深度（R2 > 0.8）。与联邦紧急事务管理局建筑受损评估数据的比较显示，在预测空间分布的洪水位置方面相关性大于 95%。最后，所提出的方法可以直接根据未蓄水河流的降雨量来估计洪水阶段。
Recent unprecedented events have highlighted that the existing approach to managing flood risk is inadequate for complex urban systems because of its overreliance on simplistic methods at coarse‐resolution large scales, lack of model physicality using loose hydrologic‐hydraulic coupling, and absence of urban water infrastructure at large scales. Distributed models are a potential alternative as they can capture the complex nature of these events through simultaneous tracking of hydrologic and hydrodynamic processes. However, their application to large‐scale flood mapping and forecasting remains challenging without compromising on spatiotemporal resolution, spatial scale, model accuracy, and local‐scale hydrodynamics. Therefore, it is essential to develop techniques that can address these issues in urban systems while maximizing computational efficiency and maintaining accuracy at large scales. This study presents a physically based but computationally efficient approach for large‐scale (area > 103 km2) flood modeling of extreme events using a distributed model called Interconnected Channel and Pond Routing. The performance of the proposed approach is compared with a hyperresolution‐fixed‐mesh model at 60‐m resolution. Application of the proposed approach reduces the number of computational elements by 80% and the simulation time for Hurricane Harvey by approximately 4.5 times when compared to the fixed‐resolution model. The results show that the proposed approach can simulate the flood stages and depths across multiple gages with a high accuracy (R2 > 0.8). Comparison with Federal Emergency Management Agency building damage assessment data shows a correlation greater than 95% in predicting spatially distributed flooded locations. Finally, the proposed approach can estimate flood stages directly from rainfall for ungaged streams.