Abstract: Ordinary Kriging of geostatistics is an effective tool in studying the spatial variability of soil moisture and describing its spatial distribution.Like other interpolation methods based on the criterion of least-squares,ordinary Kriging estimates present a serious inherent drawback well known as the smoothing effect with decreased variation of estimates.In this study,the post-processing approach of Yamamoto is used to correct the smoothing effect of ordinary Kriging estimates in observed soil moisture interpolation.The result shows that the Yamamoto's approach can effectively correct the smoothing effect,and the real soil moisture spatial distributions can thus be preserved without losing local accuracy.