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本文简单地介绍了地统计模拟中的序贯高斯方法 ,以农田土壤表层饱和导水率Ks为例 ,对其分别进行了条件模拟和克立格插值 ,并将条件模拟、克立格插值结果与实测数据进行了对比分析 .结果表明克立格插值具有明显的“平滑”效应 ,改变了Ks数据的空间结构 ;而条件模拟具有与实测数据相同的空间自相关结构 ,并且对未知点的模拟值具有不确定性 .因此 ,条件模拟对于研究那些具有空间不确定性且会对环境带来不良影响的风险性变量 ,更具有实际意义 .
In this paper, we briefly introduce the sequential Gauss method in geostatistical simulation. Taking the surface saturated hydraulic conductivity Ks of farmland as an example, the conditional simulation and Kriging interpolation are respectively carried out. The conditional simulation, Kriging interpolation result The results show that Kriging interpolation has a significant “smoothing” effect and changes the spatial structure of Ks data, while the condition simulation has the same spatial autocorrelation structure as the measured data, and the simulation of unknown points Therefore, conditional simulation is more practical for studying risk variables that have spatial uncertainty and adverse environmental impact.