中文摘要：

地统计学的普通克里金法是研究土壤水分空间变异特性和描绘其空间分布的有效方法。但与其它建立在最小二乘标准上的插值方法一样,普通克里金法也存在着平滑效应问题,即估计值的变异程度比实际要小,从而导致估计值往往不能反映出土壤水分真实的空间变化特征。结合实际的土壤水分监测数据,采用Yamamoto提出的一套针对普通克里金估计值进行后处理的方法,较好地解决了普通克里金法平滑效应的问题,在保证局部估计值精度的同时,重现了土壤含水率在空间的分布与变化特征。

英文摘要：

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.