Groundwater Quality Assessment for Agricultural Purposes Using Fuzzy Inference Model

Nowadays, groundwater quality change and salinization of water resources is a major hazard to developing of agriculture, particularly in dry lands like Iran. In this study, the application of Fuzzy Set theory to evaluate quality of groundwater was studied. In recent years, artificial intelligence methods have adjusted to spot uncertainty in environmental problems. Fuzzy Logic is one of the popular methods for decision making in complex and uncertain environments. In this study, the 49 groundwater samples of Sarab plain in 2014 that analyzed in Hydrogeology laboratory of Tabriz University was used. Values of irrigation indices including the Sodium Absorption Ratio, Permeability Index, the Kelley Ratio, Magnesium Adsorption Ratio, Residual Sodium Bicarbonate, Dissolved Sodium Percentage and Electrical Conductivity as an indicator of total dissolved solids in water are used in this research. Based on Fuzzy Water Quality Model, the groundwater quality is classified in three categories desirable, acceptable and unacceptable. Results showed 41 Samples come in desirable category with certainty level of 65 to 83 percent and 26 samples classified in the acceptable category whose certainty level ranged from 37 to 65.4 percent and the remaining three samples were in rejected category with the maximum certainty level of 23.4 percent.