Interpolating precipitation data is of prime importance to hydrological design, modeling, and water resource management. Various models have been developed that estimate spatial precipitation patterns. The purpose of this study is to analyze different precipitation interpolation schemes at different time scales in order to improve the accuracy of discharge simulations. The study was carried out in the upstream area of the Changjiang River basin. The performance of all selected methods was assessed using cross-validation schemes, with the mixed methods ultimately displaying the best performance at all three time scales. However, the differences in performance between the spatial interpolation methods decreased with increasing time scales. The unifying catchment Soil and Water Assessment Tool (SWAT), ‘abcd’, and the Budyko equation were employed at the daily, monthly, and annual scales, respectively, to simulate discharge. The performance of the discharge simulation at the monthly and annual time scales was consistent with their ranks of spatial precipitation estimation. For coarse, or long period, precipitation, there were no significant differences. However, the mixed methods performed better than the single model for the daily, or short, time scale with respect to the accuracy of the discharge simulation.

内插降水数据对于水文设计，建模和水资源管理至关重要。已经开发出各种模型来估计空间降水模式。这项研究的目的是在不同的时间尺度上分析不同的降水插值方案，以提高排放模拟的准确性。该研究在长江流域的上游地区进行。使用交叉验证方案评估了所有选定方法的性能，而混合方法最终在所有三个时间尺度上均表现出最佳性能。但是，空间插值方法之间的性能差异随时间尺度的增加而减小。统一的流域土壤和水评估工具（SWAT），“ abcd”，和Budyko方程分别在日，月和年尺度上使用，以模拟流量。每月和每年时间尺度上的排放模拟性能与他们的空间降水估算等级一致。对于粗略或长期的降水，没有显着差异。但是，就放电模拟的准确性而言，在每日或更短的时间范围内，混合方法的性能优于单个模型。