Quantifying flood model accuracy under varying surface complexities
Quantifying flood model accuracy under varying surface complexities
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DOI：
10.1016/j.jhydrol.2023.129511
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发表时间：
2023-04
影响因子：
6.4
通讯作者：
W. Addison‐Atkinson;A.S. Chen;M. Rubinato;F. Memon;J. Shucksmith
中科院分区：
文献类型：
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作者：
W. Addison‐Atkinson;A.S. Chen;M. Rubinato;F. Memon;J. Shucksmith
城市地区的洪水以管道和地表网络之间的相互作用为特征，在水力上是复杂的。此外，获得现场校准数据虽然对于稳健的模拟是必要的，但可能非常具有挑战性。这项研究的目的是评估常用的确定性一维-二维洪水模型的性能，该模型使用低分辨率数据进行校准，与包含水流、水深和速度场的较高分辨率数据集进行对比；这些数据集是从一个实验比例尺模型水设施复制的。数值模型的校准是使用较低分辨率的数据集进行的，该数据集由一个简单的矩形轮廓组成。然后根据空间分辨率更高、几何结构更复杂的数据集(包含停车位的街道剖面)对该模型进行评估。研究结果表明，当模型的场景复杂性增加时，模型的性能降低，尽管大部分模拟误差在10%(NRMSE)以下。同样，空间分辨率较高的验证模型比较低的模型误差更大。这是由于在较低的空间分辨率下进行校准时不够严格。然而，总体而言，这项工作显示了使用低分辨率数据集进行模型校准的潜力。
Floods in urban areas which feature interactions between piped and surface networks are hydraulically complex. Further, obtaining in situ calibration data, although necessary for robust simulations, can be very challenging. The aim of this research is to evaluate the performance of a commonly used deterministic 1D-2D flood model, calibrated using low resolution data, against a higher resolution dataset containing flows, depths and velocity fields; which are replicated from an experimental scale model water facility. Calibration of the numerical model was conducted using a lower resolution dataset, which consisted of a simple rectangular profile. The model was then evaluated against a dataset that was higher in spatial resolution and more complex in geometry (a street profile containing parking spaces). The findings show that when the model increased in scenario complexity model performance was reduced, though most of the simulation error was < 10% (NRMSE). Similarly, there was more error in the validated model that was higher in spatial resolution than lower. This was due to calibration not being stringent enough when conducted in a lower spatial resolution. However, overall the work shows the potential for the use of low-resolution datasets for model calibration.