Estimate the spatial distribution TDS the fusion method Geostatistics and artificial neural networks

In recent years, mathematical, statistical and computational methods to simulate and assess many aquifer water quality parameters have been considered. Monitoring water quality in the aquifer is dominated considering the effects of natural and artificial factors by assign. By groundwater monitoring data, the authors can reach to features of geological and hydrogeological aquifer hydraulic load distribution in time and setting, water quality of ground water contaminants and characteristics pollution source. There is a different algorithm for spatial interpolation that some of them are based on geometric and geostatistical methods. In this paper, the fusion of artificial neural networks and geostatistics has used order to estimate more the parameters of the spatial distribution of ground water quality TDS plain Birjand more accurately. The analysis of geostatistical interpolation methods and the application of artificial neural networks to optimize the results of geostatistical methods have been studied.