Abstract

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.

HIGHLIGHTS

  • The performances of different precipitation interpolation schemes at different time scales have been figured out.

  • The mixed spatial interpolation schemes for precipitation are found to be the best at all the time scales due to its own parameters and structure.

  • The accuracy of discharge simulation is found to be sensitive to the spatial interpolation schemes for precipitation at short time scale while there are no significant differences at monthly and annual time scales.

  • The importance of time scales in the precipitation interpolation are recommended to be considered before determining the areal precipitation.

  • The proposed framework of the selecting the methods can also be applied to another spatial precipitation interpolation methods.

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