Evaluating the Thiessen polygon approach for efficient parameterization of urban stormwater models
Evaluating the Thiessen polygon approach for efficient parameterization of urban stormwater models
复制标题
评估泰森多边形方法对城市雨水模型的有效参数化
DOI：
10.1007/s11356-022-24162-7
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发表时间：
2023
影响因子：
5.8
通讯作者：
Ng, Carla A.
中科院分区：
文献类型：
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作者：
Dong, Zhaokai;Bain, Daniel J.;Akcakaya, Murat;Ng, Carla A.
流域离散化是构建暴雨模型的关键。传统方法通常需要航空或地形数据来手动划分流域，但这种方法在数据访问能力差的地区具有挑战性。在这里，我们提出了一种替代方法，通过绘制蒂森多边形周围的下水道节点，构建一个下水道模型。这种方法的实用性进行评估，使用美国环保署的雨水管理模型（SWMM），模拟管流在匹兹堡市的污水处理厂。参数的敏感性和模型的不确定性进行了探讨，通过蒙特卡罗模拟和一个简单的算法应用于校准模型。校准后的模型可以可靠地模拟管道流量，与测量流量相比，Nash-Sutcliffe效率（NSE）为0.82。下水道数据可用性对模型性能的潜在影响作为用于建立模型的节点数量的函数进行了测试。当随机减少用于构建模型的节点数量（高达40%）时，模型性能没有观察到统计学差异。基于我们的分析，泰森多边形的方法可以用来构建城市雨水模型，并产生良好的管流模拟，即使下水道数据有限的情况下。
Catchment discretization plays a key role in constructing stormwater models. Traditional methods usually require aerial or topographic data to manually partition the catchment, but this approach is challenging in areas with poor data access. Here, we propose an alternative approach, by drawing Thiessen polygons around sewer nodes to construct a sewershed model. The utility of this approach is evaluated using the EPA’s Storm Water Management Model (SWMM) to simulate pipe flow in a sewershed in the City of Pittsburgh. Parameter sensitivities and model uncertainties were explored via Monte Carlo simulations and a simple algorithm applied to calibrate the model. The calibrated model could reliably simulate pipe flow, with a Nash–Sutcliffe efficiency (NSE) of 0.82 when compared to measured flow. The potential influence of sewer data availability on model performance was tested as a function of the number of nodes used to build the model. No statistical differences were observed in model performance when randomly reducing the number of nodes used to build the model (up to 40%). Based on our analyses, the Thiessen polygon approach can be used to construct urban stormwater models and generate good pipe flow simulations even for sewer data limited scenarios.
DOI：
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发表时间：
1992
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作者：
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通讯作者：
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