"SAR" Qualities parameter persistence by a compound method of geostatic and artificial neural network (Case study of Jiroft plain)

Water is one of the vital elements of our life, the effective part of economic activities and agricultural circulate. It is defined as a renewable asset if we pay attention to that in saving and beneficial management. The major part in making benefit of this hidden wealth is management methods of Usefulness and production. In our country, the main sources of Groundwater are used in agricultural parts, imbibing and even industry. Thus Groundwater quality persistence and its assessment are so important. In this way, the existence situation and qualities changes process are mentioned. Recently, variety methods are based on mathematic sciences and computer replaced experimental methods and also scope surveys. This ways were developed gradually because of their high calculating accuracy and low experimental costs. Artificial neural networks have been important from old days too physical and chemical properties are prepared as dot harvesting. We should universalize all dot harvests in older to define these properties. So the proper methods are geostatic methods. In this research, we are going to mix these two methods to predict "SAR" qualities parameter, analysis quantities and show high correlation of them and real amounts (R=0.96). Thus, we can know this method as the best way of predicting "SAR" qualities parameters of Jiroft plain Groundwater instead of scope ways and experimental examinations.