The Bourke Irrigation District (BID) supports approximately 14,000 Ha of irrigated agriculture and is situated along the Darling River in a semi-arid region of NSW, Australia. Soil salinity management issues have come to the fore in recent years because of the increasing occurrence of secondary soil salinization around water reservoirs and supply channels. This is impacting on the productivity of irrigated cropping. Understanding the salinity risk associated with irrigated cropping is of crucial importance to long term sustainability. Salinity risk modeling can be defined as the product of potential hazards such as primary salinity levels and groundwater conditions combined with the vulnerability of an asset (crop or natural vegetation) and its degree of exposure to the hazard. The aim of this work is to develop an interactive salinity risk model to allow farmers to understand crop specific salinity risk ratings. The development of such a model will also identify areas of concern before any impacts on vegetation growth occur and allow management options to be implemented that minimize the salinization risk. The risk model is based on two mechanisms that reflect the physical processes driving secondary salinisation in the BID. The first is termed the “evapotranspiration mechanism” which identifies salinity build-up in the upper profile through evaporative processes form irrigation, water storage leakage and capillary rise form groundwater. The second is the “groundwater mechanism” which models the groundwater interaction with extremely saline cretaceous sediments. A GIS interface is used to calculate a salinity risk associated with plant type, rooting depth and salinity tolerance based on these two mechanisms. The “evapotranspiration mechanism” assesses how close current root salinity levels are to the threshold tolerance of the plant. The “groundwater mechanism” assesses how saline the groundwater is and how close it is to the root zone. A fuzzy membership map ranging from 1 which designates a current salinity problem, to 0 which represents no threat form current root zone salinity is then developed. The model has been corroborated with many field examples of salinity and has shown to accurately represent what is occurring in the field. The results have since been used to trial a more efficient, lateral irrigation system in an area that was showing high levels of risk. The model represents a new and effective way of presenting many of the physical and biological factors that lead to salinization in semi-arid environments.