Using Fuzzy Computation in Modelling Uncertainties in Kriging Estimation Method, Case Study: Estimation of Sodium Spatial Dispersion in Zanjan Aquifer

Various methods have been used to create continuous surfaces from sampled data. One of the most common geostatistical methods is Kriging, which provides an accurate estimation based on existing spatial structure in the sample points. However, Kriging method is sensitive to the errors in the input data, the dispersion of the sample. The purpose of this research is to develop a new method to handle the uncertainties resulted from the input data in the Kriging method. In this approach, the existing uncertainties in the input data are modeled by fuzzy computations, and the variogram variables are calculated in fuzzy mode. To test the new hybrid method, the sodium contamination values in Zanjan aquifer are used. The results show a generally improved accuracy in comparison to the ordinary Kriging method. Consideration of all equations and values in fuzzy raises the complexity of the computation. On the other hand, the integrity problems associated other researches on fuzzy kriging are resolved.