Constructing rainfall-runoff models at the community scale involves challenges due to varying data availability and the potential generalization of critical microtopographical features or the use of different modeling approaches. It is crucial and urgent that the differences among various modeling methods are understood under different external boundary conditions. This work examines the synergistic relationship between these modeling approaches and the LID facilities within communities, while also considering the impact of key microtopographical features on runoff processes. The study finds that: (1) Full hydrodynamic models exhibit significant biases at lower cumulative rainfall levels, which diminish as cumulative rainfall increases. Simulation errors reduce notably after accounting for downspouts, yet considering LID facilities cause overall increase in errors. (2) LID facilities enhance runoff control at lower cumulative rainfall levels but reduce it at higher cumulative rainfall levels. (3) Directly connecting downspouts to rain gardens significantly reduces inundated area, volume, and peak flow, enhancing the regulatory efficiency of LID facilities. (4) Surface and subsurface runoff processes at the community scale show limited sensitivity to changes in rain garden overflow well heights during lower cumulative rainfall levels. This study offers insights into selecting appropriate community-scale rainfall-runoff modeling methods under various boundary conditions.

中文翻译：

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建模方法对社区规模城市洪水过程的影响


由于数据可用性不同以及关键微地形特征的潜在泛化或使用不同的建模方法，在社区规模构建降雨径流模型涉及挑战。在不同外部边界条件下理解各种建模方法之间的差异至关重要且紧迫。这项工作研究了这些建模方法与社区内 LID 设施之间的协同关系，同时还考虑了关键微地形特征对径流过程的影响。研究发现：（1） 全水动力模型在较低的累积降雨水平上表现出显著的偏差，随着累积降雨量的增加而减弱。在考虑落水管后，模拟误差显著减少，但考虑到 LID 设施会导致误差总体增加。（2） LID 设施在较低的累积降雨水平下加强径流控制，但在较高的累积降雨水平下减少径流控制。（3） 将落水管直接连接到雨水花园可显着减少淹没面积、体积和峰值流量，从而提高 LID 设施的监管效率。（4） 在较低的累积降雨量水平下，社区尺度的地表和地下径流过程对雨水花园溢流井高度变化的敏感性有限。本研究为在各种边界条件下选择合适的社区规模降雨径流建模方法提供了见解。