Research on the Zonal Water-Soil Resource Spatial Variation Using Artificial Neural Indicator Kriging Technology

Based on the spatial variation of soil water-salt at one representative experimental section in Hetao irrigation zone, directed by Indicator Kriging of non-parameter Geostatistic theory, using the high non-linear approximating ability of ANN, this paper innovated fusion of the non-parameter statistic and artificial intelligence technologies. Compared with the Ordinary Kriging, BP, Indicator Kriging, and Distinctive Kriging estimating values, it is founded that Artificial Neural Indicator Kriging has the characteristics of indicator kriging: 1) no need to make statistical assumptions for raw data; 2) not involving identification and specificity values treatment; 3) a high degree of approximation of linear and nonlinear functions; which can solve nonlinear problems effectively, so it can be used to monitor soil water and salt and the related work.