To investigate the impact of spatial autocorrelation on the accuracy of spatial interpolation for the precipitation of rainstorm events, based on the daily precipitation data from 102 rainfall stations in the Wujiang River Basin from 2009 to 2018, 88 rainstorm events were screened out. These events were interpolated using the inverse distance weighting(IDW), radial basis function(RBF), ordinary Kriging(OK), and co-Kriging(CoK) methods. Moran’s I was employed to quantitatively analyze the spatial autocorrelation of each rainstorm event precipitation at the 102 rainfall stations, and this study compared the interpolation accuracy of different methods for rainstorm event precipitation with varying spatial autocorrelation. The results show that with the increase of spatial autocorrelation of rainstorm event precipitation, indicated by the Moran’s I index, the accuracy of all four interpolation methods improves to varying degrees, and the accuracy improvement of OK method and CoK method is more obvious. For the average basin, when the Moran’s I is less than 0.28, the RBF method is recommended, whereas when the Moran’s I is greater than or equal to 0.28, OK is recommended. For the rainstorm center, when the Moran’s I is less than 0.4, RBF is recommended, when it is greater than or equal to 0.4, OK or CoK is recommended.