Water quality must be tested before it can be used for agricultural purposes since difficulties might arise in terms of increased soil salinity, decreased soil permeability, and decreased water absorption by plant roots; leading to reduced agricultural productivity. The aim of this study was to assessment suitable irrigation water based on a new approach in Asalem region, Iran. For reduce the uncertainty, fuzzy logic spatial modeling via GIS was applied. To receive these aims, four stages were performed. In stage 1, we calculate the values of nine conventional and effective parameters used for agricultural water quality classification upon analyzing the statistical quality data regarding various ions existing in 15 sample wells dug in 2015. In stage 2, interpolate these parameters by kriging method via ArcGIS software. In stage 3, parameter standardization with fuzzy membership function were done. And in stage 4, for Aggregation parameters, several fuzzy overlay operations were used. Finally, to identify the best operation, the correlations between the fuzzy membership and operation maps were used. Results showed that the "GAMMA 0.9" with six high correlation above 80%, is the best overly operation in our study area. According to the best operation map, only west and northwest parts of the study area have "good" to "excellent" groundwater quality for irrigation water and in other parts, the quality is within "poor" to "fair".