Under the background of climate change and urbanization, the localized characteristics of rainfall are becoming increasingly pronounced. The spatial resolution of rainfall data often fails to meet the requirements for accurately describing spatial distribution. Conversely, using fine spatial resolution rainfall data result in resource wastage. Based on observed and designed rainfall data, this work progressively increases grid size through spatial interpolation algorithm to achieve lower spatial resolution. By integrating spatial parameters such as rainfall center and regional characteristics, a rainfall dataset with varying spatial resolutions is constructed. This rainfall dataset is used to drive the hydrological-hydrodynamic coupled model, analyzing the influence of changes in rainfall spatial resolution on urban inundation and flood, and identifying the optimal spatial resolution of rainfall data. The results show that for urban inundation simulation, as the spatial resolution of rainfall decreases, the inundation water volume, inundation area, and inundation water depth all increase, revealing a tendency to overestimate inundation risk. For watershed flood simulation, as the spatial resolution decreases, the peak flow decreases, and the discharge process show a more flattened trend. The optimal spatial resolution of rainfall data for urban inundation simulation is 0.5 km, while for watershed flood simulation, it is 4 km.

中文翻译：

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城市洪水和流域洪水模拟对降雨数据空间分辨率的敏感性研究


在气候变化和城市化背景下，降雨的局地性特征日益明显。降雨数据的空间分辨率往往无法满足准确描述空间分布的要求。相反，使用精细空间分辨率的降雨数据会导致资源浪费。该工作基于观测和设计的降雨数据，通过空间插值算法逐步增大网格尺寸，以实现较低的空间分辨率。通过整合降雨中心和区域特征等空间参数，构建了不同空间分辨率的降雨数据集。该降雨数据集用于驱动水文-水动力耦合模型，分析降雨空间分辨率变化对城市内涝和洪水的影响，确定降雨数据的最佳空间分辨率。结果表明，对于城市淹没模拟，随着降雨空间分辨率的降低，淹没水量、淹没面积、淹没水深均增大，存在高估淹没风险的倾向。对于流域洪水模拟，随着空间分辨率的降低，峰值流量减小，流量过程呈现出更加平坦的趋势。城市洪水模拟的降雨数据最佳空间分辨率为0.5 km，流域洪水模拟的最佳空间分辨率为4 km。